FIT1055
IT PROFESSIONAL
PRACTICE & ETHICS
By Nik Nailah Binti Abdullah
Nik Nailah Binti Abdullah
ALL RIGHTS ARE RESERVED.
No permission is given for any part of this ebook to be
reproduced, transmitted in any form or means, electronic or
mechanical, stored in a retrieval system, photocopied,
recorded, scanned, or otherwise. Any of these actions require
the proper written permission of the author.
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Preface
How to use this Ebook
This is an ebook that can be read like a notebook. It includes my notes on IT Professional
Practice and Ethics in AI over a decade of working in different organizations and cultures. It
also has compiled resources from the web and other organizations to help you develop
professionalism and ethical thinking in developing algorithms or products.
I have lived and participated in different organizations in France, the United Kingdom, and
Japan. Furthermore, I have also worked with various professionals from other fields and
cultures - computer scientists from the United States of America, programmers from Russia
and France, including business people from the United States of America and Australia (some
examples). I have even collaborated with professional people from multi-national
corporations and the healthcare industry.
My more than decades of experience collaborating and working with people from different
cultures and organizations showed me the importance of developing professionalism and
making that part of a practice. It will open up new opportunities in your career and shape
your values and role in society. We are always learning and constantly evolving in our parts
of professional life.
As a computer scientist and a lecturer, I wish to share with future Computer Science student
graduates what it means to be a professional Computer Science employee. I want them to
know why learning how to collaborate and work in teams is essential, which requires
developing necessary soft skills. Ethics is central to everything you create and design,
especially in creating automated systems using artificial intelligence techniques and social
media. I want to highlight throughout this EBook how important it is to be aware of our
learning processes and experiences because we can only improve ourselves by becoming
aware.
To get you started on your journey to develop professional practice within a University
setting, you will learn how to experiment with the techniques taught in this unit through the
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project assignment we have created for you. It is only through practice that you can
understand and appreciate the content and then make it your practice to apply to other project
assignments.
So I hope you find this textbook, like a personal notebook, that can benefit you in this unit and
in completing your project assignments.
8 May 2022
Petaling Jaya, Malaysia
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Chapter One
Introduction to Professional Practice and Soft
Skills
I only learned about professionalism when working with people from multi-corporations,
research institutes, and universities abroad in the United States of America, France, the United
Kingdom, and Australia.
To understand what IT (or accurately computer science) means, professionals first recognize
what sets one employee from an organization different from another. I am sure most of you
have encountered in your life people from shops or companies and noticed that some
employees are more pleasant and easy to communicate with. They are helpful, polite, and
know what they say when speaking to you. You are happy to be served by them.
So professionalism is in how they carry themselves and how they have themselves interact
with you.
There are several different points of view on what it means to be professional. Let us start by
reviewing the below:
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Link to reference here.
Link to reference here.
We can summarize being professional as using one's knowledge and skills and demonstrating
specific attitudes that professionals must possess to practice their field of expertise
professionally, responsibly, and ethically.
Over time, you will need to develop skills that allow you to work and communicate to create
and deliver products in your organization as practice. Put another way, the approach is how
you do things to get them done effectively. You develop this over time, which is one of your
skillset that can be carried throughout your career.
Hence, we define Professional Practice as
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The use of one's knowledge, skills, and attitudes that computing professionals must
possess to practice computer science roles in a professional, responsible and ethical
manner.
Therefore, the difference with being “you” in our personal life is that when things don’t go
our way, we don’t think carefully about what we say, how we make decisions or the
consequences of our actions. We don’t dampen the “negative sides.”
As professionals, we can’t behave the same way with family and friends at home with
colleagues at work. In an organization, as a professional practice, we must ensure that we are
part of a good culture and working environment. We must know how to deal with problems
within our team professionally. We must also learn to work with our team professionally to
get things done. We also must know how to write and report our work professionally. Most
importantly, we must be aware that all our work is often in a team and involves learning to
communicate effectively to get things completed. As computer science graduates, we must
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also understand that we are developing something, be it a piece of code, a user experience
design theme, or even marketing a product.
Coding nicely is just one aspect of being a professional. This unit teaches you the other
elements that make you a complete Computer Science graduate.
The Soft Skills You Need
This section will outline the soft skills you need to have as part of developing your
professional practice. Before we do that, let us look at the proper definitions of soft skills.
Link to reference here.
Link to reference here.
Link to reference here.
We can summarize from the above definitions that soft skills are types of skills that attribute
(other than hard technical skills) to the success of your role in an organization or a profession.
The soft skills that you will learn in this unit are according to the weekly topics are;
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Communication skills, written and verbal
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Practical research skills
Oral and visual presentation
Effective conduct of meetings
Working in a team and leading a team
Whereas, from week seven onwards, we will teach you other types of soft skills within the
topic of Ethics and AI that includes:
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Ethical decision-making process
Complex problem solving
Critical thinking
Creativity
We will introduce the definitions of these soft skills in its chapter, including techniques and
methods to help you apply them in your Assignments.
Key takeaways
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Being professional is essential in the organization to get things done.
Developing professionalism requires specific soft skills and ethics.
How we develop and apply the soft skills and ethics into actual settings becomes
practice over time. This defines our professional practice.
Soft skills are skills other than technical skills such as programming that contribute to
your future profession's success.
Soft skills range from being an effective communicator, presenter, master of meetings,
effective teamwork, leader, critical thinking, and decision-making skills.
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Chapter Two
The Basics of Professional Communications
I did a chapter in my Doctorate thesis on Common Ground theory by Herbert Clark. This
theory inspired many artificial intelligence scientists to develop multi-agent systems
language. Basically, it taught us how do we develop codes embodied as artificial software
agents able to communicate with other software agents just like how humans do when
working together.
Little did I realize my chapter on Common Ground led me to the self-realization there was a
whole theory and principles to make one become an excellent communicator. I did not know
there were techniques for us to plan and develop better communication skills to convince
people to agree or work with us.
So in this chapter, I will introduce the basics of communication theory and then the valuable
communication skillsets you should have in your professional practice. Not only would you
start to become aware that every soft skill technique developed is based on scientific theories,
but some of these scientific theories inspire computer scientists to apply to robots and
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automated AI systems. You will learn more about some of the theories used to develop
artificial intelligence applications in chapters 8 onwards.
I hope you will find this chapter enlightening.
Theory of Common Ground
The theory of common ground refers to "mutual knowledge, mutual beliefs, and mutual
assumptions" that are believed to be essential for successful communication between people.
The standard ground theory is based on fundamental concepts about face-to-face
communication that have been extrapolated from both cognitive science and sociology. Faceto-face is the most basic form of communication and happens intuitively between humans,
whereas writing and reading are complex learned processes. Face-to-face communication
involves more than just words, gestures, expressions, and pointing. Face-to-face
communication is a joint action with a shared intention – and this shared intention utilizes
existing common ground between the participants to develop new common ground through
face-to-face speech.
Whenever we communicate, it could be to get things done, or to express ourselves, which
ultimately would lead to the person who listens or interacts with us to understand us, agree
with us, or we are a terrible communicator, people will dislike us and would not want to
cooperate with us!
Ultimately, the tools or ways we communicate at home, at the university, and at work are to
make others reach a “common ground” with us, have shared understanding, and have mutual
objectives. When we have established a common ground, we reach quickly at agreeing to do
something together.
Now we turn to the types of communication skillset valuable for you to develop, but as usual,
I like to introduce definitions so that we establish the common ground!
Definition of communication skills
Communication skills are demonstrated by how effective you are at getting others to
understand what you intend to say or getting others to do what you would like them to do
professionally.
It can be verbally - convincing a fellow student to join a club, or in a team - making everyone
agree on a project of your choice but with professional mannerism and ethics. You are
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accountable for whatever that you had you had committed during your communications with
your fellow students on a project together. You are sensible and open-minded in the way you
communicate issues and challenges. So effective communication skills in a professional
practice reflect proper attitude and values.
It can also be through the written form – writing a cover letter for a job application or an
email to fellow teammates or intern supervisors. The same objective as communicating faceto-face is to reach common ground with the receiver of the letter, or email by writing.
Therefore, there are different techniques you can learn to develop effective communication
skills for both face-to-face and professional writing.
Effective communication skills
There are two sets of effective communication skills required in professional practice, intra
and interpersonal.
As usual, let us review what intrapersonal skills means from various other sources:
Link to reference here.
Link to reference here.
Hence, in summary we can define intrapersonal skills relates to our ability to become aware
of our own strength and weaknesses that includes how we feel – angry, resentful, etc. This is
important because it helps us regulate how we interact and behave with others and what we
need to improve to become a professional.
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Interpersonal skills on one hand, is defined as;
Link to reference here.
Link to reference here.
Interpersonal skills to simply put is the opposite of intrapersonal skills, it’s about your skills
in interacting with others.
But in order to be good at interpersonal skills, you need to develop intrapersonal skills. This
is because the two skills go hand in hand and strengthen each other when you make it as part
of your professional practice.
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Link to reference here.
Link to reference here
Now that we are clear the definition of intrapersonal and interpersonal skills, we will now
introduce the key intrapersonal and interpersonal skills we will teach you in this unit.
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Intrapersonal Skills
In this unit, through your project assignments, you will learn how to develop the following
intrapersonal skills:
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Productivity
Resourcefulness
Introspection
Firm values and morals
We will provide you with basic techniques to develop the intrapersonal skills required for this
unit in the next sub-sections.
Productivity
The time at which you choose to perform a task is incredibly important. Not all times are
created equal. Think about your typical daily and weekly tasks and make a basic list. Mine
are:
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Productivity journal before I start with my work. In this journal, I list down what I
intent to do that can be good for others.
Check and send emails in the morning after writing my productivity journal
I will also start early on any assignments or personal project, dedicating 30 minutes or
1 hour per day. This gives me time to properly understand what is required in a
project, and what I need to do in order to deliver. I don’t like rushing because it usually
leads to poor quality of work.
I make sure I get enough rest and sleep so that I can learn and work effectively each
day.
In my university days, I bought this book on 7 Habits of Highly Effective People by Stephen
R. Covey on how to manage my time better. You can find some references online to help you
develop your productivity skills by proper time management. However, I do recommend the
book by Stephen R. Covey.
Resourcefulness
Knowing how to optimize what you have inspires creativity and helps you generate new
ideas. How does one develop resourcefulness skill? Well it’s a bit not straightforward. There
are ways to help you achieve resourcefulness and some of the attitude that can help you
develop this are:
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Being confident
Proactive
Being Imaginative
Keeping an open mind
Staying positive
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Never giving up
Read more at: https://matterapp.com/skills/resourcefulness.
Introspection
Introspection is the ability to look “into yourself” and reflect over the actions and choices you
make. This includes reflecting on your values. When you develop introspection, over time
you will be able to identify what habits work well for you, especially when it comes to facing
challenges.
In this unit, we help you to develop this by conducting reflective session at the end of each
tutorial. This is to help you become aware about what you have done during an activity and
formulate lessons learned. This will help you to develop and apply in your project
assignments. There is an assignment where we would ask you just to do that – reflect on your
actions and work output from your assignments.
Firm values
Value represents a judgment by an individual that certain things are “good” or “bad,”
“important” or “unimportant,” and so forth. As such, values serve a useful function in
providing guidelines or standards for choosing one’s own behavior and for evaluating the
behavior of others.
Personal values represent an important force in organizational behavior for several reasons.
(1) values serve as standards of behavior for determining a correct course of action; (2) values
serve as guidelines for decision-making and conflict resolution; and (3) values serve as an
influence on employee motivation.
We don’t need to wait to apply values when we join the workforce. Values would serve as a
guideline to how well you do your work, your accountability and responsibility as a student.
For example, you know not attending tutorial is a bad thing because there is expectation and
accountability on your part in return to your parents for providing you with tuition fees to
attend classes. So you should be attending these classes and gain as much learning as you can.
Without having value to guide you in your decision, you can make bad choices along the way
and has implications in your future. And we can see this in a lot of real-world cases of how
software or products developed are used in a nefarious way because values were absence in
their decision-making process! We will look more into this in Chapter 7, on Ethics and AI.
Interpersonal Skills
Let us now turn to interpersonal skills. This is what you will be continuously developing and
refining throughout your entire career life. So what are the interpersonal skills that you need
exactly for a start?
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There are a few main ones which we want you to apply in your group assignments; (1)
assertiveness; (2) listening skills; (3) questioning skills; (4) feedback skills and (5) intercultural
communication skills.
We will explain further in the next sub-sections.
Assertiveness
Assertiveness can be described as obtaining our desired outcomes from others without
contravening their rights (Eunson, 2012). Communicating with appropriate assertiveness
enables us to be effective in:
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Giving and receiving compliments
Making requests. E.g. for favours or assistance, initiating and maintaining
conversations, et
Standing up for your legitimate rights
Refusing requests
Expressing personal opinions, including disagreement
Expressing justified annoyance, displeasure and anger
Assertiveness techniques
Eunson (2012, p297-300), provides a number of specific techniques we can practice to be more
assertive and communicate more effectively.
Say “No”
There are many reasons it may be difficult to say no to someone. For example, there may be a
power imbalance where the other person is more senior, or you may find it difficult to tell a
colleague ‘no’ if they have put a lot of effort into something. Explaining to someone that you
cannot satisfy or fulfil their request can be delicate. It is important to try and avoid being
condescending. Rather, speak with a clear, firm voice, politely and without strain. Also, follow
up your negative response with an explanation, so that your audience understands why you
are responding that way. Often it is useful to offer an alternative. A good mantra to follow is
‘Come with a solution, not a problem.’
Dismiss/Redirect Conversation
Another technique we can use is the technique of dismiss and redirect, in order to get a
conversation back on track. If someone is focusing on something we think is unimportant we
can explain that (the dismissal), and then suggest what we should be focusing on (the
redirection) (Eunson, 2012).
Example: Lin has been asked to prepare a report on the user requirements for an update to
the document management system.
The conversation might go like this:
Lin: Could you tell me about any new functionality you would like to see in the document management
system?
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User: There are so many issues, I don’t know where to start. We have problems with printing, it is
difficult to find documents and management always wants things yesterday.
Lin: I acknowledge your broader concerns, but at this time we need to focus just on this aspect of the
system [Dismiss]. These broader issues could be raised with management for consideration in the future
[Redirect].
Questioning to Prompt Awareness
Also, by asking certain questions, we can bring a matter to someone’s attention. This is a way
of challenging their thinking, so we ought to consider how they will feel about being
challenged before using this technique.
“Have you noticed that whenever you talk to your subordinates, they are fearful of you?
[Questioning to prompt awareness]
If you observe their body language next time, you will find that they behave like small
children being scolded by their parents” (Eunson, 2012)
Fogging
‘Fogging’ is a technique whereby we calmly acknowledge criticism. Sometimes this criticism
will be justified, other times not. Either way, by acknowledging the criticism rather than
becoming defensive, we take the force out of the criticism. This means that “when others then
lash out, instead of connecting with something solid, they find it is like punching fog”
(Eunson, 2012, p.298)
Example: Lin faces a user who is very angry because his printer keeps failing. The
conversation might go like this:
User: Why can’t you teach people ever fix things properly? This problem has happened so many times.
I keep calling, someone comes and does something, then the next day the printer fails agai.n
Lin: I am sorry this keeps happening. It would be very frustrating ,and I apologise that we have not
been able to fix it for you. [Fogging]
Forcing a Choice
Sometimes, we may have been asked to complete a task when we have already been assigned
other tasks. It may be necessary to clarify what objective should be prioritised.
Example Lin is currently undertaking a major review of the document management system
and is talking to the users about what they want. Each conversation takes time, and at the
conclusion she must write a report for management with recommendations. Her boss Kamil
then asks her to do an audit of equipment in her area and establish what needs to be replaced.
How should she respond? Below is an example of what she might be able to say.
Kamil: We have an issue with outdated equipment in your area. We need to do a major audit to establish
what should be written off and replaced. I would like you to do this and I need it completed by the end
of month.
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Lin: I understand there are numerous issues with the equipment in our area and some of it is no longer
working. There are issues with the database of equipment so it will take time to identify everything. I
am currently working on the report on the document management system which is taking all my time.
Please tell me which task is the most important and I will focus on that one [Forcing a choice]
Broken Record
Sometimes, our audience may not receive our message clearly the first time. When this
happens we can use the ‘broken record’ technique. This involves clearly and calmly repeating
(over and over again, if necessary) our message, without getting frustrated or distracted
(Eunsons, 2012, p.299).
Ask For Specifics
Sometimes, we may face harsh criticism which isn’t really very helpful. Instead of becoming
frustrated or angry, it is more worthwhile to see if we can discern any useful, constructive
feedback, by asking for specific explanations. The other person will either be able to provide
that feedback (which can be constructive) or their lack of specific explanations will defuse
their criticism.
Example Lin has just returned from a difficult request from one of the staff, Jim. The staff
member was angry because a request to fix his computer had been logged two days earlier
but no one had come to see what the problem was. The staff member complained to Lin’s
boss.
Kamil: What on earth did you think you were doing, this was unacceptable.
Lin: Can you tell me specifically what was unacceptable? [Ask for specifics]
Workable compromise
When others become frustrated, try to find a way to compromise so that they may be satisfied.
This process of compromise is also integral to effective teamwork.
Example: Lin having asked her boss what was unacceptable, the conversation continued.
Kamil: The delay in getting back to Jim was unacceptable, he should have been a top priority.
Lin: Yes, I agree. I did try and contact him earlier but he was not at his desk, and I should have tried
again yesterday. I will make sure he is a priority in the future. [Workable compromise]
Threat
Sometimes, we may feel that it is appropriate to make others aware of the consequences of
their actions. However while threats can be useful, this assertiveness technique should be used
carefully, as the other party is likely to resent being threatened. It is best to use threats as a
last resort and ensure that you are able to carry out any threats you make. Preferably, when
using the ‘threat’ technique, also offer a ‘carrot’ to go with the ‘stick’. This gives the other
person positive options (Eunson, 2012, p.300)
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Listening Skills
Listening is one of the most important communication skills for any professional, as it can
allow:
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Understanding the full detail of a situation
Opportunity to learn and develop
Let others work through and resolve their own issues
Makes others more likely to listen to us
Below are some techniques on how to develop listening skills.
Listening and Power Dynamics
Listening abilities in communication can vary with power and gender dynamics. For example,
high- status individuals are more likely to interrupt low-status people, than vice versa. Also,
previous research (Atwater, 1991) demonstrated that men were more likely to interrupt
women, than vice-versa. These tendencies are worth keeping in mind as we audit our listening
skills.
Non-verbal Communication as a Listening Technique
Non-verbal cues such as facial expressions and body language are important aspects of both
interpreting others’ communications. This involves:
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Listening to their words
Observing their non-verbal behaviour
Evaluating whether the content of their communication (the words) match the
behaviour
Listening Responsiveness
Non-verbal cues can also make our own communications more effective – while listening. We
do this by giving the person we are listening to non-verbal feedback, to demonstrate our
attentiveness. Following are some good examples of effective ‘listening responsiveness’
techniques are (Eunson, 2012, p.315):
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Nodding our heads
An attentive, upright, slightly forward-leaning posture
Orienting our body towards the speaker
Using our facial features, including Raising our eyebrows ,Smiling (or frowning)
Making direct eye contact
Mirroring the facial expression of the speaker
Making appropriate “friendly grunts” (“uh-huh,” “mmm-hmm”)
Effective Listening Barriers
To listen effectively, we have to engage ourselves with listening to the speaker – even when
they may be boring. We can also use clarification questions, as discussed in questioning skills.
Eunson (2012, pp.318-319) suggests several barriers to effective listening, including:
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Changing the subject
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Not paying attention by daydreaming or becoming distracted
Focusing on the facts being communicated without paying attention to the thoughts
or feelings of the speaker
Attempting to ‘mind read’ by over-thinking/interpreting the speaker’s words
Letting our judgment interfere with receiving the message, for example, by
stereotyping or fixating on issues on which we have strong opinions
Rehearsing our response when we should be listening
Active Listening Techniques
Active listening is a communication skill using minimal verbal responses to spur the speaker
to articulate and clarify their meaning (Eunson, 2012). In many respects, this is a two-stage
process of listening to the speaker and then seeking feedback from the speaker to ensure that
we have adequately understood. This process involves (Eunson, 2012, p.319):
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Clarifying the speaker’s meaning
Checking the accuracy of what the speaker has said
Summarising back to the speaker what they have said
Acknowledge what the speaker has said without making any kind of commitment
‘Open a door,’ prompting the speaker to continue
Questioning Skills
Finding useful responses with effective questioning techniques is a valuable professional skill.
