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CHAPTER 9
THE USE OF ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMITE PROFESSIONAL ETHICS AND VALUESBY: GROUP 1 FIRST FIVE
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What is Artificial Intelligence (AI)?
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There are many definitions of AI. The basic objective of AI is to represent humans' thought processes in computers.Practical mechanisms that enables computers to stimulate the human reasoning process.
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Make machines smarter.(primary goal)Understand what intelligence is. (Nobel Laureate purpose)Make machines more useful. (entrepreneurial purpose)
AI Objectives
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A computer can be considered to be smart only when a human interviewer, conversing with both an unseen human being and an unseen computer, can not determine which is which.Turing Test for Intelligence
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The inability to distinguish computer responses from human responses. Turing Test for Intelligence
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A symbol is a string of characters that stands for some real-world concept.AI Represents Knowledge as Sets of Symbols
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ExamplesProductDefendant0.8 ChocolateAI Represents Knowledge as Sets of Symbols
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(DEFECTIVE product)
(LEASED {LIABILITY defendant} 0.8) Tastes good (chocolate).Symbol Structures (Relationships)
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Search Inferencing
Heuristic Methods for Processing Information
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Reasoning - Inferencing from facts and rules using heuristics or other search approaches.
Pattern Matching - Attempt to describe objects, events, or processes in terms of their qualitative features and logical and computational relationships.
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Knowledge Processing - Given facts or other representations.
Knowledge Bases - Where knowledge is stored.
Using the Knowledge Base in AI Programs Inferencing.
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Using the Knowledge BaseInputsComputerOutputs
KnowledgeBase
InferencingCapability
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Artificial Intelligence versus Natural Intelligence
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More permanent Ease of duplication and dissemination Less expensiveAI Advantages Over Natural Intelligence
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Consistent and thorough Can be documented Can execute certain tasks much faster than a human AI Advantages Over Natural Intelligence
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Natural intelligence is creative
Can use a wide context of experience in different situations
AI Advantages Over Natural Intelligence
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Can perform certain tasks better than many or even most people.
People use sensory experience directly
AI Advantages Over Natural Intelligence
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Based on symbolic representation and manipulation.
Objects can be people, things, ideas, concepts, events, or statements of fact.AI Computing
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Creates a symbolic knowledge base.
A symbol is a letter, word, or number representing objects, processes, and their relationships.AI Computing
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Manipulates symbols to generate advice.
AI reasons or infers with the knowledge base by search and pattern matching.
AI Computing
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Hunts for answers (via algorithms). Caution: AI is NOT magic. AI is a unique approach to programming computers.
AI Computing
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AI TreeFruits: ApplicationsBranches: Expert Systems, Natural Language processing, Speech Understanding, Robotics and Sensory Systems, Computer Vision, Neural Computing, Fuzzy Logic, GA
AI TreeRoots: Psychology, Philosophy, Electrical Eng., Management Science, Computer science, Linguistics
Anti-lock Braking Systems Video CamcordersData Mining Software Help Desk Software
AI Transparent in Commercial Products
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SUBWAY Control AppliancesWashersToastersStoves
AI Transparent in Commercial Products
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A computer application that employs a set o rules based on human knowledge to solve problems that require human expertise.
Expert Systems
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Most Popular Applied AI TechnologyEnhance ProductivityAugment Work Forces
Expert Systems
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Knowledge Base Inference Engine User Interface
Three Major ES Components
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Three Major ES ComponentsUser Interface
Knowledge BaseInference Engine
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Knowledge Base Inference Engine User InterfaceAll ES Components
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Blackboard (Workplace) Explanation Subsystem (Justifier) Knowledge Refining System UserAll ES Components
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The knowledge base contains the knowledge necessary for understanding, formulating, and solving problems.
Knowledge is the primary raw material of ESIncorporated knowledge representationKnowledge Base
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Two Basic Knowledge Base Elements
FactsSpecial heuristics, or rules that direct the use of knowledge.
Knowledge Base
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Inferencing is the reasoning process of AI. It takes place in the brain of an AI process.The brain of the ES The control structure (rule interpreter)Provides methodology for reasoningINFERENCE ENGINE
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Language processor for friendly, problem-oriented communication
NLP, or menus and graphics User Interface
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Knowledge acquisition is the accumulation, transfer and transformation of problem-solving expertise from experts Knowledge Acquisition Subsystem
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and/or documented knowledge sources to a computer program for constructing or expanding the knowledge base.
Knowledge Acquisition Subsystem
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Area of working memory toDescribe the current problemRecord Intermediate resultsBlackboard (Workplace)
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Records Intermediate Hypotheses and Decisions1. Plan2. Agenda3. SolutionBlackboard (Workplace)
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Traces responsibility and explains the ES behavior by interactively answering questions - Why? How?What?-Where? When? Who?Explanation Subsystem (Justifier)
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Knowledge Refining System Learning for improving performance
Explanation Subsystem (Justifier)
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Expert Knowledge Engineer User OthersTHE HUMAN ELEMENT IN EXPERT SYSTEMS
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Has the special knowledge, judgment, experience and methods to give advice and solve problems.
Provides knowledge about task performance.The Expert
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Helps the expert(s) structure the problem area by interpreting and integrating human answers to questions, drawing analogies, The Knowledge Engineer
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posing counterexamples, and bringing to light conceptual difficulties.
