This is a linkpost for https://bayesianinvestor.com/blog/index.php/2024/03/02/self-resolving-prediction-markets/

Back in 2008, I criticized the book Predictocracy for proposing prediction markets whose contracts would be resolved without reference to ground truth.

Recently, Srinivasan, Karger, and Chen (SKC) published more scholarly paper titled Self-Resolving Prediction Markets for Unverifiable Outcomes.

Manipulation

In the naive version of self-resolving markets that I think Predictocracy intended, the market price at some point is used to pay off participants. That means a manipulator can enter the market as a trader, and trade so as to drive the market price in whatever direction they want. Unlike markets that are resolved by a ground truth, there's no reliable reward for other traders to offset this distortion. It seems likely that manipulators will sometimes be able to set the price wherever they want, because there are no incentives that offset the manipulation.

SKC replace the standard prediction market [...]

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Outline:

(00:27) Manipulation

(02:14) When is this useful?

(04:11) AI Risks

(05:16) Conclusion

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First published:
March 3rd, 2024

Source:
https://www.lesswrong.com/posts/tJmpsEevCcEfL6a7Z/self-resolving-prediction-markets

Linkpost URL:
https://bayesianinvestor.com/blog/index.php/2024/03/02/self-resolving-prediction-markets/

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Narrated by TYPE III AUDIO.

[Linkpost] “Self-Resolving Prediction Markets” by PeterMcCluskey

LessWrong (30+ Karma)