As speakers (or listeners), we need to know the types of questions we can ask and match them
to the situation and the people we are communicating with. Eunson (2012) suggests a number
of several questioning types, including:
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Direct probe – a direct, perhaps blunt question, without the subtlety, often involved in
seeking information
Open – a question with a broad response scope – rather than just ‘yes’ or ‘no’. .’ese
tend to start with: who; what; when; where; how? These questions allow responders
to tell their story
Closed – questions seeking a limited response, most often ‘yes’ or ‘no,’ to confirm
specific information
Objective criteria – questions that focus on the objective facts, to defuse any
contentious situations
Testing – when we already know the answer but are testing the responder’s
knowledge or skills. Softening up – these questions allow us to ‘soften up’ our
audience by building rapport or flattering. Often we will already know the answer to
these questions
Hypothetical – ‘what if’ questions allow exploring options without binding the parties
involved
Reflective – a reflective question reflects the other person’s feelings to them, giving
them feedback that these feelings are acknowledged
Leading – more than a closed question, a leading question suggests the response – in
this regard, it is extremely limited as it only seeks the response we wish to hear.
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Using Open and Closed Questions in Information Seeking
It is important to use the right question for the right circumstance. For example, as a leading
question suggests the answer, it can be restrictive as we may not have an opportunity to hear
the full response people want to give. They can feel manipulated in some circumstances.
‘Closed’ and ‘open’ questions provide another excellent example. Questions may exist on a
spectrum from open to closed, which is helpful, for example for information seeking, both for
this unit (research and interviews) in seeking information from colleagues, clients, and
partners in our professional careers.
Open questions are useful when we meet someone for the first time or are working through
an issue for the first time; open questions can help us break the ice and build rapport.
Open questions are particularly useful because they allow broad responses, making them very
effective. Open questions can help ensure we don’t miss important aspects by becoming too
closed too quickly – however, they will not be as appropriate when seeking a specific, direct
response.
Open questions are particularly useful in the early stages of information gathering, using
phrasing which spurs a broad, discursive response: Who? What? When? Where? How?
Closed questions, at the other end of the spectrum, have a limited range of responses, often
to ‘yes’ and ‘no’ – though they may allow a range of responses, it is a limited range. The key
distinction from open questions is that closed questions are less likely to spur a broad
discussion.
Closed questions can help establish facts, get commitments or choices from people, and
sometimes help us achieve closure or precision.
However, keep in mind that closed questions can be a little bit too blunt to help build rapport
with others and that when seeking information, moving to closed questions too quickly may
result in missing out on important information.
Feedback Skills
Effective feedback gives the recipient advice, support, or constructive criticism. However,
when feedback is used or viewed as a punishment, it is not likely to be productive (Eunson,
2012, p.323-324). Accordingly, we must manage our tone when delivering feedback and try to
maintain a positive perspective when receiving feedback. Effective feedback includes both
positive and negative aspects. For feedback to be constructive, it ought to be (Eunson, 2012,
p.324):
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Fair
Accurate
Specific
Formally structured
Solution oriented
Focused on behavior, not personality
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In contrast, when feedback lacks these attributes, it is destructive and not likely to lead to
improvement. Effective feedback is assertive and clear, without being aggressive or
manipulative (Eunson, 2012, p.327).
The Ideal Ratio of Positive-to-Negative Feedback
In professional (and personal) life, positive and negative feedback is integral to working
productively with others and achieving the required outcomes and improvements.
Interestingly, research suggests that the ratio of positive-to-negative comments significantly
influences productivity and effectiveness (Losada & Heaphy, 2004).
According to the research, the highest performing teams experienced a ratio of positive-tonegative comments of 5.6:1, while poorly performing teams averaged a ratio of 0.36:1 (Losada
& Heaphy, 2004).
This is worthwhile remembering and applying in our professional capacity – in order to fulfill
this ‘5:1′ ratio, making a habit of giving our colleagues positive feedback helps to build the
positive side of the ratio so that we can provide negative feedback when required without it
having a negative effect on productivity and effectiveness.
Intercultural communication skills
There are four types of multicultural communication challenges in a workplace.
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Direct versus indirect communication.
Trouble with accents and fluency.
Different attitudes toward hierarchy and authority.
Conflicting norms for decision-making.
What does it mean exactly to have intercultural communication skills? It means the
communications skills are those required to communicate or share information, with people
from other cultures and social groups, in which you need the following:
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You understand that different cultures have different customs, standards, social
mores, and even thought patterns.
You are willing to accept differences and adapt to them. There are several techniques
to develop intercultural communication skills, which are given below.
After every intercultural communication situation, carefully reflect on its outcomes
Ask yourself questions like the following
what behaviors did the other side use that confused me/that I didn’t understand?
how did the other side perceive my behavior?
Effective written communication skills
Communication does not only involve face-to-face interaction but also includes writing. In
professional practice, we will always be required to write emails, reports, and memos to our
colleagues, bosses, or clients.
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We share below basic techniques for you to apply in developing practical written
communication skills. We categorize it into the following steps.
Organizing your content
The first thing before you get started is to organize your content by the following:
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Identify your intent and objective – Why do I need to write this, and what do I aim to
achieve?
Research your audience – Who should be reading this? Would they even care to read?
What is the organization’s objective?
Strategize your content - What is the main message you want to convey to the
person/organization. How do you get or convince this message?
Structure your content - Identify the flow of your written communication so that it
tells an exciting story, clear and concise of the purpose of the communication and what
you seek from the other person.
Once you have organized your content, the next is to write it in a logical structure generally
should be as follows:
Figure 1. A sample of a professional email structure.
It’s straightforward! This is why intrapersonal skills are important. You can only be clear in
your writing if you are clear about what you aim to achieve.
But there are other details you need to pay attention to when writing using emails. Below are
some tips for effective business emails.
23
Reference to link here.
But that’s only one part of professional writing. The other major part is how do you write it?
These are the tricky bits and require practice and overtime experience to improve your written
communication, which will turn in the next section.
Develop your writing
There are no easy ways to communicate more effectively in written text. However, there are
a few techniques you can apply to get there.
•
Research basic writing principles
One of the best ways is to attend online short courses or read books on how to write
professionally that cover the basics of advanced grammar, spelling, and general
writing.
Another way is to find an English native speaker friend or mentor (but make sure they
are good communicators). That is how I improved my writing. I used to write to my
American computer scientist mentor during my University days (even today). I
learned how to write by analyzing how he wrote, which was very clear and concise.
24
Our years of exchanging messages have shaped me to become more proficient in
professional writing. Another way of learning is through observing and analyzing
how professionals do it by interacting with them, which is far more fun and engaging.
•
Practice as much as you can
Once you have a basic understanding of what you learned in your research, reserve
time to practice it; writing is a difficult skill that develops over time as you use it.
Implement what you learn within your emails, announcements, or any other written
correspondences you create at work. If you ever encounter a word, phrase, or whole
sentence that doesn't sound correct and can't find a solution, revert to step one. Look
up your specific issue and find a new way to write it.
•
Read as much as you can
One of the best methods of improving your writing is to read. Look for online blogs
that use a professional writing style. Sites that cover business resources are great places
to start. Scour their content and take note of their verb tense, sentence structure and
other stylistic elements. Additionally, seek out possible mistakes. There's no better
way to test your skills than to identify errors in others' work and determine a solution.
You will learn how to apply this in your tutorial worksheets and assignments.
Key takeaways
•
•
•
•
•
Effective communication consists of both verbal and written
Effective verbal communications require the development of both intrapersonal and
interpersonal skills
Intrapersonal skill is about how well you have self-awareness of your actions and
attitudes
Interpersonal skills refer to the skills in interacting with others. Some of the
interpersonal skills you need to develop in the unit are assertiveness, listening skills,
questioning, feedback, and intercultural communication skills
Professional written communication skills consist of techniques in organizing your
intention, aims, and content in a manner that demonstrates clear and effective
communication.
Summary
What we have learned in this chapter is the simple diagram below.
25
Figure 2. The diagram to briefly summarized chapter.
Figure 2 will help you categorize the concepts you have learned in Chapter 2; please go ahead
and fill the rest of it. This is a technique that would help you understand better that is by
categorizing the concepts you have learned and listing down the techniques/methods for
each. When you do this, it becomes easier for you to plan how to put into practice, especially
for your group assignments.
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Chapter Three
Oral presentation
I am sure most of you have watched someone famous on stage presenting a topic or on
Youtube. What you have observed is known as an oral presentation. This is the part where we
most often get very nervous, going up front in front of an audience, be it small or large, and
presenting a topic.
Oral presentations, also known as public speaking or simply presentations, consist of an
individual or group verbally addressing an audience on a particular topic. This aims to
educate, inform, entertain or present an argument. Oral presentations are seen in workplaces,
classrooms, and even at social events such as weddings. An oral presentation at a university
assesses the presenter’s ability to communicate relevant information effectively, interestingly,
and engagingly.
Oral presentations are one of the most common assignments in college courses. Scholars,
professionals, and students in all fields desire to disseminate the new knowledge they
produce. This is often accomplished by delivering oral presentations in class, conferences,
public lectures, or company meetings. Therefore, learning to deliver effective presentations is
a necessary skill to master both for university students and future endeavors.
27
Sometimes, you may be required to present as part of a group to test your ability to work as a
team member.
In this chapter, we will teach you the stages required to develop, plan, and present, including
the use of visual aids. Visual aid is an item such as a slide designed to supplement written or
spoken information so that it can be understood more easily.
Strategies for developing effective oral
presentation
These four steps are involved in strategizing your oral presentation so it can be delivered
effectively.
The steps involved are illustrated below.
Figure 3. The four steps to the effective oral presentation
In the following subsection, we will detail what you need to do at each stage.
The planning
Oral presentations require a good deal of planning. Scholars estimate that approximately 50%
of all mistakes in an oral presentation occur in the planning stage (or rather, lack of a planning
stage).
We have prepared a checklist for you for the planning stage. You can use the template below
to fill in the information you have found for the planning stage.
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Figure 4. Planning checklist
The planning requires some research to be done about the occasion which you will be
presenting. We will teach you how to conduct research in Chapter 4.
The checklist will guide you in collecting necessary information before you go to the next
stage, the development of the content of your oral presentation.
The development
The development stage is when you focus on content curation. The information you gathered
from the planning stage can now provide you with a better strategy, the type of content, and
how it will be presented to the audience. Similarly, we have prepared a checklist for you to
use in the development of your content.
Figure 5. Development checklist
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At this stage, after the content has been identified and developed, is to start creating the use
of visual aid (i.e., presentation slides) to support the presentation. We will speak about this in
the following sub-section
Using visual aids
Visual aids are precisely what they sound like visual support for you standing up and
speaking.
Visual aids can powerfully help the effectiveness of a speech. Many speeches benefit from
having objects, images, key quotes, or data presented clearly and dramatically. Visual aids
vary in kind, but there are similar benefits and tips for dealing with any type of additional
evidence that is shown to an audience.
Moreover, they become vital when it is necessary to present information that can only be
described in a visual format, such as a product (mobile App, websites, algorithms). To use an
obvious example, if you are giving a speech to a company's board of directors on the plans for
a new building, it would be essential to have a picture or some visual aid to accompany your
speech. Yes, it would be possible to give an audible only speech about the new building's
plans, but it would be highly ineffective to do so. Occasionally, a visual aid is a necessary
component of your message.
When giving a speech, you ideally want the audience to pay complete attention to your voice
and message. A visual aid invites them to pay attention to something else, even for a moment.
Therefore, this visual aid must reinforce your message.
Reasons to use visual aids
• Improves audience understanding and memory
• Serves as notes
• Provides clearer organization
• Facilitates more eye contact and motion by the speaker
• Contributes to speaker credibility
Types of visual aids
People
Maps
Objects
Charts
-flow
-tree
-sequence
-pictographs
-flip
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Graphs
-pie
-bar
-line
Photographs, Pictures, Diagrams, Sketches, Prototypes
Projected Images
-overhead projectors
-Powerpoint presentation
-film
In this chapter, we will look at two main types of visual aids that you will learn to develop in
the unit – Powerpoint presentation and prototype.
Adapted from here
PowerPoint Presentation as a visual aid – Minto Pyramid Principle
Many online resources provide tips for creating an effective PowerPoint presentation as a
visual aid. However, before we discuss that, there is a step that you need to master the skill
from developing the content and “transferring” it to the PowerPoint.
To do this, we refer to the Minto Pyramid Principle by Barbara Minto. The concept was
documented in her book published in 1985 titled; The Pyramid Principle: Logic in Writing and
Thinking. The Pyramid Principle can be used for structuring communication to have a
meaningful impact. The structured format in which the communication relays the answer
before facts and data can help create an environment where critical thinking can be stimulated
at the very start instead of the end.
The Pyramid Principle presents the answer initially, followed by supporting arguments, data,
and facts.
The information is presented in a pyramid, with the core idea at the top, which is then broken
down by revealing fine details. The top of the pyramid contains the answer, which is the
starting point. The middle of the pyramid represents supporting arguments. At the same time,
the bottom of the pyramid gives the supporting data and facts.
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Figure 6. The Minto Pyramid Principle- structuring your content logically and strategically.
The Answer
When sitting through a lengthy PowerPoint presentation bloated with facts and data and a
leading conclusion, one can feel unsatisfied with the presenter. However, when given the
answer at the very beginning, you might feel a need to think through its merits from the very
start. As you are presented with supporting arguments and facts, you can determine whether
you agree or disagree with the statement or feel a need to raise essential questions.
This approach makes it possible to aid structured thinking and stimulate critical thinking at
the start of a presentation or when reading a report or research, rather than feeling that you
are being led towards a conclusion with convoluted information.
Supporting Arguments
Once the audience has been answered at the start, they can begin critically analyzing the
supporting argument. This is the second stage of the Pyramid Principle, where the answer is
supported with relevant ideas to help test the hypothesis’s validity or present it for critical
analysis.
Supporting Data and Facts
Unlike conventional approaches to presenting data, the Pyramid Principle makes it possible
to see supporting facts and data after a hypothesis. Rather than wondering what the long bits
of information might be leading to. The one reading through the news or sitting in the
audience does not need to wonder about the suggested conclusion, as it has already been
presented at the start. They enable critical analysis of the data and facts as given.
It was adapted from here.
How to apply the Minto Pyramid Principle to developing your presentation
When using the Pyramid Principle, you must start with the statement and break it down with
supporting arguments backed by facts and data.
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A statement is a sentence that says something is true (an answer you have found from your
planning stage using research skills – to be taught in Chapter 4).
Your audience would likely want to ask tough questions during the presentation. Using this
concept, you can enable those questions to be asked sooner and provide your breakdown of
the statement in a structured manner to ensure all your arguments are covered.
Begin with the Statement as the heading of a presentation slide
It is common to present the statement at the end after data, facts, and ideas related to the
statement or hypothesis have been given. The Pyramid Principle flips this conventional
approach by providing the statement at the beginning.
Presenting the statement at the start will stimulate critical thinking and aid structured
communication, where there might be people for and against the argument scrambling to ask
tough questions. That’s one of the benefits of the Pyramid Principle, as it helps bring out
critical questions from the very start instead of at the end of a bloated presentation or report.
Present Arguments to Support Your Statement
It is essential to back the statement with supporting arguments to enable a meaningful
discussion or raise critical questions regarding its accuracy. This can have dire implications
for businesses, and significant investment decisions might hinge on such information.
Present the Data to Support Your Argument
A supporting statement is only as good as the data and facts presented to back it up. Therefore,
the pyramid’s bottom is the foundation of the Pyramid Principle. The foundation needs to
contain accurate and reliable information to back the statement. Now, this is why you need to
have research skills, to find the truth of an issue and evaluate whether the data you have found
is reliable and accurate. We will look into research skills in Chapter 4.
It was adapted from here.
Example of a slide applying the Minto Pyramid Principle
We show a straightforward example below of how the content you have prepared can be
developed into a presentation slide in Figure 7.
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Figure 7. An example is using the Pinto Pyramid principle.
Of course, the argument can be more substantial and elaborated, including presenting several
more data to support it. The citation technique would be covered in Chapter 4.
Writing (narratives)
Now that you have identified and listed down the points and content of your presentation, it
is time for you to write out the narratives (i.e., scripts). One key point to emphasize is that it
is common for you to shift back and forth between the development and narrative stages. You
may find that you will return to the slides and refine the content when you start writing your
script.
We will go through some techniques in how you can prepare the script (narratives), which
should be based on your presentation slide.
1. Finalise the PowerPoint presentation into a storyboard
Planning is everything when it comes to writing a script for a presentation. To make the
content flow naturally, a speaker needs to be well-prepared with enough time ahead of the
event for them to practice.
To achieve excellent presentation content, a clear and concise presentation needs to be
finalized, and it can be done by finalizing your slides into a storyboard.
A storyboard is a series of ordered drawings, content, images, dialogues, or other details. It is
called to tell a story, and narratives tell a story of what you did in your work or assignments
during the presentation.
Using a storyboard makes it much easier to plan the length of the presentation along with its
content. It also creates a guideline that will enable the speaker to direct the audience from start
to finish.
2. Stick to the slide content
A key point to remember is that the content of your slides must provide the foundation of
your script. When you begin writing, it can be easy to follow the flow of ideas to create a script
that reads wonderfully on its own. You can’t forget that this must tie directly into the
presentation content you have already storyboarded.
Writing a script for a presentation that doesn’t match the content will leave the audience
feeling confused. As the script starts wandering off into tangents that do not relate to the
slides, the crowd will quickly lose their place, and their concentration will soon follow.
An easy way around this is to write the script with the presentation content close to hand.
Break down the words into sections that reflect the order of the slides so the two always
perfectly complement each other.
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3. Remember to add in some pause breaks
When an audience attends a presentation, they have two tasks to juggle: firstly, to digest the
words being delivered by the speaker, and secondly, to understand the information provided
by the presentation content.
It’s essential to place yourself in the audience’s shoes to remember this when writing a script
for a presentation. You want as much of the information you are providing to be taken in by
the audience, which means you need to factor in some time that will enable them to process
your words and the visual data.
Writing pause breaks into the script plays a crucial role in achieving this. When the speaker
pauses, it gives the audience a moment to reflect on what has been said. It also allows the
speaker to create a rhythm of speech and control the audience’s attention from start to finish.
3. Write, practice, iterate, and repeat
Once your script is ready, you will need to set aside a reasonable amount of time to practice
it. Don’t forget; the script is one half of the content you will be delivering to the audience, so
you should always practice the material alongside the finalized slides, as this gives you a
better feel for how it all comes together.
This also allows you to make final tweaks and changes to the script and physically practice
how you will deliver it on the day. You can then rehearse the way you stand, your eye contact,
and the management of your overall body language in front of an audience.
It is also worth remembering that when you write a script for a presentation, it will be written
more formally compared to the way you naturally speak. If the hand isn’t changed to reflect
this, it will sound unnatural and awkward, and the audience will pick up on it quickly.
Once you have completed your script, use the checklist below to ensure you have not missed
anything while narrating the content.
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Figure 8. The narratives – script checklist
Refer to the link below for samples.
Sample presentation script
Oral presentation script
The delivery
Below are some tips to get you ready to deliver your presentation.
Dress appropriately
Dress appropriately for the presentation, based on the context, disciplinary protocols,
formality of the occasion, and the type of audience (faculty, students, clients, etc.). Do not
wear inappropriate clothing, jewelry, hats, or footwear that distracts you.
Arrive early
Arrive early for the presentation, and do not arrive just in time or late.
Meet the moderator/the person in charge (your lecturer, tutor, etc.)
If there is a presentation moderator who will introduce you, meet that person well in advance
of the presentation so they know you are in the room on time and that you will be ready.
Decide how to handle audience questions.
Decide how you will handle questions during the presentation. Either request the audience to
wait until you are finished with your presentation or make sure you have time to answer the
question in the middle of your presentation.
Have a plan if the technology fails
Similarly, decide how you will continue your presentation if the presentation technology fails
or freezes in the middle of your presentation.
Load your visuals before your allotted presentation time
If you plan to use presentation tools, load your presentation or connect your presentation
device to the projector before you are asked to present so you do not use up your presentation
time to pack your files and make the audience wait.
Smile
Be pleasant and smile when you stand in front of an audience, making the audience feel
comfortable listening to you.
Don't eat or chew gum.
Do not chew gum or eat during your presentation. You may drink water or other allowed
beverages during the presentation.
Take a deep breath
Before speaking, take a few deep breaths and calm yourself.
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Speak clearly
Speak slowly and clearly, and do not rush through sentences, as some do when they get
nervous.
Speak at an even pace
Pay attention to the pace at which you speak to avoid your speed of delivery being either too
fast or too slow for the audience to follow.
Change the inflection of your voice to gain audience attention or to emphasize content.
If you are trying to make a point about a particular idea, enunciate or pronounce the words
clearly and distinctly. At this point, you can slow down and raise the volume of your voice to
express what you have to say clearly. Speak with authority, confidence, and enthusiasm.
Use appropriate gestures
Use appropriate gestures to emphasize appropriate points, and do not make wild gestures or
pace back and forth in front of the screen in a distracting manner.
Make proper eye contact.
