Professor John McCarthy
Father of AI


Simple Deterministic Free Will

This is a shorter paper than Free Will - Even for Robots. I think it gets to the essence of free will and formalizes it in two short situation calculus formulas.

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.

Many features usually considered as properties of free will are omitted in SDFW. That's what makes it simple. The criterion for whether an entity uses SDFW is not behavioristic but is expressed in terms of the internal structure of the entity.

Download the article in PDF.