Oly Sourbut

What's the reasoning trace preceding the decision?

What are the various other kinds of inputs?

What's the training data look like?

And these kinds of things can be scrutable.

In many cases, it might be kind of a big data problem, especially if we're talking about training data.

But if we're just talking about things like coming to like a judicial decision, you can look at what were all the inputs that went in there.

And at least that tells you what was...

salient and kind of in scope for that decision.

What you don't know then is what else is being kind of brought into latent context by the training and so on into the world.

So there's that gap there.

I don't exactly know the state of the art in terms of figuring out which training inputs were most relevant for a given decision or given output and this kind of thing.

I know there's work being done on that.

So yeah, there's maybe hope to make this kind of thing a little bit more scrutable as well.

But of course, it's the same for humans.

You can ask a human, why did you come to that decision?

But you don't know whether what they're saying is either honest or factual.

There is absolutely a demand problem.

This is very central.

And actually, yeah, so I don't think I've touched on this yet, but definitely that's pretty central to FLF strategy.

Probably the reason I haven't touched on it yet is because among the staff of FLF, I'm probably kind of least experienced in dealing with distribution and demand and so on.