Make proper eye contact: look at the audience from one side of the room to the other and from
the front to the last row. Do not look down the whole time, and do not focus on just one side
of the room or the front row of the audience.
Stand beside the screen.
If you plan to use projected visuals on a screen, stand to one side of the screen. Ideally, you
should be facing your audience at all times and just glance at the screen to look at cues from
the slides.
Do not talk to the screen or board.
Do not talk to the screen or the presentation device; look at the audience and talk. It is alright
to look at the screen occasionally and point to something important on the screen as you
present.
Do not read line-by-line.
Do not read presentation materials line-by-line unless someone in the audience is visually
impaired and cannot see the slide or if it is a quote you must read verbatim to emphasize.
If you get stuck, look at your notes.
If you get stuck on a point and do not know what to say, feel free to look at your notes to
continue.
Use the microphone effectively.
If you are presenting in a large room where a handheld microphone is needed, hold the
microphone near your mouth and speak directly into it.
Do not curse or use inappropriate language.
Do not curse or use inappropriate language if you forget a point during the presentation or
the presentation technology fails.
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Be considerate of your team.
If you are part of a team and giving a group presentation, be considerate to other team
members by not using their time or dominating the presentation. Smoothly transition from
one presenter to another.
Do not conclude abruptly.
Do not conclude the presentation abruptly by saying, "This is it" or "I'm done." Conclude
properly by summarizing the topic and thanking the audience for listening.
Be considerate of the next presenter.
After your presentation and the question and answer part, remove your presentation
materials from the desk or the podium. Close any open presentation software so the next
presenter can get ready quickly.
Thank your moderator
Remember to thank your moderator (if there is one) and the audience; if you were part of a
panel presentation, make sure to thank the panel members.
Adapted from here. You may view sample videos to guide you on delivering effectively on
the website.
Phew, that is quite a lot to absorb, isn’t it? If you want to quickly get ready to deliver, refer to
the checklist below.
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Figure 9. The delivery checklist
Key takeaways
•
•
•
•
Oral presentations, also known as public speaking or simply presentations, consist of
an individual or group verbally addressing an audience on a particular topic. This
aims to educate, inform, entertain or present an argument.
Visual aid Visual aids are precisely what they sound like visual support for you
standing up and speaking, and they may be in the form of graphs, charts, photos,
presentation slides, or prototype
There are four steps involved in making an oral presentation - planning, development,
narratives (script), and delivery.
Minto Pyramid Principle is a method to structure your content into a PowerPoint slide
in a logical and coherent manner.
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Chapter Four
Professional Research Skills
I started learning how to do research during my undergraduate thesis project. My first
research project was on developing keystrokes dynamic using neural networks. I choose the
subject because I was interested to learn machine learning however it was not taught in any
units at that time. I followed the techniques on how to do research and was successful at
learning on my own about neural networks. I got an A+ for the project, and it led to my first
ever international research publication in an AI conference.
Ever since then, I constantly refine my research skills because it has given me the capability
to develop own projects that I am interested in and pick up new topics by self-learning.
Research skills equipped me with developing my life-long learning skills.
In this unit, you will be required to develop your research skills in all your assignments. You
would be required to research a problem, understand the problem, find out how to apply the
methods we taught you in this unit, and propose and develop prototype solutions for the
problem you have researched.
So what are research skills? Why is it important to develop right now, and why is it relevant
in a workplace? How different are the research skills taught in this unit compared to what
you learned in school or college? We will address these basics in the next sections.
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What are research skills?
Research skills can be described as providing in-depth information, detailed analysis, and
useful advice on a given topic after researching extensively. It includes formulating the
problem statement, referring to good sources, and explaining your findings and observations
in the form of a report.
Why Are Research Skills Important?
Research skills enable people to identify a problem, collect informational resources that can
help address the problem, evaluate these resources for quality and relevance, and come up
with an effective solution.
There are important for a variety of reasons:
•
•
•
•
•
Develop new processes and outcomes. You don't have to be involved in research and
development to improve your team’s work. Any sensible employer will value your
efforts in researching new processes that will make your job (and your team) more
efficient.
Personal Growth. People who have a knack and a passion for research are never
satisfied with doing things the same way they've always done them. Organizations
require independent thinkers who will seek their answers and continually improve
their skills. These employees will also learn new technologies more quickly.
Customer relationship management. In almost every industry, being able to research
your customer base is critical. Moving products or selling services is difficult if you
don't know what people want. It is a valuable responsibility to research your customer
base's interests, needs, and pain points.
Cost Effective. Whether your organization is launching a new product or simply trying
to cut costs, research is critical for identifying wasted resources and redirecting them
to more worthy causes. Anyone who goes out of their way to find ways for the
company to save money will be praised by their boss.
Competitor Analysis. Knowing what your top competitors are up to is crucial for any
company. If a company wants to stay functioning, it must research what works for its
competitors, what they do better than you, and where it may improve its standing
with the least resources.
Effective research skills also rely on you having other transferable skills, such as:
•
•
•
•
•
•
Managing your time.
Communicating information clearly and simply.
Presenting information.
Taking initiative.
Lateral thinking.
Problem-solving
It was adapted from here.
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Methods for developing research skills
In this unit, we will use the intelligent research cycle method to guide you in developing your
research skills.
The intelligence cycle is a model that describes the process by which data and information can
be meaningfully converted or developed into “intelligence” that will benefit the organization
or the nation.
The intelligence cycle is an iterative process by which information is gathered, analyzed, and
produced following the below process:
•
•
•
•
•
•
Direction and planning of the activity.
Collection or gathering of data and information.
Processing of data and information.
Analysis
o Evaluating sources
o Integrating information sources
o Acknowledging information sources
Dissemination
Feedback
We will elaborate in detail on the phases in the following sub-sections.
Direction and planning of the activity.
Direction or planning of the activity would require you at this step to identify the
requirements of the work or project.
The requirements will involve identifying the needs, objectives, or aim of the work or project
given in an organization by clients or supervisors/boss. The requirements usually result from
understanding the scope and outcome expected by work or project. This could be done by
reading through the documentation provided for the project, including asking effective
questions to address any disparity in understanding the direction and expected outcome. It is
useful to go through all the work or projects required for you to undertake before you begin
the research activity.
How to apply this process in your project assignment
In your assignment, you would apply this step to identify the requirement of each of the
project assignments provided. Remember that each project is a continuation from one to the
other. You would be required to understand each project assignment's objective and expected
outcome
After you have understood the direction of the project, you should then highlight key concepts
that you must research, including any techniques or methods required to produce the project
outcome. The list would help you to direct you to the next process.
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Collection or gathering of data and information.
The data and information necessary for the project or work can be retrieved from various
sources.
At this stage, it is important to develop a collection plan. This plan will include the relevance
of available sources and methods mapped to the specific requirements you have to fulfill.
Some requirements will be better met by specific collection types, while others may need
several types of information gathering. Again, these decisions on collection capabilities are a
key issue since the decision of how much can or should be gathered to meet each requirement
must be made.
Learning the search operators will improve your search results whenever you search for
information in an online system. Search operators give you greater control over your search.
They help maximize the number of useful search results and filter out less relevant results.
Every search engine or database will have its search operators. Many systems use a variant of
Boolean search operators. If searching Google, use the Google search operators. If searching
in Monash University Library databases, learn effective search strategies.
Processing of data and information.
Processing and exploitation of the information that has been gathered potentially produce
intelligence. That is, the collected information in the previous stage is not intelligence. It is
only after the effective analysis that the product of intelligence is made available.
Transformation of large volumes of data to a form appropriate for the production of
intelligence that can be used effectively in an organization includes:
•
•
•
•
Translations.
Application of highly technical photographic and electronic processing.
Data reduction through statistical procedures.
Categorization of raw data used in training of artificial intelligence methods
The relevance and reliability of the collected data and information need to be evaluated to
determine the value of pursuing that line of exploration.
This stage will apply if you are dealing with data you need to collect for machine learning
techniques, or cybersecurity projects. For example, you may need to produce a report on bias
in machine learning techniques. You need evidence that data used in the machine learning
training contains bias. Therefore, you need to download, process and categorize these data for
your next process - analysis.
Analysis
Analysis and production of the output from processing will include integrating, evaluating, and
analyzing all available data and information. Analysis establishes the significance and
implications of the processed information and integrates it with other incongruent items of
information to identify patterns. These patterns can be interpreted in terms of the significance
of newly generated knowledge within the direction or requirements of the project.
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The analysis is initiated by some need or desire to know the components and dynamics in
greater detail than is at first evident. Thus, main activity is seeing more deeply, more closely,
and in greater detail.
Much of the art of analyzing is finding the right subject to analyze - interesting enough to tell
you what you want, but not too complicated to make sense of. An analysis may require several
levels or aspects of examination. Having seen a problem or issue at one level, you may decide
to look more deeply to find what you need.
For example, to understand a computer program, you need to know its parts; to understand
how to build a bridge, you need to know the components that give it strength; to settle a
philosophical argument, you need to know the issues that contribute to the larger problem.
Analysis is crucial to producing in-depth research because they frequently want to
understand why things happen as they do, so they open up the hood and look inside to see
the parts. The analysis looks for those things that are not obvious on the surface, that s be
hidden to casual inspection.
At this stage, you will then be a be able to understand the cause of an issue and propose a
solution.
An example of an analysis of patterns
Let us look at the example of Cambridge Analytica scandal. After looking at the current data
collected by Facebook for political campaigns, the researcher found no clear pattern of how it
was used to influence the US presidential election and Brexit. However, when looking deeper
into the data for patterns, Cambridge Analytica used Facebook’s data to categorize people
into groups based on political ideology. That was the significant pattern discovered - at the
level of data, how and what is being collected, categorized and the actions performed on those
data constructed.
The pattern showed that data collected by Cambridge Analytica was constructed with details
of the person’s photo, where she works, where she lives, who are her kids, where they go to
school, the car she drives, who she had voted, who she likes. The patterns of data also revealed
all these data were merged with all commercial and state bureau data. These data included
mortage application, how much money she made, whether she owned a gun.
From this, the data was unpacked to analyze qualitatively the perceptions of a given
population and learn what people cared about — term limits, the deep state, draining the
swamp, guns, and the concept of walls to keep out immigrants were all explored in 2014, years
before the Trump campaign. Then a hypotheses was formulated on how to sway opinion.
Based on the data, Cambridge Analytica tested these hypotheses with target segments in
online panels or experiments to see whether they performed on the expected data. They also
pulled Facebook profiles, looking for patterns too build a neural-network algorithm that
would help them make predictions. Cambridge Analytica would target those who were more
prone to impulsive anger or conspiratorial thinking than average citizens, introducing
narratives via Facebook groups, ads, or articles that the firm knew from internal testing were
likely to inflame the very narrow segments of people with these traits. It wanted to provoke
people, to get them to engage.
You may find the full article here to give you an idea the kind of analysis that could provide
deep insights into the working of what and how techniques are used on data is the cause of
negative social impacts in using AI in social media.
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In the next sub-sections, we provide basic techniques to get you started on the analysis process
below.
Evaluating sources
Information only has value if you can critically evaluate its credibility. If you trust all the
information you find at ‘face value’, you might build your analysis on unreliable evidence.
You can assess the credibility of information by considering its attributes. The key attributes
of information are shown in Table 1 below.
Table 1. Criteria for evaluation of sources
Currency
How up-to-date is the information? Is the information still relevant and recent
for the topic?
Accuracy
Is the information correct? Can you assess how accurate the information is by
examining other sources of information as well?
Authority
Who produced the information (author/s or organization), and do they have
expertise in the topic? Does the information source provide credible evidence
to support its claims?
Accessibility How easy is it to find this information source or understand its content?
(e.g. is the information in a foreign or technical language, or hidden behind a
paywall?)
Stability
How stable is this information to remain the same over time? Is the
information or website volatile (e.g. updated or altered frequently) or stable?
Integrating information sources
Writing skills help you integrate information you have found into your own ideas. Two
key techniques for integrating sources into your writing are:
Quotation: using the exact words of another author or source within your text in
quotation marks
Paraphrasing: rephrasing words expressed by another author or source, to convey the idea
in your own words
Paraphrasing is a particularly helpful technique. It enables you to demonstrate your
knowledge of a source, integrate its ideas into the flow of your argument, or convey the
information in a more concise or understandable manner.
Whether quoting or paraphrasing another information source, you must acknowledge where
the ideas came from with a citation.
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Understand the problem -what, why and how from your own independent sources
After you have integrated the sources you found, you need understand what exactly is the
problem, why has it become a problem and how did it become a problem.
Problems could be identified by analysing the patterns of the information that you have
analysed from the sources and combining it with your own directed independent sources.
Usually, research is conducted to understand an issue and find a solution to it.
To evaluate whether the problem is worth pursuing is to further look at the trends. Is the topic
current (refer back to the criteria to evaluate sources).
Once you have established the problems, consider the related problems. This is when you do
your own independent research of sources. Consider different terminologies and
representations of the problem that you are trying understand. By changing the form of the
problem and trying to describe and represent it in different ways, you might find that your
problem matches a general problem that is already formalized.
For example, the problem of identifying whether an Internet service provider is intentionally
degrading performance might be referred to as a “treatment” of class of customers. That
terminology might make you think about “random treatment”, a process by which biologists
can determine whether a particular drug or chemical has any positive (or negative) effect on
a group of humans. Always think about what techniques is used. Remember you are all
computer science student, techniques should be your concern.
Next step is to understand the concept or techniques by analogies. Analogies are incredibly
powerful. We use analogies to learn all the time, because we learn a new concept best by
relating it to a concept that we already understand. Similarly, you can solve a hard problem
by relating it to a problem that you already know how to solve. Analogies often create the
biggest breakthroughs when they come from outside of your immediate discipline (these are
the conceptual blockbusters that other people often aren’t thinking of because they’re typically
not looking for solutions outside their immediate discipline). Computational thinking was one
highly publicized example of applying analogies to problem solving—the notion that
concepts that we learn in computer science (sorting, queuing, etc.) can help us solve problems
outside of the discipline. But, these analogies can also be applied in reverse. For example,
researchers have applied concepts from epidemiology to understand how computer viruses
spread. These analogies—when applied well—can also often point exactly to a solution, since
the solution that applies to the analogous problem can sometimes be translated to the problem
you are studying.
Finally, based on these thought processes, you then conclude with what is the problem,
why it is a problem and how did it become a problem.
.Acknowledging information sources (citations, APA)
Ethical research practice requires you to always acknowledge when you have used
information from another author or source. At Monash University, we refer to the ethics of
academic conduct as academic integrity.
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Failing to properly acknowledge your use of information or words produced by others is
known as plagiarism – which can carry heavy academic and professional penalties.
Citing and referencing is the primary technique for acknowledging your use of information
sources. Every claim or assertion you make in an assignment should be supported by a
relevant citation. Every information source you used in your assignment should be listed at
the end of the document in a reference list.
A range of resources can help you develop skills in academic integrity and citing and
referencing:
Monash IT Academic Integrity Moodle site
Monash IT Style Guide on referencing
Ask library staff for advice on your citing and referencing
In our unit, we will apply the APA citation technique. APA style uses the author/date method
of citation in which the author's last name and the year of the publication are inserted in the
actual text of the paper.
You may refer to more details on the APA reference style here
How to apply this process in your project assignment
In your project assignments, you will use the intelligent research cycle to plan appropriately
what is required in your research to deliver the expected outcomes of each project.
You will then gather information and data by using search engine, and analyse these data that
you have gathered using the key attributes of sources (Table 1) to evaluate. It is important that
the data you have gathered represents what is true about a certain issue, topic, or problems.
Your Week 4 tutorial would teach you how to analyse the information you have gathered,
present and write in a professional manner.
Dissemination
Dissemination is the process by which the finished intelligence product is passed to the
consumers or clients for application. The finished intelligence products can take many forms
depending on the requirements of the clients and its potential applications. The level of
necessity will have a bearing on the form of the intelligence product and this is usually
determined by the organization. At this phase of the intelligence cycle, producers or users can
reinitiate the first phase again, so that the cycle commences again.
Feedback
Feedback can be a further phase in the intelligence cycle where either the client or the decision
maker from the initial stage provides feedback to the team, where revised requirements of the
process are needed and a further cycle in the intelligence process is instigated.
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Chapter Five
Meetings
I have participated in variety of meetings in different cultures and organizational settings. In
my experience, the most effective meetings are with the Americans and Japanese. There are
also differences in how meetings are conducted in different organizations. In an academic
setting meeting, it could be very long, more detailed, and formal, and the decision-making
process takes longer.
The meetings also vary depending on the plan (goal) and who attends the meetings. If it is a
software meeting, the discussion would be on reporting issues and the required solutions. The
discussions will be on strategizing business operations if it is a business meeting.
In all these meetings I participated in, it was very important for me to understand the purpose
of the meeting. However, of late, I now have the responsibility to organize and chair meetings.
Sometimes it takes me about one week to plan – who to involve, whether it is the right time
to involve another stakeholder, what the discussion would be about, and most often, I prepare
presentation slides with bulleted points to ensure everyone will focus on the agenda during
the meeting.
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These are some of the work involved in ensuring one has an effective meeting. An effective
meeting can be evaluated when after the meeting, participants understand, are excited, and
there is a clear course of next action.
Thus, this chapter will introduce you to the types of meetings you will be involved in and
how to participate in and plan your meetings effectively. We will also cover techniques for
interviews.
What is a Meeting?
A meeting is where a group of people come together to discuss issues, improve
communication, promote coordination, deal with any matters that are put on the agenda, and
help get any jobs done. For any meeting to be successful, it needs the support of the group
involved or the organization behind it, and it must have the intention of achieving some goal
or objective.
We detail the types of meetings below.
Structure of Meetings
Meetings can be structured in many ways. They are structured in how you plan your
communications, whether it will be conducted as a formal or informal meeting.
Formal Meetings
It is a pre-planned gathering of two or more people assembled to achieve a common goal
through verbal interaction. Formal meetings are characterized by predetermined topics, a set
of objectives, and formal notices. These meetings are held at a specific time, at a defined place,
and according to an agreed agenda. Formal meetings are typically led by a chairperson, with
the discussions and agreements recorded in a written form known as meeting minutes. A
formal meeting is also known as a board meeting, a committee meeting, a caucus meeting, a
conclave, a congress, a council meeting, a stakeholders’ meeting as a summit meeting, or a
symposium.
Features of a formal meeting:
•
•
•
•
•
Are usually well structures
Have rules and regulations that provide the framework for the meeting
Are designed to allow all members to participate, but formal procedures generally
limit interactions
Generally focus on the leader who manages the meeting and the discussion
Will generate some final decisions, whereas other decisions may be deferred to later
meetings.
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Formal meetings will follow set procedures that are not always used for informal meetings.
The following three types of meetings are formal:
•
•
•
Annual General Meetings
Extraordinary General Meetings
Board Meetings
They all have:
•
•
•
•
•
A meeting agenda
A Notice of Meeting
Motions are put, discussed, and voted on following certain rules. A motion is a
proposal made at a meeting to be considered and decided upon.
Proposers and Seconders of motions have their names recorded in the minutes.
Structured meeting minutes are taken.
Informal meetings
“The majority of meetings are held informally and use the consensus method where the
participants discuss the agenda that they can all agree (or agree to disagree and can move
forward)” (Aldridge, 2013).
An informal meeting is a meeting that is far less heavily planned and regulated than a formal
business meeting and so lacks many of the defining features of a formal business meeting,
such as minutes, a chairperson, and a set agenda.
The main feature of an informal meeting is that it is unplanned. In addition, the agenda and
topic of discussion are not predetermined. The gathering and discussion occur in an
impromptu manner and setup. Participants are not informed of specific details such as time,
venue, agenda, or other requirements. The direction of an informal meeting can change
because there is no guiding agenda. This provides an opportunity for discussing various
topics from a general perspective because no specific results or outcomes are expected. Since
there are no expected outcomes, informal meetings do not require follow-up meetings to
evaluate the results of previous meetings. In informal meetings, no single individual is
directly in charge of directing the meeting, as is the case for formal meetings, where the
chairperson guides the agenda.
Informal meetings therefore are:
•
•
•
•
not well-structured
usually held to exchange information, solve problems, make decisions, and set goals
designed to be task-oriented with group participation, feedback, and interaction,
usually leading to the final decision and action.
not necessarily in a formal setting
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Purpose of Meetings
When meetings are managed properly, they can be a dynamic arena in which:
•
•
•
•
•
•
•
Problems are solved
Decisions are made
Actions are planned and taken
Information is shared
Group morale is boosted
Communication quality and quantity are maximized
Satisfaction, rapport, synergy, and effectiveness are experienced by all present
Well-run meetings are an effective way of:
•
•
•
•
•
•
•
•
•
Planning strategies
Providing and clarifying the information
Encouraging problem-solving
Coordinating efforts
Motivating
Allowing for exchange of ideas
Evaluating performance
Giving and receiving feedback
Building a team
“The meeting that drones on and on; the meeting where everyone sits fiddling with his or her
smartphone; the meeting that Doug from Accounting hijacks; or the meeting where almost
everyone in the room is wondering the same thing: Why am I even here?” Hartman (2014)
For many people, what Hartman describes is their experience of meetings. How can we
improve on this situation? We will discuss this in the next section.
