Introduction

If we asked GPT-4 to play a prediction market, how would it do?

Actual GPT-4 probably would just give us some boring boilerplate about how the future is uncertain and it’s irresponsible to speculate. But what if AI researchers took some other model that had been trained not to do that, and asked it?

This would take years to test, as we waited for the events it predicted to happen. So instead, what if we took a model trained off text from some particular year (let’s say 2020) and asked it to predict forecasting questions about the period 2020 - 2023. Then we could check its results immediately!

This is the basic idea behind Zou et al (2022), Forecasting Future World Events With Neural Networks. They create a dataset, Autocast, with 6000 questions from forecasting tournaments Metaculus, Good Judgment Project, and CSET Foretell. Then they ask their AI (a variant of GPT-2) to predict them, given news articles up to some date before the event happened. Here’s their result: