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Wednesday, October 18, 2017

Danny Kahneman on AI versus Humans

NBER Economics of AI Workshop 2017

Here is a rough translation of an excerpt:

One point made yesterday was the uniqueness of humans when it comes to evaluations. It was called “judgment”. Here in my noggin it’s “evaluation of outcomes”: the utility side of the decision function. I really don’t see why that should be reserved to humans.

I’d like to make the following argument:
  1. The main characteristic of people is that they’re very “noisy”.
  2. You show them the same stimulus twice, they don’t give you the same response twice.
  3. You show the same choice twice I mean—that’s why we had stochastic choice theory because thereis so much variability in people’s choices given the same stimuli.
  4. Now what can be done even without AI is a program that observes an individual that will be better than the individual and will make better choices for the individual by because it will be noise-free.
  5. We know from the literature that Colin cited on predictions an interesting tidbit:
  6. If you take clinicians and you have them predict some criterion a large number of time and then you develop a simple equation that predicts not the outcome but the clinicians judgment, that model does better in predicting the outcome then the clinician.
  7. That is fundamental.
This is telling you that one of the major limitations on human performance is not bias it is just noise.
I’m maybe partly responsible for this, but people now when they talk about error tend to think of bias as an explanation: the first thing that comes to mind. Well, there is bias. And it is an error. But in fact most of the errors that people make are better viewed as this random noise. And there’s an awful lot of it.

The entire transcript and target article is here.