How to Have a Successful Meeting
For a meeting to be successful, ten steps should be followed:
Define the purpose: What is the purpose of the meeting? What does it need to achieve?
Select the participants: Determine who needs to be there. There is little point in forcing someone
to sit through a long meeting when they could get the information they need from documents
emailed later or if the matter does not involve them.
Provide sufficient notification: People generally dislike being asked to attend a meeting at the
last minute (and they may already be busy). Give them time to organize themselves and fit
the meeting into their schedule.
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Prepare a realistic plan: Depending on the length of the meeting, the number of items you can
get through may be limited. Don’t try to cram too many things in.
Arrange a suitable venue: The venue should be accessible for all attendees. If it involves only
staff within the organization, a location at that organization may be ideal. If it is between two
or more organizations, a neutral location somewhere between the two offices may be better.
Follow proper procedures: Ensure meeting procedures are followed to keep everyone on track.
Provide prompt feedback to all participants: The meeting’s actions or results should be
communicated to the participants as soon as possible.
Prepare an action list: Outline who is responsible for jobs or tasks decided upon in the meeting.
Keep an accurate record: A person should be appointed to take notes of the minutes to ensure
that all information required and decisions made in the meeting are recorded.
Follow up: Check to make sure that those responsible for completing their tasks are on track to
complete those tasks.
Preparation
Before the meeting, you need to work out the following:
Why?
Clarify the meeting’s purpose. Is it really necessary? The purpose may be:
•
•
•
•
•
Information sharing
Decision making
Information dissemination
Symbolic
Social
If little information needs to be shared and it is relatively unimportant, it may be better to
distribute it via other means (such as email) rather than holding a meeting.
Who?
Decide who needs to be there. For some meetings, this is fixed and remains more or less the
same (e.g., board members, shareholders). If some people on the list are only there to obtain
information, they could get it another way (e.g., by looking at the agenda or minutes).
Consider who specifically needs to be there to:
•
•
•
•
Provide information
Offer advice
Offer specialized expertise
Authorise action
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When?
The length and timing of a meeting depend on several factors. For example, public or
community meetings should be held in the evenings (to allow for people who work full time
during the day). If a meeting is held within the organization, it should not be held too late in
the day (people are tired) or too early (people are not fully awake), and it should not go for
too long. Ninety minutes is about the maximum before people stop paying attention.
Where?
When deciding a meeting’s location, it is important to consider some territorial and nonverbal aspects. For example, a meeting in the boss’s office may feel more intimidating than a
meeting in a meeting room or some other external, neutral location.
What?
Before holding a meeting, you should always develop a plan or agenda to know what needs
to be covered and keep the meeting on track. Otherwise, you risk wasting time on
unimportant matters and running out of time to discuss key issues.
How?
You need to plan how you would conduct the meetings to yield to your specific
purpose/team’s/organisation’s purpose (i.e., the Why)?. For example, the meeting you
would like to hold is to get many different ideas, or the meeting you would like to hold is to
get decisions to be agreed upon by members.
To do this effectively, you must consider how you will conduct the meeting that leads to
your purpose.
Some elements for you to consider are tools (i.e., PowerPoint slides, post-it, online
collaborative tools) and seating arrangements (see below). You consider these elements to
plan how you can use them to plan your meeting(s) in a coherent and structured manner that
leads to your specific purpose.
For example, if you want to discover new App opportunities in the market, you can do this.
You would first organize a survey meeting with users. And then, you could organize a
brainstorming session with developers to brainstorm new opportunities based on the survey
using post-it on the wall.
Seating Arrangements
Venue selection is important, but so are the seating arrangements within that venue. Having
people sit at the table creates formality. All should be at an equal height. Some physical factors
should be considered, such as:
•
•
Sightlineses: Can everyone see everyone else?
Acoustics: Can everyone hear everyone else?
In addition to these physical factors, the physical layout of the table and where people sit
relative to each other can symbolize power dynamics:
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•
•
•
•
Long rectangular tables: “Traditional.” Such tables focus on power, with the leader
sitting at one end.
Round tables: Ideal. Everyone is evenly spaced and can see one another’s actions and
reactions. You can see from the picture below that each person can see the others at
the table.
Oval tables: A compromise between a rectangle and round tables
Square: If a square table is too large, it can be problematic for people sitting in the
corners
Meeting Agenda
When you have decided to have a meeting and have identified the objective for the meeting
and the participants required in the meeting, you need to prepare a meeting agenda.
A meeting agenda helps you and your colleagues prepare for a meeting and guide yourselves
through the items you need to discuss. Time spent in planning an agenda will likely save time
for all meeting participants by providing a clear set of topics, objectives, and time frames.
Some meetings may require more planning time than others. For example, a department-wide
retreat will probably involve several hours of planning by several people. At the same time, a
weekly staff meeting could be planned by one person in a shorter time.
A sample agenda with commentary on each section is below.
Figure 10. Sample of a meeting agenda
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Below you'll find a description of the parts of an agenda, tips for helping them work, and
additional resources for planning and facilitating effective meetings.
Parts of an agenda
Item
The item is easy; it's the content or topic to be considered. Ensure the right people are in the
room to achieve that item’s desired outcome. Meeting participants should have the proper
role in addressing the item (for example, the authority to decide if that is the desired outcome),
and the item should justify their attention.
Desired outcome
The desired outcome is the result you would like for your item. Clarifying the desired
outcome is perhaps the most important step in agenda planning. Defining your desired
outcome helps you think about priority, time, who, and how. Some examples of desired
outcomes include "an agreement about X," "a decision about X," or "a list of X."
Priority
We have found that items bearing "low priority" never get discussed, so all our items end up
medium or high. We have no objective criteria for these ratings. When planning for the
meeting, if the total time needed for high-priority items exceeds the meeting length, the group
should negotiate which items will be handled within the meeting time or consider lengthening
the meeting. Explain that any items withdrawn will get priority at the next meeting or find a
way to address those items outside the meeting.
Time
Projecting the time you need is easier if you've planned the "how" and "desired outcome" parts
of the item. Without that planning, it's easy to underestimate how much time is needed to
achieve the desired outcome. Even with planning, you may still underestimate in the
beginning, so increasing your projected times by about 33% may be helpful until you've got
some skill at it. Your colleagues will likely be much more satisfied participating in a lengthy,
meaningful discussion than participating in a truncated conversation that doesn't allow for
meaningful participation.
Who
This person is responsible for seeing the item through to completion. Sometimes, that person
may introduce the item while a colleague guides the discussion, so the person responsible for
the topic can listen more fully to the discussion.
How
Our sample agenda lists several ways to handle a discussion:
go-around: simply taking turns to speak; generally going in a circle around the room or table
feedback: asking the group to respond to specific questions about an idea
Share info and needs: giving information about the topic. In the example, Lisa will share
information; she will describe a project and her needs for handling it and ask for volunteers’
55
spend-a-dollar and discussion: this method asks group members to assign any part of an
imaginary "100 cents" amongst several ideas. The group will use spend-a-dollar to rank their
team priorities in the example. Spend-a-dollar is similar to a "straw poll" -- it helps a group
see which ideas in a list are high priority and how strongly members feel about those ideas.
Discussion is a good follow-up step to refine the results into useful input.
Brainstorm: when a group generates ideas freely and openly. An important element of
brainstorming is that it does not involve the evaluation of ideas -- the goal is to generate as
many ideas as possible.
Adapted from here
Meeting Minutes
Meeting minutes are notes that are recorded during a meeting. They highlight the key issues
that are discussed, motions proposed or voted on, and activities to be undertaken. A
designated member of the group usually takes the minutes of a meeting. Their task is to
provide an accurate record of what transpired during the meeting.
Writing minutes can take time and may seem like an unimportant task compared with getting
on with “real work,” but not taking meeting minutes can be costly in terms of both time and
resources. If you don’t take minutes, you will find that your colleagues have different
recollections from the meeting than you. They also may have different ideas about what was
agreed. If there are no minutes, then important tasks will be forgotten or not achieved by the
due date.
Creating meeting minutes provides a written record of what was agreed at a meeting. Good
meeting minutes tell people what was decided, what they need to achieve, and by what
date. When meeting minutes are received, it jogs memories about tasks people need to do. If
a task is not performed, you can refer back to the meeting minutes and follow up on it.
Without meeting minutes, you have no recourse if an action was not carried out. In the worst
case, if meeting minutes are not written, you may have to repeat the meeting.
In some instances, meeting minutes may be required for legal reasons. An example is where
local bylaws require it for certain types of organizations. Also, they may be required for
disciplinary meetings with employees. Getting into the habit of taking meeting minutes is
good practice.
Steps Involved in Creating Meeting Minutes
There are five main steps involved in recording the minutes of a meeting. They are:
•
•
•
•
Pre-planning using meeting agenda
Record-taking
Writing or transcribing the minutes
Sharing meeting minutes
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•
Filing or storage of minutes for referencing in the future
Pre-Planning using meeting agenda
If a meeting is well-planned in advance, taking minutes will be much easier. That said, the
chairperson or the group lead should work with someone tasked to prepare the meeting
agenda beforehand. The meeting agenda will provide the format for the meeting and should
be circulated before the meeting takes place.
Record-taking
When an individual is chosen as the minute’s recorder (the one to take note of the meeting
and create the meeting minutes), they need to know what is expected of them. Therefore, the
individual should approach the chair of the meeting and ask what their role in the meeting
will be and the level of details to record.
Writing or transcribing the minutes.
During the meeting, it is good to prepare a specific format used to write or transcribe what
transpired during the meeting. Overall, the minutes of a meeting typically includes the
following details:
•
•
•
What was decided on.
A description of what was accomplished.
The actions that need to be taken in the future.
The Process of Writing Meeting Minutes
When the meeting ends, the individual tasked with writing the minutes should get all the
resources he needs to write the minutes in a clear, presentable way. Here are some tips to
consider:
Once the meeting ends, don’t take too long to write the minutes. This way, everything that
took place in the meeting is still fresh in your mind.
Review the outline that had been created earlier and make adjustments where necessary. This
might include adding extra information or clarifying some of the issues raised. Also, check
that all verdicts, activities, and motions were recorded.
Revise the minutes and ensure they’re brief but clear. We show a sample format you can use
to write the meeting minutes below.
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Figure 11. Sample of meeting minutes.
Distributing the Meeting Minutes
Once the person in charge of the meeting minutes completes writing the minutes, he’s
supposed to share them with the group members. They can be shared online or through the
cloud. Considering that minutes and other types of documents can entail a lot of paperwork,
it may be preferable to use a paperless sharing approach.
For example, suppose the minutes recorder was documenting the minutes using Microsoft
Word, which does not offer online sharing. In that case, they might consider using Google
docs, which offers a way of sharing documents online with other users.
Team meetings and relevance in the software
development process
As technical students, we usually believe that developing algorithms or software products
involves long hours working alone in our room. Unfortunately, that no longer holds today in
developing modern software and algorithms.
I explain below why learning and practicing how to do meetings will help you in coping well
in the software development process.
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Two main software development processes are commonly used in the tech industry –
waterfall and agile.
The Waterfall methodology—also known as the Waterfall model—is a sequential
development process that flows like a waterfall through all phases of a project (analysis,
design, development, and testing, for example), with each phase completely wrapping up
before the next phase begins.
Figure 12. Waterfall model
Meetings are held during the requirements and verification and testing phase (refer to Figure
12).
Agile software development on one hand always starts by defining a product’s users and
documenting a vision statement for the scope of problems, opportunities, and values to be
addressed.
Figure 13. Agile Development Methodology
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Figure 13 illustrates the overall methodology using agile approach. They are iterative with
demo and feedback taking place during the entire development.
Agile focuses on teamwork in delivering working software. Team members must align on
what they are building, who is doing what, and how the software will be developed.
Agile in practice is implemented as scrum, which organizes the work in cadences
called sprints, usually lasting one or two weeks.
Scrum includes several formal meetings (sometimes called scrum ceremonies or scrum
rituals) to help teams commit to sprint priorities, complete the work during the sprint, and
end each sprint successfully. These meetings usually include a few common elements:
Sprint planning is where the product owner shares priorities, and the team decides how
much work it can complete during the sprint.
Daily standup meetings help teams discuss the status of user stories; teammates share their
daily goals, and anyone can escalate blocks that impede the team’s progress.
Sprint reviews are demo meetings at the end of the sprint, where the functionality is shown
to the product owner to gain acceptance of completed work.
Retrospective meetings are where the team discusses what went well and what needs
improvement in their agile and software development processes.
Information sharing in teams is one of the most important aspects of successful software development.
For instance, requirements, design decisions, and guidelines must be communicated with the
whole team or specific team members.
Meetings are an effective way to communicate with many team members. Hence, much
information can be shared during team meetings.
I hope with the above, you can understand why learning how to plan and conduct meetings
is central to progressing your work as a team in your project assignments. It is how software
development processes are conducted in the real-world, as formal meetings.
How to apply this process in your project assignment
You will apply the learned techniques in planning and conducting meetings for your project
assignments as a process to your group’s solution and product prototype.
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Chapter Six
Teamwork and Leadership
A team is a small group of people with complementary skills committed to a common purpose
for which they hold themselves and each other accountable. What defines a team includes the
following:
•
deliverables, both individual results and “collective work products.”
•
Complementary skills and mutual accountability
•
Committed to a common goal/approach
•
Shared leadership
Why have teams? Companies use teams when people from different groups are needed to
meet goals, such as developing a new product. Some reasons for organizing a group of people
as a team, instead of a committee or other group structure, are discussed below.
•
Enhanced Cooperation and Coordination
Teams can perform better than individuals or functional groups with tasks that need
cooperation and coordination. Cross-functional teams reduce the number of hand-offs
and the amount of coordination needed between the functions. Because more of the
expertise to do the job belongs to the team, there is less need to pass work on to another
group. This improved coordination can provide strategic advantages to companies
such as reduced time to market.
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•
Working Together
Teamwork is more than getting along or being helpful. In a real team, the members
work toward a common goal. By working together, team members help each other to
accomplish tasks. A team working together usually gets more results in less time than
other types of organizations.
•
Organizational Flexibility
An organization can be more flexible by using teams. Management can put a team
together to accomplish a specific task and disband it. Or, a team can be kept together
more or less permanently to address an ongoing need -- such as running an operation
or developing a series of new products.
Teamwork can have a different meaning when it comes to software development. Especially
in light of innovative trends like agile development methodology, effective teamwork is
becoming more of a priority for development organizations. We have reviewed in Chapter 5
how important conducting meetings in a team in an agile development methodology.
Teamwork involves effective communication skills and collaboration. When developers can
clearly communicate with one another about their needs, the overall demands of the project
and specific work processes, team members can be more productive in their actions and
improve their collaboration.
It’s similar to the inner workings of a machine. When all the pieces fit together as they should,
and all cogs are running at the right speed, the machine can hum along and perform the
actions that it was created for. However, when even a single piece is out of place or not
operating at the correct rate, the machine doesn’t function properly and isn’t as efficient as it
should be.
In this unit, two of your project assignments require you to work in team so make sure you
go through the chapter carefully.
Effective team structure and values
Below we detail out effective team structure.
•
Small Team Size
Teams usually work best with a small group of people. Smaller numbers make team
administrative tasks easier, such as deciding where and when to meet. Meetings are
generally shorter when fewer people need to speak. Small size also makes it easier to
develop a common purpose with mutual goals and mutual accountability, which is
so important for good teamwork. In addition, a small team of people avoids the "herd"
mentality of large teams. In a large team people tend to go along with popular opinion
rather than thinking for themselves. In general, the larger the team of people, the
harder it is for the team to work well together.
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•
Complimentary Skills
Complimentary skills are also important for a team. Necessary skills include: technical,
problem solving, decision-making, and interpersonal skills. Technical skills are needed to
provide the expertise to meet the goals of the team. The other skills are necessary for the
team to work effectively together.
•
Commitment
High-performance teams must make a strong commitment to a common purpose and
goals. A common, meaningful purpose sets the tone and aspirations of the team. The
team's purpose must then be translated into specific, measurable goals, often called
milestones. The milestones help to focus the team and make it more productive.
Meeting milestones also gives the team small victories crucial to its commitment and
morale. This combination of purpose and goals is important for the
success of the team.
•
Common Approach
The members of a team must also commit to a common approach. What are the
standards of behavior? How will the team go about its tasks? Who will perform which
task? How will schedules be assigned and how are decisions made? These are the
nuts-and-bolts issues that need to be agreed upon by all members of the team.
•
Accountability
The members of the team must also share a sense of mutual accountability. In other
words, they must hold themselves and each other answerable for meeting the team's
goals. They must know what they are responsible for individually and as a team.
Tuckman’s Teamwork Development Stages
In this section, we will introduce a very important theory of Bruce Tuckman in 1965 – on the
teamwork development stages (phases). Tuckman's model is significant because it recognizes
the fact that groups do not start off fully-formed and functioning. He suggests that teams
grow through clearly defined stages, from their creation as groups of individuals, to cohesive,
task-focused teams. The theory describes how the members of small teams tend to act as the
team develops. Each phase is described below.
•
Forming
This phase occurs when a team first comes together. Sometimes this phase is called
the "honeymoon" period because everyone is nice to each other. Team members are
usually cautious and polite with each other while exploring their new circumstances.
A good way to expedite this phase is to have "icebreaker" activities that allow team
members to understand each member's capabilities and motivations. Recall that we
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had an “icebreaking” activity in Week 1. This will help you to initiate your first team
encounter.
•
Storming
During this phase, team members begin challenging and disagreeing with one another.
They often jockey for positions and use their expertise as weapons. Teams can get stuck
in this phase and as a result can fail. The key to moving quickly through this phase is
explicitly defining the roles and responsibilities of each team member.
•
Norming
In this phase, team members start offering ideas and suggestions. They reveal their
preferences for performing tasks. Standards of behavior and team processes are defined.
By defining team processes, one can move on to performing.
•
Performing
This phase is the ideal phase for a team. They work hard together. Team members
anticipate problems, changes in direction, and each other's moves. The focus of the team
is on accomplishing their goals and not on blaming each other.
Figure 14: What to look out in the stages
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You can use Figure 14 to troubleshoot your team’s development stages. By recognizing the
stage where your team is at, it will help you plan how to get to the performing stage.
Tuckman’s theory also helps you understand the challenges of working in groups and how to
overcome them. Insight into how groups develop gives leaders knowledge of the stages a
group goes through to become cohesive and effective over time, the factors that influence
these changes, and the leadership style (details in next section) needed at each stage to create
positive progress.
Tuckman also made important observations on teamwork stages as follows. A team will not
be fully effective unless it reaches performing/interdependence. Many teams accept
storming as a normal way of operating. A number of teams may never get beyond forming.
Unless the process of norming is fully completed, teams may degenerate into storming. The
time taken to complete the cycle will vary tremendously between teams.
According to Tuckman’s theory, a team will fully grow to a productive stage if these issues
are not satisfactorily addressed:
•
•
•
Content. Content relates to what the team does
Processes. Process relates to how the team works towards its objectives
Feelings. Feelings applies to how team members relate to one another.
Most teams concentrate almost exclusively on content, to the detriment of process and
feelings. This explains why strong teams on paper (grades) can under-perform.
How do develop effective teamwork?
Today’s teams are different from the teams of the past: They’re far more diverse, dispersed,
digital, and dynamic (with frequent changes in membership). But while teams face new
hurdles, their success still hinges on a core set of fundamentals for group collaboration.
Below we provide techniques for you to develop effective teamwork, step-by-step.
1. Assemble the team
High-performance teams are comprised of individuals that passionately embrace the vision,
believe their contribution is meaningful, and are motivated to give their best effort. All team
members should trust, respect and support each other. Select members with complementary
skills and abilities, who can bring a diverse range of viewpoints and ideas to the table.
Achieving a good balance of personality types will enable the group to work together
harmoniously but challenge each other when necessary. You should use personality test to
understand your team’s personality and plan the role according to their test score.
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2. Appoint a strong leader
Once you have assembled a team, is to conduct an effective meeting (See chapter 5) to make
decision on appointing a team leader. A team has no direction without an elected leader. It is
vital that this person is efficient and switched on when it comes to delegating tasks to the
appropriate team members. This leader must also prioritise team goals over individual goals,
ensuring they are committed to getting the job done. Finally, they must be capable of showing
direction and increasing the morale of the team.
3. Define the purpose
Clearly define the purpose of the team (which in this unit is to identify solution and develop a
product prototype together), including the overall outcome it has been brought together to
achieve. What do you want to create, improve or change? What is the purpose of each person’s
role in the team? Providing a clear, inspiring vision sets the foundation for successful
teamwork, and helps guide the direction of the group when they face challenges and
decisions. Make sure this is done by conducting an effective meeting following techniques in
Chapter 5.
