TEST YOUR UNDERSTANDING
1.
If intelligence is the capacity to acquire and apply knowledge, what is knowledge?
Knowledge is one’s capacity to acquire and apply knowledge. Knowledge is familiarizing, understanding, or awareness acquired through experience. An intelligent person has the ability to think and reason.
2.
Briefly explain the key attributes of intelligent behavior.
The key attributes of intelligent behavior are: a.
Ability to understand and use language. Such language understanding is not so easy for the computer. Prior knowledge and common sense also enter the picture. b.
Memory or storing and retrieving relevant experience at will. How this is all done is unclear. c.
Learning is knowledge or skill acquired by instruction or study. We have yet to see some success in “machine learning.” People learn from experience—not computers
3.
Distinguish between: a.
fact and rule b.
knowledge and common sense c.
experience and heuristics d.
learning by example and learning by discovery a.
A fact is a statement that relates a certain element of truth about a subject matter or domain. A rule describes a sequence of relations relative to the domain or subject matter. b.
Knowledge is a person’s range of information, embracing a wider sphere than information. Knowledge includes common sense, perception, and experience.
Common sense is unreflective opinions of ordinary people. It comes to them naturally. Lack of it makes knowledge-based systems brittle. c.
Experience is closely related to knowledge. We use experience to change facts into knowledge, which separates novices from experts. Experience is the factor that changes unrelated facts into expert knowledge. Heuristics is a rule of thumb based on experience. So, heuristics takes experience as the bases for rules of thumb. d.
Learning by example incorporates specially constructed examples rather than a broad range of experience. Much classroom learning is learning by exception. In contrast, learning by discovery is an undirected approach where humans or machines explore a domain with no advance knowledge of what their object is. It is difficult to teach and will be years before we can benefit from this approach.

CHAPTER 2
UNDERSTANDING KNOWLEDGE
4.
Define episodic knowledge and semantic knowledge. Give an example of each.
Episodic knowledge is knowledge based on experiential information chunked as an entity and retrieved from long-term memory on recall. It is synonymous with deep knowledge.
For example, a professor with years of consulting experience tends to teach by scenarios or by examples. Such a person doesn’t have to think long about citing an episode to illustrate a point.
Semantic knowledge is highly organized, “chunked” knowledge that resides in the expert’s long-term memory and represents concepts, facts, and relationships among facts.
For example, a professor teaching networking would explain openly and clearly the network concepts, types of cables and their functions, how PCs are connected to a server, etc. These are all facts, relationships, and realities based on experience.
5.
Illustrate by example the possible relationship between (a) knowledge and information and (b) knowledge and data. a.
Knowledge is understanding of information based on its perceived importance or relevance to a problem domain. It is a person’s range of information. It includes perception, skills, training, common sense, and experience. It is the sum total of our perceptive processes that helps us draw meaningful conclusions. In contrast, information is an aggregation of data that makes decision making easier. It is reformatted or processed data. A step higher in abstraction than information is knowledge. b.
Compared to knowledge, data are unprocessed facts. However, the meaning one brings to the evaluation of data becomes information which, in turn, could add to one’s knowledge.
6.
Why is knowledge compiled? Discuss its relationship to long-range memory.
Knowledge is compiled in the expert’s long-range memory as chunks. Knowledge compilation, or chunking, enables experts to optimize their memory capacity and process information quickly. Chunking promotes expert performance. The more chunking a person does, the more efficient is his or her recall. So, as a person becomes an expert, more and more of the knowledge and experience is compressed in one’s long-range memory. It is tantamount to storing files on the hard disk when not in use.
7.
Review the types of knowledge discussed in the chapter. Use an illustration of your own to show how each type differs from the other types.
This question should encourage students to think creatively regarding the types of knowledge (shallow vs. deep, procedural vs. episodic, or explicit vs. tacit) and how they can be identified in everyday situations. They should be able to explain by experience or by example the contrasting types of knowledge. The author has learned from experience
2-2

