John McCarthyJohn McCarthy was a computer scientist who pioneered artificial intelligence (he named the field) and was thus also a cognitive scientist who thought that the brain could be reduced to, or at least modeled by, a computer. The brain clearly does something like computation and it contains something like algorithms as argued by McCarthy's colleagues Allen Newell and Herbert Simon, with their idea of a two-stage "General Problem Solver," which was partial inspiration for Daniel Dennett's "Valerian Model" in 1978. In 1955, a summer study project at Dartmouth College was proposed by McCarthy (with Marvin Minsky and Claude Shannon). The proposal is credited with introducing the term 'artificial intelligence'.
“We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer. ” The proposal goes on to discuss computers, natural language processing, neural networks, theory of computation, abstraction and creativity (these areas within the field of artificial intelligence are considered still relevant to the work of the field)"The attendees included: Marvin Minsky, Julian Bigelow, Donald Mackay, Ray Solomonoff,. John Holland, John McCarthy, Claude Shannon, Nathanial Rochester, Oliver Selfridge, W. Ross Ashby, W.S. McCulloch, Abraham Robinson, Tom Etter, John Nash, David Sayre, Arthur Samuel, Kenneth R. Shoulders, Alex Bernstein, Allen Newell, and Herbert Simon. The absence of the pioneer of cybernetics, MIT's Norbert Wiener, was most conspicuous. The conference proposal deliberately did not mention cybernetics. That was the basis of the famous Macy Conferences, which ran from the late 1940's to around 1960, and included several of the AI pioneers mentioned above. McCarthy wanted to avoid discussions of simple automata theory. By avoiding cybernetics, which focused on analog feedback, it meant he also avoided debates with the powerful Wiener. McCarthy thought mathematical logic should be the basis for the new field. His slogan was "He who refuses to do arithmetic is doomed to talk nonsense."
Simple Deterministic Free WillIn the mid 2000's, McCarthy invented a model for free will to be used in artificially intelligent machines. He discussed it with Dennett, whose defining of free will as moral responsibility allowed free will to be "compatible" with determinism.
A common feature of free will is that a person has choices among alternative actions and chooses the action with the apparently most preferred consequences. In a determinist theory, the mechanism that makes the choice among the alternatives is determinist. The sensation of free will comes from the fact that the mechanism that generates the choices uses a non-determinist theory as a computational device and that the stage in which the choices have been identified is introspectable. The present formalism is based on work in artificial intelligence (AI). We present a theory of simple deterministic free will (SDFW) in a deterministic world. The theory splits the mechanism that determines action into two parts. The first part computes possible actions and their consequences. Then the second part decides which action is most preferable and does it. We formalize SDFW by two sentences in situation calculus, a mathematical logical theory often used in AI. The situation calculus formalization makes the notion of free will technical. According to this notion, almost no animal behavior exhibits free will, because exercising free will involves considering the consequences of alternative actions. A major advantage of our notion of free will is that whether an animal does have free will may be determinable by experiment. Some computer programs, e.g. chess programs, exhibit SDFW. Almost all do not. At least SDFW seems to be required for effective chess performance and also for human-level AI.
ReferencesSimple Deterministic Free Will (PDF) Normal | Teacher | Scholar