Summary: Mindware An Introduction To The Philosophy Of Cognitive Science | 9780199828159 | Andy Clark

Read the summary and the most important questions on Mindware An Introduction to the Philosophy of Cognitive Science | 9780199828159 | Andy Clark

• 1 Meat Machines: Mind as Software

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• Syntax, semantics & token

  • Syntax = rules and structure for manipulating symbols.
  • Semantics = what those symbols mean in the real world.
  • Tokens = the physical instances of symbols (e.g., printed word, memory pattern).
  • Clark: systems can process tokens syntactically without grasping their semantics.

  
  
  he big question in philosophy of mind (and AI) is: If a system only ever manipulates syntax, can it ever truly have semantics? (Cue Searle’s Chinese Room later in the chapter.)

• Brain as a natural computer

  Incorporating inner states that represent external events and exploiting stat transition routines that make sensible use of the information thus encoded

• Comments on early Chatsbots & LLM's

  • PARRY, Deep Blue, Watson -> brute force vs pattern recognition = top-level mimicking: unfit as a substrate for real intelligence 
  • "Does a submarine swim?" 
  • No faithful psychological model of the inner states that underlie human performance

• What is the role of all the hormones, chemicals and organic matter that build the brain?

  Two different possibilities, no one knows which one is correct;
  1. They affect our conscious experiences only by affecting the way information flows and is processed in the brain
  2. The experienced nature of our mental life is not (or is just not) a function of the flow of information.

• 3 crucial developments in the history of AI:

  1. Appreciation of the power and scope of formal logic – Realizing that logical systems can capture and manipulate truths mechanically.
  2. Turing’s demonstration that machines could implement these formal systems – The Turing machine as a proof-of-concept for mechanical computation.
     
  3. The rise of the digital computer – Providing the physical hardware to run such formal procedures at scale.
     

• Syntactic engines (Dennett)

  Quasi-autonomous systems whose sheer physical makeup ensured (under interpretation) some kind of ongoing reason-respecting behavior.

• What is the dual profile?

  Physical substance and reason-respecting behavior

• Why treat thought as a computation?

  Thinkers are physical devices whose behavior patterns are reason-respecting

• Pylyshyn (1986) the brain is a computer

  • Pylyshyn: cognitive capacities come from symbolic representations and rule-governed processes operating over them.
  • Example: see a car crash → representation “There’s an accident” → rule “If accident, call 911” → action: call 911.
  • Mind’s architecture is like a computer’s, manipulating symbols via formal rules to produce intelligent behavior.

• Fodor (1987) the brain is a computer

  • Fodor’s view: the brain is a computer — it manipulates symbolic representations via formal rules (syntax) to produce thought and behavior. (neural symbols)
  • Example: input “It is raining” → rule “If raining, then go indoors” → output “Let’s go indoors.”
  • Supports the representational theory of mind and classical cognitive science.