4. Clarify all responsibilities
From the moment the team is formed, particular attention must be paid to assigning direct
responsibilities to each team member. You should conduct a meeting to clarify all
responsibilities (this could be done at the same time that you define the purpose of the team assembling
together). If clear parameters are set from the beginning, there will be no overlaps of authority.
This is an important step to make before delving into the project so that everyone is clear and
on the same page. If everyone is clear on what they are responsible for producing, it helps
prevent situations such as staff overlapping on tasks and the less desirable tasks being
avoided.
5. Set common goals
Each team will comprise of a range of people from diverse backgrounds and skillsets. It is
therefore important to set common goals in which the team is working towards so that the
focus always remains on the finished product. Each team member must understand that
personal goals must be set aside and team goals must remain a focus throughout the project.
As the well-known saying goes, ‘There is no I in team’. If conflicts arise, refer back to these
original goals and make decisions with a primary focus on them. Make sure you have a
meeting discussion on this to agree on a set of common goals.
6. Set expectations and schedule
Once the team is established and united behind a shared, compelling purpose, the next step
is to break the vision down into smaller, manageable expectations and schedule. Outline the
required tasks in a schedule, with agreed deadlines, milestones and responsibilities. This is
when understanding the requirements of the project (see Chapter 3 on research) is important.
You would want to make sure you deliver the right thing and on time.
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7. Monitor and review
Regularly review the group’s performance through team meetings and one-on-one catch ups
to ensure that progress is being made. Good questions to ask are: how are we doing? What
have we achieved so far? What have we learned? What isn’t working so well? How can we
improve? Monitoring and reviewing progress allows for adjustments and improvements to
be incorporated along the way. This is where meeting agenda and meeting minutes become
valuable tools for reviewing and monitoring of team’s work.
8.
Celebrate and reward
Make the time to regularly recognise, reward and celebrate both team and individual
performance. This will help to build morale and bolster the motivation of the group to
continue their hard work. Find the most appropriate way to celebrate team milestones, such
as a personal ‘thank you’ at a team meeting, an email copied to senior managers, or a team
lunch. Ensure that recognition is consistent, and that the method you choose inspires and
reinforces the team members to continue their positive contribution to the team’s progress.
Important teamwork values
It is important that you establish a set of values for the team. Values would be your guiding
principles in what is important for you team, that should create good team dynamics and
process. Below are some of the key values a team should cultivate.
•
Encourage open communication
Encouraging team members to be forthcoming with their ideas is very important for the
success of the team. When team members feel that they can freely contribute ideas, there is
more scope for creativity and innovation. It is also important to establish two-way
communication of information between both the members within the team, as well as between
team members and their manager. This ensures that everyone is always appropriately
informed and no topics of conversation are avoided.
•
Be willing to help others
In a team project, although you are assigned personal tasks you must remember that your
overall goal is to contribute to completing the project. This, therefore, means that if you have
finished your workload, you must be willing to help out where needed. This may mean
contributing to tasks that are perhaps below your level, but the overall goal must be kept in
mind.
•
Be honest
Honesty is the an important principle of team value. An honest team should be able to debate
with one another over issues and resolve those issues before the problem boils. Teams may
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develop the ability to be honest with one another if a leader mediates some smaller debates
and shows that it is okay to disagree
But what happens when teams go remote?
As the world increasingly becomes reliant on remote work, it is critical to ensure that team
members are on the same page. Communication around project timelines and delivery will
be important, and accountability will need to be defined. Creating trustworthy relationships
to overcome the virtual distance between remote team members will impact success. For this,
online tools, video chats and phone conversations become beneficial for increasing
connectivity and communication, and avoiding the sense of isolation that teams may
experience.
What is Leadership?
Leadership is the ability of an individual or a group of individuals to influence and guide
followers or other members of an organization. It is essentially a continuous process of
influencing behavior. It may be considered in context of mutual relations between a leader
and his followers.
The leader tries to influence the behavior of individuals or group of individuals around him
to achieve desired goals.
Therefore, to become leader, you need to have followers.
Types of leadership theory
There are two major types of leadership theory: transactional and transformational.
In a transactional leadership, the leader focuses on supervision, organization and
performance. The leadership style are:
•
Contingent reward – Leaders try to obtain agreement on what needs to be done and what
the payoffs will be for the people doing it.
•
Management-by-exception – Leaders use corrective criticism, negative feedback, and
negative reinforcement.
•
Active: Micromanagement.
•
Passive: Problem-based intervention.
This leadership style is suitable in crisis and emergency situations, as well as for project that
need to be carried out in a specific way (i.e., critical projects)
The downside of this type of leadership is the following:
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•
Low expectations
•
Low levels of satisfaction
•
Focus is on short-term, immediate outcomes only
Whereas, transformation leadership focuses on working with teams to identify the needed
change. They also create vision to guide the change through inspiration, and executing the
change in tandem with committed members of a group.
The leadership style includes:
•
long-term, higher-ranked values and ideals
•
Creating an ethical climate (share values, high ethical standards)
•
Encouraging followers to look beyond self-interests to the common good
•
Allowing freedom of choice for followers
There are four components of transformational leadership, reviewed below.
Idealized Influencer (II)
The leader serves as an ideal role model for followers; the leader "walks the talk," and is
admired for this. He/She will embody the qualities that he/she wants in his/her team
Inspirational Motivation(IM)
The leaders have the ability to inspire and motivate followers through having a vision and
presenting that vision. They do this by creating an emotional bond between leader and group
Intellectual Stimulation (IS)
The leader challenges followers to be innovative and creative, they encourage their followers
to challenge the status quo. They do this by challenging the group to identify and solve
challenges (out of the box).
Individualized Consideration (IC)
The leader demonstrates genuine concern for the needs and feelings of followers and help
them self-actualize. They do this by developing appropriate personal relationships with
members and treat members differently but equitably
How to become an effect leader?
Regardless of which leadership theory you follow, below are some of the attributes - mindset, skills and values that you should develop to become an effective leader.
•
Purpose
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Leaders must have a clearer understanding of the team's purpose and what it must do to
make it a reality. Effective leadership not only guides but identifies, understands and
communicates team’s vision to support them to achieve objectives. During the designing
and implementation of a project, it is the leader who ensures every team member
understands their roles and provides an enabling environment to help them perform at
their best.
•
Promote values
Team leaders can encourage others to take up essential values vital for the organization's
success. If you are upright, honest, punctual and serve as a good role model to your team
members, they will emulate your behavior. Values such as accountability and taking
responsibility when things go wrong can also make the organization a better place for
employees and clients
•
Promote creativity
Team leaders can also foster an atmosphere of creativity in a team. While leaders help
others see the vision of the work, they can also provide more flexibility on how team
member do their work. This can help produce new insights on how to perform tasks, make
decisions and deliver on projects, improving efficiency and productivity
•
Effective Communication.
If you’re in a leadership position or role, good communication skills are one of the
leadership attributes that are absolutely crucial. Using language to perform one-to-one
communication is really all that we have as human beings.
This is when you should develop effective communication skills (Chapter 2) such as active
listening. Strong leaders listen and pay attention to all of their followers, employees, and
every single individual person they are leading. Good leaders, and even great leaders, are
not born; they are made. You have to be a good communicator if you actually want your
followers to trust you fully.
•
Integrity
Without integrity, no real success if possible. You can’t expect your followers to be honest
when you lack integrity yourself. Honest and great leaders succeed when they stick to
their word, live by their core values, lead by example, and follow-through.
Integrity is the cornerstone of all other leadership qualities.
There are many things to look for in leaders with integrity:
•
•
•
Apologizing for mistakes
Highlighting the best work of their employees and downplaying their own
contributions
Giving the benefit of the doubt when circumstances are unclear
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•
Being appreciative of people’s time
•
Accountability
Strong and good leaders are accountable for the team’s results, good or bad. They give
credit where credit is due, and take responsibility for blame when necessary. Being
accountable and leading by example is one of the quickest ways leaders can become good
leaders are by building trust with their team.
•
Empathy
Truly great leaders have enough open-mindedness to understand their followers’
motivations, hopes, dreams, and problems so that they can forge a deep personal
connection with them. Empathy is understanding. It’s a mindset that enables leaders to:
•
•
•
•
•
•
Make better predictions
Improve teamwork strategies
Inspire loyalty among their teams
Better their negotiation tactics
Increase creativity
Humility
When it comes to developing leadership qualities, it can be tempting to become enamored
with a new title or status instead of putting in the actual work to become a good leader
with humility.
However, great leadership styles focus on problem-solving and team dynamics much
more than self-promotion. A good leader will never be effective if they’re more concerned
with themselves than with the well-being of their team. As Thomas Merton said,
Being humble and vulnerable with their team members will make a leader much more
relatable and effective.
•
Resilience
The true grit of a good leader is not how they perform during good times, but how they
roll up their sleeves and produce when times get difficult.
Great leaders with positive attitudes lead by example and rally their team no matter the
circumstances. It’s this inherent positivity that helps react to difficult situations with a
calm, collected manner and focus on solutions rather than on problems.
Resilience is one of the essential leadership qualities that is earned from experience.
•
Delegation
A difficult transition for many leaders is shifting from doing to leading.
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Many new leaders are accustomed to doing all the work themselves and struggle to let
others handle responsibilities on their own. Great leaders must elevate their team – they
must be more essential and less involved.
This requires leaders to shape others’ thoughts and ideas toward a common goal. They
give their team everything they need to be successful and get out of the way, not directing
their path, but setting clear expectations and explaining where the finish line is.
They aren’t scared of their subordinates’ successes and don’t feel threatened by them. One
of the most important leadership qualities of good leadership is delegating tasks and
elevating their team.
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Chapter Seven
Introduction to Professional Code of Ethics and
Conduct, and Ethical AI guidelines
In this chapter we will look into what is a computing professionals, and why Code of Ethics
is important.
Computing professionals perform a variety of tasks: they write specifications for new
computer systems, they design instruction pipelines for superscalar processors, they diagnose
timing anomalies in embedded systems, they test and validate software systems, they
restructure the back-end database of an inventory system, they analyze packet traffic in a local
area network, and they recommend security policies for a medical information system.
Computing professionals are obligated to perform these tasks conscientiously, because their
decisions affect the performance and functionality of computer systems, which in turn affect
the welfare of the systems’ users directly and that of other people less directly. For example,
the software that controls the automatic transmission of an automobile should minimize
gasoline consumption, and more important, ensure the safety of the driver, any passengers,
other drivers, and pedestrians.
Computing professionals have ethical obligations to clients, employers, other professionals,
and the public, in fulfilling their professional responsibilities. These obligations are expressed
in codes of ethics, which can be used to make decisions about ethical problems.
Ethics is defined as a moral philosophy or code of morals practiced by a person or group of
people.
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The ethical obligations of computing professionals go beyond complying with laws or
regulations; laws often lag behind advances in technology. For example, before the passage of
the Electronic Communications Privacy Act of 1986 in the United States, government officials
did not require a search warrant to collect personal information transmitted over computer
communication networks. Nevertheless, even in the absence of a privacy law before 1986,
computing professionals should have been aware of the obligation to protect the privacy of
personal information.
In the next section we will revisit the term professional practice within the scope of Code of
Ethics and Conduct.
Revisiting the term professional practice
Let us revisit what it means by professional practice.
•
Professional practice is defined as the use of one's knowledge, skills, and attitudes that
computing professionals must possess to practice computer science roles in a
professional, responsible and ethical manner.
In general term, professional practice refers to the conduct and work of someone from a
particular profession. Professions are occupations that require a prolonged period of
education and training.
Computing professionals include hardware designers, software engineers, database
administrators, system analysts, and computer scientists.
To become a computing professional, an individual must acquire specialized knowledge
about discrete algorithms and relational database theory, and specialized skills such as
software development techniques and digital system design.
The purposes and values of a profession, including its commitment to a public good, are
expressed by its code of ethics.
A profession’s code of ethics is developed and updated by a national or international
professional association. In the below, we list the responsibilities of computing professionals.
RESPONSIBILITIES TO CLIENTS AND USERS
Whether a computing professional works as a consultant to an individual or as an employee
in a large organization, the professional is obligated to perform assigned tasks competently,
according to professional standards. These professional standards include not only attention
to technical excellence but also concern for the social effects of computers on operators, users,
and the public.
When assessing the capabilities and risks of computer systems, the professional must be
candid: the professional must report all relevant findings honestly and accurately. When
designing a new computer system, the professional must consider not only the specifications
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of the client, but also how the system might affect the quality of life of users and others. For
example, a computing professional who designs an information system for a hospital should
allow speedy access by physicians and nurses, yet protect patients’ medical records from
unauthorized access; the technical requirement to provide fast access may conflict with the
social obligation to ensure patients’ privacy.
Computing professionals enjoy considerable freedom in deciding how to meet the
specifications of a computer system. Provided that they meet the minimum performance
requirements for speed, reliability, and functionality, within an overall budget, they may
choose to invest resources to decrease the response time rather than to enhance a graphical
user interface, or vice versa. Because choices involve tradeoffs between competing values,
computing professionals should identify potential biases in their design choices (6). For
example, the designer of a search engine for an online retailer might choose to display the
most expensive items first. This choice might favor the interest of the retailer, to maximize
profit, over the interest of the customer, to minimize cost.
To acknowledge responsibilities for the failure of software artifacts, software developers
should exercise due diligence in creating software, and they should be as candid as possible
about both known and unknown faults in the software—particularly software for safetycritical systems, in which a failure can threaten the lives of people.
RESPONSIBILITIES TO EMPLOYERS
Most computing professionals work for employers. The employment relationship is
contractual: the professional promises to work for the employer in return for a salary and
benefits. Professionals often have access to the employer’s proprietary information such as
trade secrets, and the professional must keep this information confidential. Besides trade
secrets, the professional must also honor other forms of intellectual property owned by the
employer: the professional does not have the right to profit from independent sale or use of
this intellectual property, including software developed with the employer’s resources.
Every employee is expected to work loyally on behalf of the employer. In particular,
professionals should be aware of potential conflicts of interest, in which loyalty might be owed
to other parties besides the employer. A conflict of interest arises when a professional is asked
to render a judgment, but the professional has personal or financial interests that may interfere
with the exercise of that judgment.
For instance, a computing professional may be responsible for ordering computing
equipment, and an equipment vendor owned by the professional’s spouse might submit a
bid. In this case, others would perceive that the marriage relationship might bias the
professional’s judgment. Even if the spouse’s equipment would be the best choice, the
professional’s judgment would not be trustworthy. In a typical conflict of interest situation,
the professional should recuse herself: that is, the professional should remove herself and ask
another qualified person to make the decision.
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RESPONSIBILITIES TO OTHER PROFESSIONALS
While everyone deserves respect from everyone else, when professionals interact with each
other, they should demonstrate a kind of respect called collegiality. For example, when one
professional uses the ideas of a second professional, the first should credit the second. In a
research article, an author gives credit by properly citing the sources of ideas due to other
authors in previously published articles. Using these ideas without attribution constitutes
plagiarism.
Because computing professionals work together, they must observe professional standards.
These standards of practice are created by members of the profession, or within organizations.
For example, in software development, one standard of practice is a convention for names of
variables in code. By following coding standards, a software developer can facilitate the work
of a software maintainer who subsequently modifies the code.
Senior professionals have an obligation to mentor junior professionals in the same field.
Although professionals are highly educated, junior members of a profession require further
learning and experience to develop professional judgment. This learning is best accomplished
under the tutelage of a senior professional. In engineering, to earn a P.E. license, a junior
engineer must work under the supervision of a licensed engineer for at least four years. More
generally, professionals should assist each other in continuing education and professional
development, which are generally required for maintaining licensure.
RESPONSIBILITIES TO THE PUBLIC
Computing professionals should enhance the public’s understanding of computing. The
responsibility to educate the public is a collective responsibility of the computing profession
as a whole; individual professionals might fulfill this responsibility in their own ways.
Examples of such public service to include advising a church on the purchase of computing
equipment, and writing a letter to the editor of a newspaper about technical issues related to
proposed legislation to regulate the Internet.
It is particularly important for computing professionals to contribute their technical
knowledge to discussions about public policies regarding computing. Many communities are
considering controversial measures such as the installation of Web filtering software on public
access computers in libraries. Computing professionals can participate in communities’
decisions by providing technical facts. Technological controversies involving the social
impacts of computers are covered in a separate article of this encyclopedia.
When a technical professional’s obligation of loyalty to the employer conflicts with the
obligation to ensure the safety of the public, the professional may consider whistle-blowing,
that is, alerting people outside the employer’s organization to a serious, imminent threat to
public safety.
Computer engineers blew the whistle during the development of the Bay Area Rapid Transit
(BART) system near San Francisco (9). In the early 1970s, three BART engineers became
alarmed by deficiencies in the design of the electronics and software for the automatic train
control system, deficiencies that could have endangered passengers on BART trains. The
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engineers raised their concerns within the BART organization without success. Finally, they
contacted a member of the BART board of directors, who passed their concerns to Bay Area
newspapers. The three engineers were immediately fired for disloyalty. They were never
reinstated, even when an accident proved their concerns were valid. When the engineers sued
the BART managers, the IEEE filed an amicus curiae brief on the engineers’ behalf, stating that
engineering codes of ethics required the three engineers to act to protect the safety of the
public. The next section describes codes of ethics for computing professionals.
Codes of Ethics and Conduct
In the previous sub-section we have delved into quite detail on the expectation of a computing
professional.
Computing professionals are obligated to follow code of ethics and conduct.
Such codes have been developed by, the Association for Computing Machinery (ACM), the
British Computer Society (BCS), the Computer Society of the Institute of Electrical and
Electronics Engineers (IEEE-CS), the Association of Information Technology Professionals
(AITP), the Hong Kong Computer Society, the Systems Administrators Special Interest Group
of USENIX (SAGE), and other associations. Two of these codes will be described briefly here:
the ACM code and the Software Engineering Code jointly approved by the IEEE-CS and the
ACM.
In this unit we will introduce you to the ACM code of ethics and conduct, MNCC Malaysia
code of professionals and ACS – Australian
In your assignments, you are required to refer to ACM code of conduct and ethics.
Please refer here to the ACM Code of Ethics and Professional Conduct; MNCC Malaysia Code
of Ethics and ACS Australia Code of Ethics.
Below we summarize the differences among the codes of ethics – ACM, MNCC and ACS in
Table 2.
Table 2. Comparison of the Code of Ethics and Conduct from different associations
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Why Code of Ethics is not sufficient in making decision
We have introduced you to the meaning of professions, and how it relates to you being at the
University receiving education to become a software engineer, a developer, or a computer
scientist as your professor. The University provides you with the ground to develop all that
is necessary foundation as a future profession – in Computing.
We have also introduced you to various Computing Professionals Association in Code of
Ethics and Conduct. These Code of Ethics and Conduct would be part of defining your
professional role, attitudes, values, and skills as a software engineer, developer.
When making ethical decisions, computing professionals should rely not only on the specific
guidance from codes of ethics, such as the ACM Code of Ethics but also from general moral
reasoning.
We will explain why a moral reasoning (values) are required for computing professional to
develop and apply aside from using the Code of Ethics in making ethical decision.
Here is a fictional example, adapted from here.
Scenario: XYZ Corporation plans to secretly monitor the Web pages visited by its
employees, using a data mining program to analyze the access records. Chris, an engineer
at XYZ, recommends that XYZ purchase a data mining program from Robin, an
independent contractor, without mentioning that Robin is Chris’s domestic partner. Robin
had developed this program while previously employed at UVW Corporation, without
awareness of anyone at UVW.
Analysis: First, the monitoring of Web accesses intrudes on employees’ privacy; it is
analogous to eavesdropping on telephone calls. Professionals should respect the privacy
of individuals (ACM Code 1.7, Respect the privacy of others, and 3.5, Articulate and
support policies that protect the dignity of users and others affected by a computing
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system). Second, Chris has a conflict of interest because the sale would benefit Chris’s
domestic partner. By failing to mention this relationship, Chris was disingenuous (ACM
Code 1.3, Be honest and trustworthy). Third, because Robin developed the program while
working at UVW, some and perhaps all of the property rights belong to UVW. Robin
probably signed an agreement that software developed while employed at UVW belongs
to UVW. Professionals should honor property rights and 11 contacts (ACM Code 1.5,
Honor property rights including copyrights and patent, and 2.6, Honor contracts,
agreements, and assigned responsibilities).
Referring to the above scenario, the code of ethics will guide you into identifying the ethical
problem however it might not yield a clear solution because different principles in a code
might conflict. For instance, the principles of honesty and confidentiality conflict when a
professional who is questioned about the technical details of the employer’s forthcoming
product must choose between answering the question completely and keeping the
information secret.
