AI/ML

People sometimes ask whether deep learning is a good model of the brain. I think that’s the wrong question. The brain isn’t trying to be efficient in the way a neural network is. It’s doing something stranger — running on noisy hardware, under metabolic constraints, across decades of experience. The gap between the two is where the interesting questions live. I’ve stopped being bothered by the fact that my models don’t map cleanly onto biology. The mismatch is data.

Most of the AI safety conversation happens inside CS departments and a handful of dedicated research labs. I think that’s too narrow. If AI systems are going to be deployed in healthcare, mental health support, clinical decision-making — and they already are — then the people who understand those domains need to be in the room. Not just as end users. As researchers with opinions about what safe actually means in context. ...