July 2025
CONFIDENTIAL
About Me…
Philip Pang S H
philippang001@suss.edu.sg
About this Hybrid Course
• 3 Face-to-Face Seminars
• 3 Online Zoom Sessions
• Alternate Mondays 7-10 pm
• Attendance and engagement required for Participation Score (10%)
• Lesson Summary (cannot be AI-generated) in lieu of attendance
Assessments
CONFIDENTIAL
Plagiarism and collusion
SD103 Academic Integrity
COR160 Academic Writing
• Plagiarism and collusion are forms of cheating and are not acceptable in any
form in a student’s work, including GBA and ECA.
• Plagiarism and collusion are taking work done by others or work done together
with others, respectively, and passing it off as your own.
• You can avoid plagiarism by rephrasing/rewriting the ideas (using your own
words) and giving appropriate references when you use other people’s ideas,
words or pictures (including diagrams).
• The electronic submission of your GBA/ECA is screened by plagiarism
detection software.
• For more information about plagiarism and collusion, you should refer to the
Student Handbook. SUSS takes a tough stance against plagiarism or collusion
CONFIDENTIAL
Forming GBA Groups
This course requires you to work in groups for your GBA assignment
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Form yourselves into groups of 4 students
Say “hello” and exchange phone numbers.
Elect a group “rep”
Register your Group!
Your tutor will tell you how to register your group
1-6
July 2025
Seminar 1 Overview
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Chapter 1: Understanding AI
Defines AI as systems that interpret data, learn from it, and adapt flexibly to achieve goals
Distinguishes between Artificial Narrow Intelligence (ANI/weak AI) and Artificial General Intelligence (AGI/strong AI)
Traces AI development through alternating "summers" and "winters" from 1956 to present
Explains machine learning as pattern identification from data without explicit programming
Introduces deep learning with its layered neural network structure
Shows the hierarchical relationship: AI encompasses ML, which encompasses deep learning
Chapter 2: AI for Social Good
Defines social good as individual and community welfare across ecology, living conditions, and livelihood opportunities
Links to UN's 17 Sustainable Development Goals (SDGs)
Defines AI for social good as preventing/resolving problems affecting human life and natural world while avoiding new
harm
• Explains AI's empowerment through speed/efficiency and capabilities beyond human limitations
• Reviews research trends and case studies in AI for social good applications
• Outlines design considerations including stakeholder management and data/technology considerations
What is AI?
SU 1: Chapter 1
(Kaplan & Haenlein, 2019)
(Davenport & Ronanki, 2018)
(Kaplan & Haenlein, 2019)
(Kaplan, 2021)
Activity 1
So, where is the AI around us?
Experiential Examples demonstrated in class….
(Domingos, 2012)
(Brynjolfsson & McAfee, 2017)
(Higham & Higham, 2019)
(LeCun, Bengio & Hinton, 2015)
Activity 2
How is AI being used in Industry?
Select an industry such as Finance, Insurance, Education,
Manufacturing, Construction, Healthcare, Government, Telecoms, Real
Estate, Automotive, etc
Provide 2 examples of how AI is being applied in your chosen industry.
Social Good
SU 2: Chapter 2
Research into AI for Social Good
AI Application Areas
4-Step Framework to Apply AI
for Social Good!
Activity 3
Social Good in Singapore…
Select one of the 17 SDG goals.
Discuss the progress in Singapore. How is AI being applied?