CHAPTER 2
UNDERSTANDING KNOWLEDGE that knowing the type of knowledge being tapped can help prepare for knowledge capture sessions and identify the kinds of questions to ask the expert, session after session.
As a suggestion, this question might be a good one to promote class discussion. It is interesting how varied the students’ perception of what constitute shallow versus deep knowledge or explicit versus tacit. Knowing the lack of standardization or specificity, the discussion could conclude by wondering how “shallow” is shallow knowledge or how “deep” is deep knowledge. At what point would one consider a piece of information, compressed data versus preliminary knowledge?
8.
What is the difference between tacit and explicit knowledge? Give an example of each.
As defined in the chapter, explicit knowledge is what you see, read, or access— knowledge codified in documents, books, or other repositories. By contrast, tacit knowledge is knowledge used to create explicit knowledge; the mind-set of individuals that includes intuitions, values, and beliefs that stem from experience.
9.
If shallow knowledge is declarative knowledge, what is deep knowledge? Be as specific as you can.
Procedural and declarative knowledge are considered shallow knowledge. By contrast, semantic and episodic knowledge are viewed as deep knowledge. In some ways, what is shallow and what is deep is more a matter of degree than kind. There are situations where the type of knowledge is a borderline interpretation.
For example, a causal relationship between a loose battery cable and dim headlights is declarative or shallow knowledge. But since a car with a loose battery cable and dim headlights can conceivably start the car and in few miles the car goes dead, it takes an experienced mechanic to foresee the potential danger. Such experience would be based on semantic knowledge, which is less shallow, or deeper knowledge.
10.
Illustrate the difference between deductive and inductive reasoning. Under what conditions is one preferred over the other?
As defined in the chapter, deductive reasoning takes known principles (exact facts) and applies them to instances to infer an exact conclusion. For example, IF Fred is taller than
Nancy AND Nancy is taller than Sarah, THEN Fred is taller than Sarah. This type of reasoning is used in knowledge bases to capture this type of human expertise.
Inductive reasoning works the other way around. It is reasoning from a set of facts or individual cases to a general conclusion. For example, IF Henry is an avid fisherman, an avid hunter, and an avid mountain climber, THEN Henry likes outdoor sports. This type of reasoning is used in knowledge automation systems when experts cannot easily articulate their knowledge.
2-3

KNOWLEDGE EXERCISES
CHAPTER 2
UNDERSTANDING KNOWLEDGE
1.
People do not think in the same way as machines, because they are "biological.” Do you agree? Explain. a.
Humanlike behavior implies thinking. Since computers can only display such behavior, they are not thinking things. b.
Humans are alive and reason with reality. Computers have neither attribute; therefore, they cannot think as such. c.
Humans have consciousness. They look at options and are conscious of subtle constraints or the immediate environment before they choose to move one way or the other. Computers don’t have such freedom, because they are not conscious of the possibilities. Therefore, they don’t think. d.
Humans rely on commonsense knowledge or intuitively follow a path that leads to a solution or a decision. Computers do not have such intelligence. Therefore, they cannot think. For example:
A baseball player is ready to bat. As he waits, he looks at the pitcher’s face, reviews his peers at the bases, and the layout of the other players in the field. Something tells him that the pitcher is going to pitch a ball that will force him to walk. Or he senses that the next pitch will be for real; so, he’d better bat. This assessment is done in a matter of seconds. Computers are nowhere close to this level of intelligent decision making. Therefore, they cannot think.
You’re driving on a busy highway. There is a car in front of you traveling at the same speed. You look ahead and see a slow truck going up a hill. Something tells you that the car in front of you is going to pass the truck soon. You look at the icy conditions in the left lane and the last accident you had two weeks ago. Something tells you to pass after the front car does. Computers cannot be that intuitive.
Therefore, they cannot think.
You enroll in professor Jane Daleiden’s knowledge management course. You have already scanned the text the night before. You listen to her review of the syllabus and course requirements. She has a reputation for being a good teacher, but tough when it comes to the final grade. Something about the tone of her voice and the way she’s setting up the course tells you that you’d better enroll in a different elective.
Computers are not that intuitive. Therefore, they cannot think.
2.
What type of knowledge is used in each of these activities? a.
tying a shoelace b.
debugging a computer program c.
baking a pie d.
replacing a car’s flat tire e.
negotiating peace with a hostile country f.
driving in congested traffic
2-4

