从能力竞赛转向概念、价值与责任的澄清
Artificial-intelligence debates often present engineering as the realm of solutions and philosophy as commentary from the sidelines. Yet many stubborn problems begin before the code: What counts as understanding, whose preferences become objectives, and what evidence justifies trust?
Philosophy cannot make a model robust or remove a biased dataset. It can, however, expose category errors, distinguish prediction from explanation and test whether appealing principles survive difficult cases. That conceptual work changes what engineers measure and what regulators demand.
Inspired by a public New Scientist title/summary · Rewritten by Vocabsavvy · Vocabsavvy Original (public-snippet inspired)