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CSc-180 (Gordon) Week 1A notes Key points: • Consciousness o A “very hard problem” that we mostly will ignore o See: “Chinese Room Experiment” by John Searle o See: “Partial Brain Thought Experiment” by Jacques Mallah o See: “Consciousness” by Susan Blackmore (book) • What is intelligence? • Elements of intelligence (partial list): o Imagination, new ideas o Reasoning / solving problems o Abiltity to learn o Ability to generalize o Human-like behavior (or animal-like) o Planning o Knowledge o Rational behavior (able to explain) • Definitions of “Artificial Intelligence” (from various textbooks): o Negnevitsky: “Ability to learn and understanc, to solve problems and make decisions.” o Kurzweil: “…machines that perform functions that require intelligence when performed by people.” o Coppin: “…systems that act in a way that to any observer would appear to be intelligent.” o Coppin: “…using methods based on the intelligent behavior of humans and other animals to solve problems” o Russell/Norvig: Systems that act like humans, OR Systems that think like humans, OR Systems that act rationally, OR Systems that think rationally • “Turing Test” o Human in one room, hooked to an “agent” in another room via computer chat session (keyboard) o Human tries to determine if “agent” is a human or a computer o Human is free to discuss anything, can ask challenging questions (human knows this is a “test”) o Passing presumably requires knowledge base, natural language processing, context understanding • “Eliza” o Computer program written in 1966 (Weizenbaum) o Trivial program (~200 lines of code), simply bounces back human input with minor modifications o Many people thought it was a human o Challenges significance of Turing Test • “Weak AI” vs “Strong AI” o “WEAK” – can machines ACT intelligently? (see Kurzweil, and Coppin #1 definitions) o “STRONG” – can machines really have an underlying understanding? (see Negnevitsky, Coppin #2) o Passing Turing Test might only require weak AI… we don’t know yet. o Open question – does AI require having lots of knowledge? Or is intelligence knowledge-independent? o “Strong” doesn’t mean “perform better”. Many of the best systems are “weak AI”. • Ethical Considerations: o People can lose their jobs to automation o Loss of accountability – what if an AI system makes a fatal mistake? What if the AI system can’t explain how it made its decision? Is the programmer liable? The agency that used the software? o Is it ethical to turn off a possibly-conscious system? o “Technical Singluarity” (proposed by Kurzweil) – when computers exceed us, and improve themselves