Furthermore, the code of ethics does not inform you on how to make an ethical decision in
finding the solution.
Therefore, in this unit, we will introduce you to three types of moral reasoning or formally
known as ethical system theory. We will also introduce you to a framework that guides you
in making ethical decisions using the ethical reasoning framework.
The ethical system theory that we shall introduce are:
•
•
•
Virtue ethics
Consequentialism
Deontology
However, before we do that, we will contextualize the importance of learning this. We will
first describe the specific ethical challenges of Algorithms in AI and Autonomous Agents in
the following section.
The Ethical Challenges of Algorithms in
Artificial Intelligence and Autonomous Agents
In this section we will review research papers that has explored in detail ethical issues caused
by algorithms in AI. In particular, we refer to this paper.
But first let us start with what is an algorithm?.
An algorithm is generally defined as something like “a limited sequence of actions that is
performed”. It could be simple calculations, or more complex forms of automated reasoning.
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In Artificial Intelligence, since the 1990s, the emergence of sophisticated “autonomous
agents,” including Web “bots” and physical robots, has resulted in ethical considerations in
the use of algorithms for wide variety of applications.
Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to
the natural intelligence displayed by animals including humans. There are several notable
approaches in the filed of AI to create some kind of natural intelligence in the machine such
as machine learning, natural language processing and autonomous agents.
Machine learning is a data analytics technique that teaches computers to do what comes
naturally to humans and animals: learn from experience. Machine learning algorithms use
computational methods to directly "learn" from data without relying on a predetermined
equation as a model (Ref).
Natural
language
understanding
primarily
comprises
of natural
language
understanding (human to machine) and natural language generation (machine to human). It
involves syntax and semantics analysis to create chatbots or conversational agents able to
converse with human beings.
Autonomous agent is an intelligent agent operating on user's behalf but without any
interference of that user. They are software entities that carry out some set of operations on
behalf of a user or another program with some degree of independence or autonomy, and in
so doing, employ some knowledge or representation of the user's goals or desires.
So how does using AI results in ethical issues?
This is because if you look at the basic definition of algorithms – it is performing calculation
on a basic set of inputs. Therefore, software has been designed for predictability. When it
works right, Input X yields Output Y.
However, in AI, the goal is to create systems that can deal with unpredictability and changes
just as humans can. And in order to do that, it needs to be able to deal with uncertainties and
varieties of complexities (just as human lives are).
For example, machine learning was developed as a technique with the goal where a computer
can learn from data input, without being specifically programmed how to make certain
choices. The techniques provide predictive analytics capabilities in variety of applications, for
example in in recommendation engine (i.e. Youtube, Facebook, TiKTok). A recommendation
engine with predictive analysis can predict which type of products or services customers will
be interested in, based on their historical data.
This is where algorithms often come in, in the context of predictive analytics and predictive
modelling; the end result of machine learning software, after being trained on data-sets, is an
algorithm that tries to predict the outcome of new data sets as input.
However, the use of machine learning techniques, particularly with deep-learning,
practitioners sometimes are all based on probability and makes use of history data. It can’t
understand the result or the reasoning that led up to the result.
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Hence, deep ethical issues arise from using AI techniques due to two fundamentals.
First, the nature of human beings and the world. As humans, as we like to think about it,
behave based on certain, predictable, principles, but social phenomenon and human behavior,
tend to be continuously developed and changing over time, and would in that sense be less
predictable. We have desires, worldview, values, specific belief systems and all of this
influences how we think and what we do as actions.
For example, the statistician Nate Silver has become famous the past US elections, when he
and his team successfully have been able to predict the result of 49-50 (of 50) states since 2008,
each election. However, the 2016 election his team failed to predict the outcome of Hillary
loosing (although, granted, they had a higher probability chance of it happening than other
major forecasters). One reason why forecaster like Silver failed to predict Trump winning is
because the kind of campaign strategy, and atmosphere at the time, had never been
experienced before.
Secondly, is the responsibility of computing professionals. They are the ones who create
these sophisticated machines, and the notion that the machines themselves will, if they have
not already done so, become sufficiently sophisticated so that they will be considered
themselves moral agents, capable of ethical praise or blame independent of the engineers and
scientists who developed them. If these creators themselves are not conscious of their own
actions or can deliberate how their algorithms will work, then how can we expect the product
of their work to be to some extend “ethical?”.
The potential for algorithms to improve individual and social welfare comes with significant
ethical risks (Floridi and Taddeo 2016). Algorithms are not ethically neutral. Consider, for
example, how the outputs of translation and search engine algorithms are largely perceived
as objective, yet frequently encode language in gendered ways (Larson 2017; Prates et
al. 2019). Bias has also been reported in algorithmic advertisement, with opportunities for
higher-paying jobs and jobs within the field of science and technology advertised to men more
often than to women (Datta et al. 2015; Lambrecht and Tucker 2019). Likewise, prediction
algorithms used to manage the health data of millions of patients in the United States
exacerbate existing problems, with white patients given measurably better care than
comparably similar, black patients (Obermeyer et al. 2019). While solutions to these issues are
being discussed and designed, the number of algorithmic systems exhibiting ethical problems
continues to grow.
Imagine a care home facility where many elderly people do not drink enough water. A
software engineer is tasked with implementing a technical solution that incentivizes drinking
water. The setting is a smart care home and a smart cup is used to estimate how much water
a person drinks in a day. Out of all the possible options and after some, we assume, sloppy
deliberation, it was decided to link the cup to the smart TV and turn of the patient’s TV, if
they did not match their water quota. When asked why the developer chose that option, he
answered that it met all technical requirements. Since he knows that the elderly love nothing
more than their TV shows, they are sure to react to this.
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Whether a developer uses a for or a while loop to count to 100 makes no difference; in fact,
both versions might result in exactly the same machine instructions. If a solution is recursive
or iterative might impact performance, but will usually have no larger side effects. At the same
time seemingly innocent design decisions can have a huge impact:
•
•
•
choosing a binary datatype for a field in the database to store a person’s gender
reinforces this stereotype.
the way a software developer decides to store names might exclude most people on
earth.
The layout and the technical design of websites might exclude certain groups from
using them.
So while most decisions a software developer makes will have few, if any, ethical side effects,
some decisions can have a disproportionate impact. Even if it is not possible to foresee all
future uses and contexts of a piece of code, it is nonetheless crucial to integrate ethical
deliberation at the base of the development process to turn ethical deliberation from a chore
into a rational habit.
Despite the ethical challenges that these upcoming use of AI techniques in algorithms in
varieties of applications, there are strengths in using these new techniques.
Algorithms can siphon through large amounts of data, and to be able to estimate future
outcomes, with a probabilistic certainty. Recruiters that got 100, or 500, or 1000 applications
and CVs for a single position to hire, are quickly swamped and overwhelmed with
information, and it is difficult dealing with that in any constructive fashion without a lot of
effort and research. An unconstructive way would, for example, be to simply throw 50% of
them in the trash and read the remaining. Still, just to keep everything in the head when
weighing different aspects against each other, of a large amount of candidates, would be
cognitively taxing for a human recruiter.
Therefore, algorithms have become a key element underpinning crucial services and
infrastructures of information societies. Individuals interact with recommender systems—
algorithmic systems that make suggestions about what a user may like—on a daily basis, be
it to choose a song, a movie, a product or even a friend (Paraschakis 2017; Perra and
Rocha 2019; Milano et al. 2020). At the same time, schools and hospitals (Obermeyer et
al. 2019; Zhou et al. 2019; Morley et al. 2019a, b), financial institutions (Lee and
Floridi 2020; Aggarwal 2020) courts (Green and Chen 2019; Yu and Du 2019), local
governmental bodies (Eubanks 2017; Lewis 2019), and national governments (Labati et
al. 2016; Hauer 2019; Taddeo and Floridi 2018a; Taddeo et al. 2019; Roberts et al. 2019),
all increasingly rely on algorithms to make significant decisions.
As AI is embedded into just about everything involved with a person’s personal life and work
life, it is becoming increasingly incumbent upon developers to understand the basics of AI,
machine learning, data science and perhaps a bit more about statistics. Computer science
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majors are already getting exposure to these topics in some of the updated programs
universities are offering. Experienced developers are wise to train themselves up so they have
a better understanding of the capabilities, limitations and risks of what they’re trying to build.
“You’re going to be held accountable if you do something wrong because these systems are
having such an impact on people’s lives,” said BCG Federal’s Mills. “We need to follow best
practices because we don’t want to implement biased algorithms. For example, if you think
about social media data bias, there’s tons of negativity, so if you’re training a chatbot system
on it, it’s going to reflect the bias.”
“Every artifact, every technology is an instantiation of the designer so you have a personal
responsibility to do this in the best possible light,” said Frank Buytendijk, distinguished VP
and Gartner fellow. “You can’t just say you were doing what you were told.”
So how do we equip you – as future computing professionals in creating ethical algorithms
and product? By teaching you how to make ethical decisions in your algorithms, systems and
product design.
Thus in the next section we will introduce the Ethical Reasoning Framework followed by the
recommended “moral reasoning” – or formally known as ethical system theory.
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Chapter Eight
Introduction to Ethical AI principles and Ethical
Reasoning Framework Part I
Decisions about right and wrong permeate everyday life. Ethics should concern all levels of
life: acting properly as individuals, creating responsible organizations and governments, and
making our society as a whole more ethical. This document is designed as an introduction to
making ethical decisions. It recognizes that decisions about “right” and “wrong” can be
difficult, and may be related to individual context. It first provides a summary of the major
sources for ethical thinking, and then presents a framework for decision-making.
Ethics is sometimes conflated or confused with other ways of making choices, including
religion, law or morality. Many religions promote ethical decision-making but do not always
address the full range of ethical choices that we face. Religions may also advocate or prohibit
certain behaviors which may not be considered the proper domain of ethics, such as dietary
restrictions or sexual behaviors. A good system of law should be ethical, but the law
establishes precedent in trying to dictate universal guidelines, and is thus not able to respond
to individual contexts. Law may have a difficult time designing or enforcing standards in
some important areas, and may be slow to address new problems. Both law and ethics deal
with questions of how we should live together with others, but ethics is sometimes also
thought to apply to how individuals act even when others are not involved. Finally, many
people use the terms morality and ethics interchangeably. Others reserve morality for the
state of virtue while seeing ethics as a code that enables morality. Another way to think about
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the relationship between ethics and morality is to see ethics as providing a rational basis for
morality, that is, ethics provides good reasons for why something is moral.
We have reviewed in Chapter Seven the expectation and role of a computing professional to
follow its own Code of Ethics and Conduct.
However, we also highlighted that despite a Code of Ethics being provided that guides you
into identifying the ethical problem, it might not yield a clear solution because different
principles in a code might conflict. Furthermore, the code of ethics does not inform you on
how to make an ethical decision in finding the solution.
Therefore, in this chapter, we start by laying down the principles you will need to follow in
designing Ethical Artificial Intelligence (AI) for your assignments and future assignments.
Next, we will introduce the Ethical Reasoning Framework to guide you in your decision
making process.
Ethical Algorithms and AI Guidelines
One definition of Ethical AI states that the AI program adheres to well-defined ethical
guidelines regarding fundamental values, including individual rights, privacy, nondiscrimination, and non-manipulation.
Ethical Algorithms and AI should also respect human dignity, intellect, and values.
Therefore, in this unit, we shall follow the ethical algorithms and AI guidelines in developing
solutions (i.e., algorithms, AI applications) adapted from the Australian government.
You may refer to the originally documented guideline here for details
Figure 16. Ethical Algorithms and AI principles
Human, societal and environmental wellbeing: AI systems should benefit individuals,
society and the environment.
Human-centred values: AI systems should respect human rights, human intellect and
dignity, diversity, and the autonomy of individuals.
Fairness: AI systems should be inclusive and accessible, and should not involve or result in
unfair discrimination against individuals, communities or groups.
Privacy protection and security: AI systems should respect and uphold privacy rights and
data protection, and ensure the security of data.
Reliability and safety: AI systems should reliably operate in accordance with their
intended purpose.
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Transparency and explainability: There should be transparency and responsible
disclosure so people can understand when they are being significantly impacted by AI, and
can find out when an AI system is engaging with them.
Contestability: When an AI system significantly impacts a person, community, group or
environment, there should be a timely process to allow people to challenge the use or
outcomes of the AI system.
Accountability: People responsible for the different phases of the AI system lifecycle
should be identifiable and accountable for the outcomes of the AI systems, and human
oversight of AI systems should be enabled.
In the next section, we introduce the ethical reasoning framework.
Ethical Reasoning Framework (ERF)
First, we start with definitions of reasoning. What is reasoning? Reasoning is our unique human
intellect to be able to acquire knowledge and recognize truth.
Ethical reasoning is the ability to acquire knowledge about the true events that have
happened by identifying and evaluating events and guided by values to form ethical
decisions.
Ethical reasoning is critical to apply when making decisions in developing and creating
algorithms software or AI applications.
When making ethical reasoning, the following aspects must be involved that defines ethical
reasoning:
•
respecting other individuals and their rights,
•
making informed choices that benefit other individuals, society as a whole, and the
environment, in a manner that requires the individual to be aware of and process the
principles of right and wrong as they relate to human conduct.
•
individuals demonstrate personal and social and aware of the possible consequences
of their actions.
Now we look at what do we mean by framework? A framework is a foundation that consists a
set of ideas, beliefs or methods which you use to deal with problems or how to solve it.
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Therefore, ethical reasoning framework is defined as a foundation that consists a set of
methods which you use to decide what to do or how to develop an ethical algorithm and/or
AI application.
Refer to figure 16. The ERF framework helps you to structure the different principles and
techniques learned in this unit to provide you with a foundation to produce a solution.
Refine research and extract and gather information
At the first step, it requires you to know the problems that you need to solve. This can be
achieved by applying the intelligent research cycle (Chapter 4) to help you formulate what
the problem is really about (the what, why and how) that has given rise to ethical implications.
Figure 16. The Ethical Reasoning Framework (ERF)
Problem identification using the ACM Code of Ethics
After problems are identified, this is when you will refine the research by extracting and
gathering information from sources in further detail who are the people impacted negatively.
What were their roles? What policy, culture, or moral values are/may have been violated.
You need to also empathize with the users whom are affected.
Once this has been identified, we perform structured thinking to analyze the Code of Ethics
that has been violated. This was shown to you in Week 7 (and your tutorial). At this step, you
would have analysed whether the systems have violated privacy, honor confidentiality.
It is important that you can analyze and identify the violation of the Code of Ethics first,
because it will then provide a guideline to what should be avoided in improving the
applications to solve the problem or to create a better one that serves social good.
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Use ethical theories as guiding principle.
The next step is to apply ethical theories as a guideline for your moral reasoning in making
ethical decision. This is when the decision making process starts to formulate. The ethical
theories taught to you in this unit are virtue ethics, utility, and deontology. We have
recommended how the different theories can be used to solve and create different
applications. However, it does not mean you need to follow this strictly – you may combine
the use of the theories to guide you in the next step. We will speak in more detail about this
part in Chapter 9 – Ethical Theories.
Ideate
In the next step, we have borrowed the Ideation method from Design Thinking Approach.
Ideate is an inventive step where you will start conducting your meetings (recall the basic
principles in conducting meetings in Chapter Five). During these meetings, you can conduct
different types of processes used in ideation.
Ideation should be a creative process. You will generate ideas in meeting.
Participants gather with open minds to produce as many ideas as possible to address a
problem statement in a facilitated, judgment-free environment.
You aim to generate items or a list of features that solves, improve or innovate new application
based on the problems to be solved (socially good).
The ethical theory will provide moral reasoning for you to ideate the list of items by providing
a way to evaluate or create the items. For example, you are ideating items to improve on a
driverless and want to use virtue ethics. Using this principle, you would then use the moral
compass to design autonomous agents in driverless car that promote good well-being in
drivers.
Hence you may list these set of features in the robot:
•
When encountering a situation involving changing routes, the autonomous agents
should have a conversation with the driver to inform this and if the driver agrees. This
would help reduce passengers’ anxiety when the driverless car takes an unfamiliar
route.
It is important that during this stage, you keep in mind the following:
•
•
•
Focus on the information you gathered from the previous step- your users, policy that
you must consider, and rules or culture.
Bring together the perspectives and strengths of your team members
Step beyond the obvious solution to increase the innovation potential of your solution.
Some of the techniques you can use to create that creative process during your meeting are
brainstorming, braindump, brainwrite etcs. Please research for the techniques here
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Deliberate
Now that you have a list of items – features, etcs that you think are worth pursuing further,
you will now deliberate over each of these items.
At this stage, you have to make sure you make it explicit among your participants or team
members what you want to avoid. Again, this is when you would refer back to the first step –
the ethical implications caused by the earlier AI applications.
Deliberating is defined as the critical examination of an issue involving the weighing of
reasons for and against a course of action (Deliberative process). Deliberation can involve a
single individual, but the deliberative processes under discussion here involve group
deliberation. Thus, we define a “deliberative process” in our ERF as a process allowing a
group of team members to discuss critically a set of items and to come to an agreement which
will inform decision making.
This is when you will refer to the Ethical Algorithms and AI principles as a guideline in
examining the potential solutions you have identified from the ideation stage.
It is important as well at this step that you situate your decision making of the solution within
the use of culture and organization. It has to enable more effective work if used by people or
organizations.
Produce solution
The final step is producing the solution. It will consist of a set of requirements – needs that the
solution will have or demonstrate.
For example, transparency, explainability, and promoting good well-being towards
passengers may lead to a functional requirement for the driverless car to engage in
conversations to explain the route it is following and why. Transparency and explainability
towards nearby drivers, pedestrians, and bystanders lead to a functional requirement for the
car to signal on turns and lane changes. Transparency towards society in general benefits from
the type of analysis aforementioned, in which requirements can be traced back to the explicit
identification of stakeholders, and an explicit and semantically transparent analysis of their
values and risk.
Respect for human dignity calls for the car to stop in case it encounters a runtime stakeholder
in need of assistance. Benevolence, a trait in virtue ethics, calls for the car to let a nearby driver
cut in front and notify traffic authorities of an accident. Nonmaleficence calls for the car to
slow down in the presence of nearby pedestrians and bystanders, independently of any speed
limits that might apply. And in the case of two lanes merging into one, Justice calls for treating
drivers from the other lane fairly, rather than in a me-first manner.
Summary
We have introduced in this chapter the Ethical Algorithm and AI principles and the Ethical
Reasoning Framework. You must know how to apply this in your real-world case study in
your assignments
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Chapter Nine
Ethical Reasoning Framework Part II- Ethical
Theories as Guiding Principle
The codes of ethics and conduct are widely acknowledged as an important source of
guidelines and standards of ethical practice. However, as we have reviewed in Chapter Seven,
professional codes of ethics and conduct, however, have a number of limitations in providing
us with “how” to solve the problem or issues.
Furthermore, to speak in more detail about the complexity of computing professionals and
hence why ethics has become central to studies and profession, we elaborate further below.
Professional codes also tend to be aimed at individual practitioners, rather than organizations
or teams comprised of diverse, specialised roles, where most development work typically
occurs.
The law is a key element of computer ethics, and includes legislation that has a direct bearing
on computing field, such as data protection, more general legislation (on equality and
discrimination for example), contract law and various other regulatory frameworks. While
legal compliance is seen as a fundamental touchstone for professionals, legalistic approaches
to ethical issues also have their limitations.
An obvious problem is the diversity of legal systems, internationally, and the jurisdiction of
some laws, resulting in a lack of uniformity in enforcement and applicability in key areas.
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While some topic areas, such as intellectual property (the rights to hold exclusivity of
invention, which we will speak in Chapter 12), have an abundance of legislation, others, such
as AI, have very little. This highlights the disparity between the rapid speed of technology
innovation, and the relatively gradual pace of legislative debate and enactment.
This means that the law frequently lags behind new and emerging technologies, resulting in
areas of application where there are legal vacuums and regulatory frameworks are absent.
The associated risks of such technologies can be obscured by the initial rush of adoption and
immersion, making regulation difficult.
Laws, moreover, are not always politically or economically neutral. Some laws protect the
rights of citizens, while others are weighted in favour of state interests and contain exemptions
that enable them to be over-ridden. Other laws are weighted in favour of private, corporate
interests.
Loopholes in the law can also be exploited, such as environmental regulations on computing
energy use and hardware disposal which can be circumvented by companies through various
greenwashing strategies. More fundamentally, the relationship between the “law” and
“ethics” is not always harmonious. Technology can be built that is legally compliant but is not
necessarily ethical.
Therefore, we have introduced the ethical reasoning framework in Chapter 8 and within this
framework, ethical theories are embedded as guiding principle to help structure ethical
decision-making process in future computing professionals.
In this chapter we will introduce three types of ethical theories for you to apply in the ethical
reasoning framework. First, we will present the ethical theories and a simple example how it
is used as guiding principle. Then followed by the limitations of each theory.
