1. 0AI-based Information Technology  Information Technology Based on AI ● What is Artificial Intelligence? ● Artificial Intelligence vs. Natural Intelligence ● Corporate Applications of Artificial Intelligence ● Concept and Applications of an Expert System ● Characteristics and Examples of an Expert System ● Structure of an Expert System ● Development of an Expert System ● Fuzzy Logic ● Neural Networks

2. 1AI-based Information Technology  What is Artificial Intelligence? ● Intelligence simulated after man’s intelligence by the use of a computer - Natural Intelligence vs. Artificial Intelligence ● A science that uses a computer technoloogy to mimic human’s logical behavior ● Rational/logical behavior: - e.g., evaluation, inferencing, judgment, problem-solving, etc.

3. 2AI-based Information Technology Knowledge Processing Data, Concepts, Judgments Knowledge Base (Data Base access possible) Symbol-oriented (doesn’t need algorithms) Solutions/decisions, explanations Input Built-in Base Processing Output Information Processing Data Data Base Numerically-oriented (uses algorithms) Numeric information/data  Knowledge Proc. vs. Information Proc.

4. 3AI-based Information Technology  Artificial Intelligence Vs. Natural Intelligence

5. 4AI-based Information Technology  Corporate Applications of AI ● Industrial Robots ● Natural Language Processing ● Expert Systems ● Visual Recognition ● Machine Learning - Fuzzy Logic - Neural Networks

6. 5AI-based Information Technology  What is an Expert System ● Definition: A computer program that represents in a computer knowledge related to a specific problem domain and uses it to solve problems like a human expert. ● Applied to diagnosis, prediction, design, interpretation, planning, etc. ● Can be helpful for experts as well as novices ● Key capabilities: - inferencing - drawing conclusions from the results of inferencing - providing explanations for inferencing ● Business applications: tax advising, personnel recruiting, investment, etc.

7. 6AI-based Information Technology  Categories of Expert Systems

8. 7AI-based Information Technology  ES(Expert System) Vs. DSS

9. 8AI-based Information Technology  Characteristics of Expert Systems ● Based on knowledge ● Uses qualitative, rather than quantitative, information ● Makes use of inferencing to draw conclusions ● Uses experts’ heuristics ● Provides explanations for reasoning ● Can function even when some data are missing ● Capable of handling uncertain situations ● Support for a narrow problem domain

10. 9AI-based Information Technology ● Credit Card Approval at American Express - The Authorizer’s Assistant - determines whether to approve purchases made with an American Express credit card while the customer is awaiting to make payment - The system handles the majority of credit card approval work, whereas the experts evaluate the remaining 5 % - The productivity of the approval experts has increased by 20%  Examples of ES Uses

11. 10AI-based Information Technology ● Ticket Auditing at Northwest Airlines - When Northwest Airlines acquired Republic Airlines, its volume of operations increased to 70,000 tickets per day, that had to be audited manually. - Auditing involved a very time-consuming task of checking fare information on a copy of each ticket - A ticket auditing expert system was developed in 1990 - The system now audits 100% of the tickets. The errors made by travel agencies have decreased significantly, and as much as 10 million dollars is saved each year as a result of using the system.  Examples of ES Uses - Cont’d

12. 11AI-based Information Technology ● Commercial Loan Analysis at a Bank - Developed by a bank that specializes in loans in excess of 30 million dollars (typically for construction projects) - Usually a 6-month study costing 1 quarter million dollars is required to determine the approvability of the loan - An expert system is developed to replace the costly study. - The system classifies a loan into three categories: Approve, Reject, Gray-area. - Loan officers should take care of only the Gray-area loans, thereby significantly reducing the loan evaluation costs.  Examples of ES Uses - Cont’d

13. 12AI-based Information Technology User Interface Blackboard (Workspace) Inference Engine Explanation Module Knowledge Base Problem-related facts (data) User Knowledge Engineer Knowledge Acquisition Modulle Consulting Environment (System Use) Development Environment (Knowledge Acquisition)  The Structure of an Expert System

14. 13AI-based Information Technology Project Initialization System Design Prototype Development Complete System Development Implementation/ Installation Maintenance Problem definition; Recognition of needs for a system Development methods/tools identified; system design A conceptual prototype constructed KB construction; testing User acceptance; installation; User training Operation; modifications; maintenance  Development of an Expert System

15. 14AI-based Information Technology  Methods for Developing Expert Systems ● Custom Development - Can create a system suited to the specific needs of an organization - Is time consuming and requires lots of resources ● Expert System Shell - Uses a shell to construct a system with more ease over a short time period - The emphasis is placed upon the transfer of acquired knowledge by the user to the system ● Off-the-shelf Package - Can simply purchase a ready-made package and use it with minor modification - Can cost less and avoid the complex development project

16. 15AI-based Information Technology  Exsys Professional: An ES Shell Illustration

17. 16AI-based Information Technology  Fuzzy Logic ● A technique that deals with uncertainties by simulating the process of human reasoning, allowing the computer to behave less precisely and logically than conventional computers do. ● e.g., tall, somewhat tall, really tall, very tall, etc. ● Sample fuzzy logic applications: - vacuum cleaners - air conditioners ● An example of a fuzzy logic rule: IF the temperature is very hot AND the water level is somewhat low THEN add cold water to the container.

18. 17AI-based Information Technology  Neural Networks ● A computer-based technology that is based on the research related to the human brain and neural system ● Can process large amounts of information concurrently ● Can use the learning function of the human brain to classify information, based on data of past experience ● Neural networks - A model created after the biological neural networks - The human brain is composed of hundreds of billions of neurons, which are interconnected with one another in a sophisticated manner. ● Primary advantages of the neural network technique: - Don’t have to rely on the predefined problem-solving knowledge, but seeks a solution based on a vast amount of data

19. 18AI-based Information Technology PE Output layer Hidden layer Input layer PE: Processing Element ( 처리요소 )  Components of a Neural Network