CHAPTER 2
UNDERSTANDING KNOWLEDGE
Explain each classification. a.
Typing a shoelace is automatic after a person performs the task a number of times. It is procedural knowledge, in that it involves an understanding of how to do a task or a procedure. It is essentially motor in nature. b.
Debugging a computer program is pretty much semantic knowledge, depending on the programming language and the level of complexity of the program. Generally, in programming, debugging knowledge is hierarchically organized knowledge of relationships among facts. It could also be episodic knowledge, in that looking at segments of the program, the programmer uses past experience with similar program segments to determine the likely solution to a bug or logical error. In this case, it is experiential information that is chunked by episodes. c.
Baking a pie is procedural knowledge, if all there is to do is to measure the ingredients, and follow a procedure based on a recipe. If a pie is devised from memory and is baked using past experience with similar pies and constraints such as thickness, ingredients (number, consistency, texture, etc.), and the size of the pie, then it is episodic knowledge. d.
Replacing a car’s flat tire is procedural knowledge. It is knowledge of how to do a task that is essentially motor in nature. The same knowledge is used over and over again. e.
Negotiating peace with a hostile country is definitely episodic knowledge.
Think of former Secretary of State Henry Kissinger’s experience and knowledge in his shuttle diplomacy to negotiate the end of war in Vietnam and peace in the Middle East between Israel and Egypt. f.
Driving in congested traffic is declarative, semantic, or episodic knowledge, depending on the years of experience of the driver. A young, inexperienced driver driving during the rush hour in a large city would probably stick to one lane and stay in it all the way home. It is safe and prudent. The knowledge used is declarative, in that it is easily verbalized and is the building block toward semantic knowledge, which uses experience to hierarchically organize knowledge of facts, procedures, and relationships among facts for improved efficiency of navigating through congested traffic in the future. In contrast, a seasoned driver maneuvers around automobiles across different lanes, sizing up the traffic, the car(s) ahead, and behaving accordingly. This is referred to as episodic knowledge.
3.
List five heuristics that you employ in everyday life. By what kind of learning have you arrived at these rules of thumb?
At the beginning of each class, the text's author asks a question based on a key aspect of the assignment. In few seconds, the response (or lack of it) tells whether the assignment should be explained in detail (lecture method), approached through the case method
(learning by example), or students questioned to generate further discussions. For example, if the answer shows clear understanding of the material and the second question elicits similar response, then I proceed to supplement the assignment with professional
2-5

CHAPTER 2
UNDERSTANDING KNOWLEDGE experience or outside material. Otherwise, I would cover the assignment in detail. This is learning from 44 years of teaching experience.
When I drive on Virginia highways, I always drive within five miles of the speed limit toward the top of a hill, because Virginia state police radar is invariably located just over the hill where they are not visible. We are not recommending that anyone violates the speed limit, but it becomes second nature to conform to standards in certain locations on the highway. This is based on learning by experience.
These are only examples. Students should be encouraged to cite and discuss the heuristics they present, determining to what extent they are heuristics, and how experience accumulates over time.
4.
Determine the type of reasoning in each of the following cases: a.
Liz did not deposit money in her checking account.
Liz is a customer of the bank.
Liz’s check bounced (insufficient funds).
Conclusion: Checks drawn against negative account balance will bounce. b.
Drivers who exceed the speed limit get speeding tickets.
Donna is a licensed driver.
Donna drove at 20 miles over the speed limit.
Conclusion: Donna will get a speeding ticket.
(What is wrong with this reasoning?) c.
A customer whose account balance drops below $100 during the month is subject to $5 charge.
Bob is a bank customer.
Bob has a checking account.
Bob’s checking account balance dropped to $98.
Conclusion: Bob’s account will be charged $5. a.
Inductive reasoning. It generates a general conclusion. b.
Deductive reasoning. It generates a specific conclusion. The results
(getting a speeding ticket) are not always guaranteed). c.
Deductive reasoning. It generates a specific conclusion.
2-6