Virtue Ethics
Virtue-based ethical theories treat character as fundamental to ethics. It seeks to promote good
character. For example, courage and temperance are virtues; courage gives us the strength to
endure hardship and fear for the sake of something good, while temperance gives us the selfcontrol to resist “too much of a good thing.” Some other virtues include charity, kindness,
justice, humility, diligence, honesty, integrity, generosity, gratitude, and wisdom.
How is virtue ethics applied in computing technology such as AI?
We show below a table adapted from this paper, that outlines key virtues that can be used as
a guiding principle in technology design.
Table 5. Adaption on basic virtues as guiding principles
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Basic virtues
Explanation
How this can be used
as guiding principles
Justice
In computing application, justice efforts could
be used as a principle in determining how the
algorithm will behave within society context
that is just. It should lead to algorithmic
fairness, non-discrimination, bias mitigation
including inclusion.
Algorithmic fairness,
nondiscrimination,
bias mitigation,
inclusion, equality,
diversity
(being fair and
just, for
example
treating people
equally and
dealing fairly
with others)
Honesty
In computing application. It also promotes the
willingness to provide explainability or
(it covers telling
technical transparency regarding AI
the truth, and
applications, for instance by disclosing origins
doing the right
of training data, quality checks the data were
thing in the
subject to, methods to find out how labels
right way at the
were defined etc. Moreover, honesty enables
right time)
to acknowledge errors and mistakes that were
made in AI research and development,
allowing for collective learning processes
explainability,
interpretability,
technological
disclosure,
acknowledge errors
and mistakes
Responsibility
In AI application, this guiding principle
/Accountability should be the governance of choices made in
the creation of the technology. Mainly,
(being
responsibility builds the precondition for
responsible for
feeling accountable for AI technologies and
its own actions)
their outcomes. This is particularly relevant
since AI technology’s inherent complexity
leads to responsibility diffusions that
exacerbate the assignment of wrongdoing.
Diffusions of responsibility in complex
technological as well as social networks can
cause individuals to detach themselves from
moral obligations, possibly leading to
breeding grounds for unethical behavior.
Responsibility, seen as a character disposition,
is a counterweight to that since it leads
professionals to actually feeling liable for
what they are doing, opposing negative
effects of a diffusion of responsibility.
Responsibility,
liability,
accountability,
replicability, legality,
accuracy, considering
(long term)
technological
consequences
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Kindness
(to treat others
with care,
empathy)
Kindness means to develop a sense for others’
needs and the will to address them.
In AI, care builds the bedrock for motivating
professionals to avoid AI applications from
causing direct or indirect harm, ensuring
safety, security, but also privacy preserving
techniques. Moreover, care can motivate AI
practitioners to design AI applications in a
way that they foster sustainability, solidarity,
social cohesion, common good, peace,
freedom and the like.
Non-maleficence,
security, safety,
privacy, protection,
precaution, hidden
costs, beneficence,
well-being,
sustainability,
autonomy, liberty,
consent
Example: Virtue ethics in self driving cars
In regards to driverless cars, we may refer to Justice as guiding principle in how the selfdriving car would respond when seeing a “target” a pedestrian or another car on the road, it
needs to apply the virtue of Just in making decision.
The car’s duties of Justice include itself, its passengers, other road occupants, and the state (or
some other normative authority) within which it is driving.
With this guiding principle, we can ideate necessary features that confines within these ethical
theories. We may do the same to help us ideate creating a self-driving car that has Care, or
Responsible and so forth.
Other references to read on examples of virtue ethics into AI:
Virtue Ethics for Autonomous Car
Virtue Ethics for Social Robots
Utilitarianism ethics
Utilitarianism is a prominent form of consequentialism, which was introduced by philosopher
Jeremy Bentham and promotes maximization of human welfare. The theory determined the
ethical correctness of an act or norm solely on the basis of its (foreseeable) consequences by
maximizing the expected overall utility.
Consequentialism is the “view that morality is all about producing the right kinds of overall
consequences.” Utilitarianism is a very well-known example of Consequentialism, specifically
Act Consequentialism. Act Consequentialism states that “an act is morally right if and only if
that act maximizes the good.”. We can also define the consequence of an action as “everything
the action brings about, including the action itself.” Let us also define “good” to be “human
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welfare” or “good fortune, health, happiness, prosperity”. So to choose the best possible
consequence is to choose the consequence which maximizes human welfare.
Therefore, by assuming Utilitarianism, the ethical question shifts from what whether morality
is determined by the outcomes of actions. Instead, the question becomes about determining
what factors are morally relevant to maximizing utility and how to create an algorithm that
incorporates these factors—one that can be applied complex, real-world situations.
Utilitarianism is the most common theory chosen in AI because AI operates with large
amounts of users’ data and it is a technological tool for people, which is very close to the main
idea of this ethical theory - to achieve a greater good for society. Therefore, the utilitarianism
theory “is one of the most common approaches to making ethical decisions, especially
decisions with consequences that concern large groups of people, in part because it instructs
us to weigh the different amounts of good and bad that will be produced by our action”. The
assessment of good and bad should be done by the people using the system.
Utilitarianism can also be used for evaluation such as cost-benefit analysis in medical
diagnostics, “big data” analytics, robots to help care for the elderly, and lethal autonomous
weapons systems in war.
An example how the cost side of equation is evaluated for the above example is to evaluate
the downside. Replacing human labor with robots will threaten to take away jobs, separate us
from meaningful work, separate us from being able to understand the data we analyze, leave
the elderly isolated from human contact, and, ultimately even threaten our lives, perhaps even
driving us extinct. These downside risks are significant and worthy of serious consideration
starting before these technologies are implemented.
Example: Utilitarianism in self driving cars
We use the self-driving car as an example of how utility theory can be used as a guiding
principle in ethical reasoning framework.
Utilitarianism can be applied in the algorithm of self-driving cars in calculating the
distribution of risks in avoiding car crash. We can ideate some ideas such as:
•
•
•
self-driving cars to follow a utilitarian standard of saving the maximum number of
statistical lives
the distribution of risk is applied equally to everyone in the society.
Parameters will not include age and gender etcs so that everyone has an equal risk of
being harmed but everyone in society also is probabilistically safer due to self-driving
car technology.
Further details can be referred to the below:
•
The utilitarian approach to self-driving cars
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Deontology
Deontology is derived from the Greek words deos meaning “duty” and logos meaning “the
study of”. Duty-based ethics, in direct contrast to Consequentialism, does not look at the “
states of affairs ... choices bring about” but rather states that “some choices cannot be justified
by their effects.” For example a person may commit a crime but one cannot take matters in
own hand to kill that person, rather that person who committed the crime has to go through
formal justice.
Deontology is often associated with Immanuel Kant. He believed that because every person
has an ability to reason, they have inherent dignity. Therefore, it is immoral to violate or
disrespect this dignity. For example, we shouldn’t treat a person as merely ‘a means to an
end’.
According to Kant, a primary proponent in Deontology, “the sole feature that gives an action
moral worth is not the outcome that is achieved by the action, but the motive that is behind
the action.” People have the duty of doing the right thing, even if the result is bad. In order to
know what is “right” a rule set is usually set in place such as “It is wrong to kill innocent
people” or “It is wrong to tell a lie.”
The majority of ethicists today think that deontology is the approach that should be used to
develop AI systems. We can encode rules in their programs and that will guarantee that AI
will always be on our side. But still, the consequences of closely following a predefined set of
rules can still be rather unpredictable. It is hard to make rules that for sure won’t make all the
universe go into paperclips.
Hence, Deontology is usually used together as a guiding principle with the Three Law of
Robotic by Isaac Asimov. The Law are:
•
•
•
A robot may not injure a human being or, through inaction, allow a human being to
come to harm.
A robot must obey the orders given it by human beings except where such orders
would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with
the First or Second Laws.
In summary, the Asimov’s laws basically encompass the values of beneficence and nonmaleficence, fairness, and privacy protection.
Example: Deontology in self driving cars
Taking the idea of prioritizing human life and the most vulnerable road users and phrasing
the resulting hierarchy in the spirit of Asimov’s laws, we can ideate the below ideas in using
deontology to design the self-driving cars:
•
Minimize the harm to the driver and passengers of the self-driving car.
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•
•
•
Minimize the harm to any human outside of the self-driving car, as long as it does not
conflict with the first rule.
Do not destroy the property of others, as long as it does not conflict with the previous
two rules.
Follow all of the rules of the road that apply to your current location, as long as it does
not conflict with the previous 3 rules.
You can define “minimize” as “to reduce to the smallest possible amount or degree.”
You may refer in more detail from this paper “Deontological Ethical System for Google’s SelfDriving Car”
Limitations of each ethical theories
It is important to be aware that despite these guiding principles are based on long standing
philosophy on morality, each has it’s own limitation. We will use the same example of selfdriving car to illustration the limitation of each ethical theory.
We detail below based on this reference Autonomous Driving Ethics: from Trolley Problem
to Ethics of Risk
Virtue ethics limitation
Presently, the actual
variants of machine
reinforcement, where
feasibility is shown by
called ChaffeurNet.
operating systems of autonomous vehicles demonstrate different
learning. For example, autonomous vehicles can be trained via
wrong acts are punished and right acts are rewarded. The technical
a recent implementation of imitation learning for real-world driving
In this process, ethics in the form of a set of virtues can provide guidance as a pattern of the
positive signals. Ultimately, machines or autonomous vehicles themselves should (learn to)
recognize situations that require moral action, and decide to act accordingly. Depending on
the number of trainable parameters, even complex correlations from reality can be
represented, which would provide an adequate representation of reality. To enable a
good universality, it is important that the machine learning models can generalize well. The
problem with such models is that corner cases, which are poorly represented by the training
data, lead to unwanted decisions.
However, the most pressing challenge for a virtue-based autonomous vehicle is
the explainability of its underlying logic and thus the attribution of responsibility. Namely, it
should be made clear how the virtues of such cars have been formed through experience, and
how a given car has been led to its particular action. In this regard, autonomous vehicles or
driver assistance systems at present should and cannot be regarded as moral agents, but rather
weak actors of responsibility. Therefore, truly applying virtue ethics to autonomous vehicles
seems impermissible until questions of explainability and responsibility can be answered.
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Utilitarianism ethics limitation
The problem here is that having a utilitarianism self-driving car will lead to unreliable and
unsafe outcomes for those involved in an accident with the self-driving car..
In using utilitarianism, the situation does not involve choosing the life of the user over the life
of many people but rather focuses on choosing between two people of different worth. The
utilitarianism solution would be to choose the person with the lowest “worth” and hit them.
A big problem with the situation is that the self-driving car cannot put any value on the two
motorcyclists.
The self-driving car only has sensors that can distinguish shapes and can categorize those
shapes into accurate predictions. From looking at those shapes it can accurately tell that the
two motorcyclists are in fact motorcyclists but it cannot tell which one is worth hitting.
Making a decision that has the best consequence would be difficult to implement. We can
refer to the Google Self-driving car. It uses two visual cameras. These cameras are used as
stereo cameras meant to judge the distance as well as to visually see if there is an obstacle. The
lidar, or light detection and ranging, system is what does most of the sensor work.
The cameras are not meant to visually analyze a specific object, which is what it would need
to do in order to determine the worth of the motorcyclist. However, this leads to another
problem where the car won’t be able to make a decision because of technological limitations.
In order to make a proper utility decision it has to determine which consequence is the best.
If the self-driving car did hypothetically have the proper technology to determine every factor
from visual recognition, it would still need to run scenarios that would determine which
outcome is the best and the number of scenarios increase drastically with more information.
For example, with better technology perhaps the car could estimate that the car behind him is
moving slower and can take the impact without much damage. So now the car would have to
compare this outcome with the outcome of swerving into the helmeted motorcyclist. There
could be many more of these estimations, all adding significantly more computation
Furthermore, utilitarian vehicle that pursues unrestricted optimization may be
less transparent or at least less foreseeable before the underlying logic is inspected to explain
why a certain decision was made by the self-driving car (most machine learning uses statistical
analysis hence there is no reasoning or explainability provided to why a decision was made).
Besides, the central question here is whether it is right and permissible to actively inhibit the
utility of an individual to achieve greater utility for other individuals.
Deontology ethics limitation
In general, deontological theories judge the morality of choices by criteria different from the
states of affairs the choice brings about. One of the limitation of applying deontology for
building rules into a self-driving car is building a hierarchy of constraints (e.g., “forbidden,
permissible, obligatory actions”) following the Asimov’s Law to guide them towards
desirable behavior in dilemma situations.
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In general, deontology in its strengths offers a computational structure for judgment and thus,
at least from a practical perspective, are achievable, However, it can be argued that such rulebased approaches ignore context-specific information such as the probability of occurrence of
current and future conditions. Hence, the self-driving car may undertake dangerous
behaviors in order to adhere to its strict rule. According to this, the representation of reality is
only possible to a limited extent. This may also lead to a lower level of social acceptance of
implementing rule-based approaches since moral decisions and obligations are not absolute
but dependent on context. Although rule-based approaches can be implemented very well in
software (technical feasibility), the number of rules needed that can conflict with each other
arbitrarily represents an enormous complexity. The universality of such approaches is also
poor since each so-called corner case must be covered by a rule in advance. Only
the explainability is given by the representation of rules with different prioritization. Therefore,
from a technical and functional perspective, implementing a deontic approach in the systems
of AVs seems to exhibit many complications.
Summary
We have seen how it is complex to create, or develop Ethical AI applications. Hence why it is
required a thorough framework to support the ethical reasoning.
Which brings us to the next step in Ethical reasoning, deliberating which would be the best
decision to make in either improving, or creating new ethical AI applications in the next
chapter.
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Chapter Ten
Ethical Reasoning Framework Part III - Work
System Design – Deliberation, Solution and
Prototyping
In Chapter 9, we have explained further how guiding principles can be used within the ethical
reasoning framework and the limitation of guiding principles which brings us to the next step
in ethical reasoning framework – deliberation and prototyping.
Hence, in this chapter, we will explain how do we further solve the problem to get to the
solution that is minimizing the ethical implications or issues.
We shall firstly introduce the Work System Design which forms the theory in laying out the
next steps in deliberation and prototyping.
Work System Design
Work system design is a process of changing organization, technology, and facilities to
improve work practices. A redesign team includes workers, management, organizational
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specialists, and system analysts. The redesign process focuses on worker reflection on how
work is typically done. New designs focus on including human in the loop in the work
practices.
By understanding people at work in everyday setting, observing activities over time in different
circumstances, we can study and document work practices.
We view natural settings broadly: We consider a teacher in a school within a community,
not just a classroom. We seek to grasp an entire place, with its nested contexts: Rather than
focusing on a physician in a patient exam room, we study the clinic, including the waiting
room.
Thus, a study of work practices is actually a study of a setting; how do people get work done
over time as a practice. Practice is defined as something that you do routinely or habitually.
We describe this method better in an example below.
A team of technologists and system analysts proposes an integrated computer system, called
the “Job Multiplexer”.
Figure 16: Job Multiplexer.
This AI system will dynamically transform a customer order into a work plan. The goal
initially was to drive people out of the system and hence cut costs.
But using work system design, the AI system works in a different work that includes human
in the loop.
The job multiplexer will automatically transmit messages between the diverse databases and
scheduling programs. The information systems will validate and complete orders, confirm
resource availability, order supplies, and schedule tasks. Individual workers will receive on
their workstations an ordered queue of tasks to do. These tasks involve getting information
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from outside the system (e.g., contacting the customer, confirming credit worthiness) and
assembling the actual work product (e.g., telephone circuits).
As new jobs enter the system from customers, the job multiplexer dynamically reassigns tasks
to workers to satisfy the company’s objectives of timeliness and resource priorities for
different customers. In so far as different workers are trained to accomplish different tasks,
the job multiplexer will dynamically reconfigure the office.
Workers sitting at their terminals will constitute new organizations, integrated and focused
in new ways, under control of the job multiplexer, without any management intervention or
communication between workers.
Dynamic reconfiguration of people, technology, and facilities will maximize efficiency. This
design allows for real-time and seamless flow of information throughout the business.
Tedious and error-prone human copying of information is eliminated. The overall system is
easily modified and updated. Formal proofs of correctness demonstrate that the scheduling
algorithm is correct.
By this design, people stay in place and work is reconfigured around them. The opportunity
for unnecessary and distracting communication between people is eliminated. Unusual
situations will be handled by the manager, who will be notified of delays and error conditions.
Automatic reporting to supervisors on a daily basis will quickly show and compare each
worker’s throughput, revealing where training is required.
Thus by the use of work system design – understanding how people go about their practices
in the real-world setting (i.e, how they shop, make decision in patient care, etcs), the AI system
works together with “humans” in the loop rather than replacing jobs and putting workers out
of jobs. In the end, new expertise arises from this system, and potentially new job creation.
Therefore when designing AI automation using this work system design thinking, we always
put understand humans and socio-technical elements within the solution. We would need to
understand roles, policies, procedures, including culture.
References on work system design can be referred to the following
Formal Modeling Brahms
Modeling and Simulating Work Practices
In this unit, we adapt the scientific method of work system design at the deliberation step in
Ethical Reasoning Framework.
To illustrate an example how we can think in terms of work system design for deliberation in
Ethical Reasoning Framework is to design how can we focus including human in the loop
working with the AI automation to improve the what people naturally do in practice.
Let us revisit the ethical reasoning framework:
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Figure 17. Ethical Reasoning Framework (ERF).
Let us refer to step Deliberate. We have seen in the previous chapters, examples of how
problems are identified using Code of Ethics (Chapter 7), and how we use guiding principles
(Chapter 8) to think about the features (functions, design as a whole), that improves selfdriving cars.
We have argued that even by using Guiding principles as a moral guidance in ideating
features, etcs in improving or creating self-driving cars, it still has its limitations.
In the most basic sense, it is because of the limitation of algorithms and predictive analytics
that they are estimations; probabilistic outcomes, based on historical data. This is because the
historical data that is recorded and perceive are about materials, such as objects, terrain and
they tend not to change too much over time. A face is a face, a figure is a figure, a road is a
road. However, human behavior, and society, that is continuously developing, and in many
ways changing.
Furthermore, sensors camera’s performances as we have described in Chapter 8 are not meant
to visually analyze a specific object, which is what it would need to do in order to determine
the worth of the motorcyclist if using virtue ethics.
Hence why the next step is to further deliberate all the items we have ideate using work
system design as a method to deliberate. The aim should be to include human in the loop of
this system that respects Ethical Algorithms and AI principles, revisiting the principles below.
Table 5. Ethical Algorithms and AI principles
Human, societal and environmental wellbeing: AI systems should benefit individuals,
society and the environment.
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Human-centred values: AI systems should respect human rights, human intellect and
dignity, diversity, and the autonomy of individuals.
Fairness: AI systems should be inclusive and accessible, and should not involve or result in
unfair discrimination against individuals, communities or groups.
Privacy protection and security: AI systems should respect and uphold privacy rights and
data protection, and ensure the security of data.
Reliability and safety: AI systems should reliably operate in accordance with their
intended purpose.
Transparency and explainability: There should be transparency and responsible
disclosure so people can understand when they are being significantly impacted by AI, and
can find out when an AI system is engaging with them.
Contestability: When an AI system significantly impacts a person, community, group or
environment, there should be a timely process to allow people to challenge the use or
outcomes of the AI system.
Hence, even when you are concerned with algorithms you must have a work system design
thinking and fall back on the Ethical Algorithms and AI principles to help you further
deliberate the How to implement it as part of a system.
We shall use the continued example from previous steps, on self-driving cars to show how to
deliberate.
Example: Deliberation from the ideas ideated for self-driving cars
The steps below is a simple example to show how deliberation process can take place from
previous steps. Assume that you had decided for using utilitarianism and deontology as a
guiding principle to ideate features on improvement. Let us assume now you have a series
of ideas such as:
Step 1: Understanding human’s use of cars in natural setting, and policy and culture
Humans are dynamic in multiple ways. First, humans might use systems differently than
designers intended. For example, one motivation for automated driving is to minimize the
potential for human error. Systems try to achieve this by reducing the number of basic vehicle
tasks that the driver has to perform, to allow them to focus more on other important drivingrelated tasks, such as monitoring traffic and anticipating dangerous situations.
Unfortunately, in practice, studies have observed that in situations where more tasks are
transferred from the human to the machine, people perform other non-driving-related tasks
more frequently. The result is reduced (instead of improved) situational awareness, and
slower (instead of faster) responses to safety-critical events.
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This can be described as an “irony of automation”, where the introduction of automation
does not solve an issue (e.g., reduce human errors), but instead changes human behavior
and introduces new, different problems.
The human remains dynamic. A second way in which humans are dynamic is in their
learning and unlearning of skills, habits, and knowledge. Together, these shape expectations
of a system and specific interaction patterns. However, knowledge (of a system’s functioning)
might be incomplete and habits might prevent the learning of new skills, and these together
might limit appropriate system use.
