The way we train AI is fundamentally flawed

Underspecification is a known issue in statistics, where observed effects can have many possible causes. D'Amour, who has a background in causal reasoning, wanted to know why his own machine-learning models often failed in practice. He wondered if underspecification might be the problem here too. D'Amour soon realized that many of his colleagues were noticing the same problem in their own models. "It's actually a phenomenon that happens all over the place," he says.