Prediction markets create harmful outcomes: a case study | Hacker News Reader

Prediction markets create harmful outcomes: a case study

bobjacobs.substack.com

19 pointsZipzip9 comments

This seems to have just happened: https://polymarket.com/event/another-dildo-thrown-at-wnba-ga...

(and it could happen again: https://polymarket.com/event/another-dildo-thrown-at-wnba-ga...

https://polymarket.com/event/dildo-thrown-at-wnba-game-on-au... )

Update: It did happen again. In fact, the dildo-throwings seem to have been a pre-planned tie-in for "Green Dildo Coin": https://www.nbcnews.com/news/amp/rcna223905

So the prediction market in this case maybe isn't so much causing the bad events, as just being a useful side channel by which the insiders/bad actors who've already planned the events can sweep up a little extra money from the prediction-market equivalent of "retail investors" — the ones who are inexplicably willing to put their money on the table with no information whatsoever and wait for someone else to take it.

black swans.

there's always people working on spotting or breeding them and home and corporate labs have gotten pretty damn big and powerful way back when.

prediction markets, stock markets, even the news and entertainment industry, and big tech, of course; everybody is breeding black swans.

What makes them fundamentally different from the stock market?

The stock market has so much more scale, in money at stake, data, news coverage, experts followup on rumors, etc. it would be relatively harder, and take more potentially traceable effort, to impact pricing with a rumor.

But it almost certainly happens.

So not fundamentally different.

And I just figured out how I would leverage particular kinds of existing credibility, and vulnerability, to do it. But the harder part is making significant bank, while not getting caught. (And spending eternity with your black soul!)

It sounds like the problem is that not enough people are using prediction markets then!

I think they are morally corrupt.

The forecasting community often promotes prediction markets as information aggregation tools, but sports betting provides a real-world test case for their claimed benefits vs. actual risks. As a concrete example of what can go wrong: NBA player Jontay Porter was banned for life after deliberately underperforming in games where he and associates had bet on his poor performance. He'd grab a few rebounds then fake an injury to stay under betting thresholds, profiting from markets on his own stats. This isn't isolated - similar manipulation scandals now exist across tennis, football, rugby, cricket, and other sports. The incentive structure is clear: participants don't just predict outcomes, they can influence them. Beyond direct manipulation, prediction markets also incentivize misinformation campaigns. Buy contracts cheap, spread convincing rumors to move market prices, then sell at profit.

No AI, please

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