Yoshua Bengio
speaker
2,216 appearances
5 recordings
5 series
first heard Oct 2018
last heard 7 May
Yoshua Bengio’s voice in public audio — every appearance, attributed to the second.
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Appearances
to reject threshold on the risk probability to reject those questions.
And that threshold is a normative choice.
It is something that society decides, like how much risk are we willing to take depending on the kind of harm that we're talking about.
The guardrail also has other roles to handle what is called performative prediction.
So sometimes a question can have multiple answers because the answer will influence the future.
So a classical example is if the question is about who's going to win the next election and maybe the AI is considered very capable and people will believe whatever it says and vote for that candidate, which means the AI could say,
this guy or that guy.
And both of them would be true either way.
And both would be true, right?
So then it's starting to have agency through his prediction in a way that seems that we don't control.
And the guardrail is going to manage that to decouple the predictions from the effect of those predictions.
So to be more concrete, the neural net predictor is trained
so that in its input conditions, there's always a particular statement that asks, what if we did produce this prediction?
What would be, for example, the harm effect, right?
And so when you condition on the intervention of producing a particular answer, now there's only one
You're saying, oh, I'm going to put out this prediction and what will be the effect?
So there's more to say about this, but the bottom line is you can control this kind of risk and the agency that could come from it.
And it's the job of the guardrail to do that job.
So I think we have to distinguish two problems to have a clear idea about your question.
One is...
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