Usually also the System Builder
The Knowledge Engineer
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Possible Classes of Users A non-expert client seeking direct advice (ES acts as a Consultant or Advisor) A student who wants to learn (Instructor)
THE USER
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An ES builder improving or increasing the knowledge base (Partner) An expert (Colleague or Assistant)The Expert and the Knowledge Engineer should Anticipate Users' Needs and Limitations When Designing ES.
Permanence- Expert systems do not forget, but human experts may.Advantages of Expert Systems
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Reproducibility
- Many copies of an expert system can be made, but training new human experts is time-consuming and expensive.
Advantages of Expert Systems
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- If there is a maze of rules (e.g. tax and auditing), then the expert system can "unravel" the maze.
Advantages of Expert Systems
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Efficiency- can increase throughput and decrease personnel costsDevelopment and maintenance costs can be spread over many users.
Advantages of Expert Systems
The overall cost can be quite reasonable when compared to expensive and scarce human experts.Cost savings.Wages - (elimination of a room full of clerks)
Humans are influenced by: recency effects (most recent information having a disproportionate impact on judgment)primacy effects (early information dominates the judgment).
DOCUMENTATION- An expert system can provide permanent documentation of the decision process.
COMPLETENESS- An expert system can review all the transactions, a human expert can only review a sample.
TIMELINESS- Fraud and/or errors can be prevented. Information is available sooner for decision making.
BREADTH- The knowledge of multiple human experts can be combined to give a system more breadth that a single person is likely to achieve.
Reduce risk of doing business.
Consistency of decision making.
Documentation.
Achieve Expertise.
ENTRY BARRIERS- Expert systems can help a firm create entry barriers for potential competitors.
DIFFERENTIATION- In some cases, an expert system can differentiate a product or can be related to the focus of the firm (XCON).
Computer programs are best in those situations where there is a structure that is noted as previously existing or can be elicited.
Knowledge is not always readily available.Expertise can be hard to extract from humans.PROBLEMS AND LIMITATIONS OF EXPERT SYSTEMS
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Each experts approach may be different, yet correct.PROBLEMS AND LIMITATIONS OF EXPERT SYSTEMS
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Hard, even for a highly skilled expert, to work under time pressure.
Expert system users have natural cognitive limits.
Most experts have no independent means to validate their conclusions
Experts vocabulary often limited and highly technical
Lack of trust by end-users
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Knowledge transfer subject to a host of perceptual and judgmental biases
ES may not be able to arrive at valid conclusions
ES sometimes produce incorrect recommendations
Expert Systems Versus Knowledge-based SystemsRule-based Expert SystemsFrame-based SystemsEXPERT SYSTEMS TYPES
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Hybrid SystemsModel-based SystemsReady-made (Off-the-Shelf) SystemsReal-time Expert Systems
EXPERT SYSTEMS TYPES
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Provide knowledge and adviceHelp desksSpread of multimedia-based expert systems (Intel media systems)USING ES ON THE WEB
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Support ES and other AI technologies provided to the Internet/IntranetUSING ES ON THE WEB
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The end
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson 6th ed, Copyright 2001, Prentice Hall, Upper Saddle River, NJ
Accounting Expert Systems Applicationscompiled by Carol E. Brown
REFERENCES
Artificial Intelligence in Businessby Daniel E. O'Leary
Artificial Intelligence / Expert Systems Section of the American Accounting Association
International Journal of Intelligent Systems in Accounting, Finance and Management
What is Artificial Intelligence?Enumerate & explain the 3 objectives of Artificial Intelligence.Discuss fully the Turing test.What does AI represent?What is a symbol & give examples?Give at least 3 symbol structures and explain each.Name the 2 heuristic methods for processing information & explain each.Explain: Reasoning; pattern matching; knowledge processing and knowledge bases.Draw the diagram of a computer using the knowledge baseEnumerate & discuss the advantage of AI over Natural Intelligence.
QUESTIONS
11. Discuss fully: AI computing.12. Illustrate Artificial Intelligence like a tree.13. Enumerate the possible presence of AI in commercial products.14. Discuss fully: The expert system.15. Enumerate and explain the 3 major expert system components.16. Enumerate & explain the 2 most popular technology application of expert system.17. Make a diagram showing the 3 major ES components.18. Enumerate at least 7 components of expert system & explain each.19. What are the 2 basic knowledge base elements & explain each.20. Give at least 2 functions of the area of the working memory.21. Name the 3 important things in the blackboard or workplace where intermediate hypothesis & decisions are recorded. QUESTIONS
Questions22. What questions where the justifier or the explanation subsystem traces responsibility and explains behavior interactively?23. Enumerate and explain the human elements in expert system.24. What is inference engine?
Practical mechanisms that enables computers to stimulate the human reasoning process.
The inability to distinguish computer responses from human responses
-Make machines smarter -Understand what intelligence is -Make machines more useful
ANSWER
Inferencing is the reasoning process of AI. It takes place in the brain of an AI process.AI is permanent, can be easily duplicated, can be less expensive, and can be documented.Artificial intelligence is not creative , it is limited in the use of sensory devices, it cannot make use of a very wide context of experiences, and it does not use common sense
ANSWER
7. A computer application that employs a set o rules based on human knowledge to solve problems that require human expertise.
8. -Knowledge Based -Inference Engine -User Interface
ANSWER
9. -Knowledge is not always readily available -Expertise can be hard to extract from humans -Each experts approach may be different, yet correct
10.- Rule-based Expert Systems -Frame-based Systems -Hybrid Systems