Carissa Véliz

And it's not obviously causally related to your ability to pay back the loan.

And it's just because people who had that same data didn't pay back a loan that you might not get a loan.

and that seems very unfair to me and that we are not giving people enough chance to defy their odds and that is not only bad for those people it's bad for society because when we you shackle people's ability to defy their odds you shackle society's ability to come up with creative solutions to our most pressing problems i think i would assume that if you're going to make a prediction

Yes, that's an assumption and it's a very wrong assumption for many reasons.

Sometimes the relevant data is not there.

Sometimes data is just noise.

It's like trying to find a needle in a haystack and adding hay.

Sometimes it's not helpful.

Is it the right data?

Is it true?

Is it accurate?

Is it relevant?

Then yes.

But we shouldn't assume that.

So the work of people like Gerd Gigerentzer, who is a social scientist in Germany, suggests that sometimes we make much better decisions with less data.

There are many examples, but here's one.

Imagine that you want to decide whether to become a gambler and you try to collect as much data as possible on gambling and you realize something astonishing.

And that is that the trope about beginner's luck is true, that many gamblers at the beginning of their career do incredibly well.

And the more data you collect, the more it verifies this conclusion.

And if that were true, if it were true that the more data you have, the better, then the more data you collected that verifies this would push you onto becoming a gambler and then stopping, because gambler's luck seems to be a thing.