computational theory of mind
In plain wordsThe idea that thinking is a kind of computation: the mind processes information by following rules, much as a computer runs a program, and the brain is the machine doing it.
The thesis that cognition is computation: mental processes are operations on internal representations, carried out by rules sensitive to the representations' structure, and the brain is a computing system. In its classical version, associated with Jerry Fodor and Zenon Pylyshyn, the representations are symbol structures in a language of thoughtlanguage of thought hypothesis, n.: The theory that we think in an inner, wordless mental language with its own symbols and grammar, which the brain manipulates when we reason, much as a computer manipulates code. manipulated as in a digital computer; connectionist versions treat cognition as computation over distributed numerical representations in neural networksneural network, n.: A kind of computer program that learns a task from examples by tuning thousands to billions of connections between simple number-crunching units, an arrangement loosely inspired by nerve cells in the brain.. The thesis was a founding assumption of cognitive sciencecognitive science, n.: The scientific study of how minds work — how we reason, use language, remember and see — combining psychology, neuroscience, linguistics, philosophy, anthropology and artificial intelligence. and of AI's ambition to model minds. Critics argue that computation is observer-relative (John Searle), that meaning cannot be captured by formal operations (the Chinese roomChinese room, n.: A thought experiment: a person who knows no Chinese follows a rulebook to answer Chinese messages so well that outsiders think they understand. If the person doesn't understand, does a computer running a program? and symbol grounding problemsymbol grounding problem, n.: The puzzle of how words or symbols inside a machine can mean anything by themselves, rather than only pointing to more symbols — like a dictionary that defines every word using other words.), or that cognition is embodied and dynamical rather than computational (embodied cognitionembodied cognition, n.: The idea that thinking is not something the brain does on its own: the body, its senses and movements, and its surroundings play a real part in how we think and understand.).
Origin
Anticipated by Thomas Hobbes's claim that reasoning is reckoning (Leviathan, 1651) and by Warren McCulloch and Walter Pitts's network of logical neurons (1943). Hilary Putnam formulated it in papers of the 1960s, notably 1967, and Jerry Fodor systematized it in The Language of Thought (1975).
Usage note
Computationalism about cognition (thinking, perceiving, deciding) is far more widely accepted than computationalism about consciousness, which is the stronger claim at issue in debates over machine consciousnessmachine consciousness, n.: Whether a machine such as an AI system could have genuine experiences of its own — and the research field that tries to find out, or to build such a machine..
Related
- functionalismfunctionalism, n.: The view that minds are defined by how they work, not what they are made of: pain, for example, is whatever inner state plays pain's part, linking injury, other thoughts and behavior.
- language of thought hypothesislanguage of thought hypothesis, n.: The theory that we think in an inner, wordless mental language with its own symbols and grammar, which the brain manipulates when we reason, much as a computer manipulates code.
- physical symbol system hypothesisphysical symbol system hypothesis, n.: The 1976 claim by two AI pioneers that a machine which stores and rearranges symbols according to rules has everything needed for general intelligence, and that anything generally intelligent must be such a machine.
- connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.
- cognitive sciencecognitive science, n.: The scientific study of how minds work — how we reason, use language, remember and see — combining psychology, neuroscience, linguistics, philosophy, anthropology and artificial intelligence.
- Marr's levels of analysisMarr's levels of analysis, n.: A way of explaining any information-processing system on three levels: what problem it solves and why, what step-by-step method it uses, and how that method is physically built.
- Chinese roomChinese room, n.: A thought experiment: a person who knows no Chinese follows a rulebook to answer Chinese messages so well that outsiders think they understand. If the person doesn't understand, does a computer running a program?
- embodied cognitionembodied cognition, n.: The idea that thinking is not something the brain does on its own: the body, its senses and movements, and its surroundings play a real part in how we think and understand.
Sources
- Fodor, J. A. (1975). The Language of Thought. Thomas Y. Crowell.
- Putnam, H. (1967). Psychological Predicates. In W. H. Capitan & D. D. Merrill (eds.), Art, Mind, and Religion. University of Pittsburgh Press.
Mentioned in
cognitive sciencecognitive science, n.: The scientific study of how minds work — how we reason, use language, remember and see — combining psychology, neuroscience, linguistics, philosophy, anthropology and artificial intelligence., embodied cognitionembodied cognition, n.: The idea that thinking is not something the brain does on its own: the body, its senses and movements, and its surroundings play a real part in how we think and understand., functionalismfunctionalism, n.: The view that minds are defined by how they work, not what they are made of: pain, for example, is whatever inner state plays pain's part, linking injury, other thoughts and behavior., mind–body problemmind–body problem, n.: The age-old question of how the mind — thoughts, feelings, experiences — relates to the physical body and brain. Is the mind simply what the brain does, or something more?, philosophy of artificial intelligencephilosophy of artificial intelligence, n.: The branch of philosophy that asks what AI is and could be: whether machines can think, understand or be conscious, what intelligence is, and what we owe to and should expect from intelligent machines., strong AIstrong AI, n.: Originally, the claim that a computer running the right program would literally have a mind and understand, not just imitate understanding. Today it often simply means AI as capable as humans across the board., Turing machineTuring machine, n.: An imaginary, extremely simple computer — a read-write head moving along an endless tape — that Alan Turing used in 1936 to define exactly what can be computed at all., behaviorismbehaviorism, n.: The view that the mind should be studied, or even defined, only through observable behavior rather than inner thoughts or feelings. It shapes debates about whether AI that acts intelligently really is intelligent., Jerry FodorJerry Fodor, prop. n.: An American philosopher who argued that thinking is computation in an inner 'language of thought', and that neural networks cannot explain the structured nature of thought., language of thought hypothesislanguage of thought hypothesis, n.: The theory that we think in an inner, wordless mental language with its own symbols and grammar, which the brain manipulates when we reason, much as a computer manipulates code., Lucas–Penrose argumentLucas–Penrose argument, n.: An argument that human minds cannot be computers because, using a famous result in logic, people can see that certain statements are true that no fixed computer program could prove., Marr's levels of analysisMarr's levels of analysis, n.: A way of explaining any information-processing system on three levels: what problem it solves and why, what step-by-step method it uses, and how that method is physically built., multiple realizabilitymultiple realizability, n.: The idea that the same mental state, such as pain, could be produced by very different physical systems — human brains, octopus brains or perhaps computers — just as one program can run on different machines., Roger PenroseRoger Penrose, prop. n.: A British mathematical physicist and Nobel laureate who argues that human understanding is not computational, so that no computer, however powerful, could truly think like a mathematician.