1. INTELLIGENT SYSTEMS 3. M. Gams

2. Intelligent systems ENGINEERING, TECHNOLOGY ARTIFICIAL INTELLIGENCE IN. SOCIETY

3. Definition (scientific): Intelligent ststem is a system that learns during its existence. It senses its environment and learns, for each situation, which action permits it to reach its objectives. It continually acts, mentally and externally, and by acting reaches its objectives. To reach its objective it has to select its response. A simple way to select a response is to select one that was favorable in a similar previous situation. Engineering definition: more advanced than current ones.

4. Properties / Learning Learning Flexibility Adaptation Explanation Discovery (engineering – mouse?)

5. Intelligent systems Engineering, invisible intelligence Practical directions, real-life problems Verified AI methods: rule-based systems, trees, expert systems, fuzzy systems, neural networks, genetic algorithms, hybrid systems Intelligent systems often simulate human bureaucrats, expert systems simulate experts

6. Motivation People are expensive (to buy or maintain), computers cheap: computers work 24 hours a day, no vacations, network accessibility is worldwide, only 3% microprocessors in computers, an average car 16 microprocessors, exponential trend (faster, cheaper, more applications) Intelligent systems are more friendly, more flexible than classical systems (not truly intelligent, just a bit more than classical)

7. S. Goonatilake, P. Treleaven: I. S. for Finance and Business 20 years ago substantial increase in IS Killer applications - breakthrough Visa, 6 G trans. ann., 550G$, security; American Express, 15$ > 1.4$ typical: lots of data, new AI and HW cap. quality improvement, lower costs,

8. Killer application American Express, Visa Authorizer’s Assistant - an expert system before: simple rigid rules, majority left to human supervisors, many people with different performance Then new: an expert / intelligent system with many rules, copies expert supervisors, faster, cheaper, more equilibrated 15$ > 1.4$ per one transaction (Visa - an neural network – DM and ML prevail)

9. Benefits The key question – trust – can IS be trusted - obviously good enough (actually as good as average humans) Intelligent systems enabled organizational changes in terms of HW, SW and humans Work done better and faster, more profits, cheaper transactions Less employed, more work done by computers Problem - unemployment

10. Conclusion Intelligent systems apply AI methods and introduce intelligent services IS combine advantages of computer systems (cost, availability) with some human properties (simple engineering intelligence – learning, adapting, reasoning), and achieve better cost/benefit for several tasks Especially appropriate for mundane bureaucratic tasks in information society