1. Introduction to AI & AI Principles (Semester 1) WEEK 2 – Tuesday part A Introduction to AI & AI Principles (Semester 1) WEEK 2 – Tuesday part A (2008/09) John Barnden Professor of Artificial Intelligence School of Computer Science University of Birmingham, UK

2. Stupidity and Intelligence uSo, we’re not intelligent creatures? /// uCould an ant/rat/dog/monkey be stupid in those ways? uDid those mistakes arise out of good reasons, actually? uThe necessity of stupidity. Stupidity in the context of intelligence. uEmotion and thought. (Huge but hot topic.) uWe can intelligently reflect on our stupidity! uAs well as being stupid about our intelligence!!

3. INTRODUCTION to AI, at last!

4. What is the Field of “Artificial Intelligence” ???? uNot an easy question, for many reasons, incl.: l What is “intelligence”???? [often asked] l What does “artificial” mean? [not so often asked, but implicit in discussions of whether AI can merely simulate intelligence or can achieve it]

5. What is “AI” ???? contd uBasically, AI (the field) is the study of how to create artificial entities that have features that we associate with intelligence, and cognition more generally, in humans and other living things, such as reasoning, planning, communicating in language, solving problems, seeing what’s around, moving around in the world, creating artworks, playing games, learning, emoting, being conscious, having society, etc.

6. Cautions 1 … uThe “artificial objects” are currently computers, robots, computer programs, etc., as we know them today, but could include radically different types of artefact in future … … uAnd given the possibility of synthetic biology, we might eventually grow our artefacts … and how different would that be from a woman just giving birth?

7. Cautions 2 uAnd who is it that “associates” those features with intelligence? … In fact AI covers a lot of things most people would not have thought of as “intelligent” – e.g. seeing that there’s a pencil on a desk. (Hence my inclusion of “cognition in general”.)

8. Cautions 3 uMany AI researchers don’t themselves produce or directly study programs, computers, robots, etc., but instead create: underlying computational principles or frameworks, mathematical theory, etc.

9. Why Do We Do AI? uAn “Engineering” Aim uA “Psychological” Aim uA “General/Philosophical” Aim

10. “Engineering” Aim uTo engineer, or provide computational principles and methods for engineering, / useful artefacts that are arguably intelligent (in the broad sense above), without necessarily having any mechanistic similarity to human or animal minds/brains. uThe usefulness may be in an industrial domain or an everyday, practical domain, but may also be in other domains such as art or mathematical theorem proving.

11. “Psychological” Aim uTo devise computational principles, computationally- detailed theories, or running computational systems that provide a basis for possible testable accounts of cognition in human or animal minds/brains. In short, contributing computationally to questions such as, how does the human mind work? uBut why not leave that to Psychologists? Answer: they don’t know as much about computation. Also, thinking “outside the biological box” is liberating.

12. “General/Philosophical” Aim uTo devise computational principles, computationally- detailed theories, or running computational systems that serve as, or suggest, possible accounts of cognition in general, whether it be in human-made artefacts, in naturally-occurring organisms, or in beings yet to be discovered, or that illuminate philosophical issues such as the nature of mind, thought, intelligence, consciousness, perception, language, representation, learning, creativity, rationality, society, etc.

13. Mixing of Aims u The three aims are often inextricably combined in a given piece of AI work. l An individual researcher may subscribe to more than one of the aims. l Developments in pursuit of any one of the aims could happen to inspire advances towards one of the others. l Endeavours that have any one of the aims can deliberately look for inspiration from research that has one of the other aims.

14. Why Am I (Puzzled Student) Doing AI?? i.e., “Eh? I?” uIt is a particularly fascinating, fun, liberating, inspiring, challenging, breathtaking, … in short, sexy aspect of CS. uAI technology (software, hardware) is creeping more and more into practical applications. / uIt’s a relatively people-orientated side of CS, and interacts/overlaps with many other disciplines such as Psychology. uIt’s a good basis for interesting undergrad/master’s/doctoral projects. uIt involves many general CS issues, and there are no clear boundaries anyway.

15. Some Actual or Emerging Applications uLearning, planning & communication in computer games. uDiagnosis, in many areas including medical. uIntelligent conversational agents (incl. chatbots, helpful avatars on company sites, ICAs fronting travel services). uEmotive ICAs. uMilitary apps, incl. battle planning, target identification. uAircraft/spacecraft/planetcraft control & action planning. [See Callan book] uSatnavs.

16. Some Example Applications, contd. 1 uStock market prediction. uFraud-detection: credit cards, phone usage. uData mining for marketing purposes. uText summarization and information-extraction. uArtistic creativity (music, paintings, …). uBuilding design. uIntelligent transport systems, utility networks, etc.

17. Some Example Applications, contd. 2 uIntelligent personalized web-search agents. uPolicing and national security. uMachine translation (of language). uSemantic web.

18. “Digital Economy” uMajor new national research-funding priority, led by the EPSRC (Engineering and Physical Sciences Research Council). uIncludes concern for issues like how large computer- based systems can interact with people in a good way, avoid social exclusion, etc. uNaturally brings in many AI and other CS concerns. uTo be led by the needs of industry, community, society.