Incentivizing forecasting via social mediapost by David Althaus (wallowinmaya), Daniel Kokotajlo (daniel-kokotajlo) · 2020-12-16T12:15:01.446Z · LW · GW · None comments
- Most people will probably never participate on existing forecasting platforms which limits their effects on mainstream institutions and public discourse.
- Changes to the user interface and recommendation algorithms of social media platforms might incentivize forecasting and lead to its more widespread adoption. Broadly, we envision i) automatically suggesting questions of likely interest to the user—e.g., questions related to the user’s current post or trending topics—and ii) rewarding users with higher than average forecasting accuracy with increased visibility.
- In a best case scenario, such forecasting-incentivizing features might have various positive consequences such as increasing society’s shared sense of reality and the quality of public discourse, while reducing polarization and the spread of misinformation.
- Facebook’s Forecast could be seen as one notable step towards such a scenario and might offer lessons on how to best proceed in this area.
- However, various problems and risks would need to be overcome—e.g., lack of trust or interest, cost, risks of politicization, and potential for abuse.
- While recommendation algorithms seem to present a particularly high-leverage point, there are other ways of promoting truth-seeking.
- Similar ideas might be applied to fact-checking efforts.
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