The Dartmouth Workshop

In the summer of 1956, John McCarthy (then at Dartmouth), Marvin Minsky, Nathaniel Rochester (IBM), and Claude Shannon (Bell Labs) organize a two-month workshop that gives the field its name. Their 1955 funding proposal states the founding premise plainly: “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” They ask the Rockefeller Foundation for funding on the assumption that “a significant advance can be made” if a select group of scientists works on the problem together for a summer.

The workshop does not produce the significant advance it promises. It produces something more durable: a name for the field, a founding cohort of researchers who go on to define its early decades, and a template for how AI research gets pitched – ambitious timelines, small teams, funding secured on the strength of what the technology will soon be able to do rather than what it currently does.

That template recurs almost immediately. A year later, Frank Rosenblatt’s Perceptron generates its own wave of confident prediction, followed by its own collapse in funding. The pattern set at Dartmouth – bold claim, institutional investment, discovery of limitations – becomes a structural feature of how AI research gets resourced, not a one-time miscalculation.

Source: John McCarthy, Marvin L. Minsky, Nathaniel Rochester, and Claude E. Shannon, “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955,” reprinted in AI Magazine, 27(4), 2006, 12–14.