Similar to humans, automated systems and the environments in which they operate are also
dynamic. First, as an instantiation of artificial intelligence, automated systems often learn from
their environment, which can shape and change their responses over time.
Second, automated systems are typically developed for use in specific contexts. In the case of
automated vehicles, the Society of Automotive Engineers (SAE) has identified specific levels
of automation for the functionality of the car, which can be used in specific “operational
design domains,” or contexts.
However, the context in which a car is driving can change over time and space, and thereby
the system’s functioning and reliability can change over time and space. For example,
adaptive cruise control might maintain the speed of a vehicle and a safe distance to cars in
front of it on regular highways, under normal traffic and weather conditions. Yet what is safe
might change with context: If there is suddenly heavy snowfall, the system might fail to act
appropriately, and responsibilities that the car had (e.g., maintaining a safe distance to the car
in front of it) might suddenly be transferred to the human.
The combination of dynamic humans that use dynamic systems can create situations in which
there is confusion.
If the user is not alerted, or if they overlook an alert, the result is mode confusion: a
discrepancy between the actual system state and the human’s belief about the state.
In terms of policy and legality, if a car is given the “power” to decide on when and how to
crash, and if it hits the pedestrian, who is then responsible for the accident? Is it the
manufacturer, the designer of the car?
In terms of culture, how do we incorporate the dynamics of drivers for example in Malaysia
who often cut the driving lanes and may do so suddenly. The drivers in a culture context uses
hand as a stop” to stop car. Secondly, parking space are not followed, anything could be used
as a parking space. How would a self-driving car deal with making decision on how and
where to park when there formal rules are often not followed?
Hazard lights, signal lights are not used according to guidelines. The system would detect
fails emergency, false turning and make the wrong decisions.
The culture aspect is what makes AI automation fail in the real world because all these are
implicit knowledge, and practices that vary from one culture to the other.
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You may refer in detail of the example from this paper Getting and Keeping Human in the
Loop
Step 2 Lay out the items ideated
Let us assumed from the previous, that we have chosen deontology ethics to ideate how we
can improve current self-driving car system. It resulted in the following ideas (items).
•
•
•
•
Minimize the harm to the driver and passengers of the self-driving car.
Minimize the harm to any human outside of the self-driving car, as long as it does not
conflict with the first rule.
Do not destroy the property of others, as long as it does not conflict with the previous
two rules.
Follow all of the rules of the road that apply to your current location, as long as it does
not conflict with the previous 3 rules.
Step 3 Deliberate on the ideas
Now we will deliberate our ideas (items) that we have laid out.
Our improved self-driving car would need to avoid the head-first collision, since that would
break the very first rule, minimize the driver/passenger of the self-driving car. The second
rule states that the car should minimize harm to any other people outside the car unless it
conflicts with the first rule. Since we devised this situation to have no other solution other
than running into the pedestrians, it would choose to run into the pedestrians because
otherwise the first rule would be broken.
However, if the self-driving cars choose to run into the pedestrian, this will in turn violate the
legal framework. Who would be responsible for the accident?. In this case, it would be us –
the designers of the system.
Thus, we will decide that the decision to crash a car should not be made by the vehicle, and
instead the self-driving car when detecting that there is a risk of crash cash, would inform the
driver to take control over the self-driving car.
The next step is to think about how to design an autonomous agent (self-driving car) system
– its algorithm to interact with the user. What are the considerations that we must take into
account?
We may refer to the Ethical Algorithms and AI principles (table 5) and we shall describe some
examples how this can be used to further deliberate our ideas.
Deliberate human centered values – our system would respect human right and respecting
human intellect in making its own moral decision in the matters of life and death. Therefore
we would use algorithms to make calculation of risks and when at a certain risks that requires
moral decision, would interact and inform the driver.
Deliberate fairness – our system should be inclusive and accessible to all group of people,
thus computation should be cost-effective, where even population in developing country may
benefit from the system.
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Deliberate privacy protection and security – we have to ensure in our system that all data
collected are not shared with any third party and is used solely to improve the safety of our
passengers.
Hence we have to ensure data that we collect from sensor camera, and computed on the cloud
are anonymous and secured. Each individual users are given a unique ID and any name
details and associated identification are masked.
Deliberate reliability and safety – we will have to consider the user experience and
engagement AI systems should reliably operate in accordance with their intended purpose.
Now that we have deliberate, we have now made an ethical decision to how we want to
improve or create new self-driving car that considers human in the loop.
Thus, we go to the next step, that is to produce the solution, following ERF (see again Figure
17).
Produce solution based on the deliberation
The next step is to now turn the results from our deliberation into clear documentation of the
solution that we will propose.
Below, we show a simple table where we list down what we had decided that is best ethically
for the user and environment.
Table 7. Our solution
Our algorithm and user interaction design as a system for the self-driving car would be
designed with the following features.
Functional features (algorithms)
1. The algorithm would also take over the driver’s manual driving when traffic is
normal, no weather issue, and is on a straight and safe highway
2. The algorithm would calculate the risks of accidents by alerting user on the scale of
moderate to severe risk.
a. The risk calculation to avoid errors in its calculation would look at data of
weather (if raining higher risk of accidents), traffic congestion, including
level of driver’s attention.
b. The risk calculation must consider time, it has to be sensitive in alerting, at
least 10 minutes before the situation could occur.
3. The algorithm when detecting the risk would alert by sound and speech to the
driver and show an amplified user interface to augment the driver’s decision
making process (it could show a text with Alert – Risk of safety and shows why it
has computed as so – weather is bad, its limitation to perceive environment that may
obstruct its sensor sensitivity and hence asks driver to now take over the control)
User experience features (interface design)
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1. The interface design will show interesting visual of the car making its decision each
time in driving the car for the user to engage and augment’s driver’s intellect. (this
is to ensure they pay attention to what’s ahead and can be prepared to take over
when needed)
2. The interface design should allow users’ to give feedback on its performances and
interaction (e.g. this is dull, I am sleepy, or I don’t understand why we are going
through this route).
We have shown an excerpt of how we can use Ethical Reasoning Framework (ERF) and so
now we can move to the next step which is prototyping.
Prototyping
When you are including humans in the loop of your system design (we refer to system to
include algorithms, and user interaction design), we therefore must involve users in how we
develop our system. Their feedback is most important in order for us create a system that
includes the user in the loop.
The user must be able to visualize what the system can do and interact with a dummy data
and the designer (the computing professional) must then further deliberate and ideate to
improve it. So, system designing in principle is always an iterative and continuous process.
You may find yourself then doing further research to refine the problem and principles used.
When you view building computer system this way, your system will always be getting better
in performances. Because remember human nature is dynamic and you would always need
to learn in order to make sure your system fits within the work practice of natural settings.
This is where prototyping becomes an important technique to include in any system design
and remember that an algorithm does not sit in silo in a software system. An algorithm needs
to factor in how the users would be using and manipulating those data computed. So in the
modern design of software system, algorithms should never be viewed as a piecemeal
solution to a problem.
So what is exactly is a prototype and how do develop prototypes?
A prototype is a simple experimental model of a proposed solution used to test or validate
ideas, design assumptions and other aspects of its conceptualisation quickly and cheaply, so
that you can make appropriate refinements or use it to demonstrate your solution to users
before you actually implement it.
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Prototypes can take many forms, that is tangible in demonstrating the potential solutions. You
may use sketches of storyboards to illustrate it, rough paper prototypes of digital interfaces,
and even role to play out how a service will be provided.
So how do you conduct prototyping? We describe this in the next section
How to build prototypes
We will list down the simple steps to build a prototype.
Create a rough presentation of your solution
There are two types of prototypes to start creating a rough presentation of your solution – low
fidelity or high fidelity.
Low fidelity prototypes techniques
A low fidelity prototype represent a simple and incomplete version of the solution (i.e, final
product). In a low-fidelity prototype, not all visual features and content elements are
conveyed.
The most common approach in creating a low-fidelity prototype is using wireframe.
Wireframes are used to represent the basic structure of a website/ web page/ app. It serves
as a blueprint, highlighting the layout of key elements on a page and its functionality.
You can use tools such as Creately you can create clickable wireframes by adding links to the
wireframe elements, that will allow your users to navigate from one interface to the other.
Below is an example what a wireframe looks like:
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You can visit this page to use the template.
Another method is called the storyboard. Storyboards are another low-fidelity prototyping
method that helps visualize the user’s experience in using your product or how the user
would interact with your product. Below, is an example how it looks like.
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You may also use diagrams. There are multiple diagram types that can help you visualize
different aspects of a product, which can in turn help you optimize your prototype.
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•
•
•
Mind maps can help visualize the structure of a system. You can use it to develop the
idea in your head and identify the different elements of your product.
Customer journey maps can help you understand how the customers would interact
with your product across various touchpoints. Like with storyboards, customer
journey maps will help you develop an empathetic understanding of the user.
Flowcharts can be used to visualize user flows or system flows.
You can also create animation to visualize how your product works.
For example, if it is a mobile app, you can animate how a user would navigate from one screen
to the other. This will help the stakeholders or users get an idea about the functionality of the
product.
High-fidelity prototypes
Compared to low-fidelity prototypes, high-fidelity ones are more interactive and highly
functional. They represent something that is closer to the real product with most of the design
elements developed.
You can use the interactive UI Mockups as a method. A UI mockup is a more fleshed-out
version of the wireframe. It represents the color schemes, typography and other visual
elements that you have chosen for the final product.
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Another method is to use physical models if the final product is a physical one. you can use
different materials to create a model that represents the final look, shape and feel of the
product. You can use materials such as cupboards, rubber, clay etc. here. Think of designing
a new interactive AI wearable so you may use physical model to show this.
The final and interesting method to use is the Wizard of Oz prototyping. This is a type of
prototype with faked functions. This means when a user interacts with the product, the system
responses are generated by a human behind the scene rather than by a software or code.
This prototyping technique allows you to study the reaction of the user at a lesser cost.
https://medium.com/divya-krishnan-design/ui-ux-for-autonomous-vehicle-interface-tobuild-trust-de7f4c545c3b
Summary
In this chapter we have reviewed and argue why the deliberation and prototyping is an
important step to carry out within the ethical reasoning framework.
You will realised that at the end of the process, you have actually created or improved an
existing system that is more ethical! It respects human capabilities, policy, law, including
culture.
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Chapter Eleven
Becoming a reflective computing professional
University is a new environment. You are probably surrounded by a wider variety of
classmates than you experienced in high school - students of different ethnicities and
nationalities; students of different economic and social backgrounds; students from more
regions of the state, country, and the world; students of more interests and accomplishments;
older students returning to school after varied experiences; and upperclassmen and graduate
students with developed knowledge and commitments.
Your lecturers will often be deeply involved in their areas of specialization, in ideas they have
pursued over time with their colleagues, and in projects that apply their learning to improving
various aspects of life.
The content and assignments you have been assigned in your courses will introduce you to
new subjects and to deeper levels of understanding of subjects. The project assignments
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especially provide opportunities to pursue ideas and learning on your own in directions not
limited by the unit offering.
Many of your classmates may also have abilities, skills, and knowledge you may admire- from
the computer programming whiz to the wrestling champion to the classmate who is just so
witty. Seeing these accomplishments may open your eyes to new goals and lead you to
reassess exactly where your best talents lie.
How do you make sense of all you come in contact with and set some directions for yourself?
Some questions will sort themselves out spontaneously as you become involved in a heated
discussion or suddenly want to do extra reading for a course that fascinates you.
Some instructors may encourage you to think about your reaction to what you are learning
through discussion questions and informal assignments. They may be available for you to talk
with outside of class, during office hours, or even over coffee.
Informal talk with your friends and classmates also helps you sort through all the new
ideas and experiences you are confronting.
Thus, in this chapter, we will teach you a very valuable skill, reflective writing. This skill will
help you to become a reflective computing professional, and will also improve your
intrapersonal skills (see Chapter 2 on what it means).
We will first introduce the definition of reflection in general, its theory, following by the Gibbs
Reflective Cycle model as method to guide you in reflective writing. Then we will show an
example how to write your reflection using Gibb’s model.
What, Why and How? Reflective writing
For students to engage in deep learning, reflection is required, whereas surface learning may
occur because of a lack of reflection. In this unit, we define reflection as conceptualized selfstudy, in which one engages in intentional and systematic inquiry in one’s own practice,
recognized as a complex and deliberate process of thinking about and interpreting an
experience in order to learn from the experience to improve practice.
Reflective writing helps you make personal sense out of the rich, complex ,and confusing
information you are learning, ideas you are confronting, and people you are working with.
As the term implies, this writing is like a mirror, giving you an opportunity to look at your
developing self. This personal connection increases your motivation, purpose, and
involvement by helping you define what you want to learn and say.
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Gibb’s reflective cycle
Gibbs' Reflective Cycle was developed by Graham Gibbs in 1988 to give structure to learning
from experiences. It offers a framework for examining experiences, and given its cyclic nature
lends itself particularly well to repeated experiences, allowing you to learn and plan from
things that either went well or didn’t go well. It covers 6 stages:
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Description of the experience
Feelings and thoughts about the experience
Evaluation of the experience, both good and bad
Analysis to make sense of the situation
Conclusion about what you learned and what you could have done differently
Action plan for how you would deal with similar situations in the future, or general
changes you might find appropriate.
Each stage is given a fuller description, guiding questions to ask yourself and an example of
how this might look in a reflection. It guides you in different depths of reflection.
The model
Below is the Gibbs’ reflective cycle.
Figure 18. Gibbs reflective cycle
Refer to Figure 18. This model is a good way to work through an experience. This can be either
a stand-alone experience or a situation you go through frequently, for example meetings with
your team. Gibb’s originally advocated its use in repeated situations, but the stages and
principles apply equally well for single experiences too. If done with a stand-alone experience,
the action plan may become more general and look at how you can apply your conclusions in
the future.
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For each of the stages of the model a number of helpful questions are outlined below. You
don’t have to answer all of them but they guide you about what sort of things make sense to
include in that stage. You don’t have to answer all of them but they guide you about what sort
of things to make sense to include in that stage. You might have other prompts that you may
include within this model.
For each of the stages of the model a number of helpful questions are outlined below.
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What happened?
When and where did it happen?
Who was present?
What did you and the other people do?
What was the outcome of the situation?
Why were you there?
What did you want to happen?
Example- Application of Gibb’s to group assignment
We shall in the below some examples of reflective writing using Gibb’s model for each stages
for a group assignment that you are involved in.
Description
Here you have a chance to describe the situation in detail. The main points to include here
concern what happened. Your feelings and conclusions will come later.
Helpful questions:
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What happened?
When and where did it happen?
Who was present?
What did you and the other people do?
What was the outcome of the situation?
Why were you there?
What did you want to happen?
Example of Description
For an assessed written group-work assignment, my group (3 others from my course) and I
decided to divide the different sections between us so that we only had to research one
element each. We expected we could just piece the assignment together in the afternoon the
day before the deadline, meaning that we didn’t have to schedule time to sit and write it
together. However, when we sat down it was clear the sections weren’t written in the same
writing style. We therefore had to rewrite most of the assignment to make it a coherent piece
of work. We had given ourselves enough time before the deadline to individually write our
own sections, however we did not plan a great deal of time to rewrite if something were to go
wrong. Therefore, two members of the group had to drop their plans that evening so the
assignment would be finished in time for the deadline
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Feelings
Here you can explore any feelings or thoughts that you had during the experience and how
they may have impacted the experience.
Helpful questions:
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What were you feeling during the situation?
What were you feeling before and after the situation?
What do you think other people were feeling about the situation?
What do you think other people feel about the situation now?
What were you thinking during the situation?
What do you think about the situation now?
Example of Feelings
Before we came together and realised we still had a lot of work to do, I was quite happy and
thought we had been smart when we divided the work between us. When we realised we
couldn’t hand in the assignment like it was, I got quite frustrated. I was certain it was going
to work, and therefore I had little motivation to actually do the rewriting. Given that a couple
of people from the group had to cancel their plans I ended up feeling quite guilty, which
actually helped me to work harder in the evening and get the work done faster. Looking back,
I’m feeling satisfied that we decided to put in the work
Evaluation
Here you have a chance to evaluate what worked and what didn’t work in the situation. Try
to be as objective and honest as possible. To get the most out of your reflection focus on both
the positive and the negative aspects of the situation, even if it was primarily one or the other.
Helpful questions
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What was good and bad about the experience?
What went well?
What didn’t go so well?
What did you and other people contribute to the situation (positively or negatively)?
Example of Evaluation
The things that were good and worked well was the fact that each group member produced
good quality work for the agreed deadline. Moreover, the fact that two people from the group
cancelled plans motivated us to work harder in the evening. That contributed positively to the
group’s work ethic. The things that clearly didn’t work was that we assumed we wrote in the
same way, and therefore the overall time plan of the group failed
Analysis
The analysis step is where you have a chance to make sense of what happened. Up until now
you have focused on details around what happened in the situation. Now you have a chance
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to extract meaning from it. You want to target the different aspects that went well or poorly
and ask yourself why. If you are looking to include academic literature, this is the natural
place to include it.
Helpful questions:
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Why did things go well?
Why didn’t it go well?
What sense can I make of the situation?
Example of Analysis
What knowledge – my own or others (for example academic literature) can help me
understand the I think the reason that our initial division of work went well was because each
person had a say in what part of the assignment they wanted to work on, and we divided
according to people’s self-identified strengths. I have experienced working this way before
and discovered when I’m working by myself I enjoy working in areas that match my
strengths. It seems natural to me that this is also the case in groups.
I think we thought that this approach would save us time when piecing together the sections
in the end, and therefore we didn’t think it through. In reality, it ended up costing us far more
time than expected and we also had to stress and rush through the rewrite. I think the fact we
hadn’t planned how we were writing and structuring the sections led us to this situation.
I searched through some literature on group work and found two things that help me
understand the situation. Belbin’s (e.g. 2010) team roles suggests that each person has certain
strengths and weaknesses they bring to a group. While we didn’t think about our team
members in the same way Belbin does, effective team work and work delegation seems to
come from using people’s different strengths, which we did.
Another theory that might help explain why we didn’t predict the plan wouldn’t work is
‘Groupthink’ (e.g. Janis, 1991). Groupthink is where people in a group won’t raise different
opinions to a dominant opinion or decision, because they don’t want to seem like an outsider.
I think if we had challenged our assumptions about our plan - by actually being critical, we
would probably have foreseen that it wouldn’t work. Some characteristics of groupthink that
were in our group were: ‘collective rationalisation’ – we kept telling each other that it would
work; and probably ‘illusion of invulnerability’ – we are all good students, so of course we
couldn’t do anything wrong.
I think being aware of groupthink in the future will be helpful in group work, when trying to
make decisions in future situation
Conclusions
In this section you can make conclusions about what happened. This is where you summarise
your learning and highlight what changes to your actions could improve the outcome in the
future. It should be a natural response to the previous sections.
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Helpful questions:
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What did I learn from this situation?
How could this have been a more positive situation for everyone involved?
What skills do I need to develop for me to handle a situation like this better?
What else could I have done
I learned that when a group wants to divide work, we must plan how we want each section
to look and feel – having done this would likely have made it possible to put the sections
together and submit without much or any rewriting. Moreover, I will continue to have people
self-identify their strengths and possibly even suggest using the ‘Belbin team roles’framework with longer projects. Lastly, I learned that we sometimes have to challenge the
decisions we seem to agree on in the group to ensure that we are not agreeing just because of
groupthink
Action plan
At this step you plan for what you would do differently in a similar or related situation in the
future. It can also be extremely helpful to think about how you will help yourself to act
differently – such that you don’t only plan what you will do differently, but also how you will
make sure it happens. Sometimes just the realisation is enough, but other times reminders
might be helpful.
Helpful questions
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If I had to do the same thing again, what would I do differently?
How will I develop the required skills I need?
How can I make sure that I can act differently next time
Example of Action Plan
When I’m working with a group next time, I will talk to them about what strengths they have.
This is easy to do and remember in a first meeting, and also potentially works as an ice-breaker
if we don’t know each other well. Next, if we decide to divide work, I will insist that we plan
out what we expect from it beforehand. Potentially I would suggest writing the introduction
or first section together first, so that we have a reference for when we are writing our own
parts. I’m confident this current experience will be enough to remind me to suggest this if
anyone says we should divide up the work in the future. Lastly, I will ask if we can challenge
our initial decisions so that we are confident we are making informed decisions to avoid
groupthink. If I have any concerns, I will tell the group. I think by remembering I want the
best result possible will make me be able to disagree even when it feels uncomfortable
Adapted from Gibbs' Reflective Cycle Writing
Summary of chapter
Most often as a technical student, we do not really enjoy writing. However, writing in a
reflective manner would help us to become aware of our learning experiences, including how
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we learn. Gibbs reflective cycle model is one method to help you structure properly how you
can carry out reflective writing.
Reflection is important, it is a skill that goes hand in hand with your research skills to develop
your life-long learning skills.
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