A thread through the archive
Essays tagged “prediction markets”. Follow an idea across the archive.
Scott Alexander explores various COVID-19 topics including lockdown effectiveness, infection rate variations, transmission risks, prediction markets, and ethical considerations of pandemic response.
Scott Alexander examines the underutilization of prediction aggregation platforms like Metaculus, exploring potential reasons and expressing surprise at their lack of widespread adoption.
Scott Alexander evaluates the accuracy of his 2015 predictions, finding overall good calibration and considering it a successful year.
Scott Alexander argues for the use of probabilities in decision-making even without well-defined models, using examples to show why this approach is necessary and beneficial in real-world situations.
Scott Alexander explores how perfect predictions of war outcomes, through oracles or prediction markets, could potentially prevent wars, and extends this concept to conflicts between superintelligent AIs.
Scott Alexander explores social impact bonds as a potential way to use corporate greed to solve social problems more efficiently than current government programs.
Scott reflects on his hasty utopian science post, viewing it as a success for prompting Robin Hanson to expand on academic prediction markets.
Scott Alexander proposes a utopian scientific system using prediction markets and impartial researchers to eliminate bias and efficiently resolve controversies.
Scott shares and comments on a diverse collection of news items and interesting links from March 2014, covering topics from medical advances to political issues and quirky stories.
The post details the Third Eye surveillance system and Priesthood of Truth in the fictional society of Raikoth, exploring how these institutions work to prevent corruption and maintain social order.
Scott Alexander humorously explores the potential for arbitrage in papal betting markets, noting legal and religious obstacles, while highlighting some curious odds and betting options.
Scott distinguishes between bias as a cognitive process versus bias as a faulty belief, then proposes using the Implicit Association Test to empirically test whether debiasing techniques work by either fighting bias directly or routing around it.