In artificial intelligence research, GOFAI ("Good Old-Fashioned Artificial Intelligence") describes the oldest original approach to achieving artificial intelligence, based on logic and problem solving. In robotics research, the term is extended as GOFAIR ("Good Old-Fashioned Artificial Intelligence and Robotics").

GOFAI was the dominant paradigm of AI research from the middle fifties until the late 1980s. After that time, newer sub-symbolic approaches to AI were introduced. The term "GOFAI" was coined by John Haugeland in his 1986 book Artificial Intelligence: The Very Idea, which explored the philosophical implications of artificial intelligence research.

The approach is based on the assumption that many aspects of intelligence can be achieved by the manipulation of symbols, an assumption defined as the "physical symbol systems hypothesis" by Allen Newell and Herbert A. Simon in the middle 1960s. By the 1980s, many researchers began to doubt that high-level symbol manipulation alone could account for all intelligent behaviors. Opponents of the symbolic approach include roboticists such as Rodney Brooks, who aims to produce autonomous robots without symbolic representation (or with only minimal representation) and computational intelligence researchers, who apply techniques such as neural networks and optimization to solve problems in machine learning and control engineering. Now, both approaches are in common use, often applied to different problems.

GOFAI was intended to produce general, human-like intelligence in a machine, whereas most modern research is directed at specific sub-problems. Research into general intelligence is now studied in the sub-field of artificial general intelligence.