Seymour Papert (1928-2016) was a South African-born mathematician who spent most of his career at MIT. He joined as a research associate in 1963, became a professor of applied mathematics in 1967, and co-directed the MIT Artificial Intelligence Laboratory with Marvin Minsky. He was also a founding faculty member of the MIT Media Lab in 1985. Beyond AI, he is celebrated as a pioneer of educational technology: he invented Logo, the first programming language designed for children, and developed “constructionism,” the theory that people learn best by actively building things.
In the history of AI, Papert is best known for the 1969 book “Perceptrons,” co-authored with Minsky. The book gave a rigorous mathematical analysis of the limits of single-layer perceptrons, the simple neural networks of the day, showing they could not solve certain basic problems. Its influence is contested: it is often credited with helping to redirect funding away from neural networks and toward symbolic AI, contributing to the long quiet period before neural networks returned.
For the library’s reader, Papert appears throughout the neural-network story as the co-author whose critique helped pause a field that would later dominate AI. It is a useful corrective to read him in full, though: the same person who sharpened the case against early neural nets also spent decades arguing that children should program computers rather than be programmed by them, an unusually humane strand of thinking about what computing is for.