Before the term “Artificial Intelligence” existed, thinkers were already imagining machines that could think. In 1950, British mathematician Alan Turing published “Computing Machinery and Intelligence,” introducing what would become known as the Turing Test – a way to assess if a machine could mimic human conversation [citation:11][citation:12]. Turing envisioned a computing machine that could advance far past its original programming, laying the theoretical foundation for AI [citation:7].
The term “artificial intelligence” was coined by John McCarthy in 1955, and the field was officially born at the Dartmouth Summer Research Project in 1956 [citation:1][citation:9][citation:11]. McCarthy, along with Marvin Minsky, Nathaniel Rochester, and Claude Shannon, proposed a summer workshop to explore the possibility of “thinking machines” [citation:1]. This event is widely considered the official birth of AI as a formal discipline [citation:1][citation:12].
Dartmouth brought together a small group of researchers from various disciplines to investigate whether machines could simulate human intelligence [citation:1][citation:7]. The project proposal itself introduced the term “artificial intelligence” and set the stage for decades of research in symbolic reasoning, statistical learning, and neural computation [citation:3].
Early AI research focused on logic-based systems. In 1956, Allen Newell, Herbert A. Simon, and Cliff Shaw created the Logic Theorist, a program designed to perform automated reasoning [citation:1]. It is often called the “first program with artificial intelligence” because it could prove mathematical theorems from Principia Mathematica [citation:1][citation:2]. This demonstrated that machines could mimic human reasoning, at least in limited domains.
These early pioneers established the foundational belief that human thought could be simulated by machines – a vision that continues to drive AI research today.