Artificial intelligence is a field that has been influenced by mathematics, computer science, psychology, neurobiology, linguistics, economics, and others.
The term artificial intelligence (AI) was officially coined in 1956 at the Dartmouth Summer Research Project meeting; however, the concept of AI can be traced to as far back as 700 BC, when tales of “mechanical” humans were incorporated into Greek mythology.
Developments in AI often occurred in parallel with different research streams converging to lead to significant advances in the technology.
Artificial intelligence (AI) has a variety of definitions depending on the context, basic theory, or era under consideration1,2; however, it can be understood broadly as the ability of a machine to recreate, approximate, or otherwise simulate intelligent human actions. An intelligent machine that can understand and solve problems in a manner similar to, if not superior to, the human brain is perhaps the ultimate goal of AI. However, because this goal is undoubtedly ambitious, it remains far out of reach despite significant advances that have occurred in the field. AI is a broad and disparate discipline derived from a vast array of fields that have made many significant contributions to the development of AI throughout history. Disciplines such as biology, philosophy, and computer science, among others, have each played an important role in AI’s development, sometimes working in parallel before intersecting at various points in time as technology and interests have converged.
Fundamental advances in philosophy and biology led to analogous advances in applied fields such as economics, engineering, and computer science. The interaction and cross-integration of these various disciplines and their visions promoted growth and stimulated creative thinking. Together, centuries of small discoveries in philosophy, mathematics, economics, linguistics, psychology, neurobiology, and computer science laid the foundation upon which the concept of AI was established. In our view, there were 3 notable pillars of progress that led to the advancement of AI as we know it today. The first is marked by the attempt to connect basic machinery to the philosophy of thinking—as seen in works spanning from Leonardo da Vinci to Alan Turing—and the rise of numerical reasoning and computing. The second pillar is the establishment of a basic understanding of logical reasoning coupled with attempts to define a reasoning machine. The third surrounds the development of techniques to answer the question of how one can quantify reasoning.
We see these pillars often occurring in parallel over time. Because the development of AI did not occur in discrete segments but rather as amorphous advances occurring together across history and different fields, it is quite difficult and arbitrary to divide the history of AI into specific time periods. Thus, although we provide some distinctions for relative time periods in this chapter, please note that these are not, by any means, “official” transitions or historical markers. The sections are meant to ...