1. Topics Lesson 10 AI (Artificial Intelligence) Expert Systems
Application of ES and AI

2. An Overview of Artificial Intelligence
The term “artificial intelligence” was coined in the nineteen fifties to describe computers with capabilities that duplicated or mimicked the functions of a human brain. At the time, some predicted that computers would be as smart as people within a matter of years. While developments in AI have not met these optimistic early expectations, they have been beneficial.
AI systems demonstrate characteristics of human intelligence, replicating human decision-making for certain problems. Since AI focuses on replicating intelligent human behavior, it helps to understand the nature of intelligence. Unfortunately, intelligence is not easily defined. The next 2 slides contain at least a partial description.

3. Artificial intelligence (AI)
Artificial intelligence is the study and creation of machines that exhibit humanlike qualities, including the ability to reason.
The Turing test is a test devised by Alan Turing to determine how well a computer emulates human intelligence.

4. The Nature of Intelligence
Learn from experience & apply the knowledge
Handle complex situations
Solve problems when important information is missing
Determine what is important
Humans naturally learn from experience – that is, by trial and error. And humans can apply what they learn to different contexts. Neither trait comes naturally to AI systems – they can only learn and apply what they’ve been programmed to learn – and the programming is difficult. Humans can learn in multiple areas and automatically apply what they learn.
Humans are often involved in complex situations. In business, executives face complicated legislation, rapidly changing markets and competition, and many more complexities, yet must make decisions, sometimes quickly, that affect their company’s future. People can make mistakes and learn from them. However, computers can handle only those complex situations that they’re programmed to handle.
Humans continually make decisions under uncertainty – that is, with partial or even inaccurate, information. AI systems can handle such situations in many contexts.
Everyday humans receive masses of incoming information. People can screen the information and discard irrelevant information – a skill built through experience. Computers are limited by their programming – and it’s not easy to program a computer to know what’s irrelevant.

5. The Nature of Intelligence
React quickly & correctly to new situations
Understand visual images
Process & manipulate symbols
Be creative & imaginative
Use heuristics
Humans experience “gut instincts” – like when you walk down a street and “know” you should leave or get hurt. Children know not to touch a flame. Computers have no gut feelings, and can only react quickly to specific stimuli for which they’re programmed.
Even state of the art computers have trouble interpreting visual images. When a person sees their reflection in the mirror, they know it’s a reflection and not a clone. When you see people, you look for many clues in dress, grooming, and behavior to determine their gender. Walking down a crowded street is natural even for children. But none of this is natural to computers. Research in the area of perceptive systems – that is, machines that can mimic human hearing, sight, or touch – has progressed and, as we’ll see later in the chapter, some systems have limited recognition ability.
Although computers excel at rapidly processing numbers, they’re not so good at processing visual information. Again, they’re limited by their programming.
Humans can think of new products and services and create novel objects. Although computers have been used to write poetry or draw, few can yet be considered truly creative.
Heuristics are rules of thumb developed through experience. People often use heuristics in decision-making. For instance, if you leave home for work after 7:30 AM, you may choose an alternate route, since experience has shown that by then there is often an accident backing up traffic on your normal route. Or you may ignore the weather forecast of precipitation if the chance is less than 70%, because based on your experience, it rarely rains or snows unless the chance is 70% or higher.

6. Technology to Support Knowledge Management (continued)
Table 11.1: Additional Knowledge Management Organizations and Resources
Principles of Information Systems, Eighth Edition

7. An Overview of Expert Systems
Expert systems contain the knowledge of an expert in a specific area and use that knowledge to replicate human problem solving in that area. Like human experts, expert systems draw inferences from the rules, facts, and relationships in their knowledge base and use heuristics to draw conclusions or make recommendations. Expert systems exist to diagnose problems, predict events, plan, and design new products and systems. For example, expert systems can be used by help desk personnel to troubleshoot problems end users have with software. Expert systems can be used to configure a complex computer system. Expert systems have been used in business to reduce costs, increase profitability, explore business options, and improve customer service.

8. The Difference Between Natural and Artificial Intelligence
Table 11.2: A Comparison of Natural and Artificial Intelligence
Principles of Information Systems, Eighth Edition

9. The Major Branches of Artificial Intelligence
Figure 11.5: A Conceptual Model of Artificial Intelligence
Principles of Information Systems, Eighth Edition

10. When to Use Expert Systems
Provide a high potential payoff or significantly reduce downside risk
Capture and preserve irreplaceable human expertise
Solve a problem that is not easily solved using traditional programming techniques
Develop a system more consistent than human experts
Principles of Information Systems, Eighth Edition

11. When to Use Expert Systems (continued)
Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health
Provide expertise that is expensive or rare
Develop a solution faster than human experts can
Provide expertise needed for training and development to share the wisdom and experience of human experts with many people
Principles of Information Systems, Eighth Edition

12. Components of Expert Systems
Figure 11.8: Components of an Expert System
Principles of Information Systems, Eighth Edition

13. Components of Expert Systems (continued)
Knowledge base
Stores all relevant information, data, rules, cases, and relationships used by expert system
Create a knowledge base by :
Assembling human experts
Using fuzzy logic
Using rules, such as IF-THEN statements
Using cases
Principles of Information Systems, Eighth Edition

14. Components of Expert Systems (continued)
Figure 11.9: The Relationships Among Data, Information, and Knowledge
Principles of Information Systems, Eighth Edition

15. Components of Expert Systems (continued)
Figure 11.10: Rules for a Credit Application
Principles of Information Systems, Eighth Edition

