2min chapter

80,000 Hours Podcast cover image

#60 - Phil Tetlock on why accurate forecasting matters for everything, and how you can do it better

80,000 Hours Podcast

CHAPTER

Extremising

The best extremising agarithms are ones that are sensitive to the cognive diversity of the crowd. If you have a deep aversion to a false negative, for example, or a false positiveou, you're going to need to adjust your iuraccuracy function. I was always nervous about extremising but it worked remarkably well. It's like everything changes kind of all at once. Youre yo yu, saying only negatively correlated suddenly stop becoming correlated on the one question. And d that that ti, and that gives you reason to be a to be more extreme.

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