In this article, we provide a brief history of the disciplines that contributed ideas, viewpoints, and techniques to AI. Like any history, this one concentrates on a small number of people, events, and ideas and ignores others that also were important. We organize the history around a series of questions. We certainly would not wish to give the impression that these questions are the only ones the disciplines address or that the disciplines have all been working toward AI as their ultimate fruition.

Philosophy

• Can formal rules be used to draw valid conclusions?

• How does the mind arise from a physical brain?

• Where does knowledge come from?

• How does knowledge lead to action?

Aristotle (384–322 BCE) was the first to formulate a precise set of laws governing the rational part of the mind. He developed an informal system of syllogisms for proper reasoning, which in principle allowed one to generate conclusions mechanically, given initial premises. Ramon Llull (c. 1232–1315) devised a system of reasoning published as Ars Magna or The Great Art (1305). Llull tried to implement his system using an actual mechanical device: a set of paper wheels that could be rotated into different permutations. Around 1500, Leonardo da Vinci (1452–1519) designed but did not build a mechanical calculator; recent reconstructions have shown the design to be functional. The first known calculating machine was constructed around 1623 by the German scientistWilhelm Schickard (1592–1635). Blaise Pascal (1623–1662) built the Pascaline in 1642 and wrote that it “produces effects which appear nearer to thought than all the actions of animals.” Gottfried Wilhelm Leibniz (1646–1716) built a mechanical device intended to carry out operations on concepts rather than numbers, but its scope was rather limited. In his 1651 book Leviathan, Thomas Hobbes (1588–1679) suggested the idea of a thinking machine, an “artificial animal” in his words, arguing “For what is the heart but a spring; and the nerves, but so many strings; and the joints, but so many wheels.” He also suggested that reasoning was like numerical computation: “For ‘reason’ . . . is nothing but ‘reckoning,’ that is adding and subtracting.”.

The final element in the philosophical picture of the mind is the connection between knowledge and action. This question is vital to AI because intelligence requires action as well as reasoning. Moreover, only by understanding how actions are justified can we understand how to build an agent whose actions are justifiable (or rational).

In contrast, Immanuel Kant, in 1785, proposed a theory of rule-based or deontological ethics, in which “doing the right thing” is determined not by outcomes but by universal social laws that govern allowable actions, such as “don’t lie” or “don’t kill.”

Many modern AI systems adopt exactly this approach.