16. The Inference Engine Inference engine
Seeks information and relationships from knowledge base
Provides answers, predictions, and suggestions, like a human expert
Backward chaining: starts with conclusions and works backward to supporting facts
Forward chaining: starts with facts and works forward to conclusions
Principles of Information Systems, Eighth Edition

17. The Explanation Facility
Allows a user or decision maker to understand how the expert system arrived at certain conclusions or results
Example: a doctor can find out the logic or rationale of diagnosis made by a medical expert system
Principles of Information Systems, Eighth Edition

18. The Knowledge Acquisition Facility
Provides convenient and efficient means of capturing and storing all components of knowledge base
Acts as an interface between experts and knowledge base
Principles of Information Systems, Eighth Edition

19. The Knowledge Acquisition Facility (continued)
Figure 11.11: Knowledge Acquisition Facility
Principles of Information Systems, Eighth Edition

20. The User Interface
Specialized user interface software is employed for designing, creating, updating, and using expert systems
Main purpose of user interface: makes development and use of an expert system easier for users and decision makers
Principles of Information Systems, Eighth Edition

21. Expert Systems Development
Figure 11.12: Steps in the Expert System Development Process
Principles of Information Systems, Eighth Edition

22. Participants in Developing and Using Expert Systems
Domain expert: individual or group who has the expertise or knowledge one is trying to capture in the expert system
Knowledge engineer: individual who has training or experience in design, development, implementation, and maintenance of an expert system
Knowledge user: individual or group who uses and benefits from the expert system
Principles of Information Systems, Eighth Edition

23. Participants in Developing and Using Expert Systems (continued)
Figure 11.13: Participants in Expert Systems Development and Use
Principles of Information Systems, Eighth Edition

24. Expert Systems Development Tools and Techniques
Traditional programming languages
Special programming languages for AI applications
LISP, PROLOG
Expert system shells
Collections of software packages and tools used to design, develop, implement, and maintain expert systems
Principles of Information Systems, Eighth Edition

25. Expert Systems Development Tools and Techniques (continued)
Figure 11.14: Expert Systems Development
Principles of Information Systems, Eighth Edition

26. Applications of Expert Systems and Artificial Intelligence
Credit granting and loan analysis
Stock picking
Catching cheats and terrorists
Budgeting
Games
Principles of Information Systems, Eighth Edition

27. Applications of Expert System and Artificial Intelligence (continued)
Information management and retrieval
AI and expert systems embedded in products
Plant layout and manufacturing
Hospitals and medical facilities
Principles of Information Systems, Eighth Edition

28. Applications of Expert System and Artificial Intelligence (continued)
Help desks and assistance
Employee performance evaluation
Virus detection
Repair and maintenance
Principles of Information Systems, Eighth Edition

29. Applications of Expert System and Artificial Intelligence (continued)
Shipping
Marketing
Warehouse optimization
Principles of Information Systems, Eighth Edition

30. Robotics Mechanical or computer devices that perform tasks:
Requiring a high degree of precision, or
Tedious or hazardous for humans
Robots are essential components of today’s automated manufacturing and military systems
Future robots will find wider applications in banks, restaurants, homes, doctor offices, and hazardous working environments
Principles of Information Systems, Eighth Edition

31. Virtual Reality
A virtual reality system allows one or more users to interact with the system in a computer-simulated environment.

32. Forms of Virtual Reality
Immersive virtual reality
Mouse-controlled navigation through a three-dimensional environment on a graphics monitor
Stereo projection systems
Stereo viewing from the monitor via stereo glasses
Telepresence systems
Principles of Information Systems, Eighth Edition

33. Virtual Reality Applications
Medicine
Pain and anxiety; examinations and diagnoses; physical therapy
Education and training
Virtual school trips, military training
Real estate marketing and tourism
Virtual tours
Entertainment
CGI; virtual reality games
Principles of Information Systems, Eighth Edition

34. Other Specialized Systems
Segway
Tracking devices for crime fighting
Radio-frequency identification (RFID) tags
3-D holograms used by military
“Smart containers” for ships, railroads, and trucks
Principles of Information Systems, Eighth Edition

35. Other Specialized Systems (continued)
Game theory
Informatics
Small radio transceivers placed in products, such as cell phones
Microsoft’s Smart Personal Objects Technology (SPOT)
Principles of Information Systems, Eighth Edition

36. Vision Systems
Hardware and software that permit computers to capture, store, and manipulate visual images and pictures
Fingerprint analysis
Identifying people based on facial features
Used in conjunction with robots to give these machines “sight”
Principles of Information Systems, Eighth Edition

37. Natural Language Processing and Voice Recognition
Processing that allows the computer to understand and react to statements and commands made in a “natural” language, such as English
Voice recognition: converting sound waves into words
Principles of Information Systems, Eighth Edition

38. Other AI Applications Search Engines
Intelligent database search machines can direct a search of a very large database by giving the target pattern to many machines that search simultaneously.
Any machine that finds a possible match sends the match to the controller machine to make the final assessment.

39. Fuzzy Logic
Fuzzy logic is a rule-based development in AI to infer knowledge that is imprecise, uncertain, or unreliable.
It can express logic with carefully defined imprecision to solve problems that cannot be handled with restrictive IF-THEN rules.

40. Fuzzy Logic
A variety of concepts and techniques in AI for using rules to represent knowledge that is imprecise, uncertain, or unreliable
use in products such as autofocus cameras, cruise missiles, trains & automobiles
analog based systems

41. Questions (?)