Very often these articles ask excellent questions -- but fully 80% of their value is in the prompt-question. On the one hand, this question explodes into the "

Very often these articles ask excellent questions -- but fully 80% of their value is in the prompt-question. On the one hand, this question explodes into the "general purpose AI" literature. Less Wrong actually originated from a smaller community of people asking what did it mean for AI to be "friendly" to humans, very abstractly. On the other hand, there's "good citizenship" desiderata. Maybe Hubert Dreyfus is correct and there can't be general AI, but the fact of the matter is that our actor-networks (as in Latour) are already crowded with algorithms and machines. What does it mean for a machine to be accountable, dependable, reliable, and yes, fair? An image classifier should be invertible -- if we're consistently getting that black men look like apes, we should know what the machine thinks an ultra-archetype ape is. Interestingly, this has been the focus of a lot of research since I took that NN class in college back in 2001 -- we're able to visualize hidden layers now. A credit scorer should be consistent with some wider sense of credit worthiness, sure. It should be possible to increment your credit score, at the margin, with marginal changes to (real, important) inputs, rather than have it place you in a brittle "unreliable" type. You should be able to dig yourself out of debt. All of these are kind of domain specific, but I haven't spent much thought on it. It seems to me that there are some general characteristics (invertibility, smoothness across key controls) that should be identifiable.