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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Base Rate Times, news through prediction markets, published by vandemonian on June 6, 2023 on LessWrong.
Introduction
I made a news site based on prediction markets
The Base Rate Times is a nascent news site that incorporates prediction markets prominently into its coverage.
Please see current iteration: www.baseratetimes.com
Twitter: www.twitter.com/base_rate_times
What problem does it solve?
Forecasts are underutilized by the media
Prediction markets are more accurate than pundits, yet the media has made limited use of their forecasts. This is a big problem: one of the most rigorous information sources is being omitted from public discourse!
The Base Rate Times creates prediction markets content, substituting for inferior news sources. This improves the epistemics of its audience.
Forecasts are dispersed, generally inconvenient to consume
Prediction markets are dispersed among many different platforms, fragmenting the information forecasters provide. For example, different platforms ask similar questions in different ways. Furthermore, platforms’ UX is orientated towards forecasters, not information consumers. Overall, trying to use prediction markets as ‘news replacement’ is cumbersome.
There is value in aggregating and curating forecasts from various platforms. We need engaging ways of sharing prediction markets’ insights. The Base Rate Times aims to make prediction markets easily digestible to the general public.
How does it work?
News media (emotive narrative) vs Base Rate Times (actionable odds)
For example, this is a real headline from a reputable newspaper: “Taiwan braces for China's fury over Pelosi visit”. Emotive and incendiary, it does not help you form an accurate model of the situation.
By contrast, The Base Rate Times: “China-Taiwan conflict risk 14%, up 2x from 7% after Pelosi visit”. That's an actionable insight. It can inform your decision on whether to stay in Taiwan or to flee, for example.
News aggregation, summarizing prediction markets
Naturally, the probabilities in the example above come from prediction markets. The Base Rate Times presents what prediction markets are telling us about news in an engaging way.
Stories that shift market odds are highlighted. And if a seemingly important story doesn’t shift market odds, that also tells you something.
On The Base Rate Times, right now you can see the latest odds on:
Putin staying in power
Russian territorial gains in Ukraine
Escalation risk of NATO involvement
and more...
By glancing at a few charts, you can form a more accurate model (in less time) of Russia-Ukraine than reading countless narrative-based news stories.
Inspiration
A key inspiration was Scott Alexander’s Prediction Market FAQ:
I recently had to read many articles on Elon Musk’s takeover of Twitter, which all repeated that “rumors said” Twitter was about to go down because of his mass firing. Meanwhile, there were several prediction markets on whether this would happen, and they were all around 40%. If some journalist had thought to check the prediction markets and cite them in their article, they could have not only provided more value (a clear percent chance instead of just “there are some rumors saying this”), but also been right when everyone else was wrong.
Also Scott’s 'Mantic Monday' posts and Zvi’s blog.
This simple chart by @ClayGraubard was another inspiration. Wanted something like this, but for all major news stories. Couldn't find it, so making it myself. (Clay is making geopolitics videos and podcasts now, check it out.)
Goals
Like 538, but for prediction markets
The Base Rate Times is a bet that forecasts can be popularized, as opinion polls have been, and improve society’s models of the world.
Goal: Longshot probability of going mainstream, e.g. like 538.
If highly successful in scaling, we’d be effectively run...
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