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Globalisation for me seems to be not first-order harm and I find it very hard not to think about the billion people who have been dragged out of poverty as a result.

But here are some general impressions I got from the talks and participants: 1.

I still wanted to ask the panel “Given that 30-50% of kids fail high school algebra, how do you expect them to learn computer science?

”, but by the time I had finished finding that statistic they had moved on to a different topic. The cutting edge in AI goal alignment research is the idea of inverse reinforcement learning.

Normal reinforcement learning is when you start with some value function (for example, “I want something that hits the target”) and use reinforcement to translate that into behavior (eg reinforcing things that come close to the target until the system learns to hit the target).

Inverse reinforcement learning is when you start by looking at behavior and use it to determine some value function (for example, “that program keeps hitting that spot over there, I bet it’s targeting it for some reason”).

Since we can’t explain human ethics very clearly, maybe it would be easier to tell an inverse reinforcement learner to watch the stuff humans do and try to figure out what values we’re working off of – one obvious problem being that our values predict our actions much less than we might wish.

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