Executive summary: The forecasting ecosystem produces accurate predictions but lacks sufficient focus on generating knowledge through facts, reasons, and models, especially for important questions like those related to AGI.
Key points:
Recent high-profile forecasting efforts on AGI and other topics provide forecasts but lack detailed rationales and models.
Elite forecasters face time constraints in tournaments, limiting their ability to deeply explore questions and build comprehensive models.
Published forecasts should cite key facts and primary sources to support their conclusions.
Adversarial collaborations where dissenting forecasters write up a shared view could help resolve debates and persuade the public.
Quantitative models, even if imperfect, can help decompose questions, generate probabilities, and allow for inspection and adjustment.
Focusing on facts, reasons, and models is especially important for AGI forecasting, where accuracy remains low and the stakes are high.
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.
Executive summary: The forecasting ecosystem produces accurate predictions but lacks sufficient focus on generating knowledge through facts, reasons, and models, especially for important questions like those related to AGI.
Key points:
Recent high-profile forecasting efforts on AGI and other topics provide forecasts but lack detailed rationales and models.
Elite forecasters face time constraints in tournaments, limiting their ability to deeply explore questions and build comprehensive models.
Published forecasts should cite key facts and primary sources to support their conclusions.
Adversarial collaborations where dissenting forecasters write up a shared view could help resolve debates and persuade the public.
Quantitative models, even if imperfect, can help decompose questions, generate probabilities, and allow for inspection and adjustment.
Focusing on facts, reasons, and models is especially important for AGI forecasting, where accuracy remains low and the stakes are high.
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.