Download 01A

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