History of AI

1. CMSC 471 History of AI Chronology of AI, R&N Chapter 26 Adapted from slides by Tim Finin and Marie desJardins.

2. Today’s class • History of AI • Key people • Significant events • Future of AI • Where are we going • Philosophy of AI • Can we build intelligent machines? • If we do, how will we know they’re intelligent? • Should we build intelligent machines? • If we do, how should we treat them… • …and how will they treat us?

3. Key people (AI prehistory) • George Boole invented propositional logic (1847) • Karel Capek coined the term “robot” (1921) • Isaac Asimov wrote many sf books and essays (I, Robot (1950) introduced the Laws of Robotics – if you haven’t read it, you should!) • John von Neumann: minimax (1928), computer architecture (1945) • Alan Turing: universal machine (1937), Turing test (1950) • Norbert Wiener founded the field of cybernetics (1940s) • Marvin Minsky: neural nets (1951), AI founder, blocks world, Society of Mind • John McCarthy invented Lisp (1958) and coined the term AI (1957) • Allen Newell, Herbert Simon: GPS (1957), AI founders • Noam Chomsky: analytical approach to language (1950s)

4. Key people (early AI history) • Hubert and Stuart Dreyfus: anti-AI specialists • Ed Feigenbaum: DENDRAL (first expert system, 1960s) • Terry Winograd: SHRDLU (blocks world, 1960s) • Roger Schank: conceptual dependency graphs, scripts (1970s) • Shakey: mobile robot (SRI, 1969) • Doug Lenat: AM, EURISKO (math discovery, 1970s) • Ed Shortliffe, Bruce Buchanan: MYCIN (uncertainty factors, 1970s)

5. Key events: Genesis of AI • Turing test, proposed in 1950 and debated ever since • Neural networks, 1940s and 1950s, among the earliest theories of how we might reproduce intelligence • Logic Theorist and GPS, 1950s, early symbolic AI • Dartmouth University summer conference, 1956, established AI as a discipline • Early years: focus on search, learning, knowledge representation • Development of Lisp, late 1950s

6. Key events: Adolescence of AI • The movie 2001: A Space Odyssey (1968) brought AI to the public’s attention • Early expert systems: DENDRAL, Meta-DENDRAL, MYCIN • Arthur Samuels’s checkers player, Doug Lenat’s AM and EURISKO systems, and Werbos’s and Rumelhart’s backpropagation algorithm held out hope for the ability of AI systems to learn • Hype surrounding expert systems led to an inevitable decline in interest in the mid to late 1980s, when it was realized they couldn’t do everything • Hype surrounding neural networks in the late 1980s led to similar disappointment in the 1990s • Roger Schank’s conceptual dependency theory and Doug Lenat’s Cyc started to address problems of common-sense reasoning and representation • Hans Berliner’s heuristic search player defeated the world backgammon champion in 1979

7. Key events: AI adulthood (barely) • Many commercial expert systems introduced, especially in the 1970s and 1980s • Fuzzy logic and neural networks used in controllers, especially in Japan and Europe • Recent developments and areas of great interest include: • Bayesian reasoning and Bayes nets • Ontologies, knowledge reuse, and knowledge acquisition • Mixed-initiative systems that combine the best of human and computer reasoning • Multi-agent systems, Internet economies, intelligent agents • Autonomous systems for space exploration, search and rescue, hazardous environments

8. What do AI people do? • Subject headings from IJCAI-01 conference proceedings: • Knowledge Representation and Reasoning • Search, Satisfiability, and Constraint Satisfaction • Cognitive Modeling • Planning • Games • Diagnosis • Logic Programming and Theorem Proving • Uncertainty and Probabilistic Reasoning • Neural Networks and Genetic Algorithms • Machine Learning and Data Mining • Case-Based Reasoning • Multi-Agent Systems • Natural Language Processing and Information Retrieval • Robotics and Perception • Web Applications

9. Are we there yet? • Great strides have been made in knowledge representation and decision making • Many successful applications have been deployed to (help) solve specific problems • Key open areas remain: • Incorporating uncertain reasoning • Real-time deliberation and action • Perception (including language) and action (including speech) • Lifelong learning / knowledge acquisition • Common-sense knowledge • Methodologies for evaluating intelligent systems

10. Philosophy of AI Alan M. Turing, “Computing Machinery and Intelligence” John R. Searle, “Minds, Brains, and Programs”

11. Philosophical debates • What is AI, really? • What does an intelligent system look like? • Does an AI need—and can it have—emotions, consciousness, empathy, love? • Can we ever achieve AI, even in principle? • How will we know if we’ve done it? • If we can do it, should we?

12. Turing test • Basic test: • Interrogator in one room, human in another, system in a third • Interrogator asks questions; human and system answer • Interrogator tries to guess which is which • If the system wins, it’s passed the Turing Test • The system doesn’t have to tell the truth (obviously…)

13. Turing test objections • Objections are basically of two forms: • “No computer will ever be able to pass this test” • “Even if a computer passed this test, it wouldn’t be intelligent” • Chinese Room argument (Searle, 1980), responses, and counterresponses • Robot reply • Systems reply

14. “Machines can’t think” • Theological objections • “It’s simply not possible, that’s all” • Arguments from incompleteness theorems • But people aren’t complete, are they? • Machines can’t be conscious or feel emotions • Reductionism doesn’t really answer the question: why can’t machines be conscious or feel emotions?? • Machines don’t have Human Quality X • Machines just do what we tell them to do • Maybe people just do what their neurons tell them to do… • Machines are digital; people are analog

15. “The Turing test isn’t meaningful” • Maybe so, but… If we don’t use the Turing test, what measure should we use? • Very much an open question…

16. Ethical concerns: Robot behavior • How do we want our intelligent systems to behave? • How can we ensure they do so? • Asimov’s Three Laws of Robotics: • A robot may not injure a human being or, through inaction, allow a human being to come to harm. • A robot must obey orders given it by human beings except where such orders would conflict with the First Law. • A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

17. Ethical concerns: Human behavior • Is it morally justified to create intelligent systems with these constraints? • As a secondary question, would it be possible to do so? • Should intelligent systems have free will? Can we prevent them from having free will?? • Will intelligent systems have consciousness? (Strong AI) • If they do, will it drive them insane to be constrained by artificial ethics placed on them by humans? • If intelligent systems develop their own ethics and morality, will we like what they come up with?