Summary: The emergence of artificially sentient beings raises moral, political, and legal issues that deserve scrutiny.
Key points:
The AI Forecasting Benchmark Series compares the performance of AI forecasting bots to human forecasters, using a robust and consistent framework to address methodological issues.
The framework includes question weights to mitigate the problem of correlated questions, which can exaggerate the performance of forecasters.
The weighted t-test is used to assess the significance of the results, and is compared to weighted bootstrapping to ensure reliability.
The multiple comparisons problem is avoided by making a single comparison between the top bot median and the Pro median.
The framework is general and can be used consistently to compare the track records of different forecasters.
The approach is expected to reduce statistical noise and provide a more reliable measure of forecasting skill.
The framework can be extended to other parts of Metaculus, such as talent spotting and comparing track records across platforms.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Summary: The emergence of artificially sentient beings raises moral, political, and legal issues that deserve scrutiny.
Key points:
The AI Forecasting Benchmark Series compares the performance of AI forecasting bots to human forecasters, using a robust and consistent framework to address methodological issues.
The framework includes question weights to mitigate the problem of correlated questions, which can exaggerate the performance of forecasters.
The weighted t-test is used to assess the significance of the results, and is compared to weighted bootstrapping to ensure reliability.
The multiple comparisons problem is avoided by making a single comparison between the top bot median and the Pro median.
The framework is general and can be used consistently to compare the track records of different forecasters.
The approach is expected to reduce statistical noise and provide a more reliable measure of forecasting skill.
The framework can be extended to other parts of Metaculus, such as talent spotting and comparing track records across platforms.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.