“Higher-Order Forecasts” by Ozzie Gooen

Higher-order forecasting could be a useful concept for prediction markets and forecasting systems more broadly. The core idea is straightforward: Nth-order forecasts are forecasts about (N-1)th order forecasts.Abstract representation of 2nd-order forecasts. Dall-E 3 Examples Here are some examples: 0-Order Forecasting (i.e., the ground truth) Biden won the 2020 U.S. presidential election The US GDP in 2023 was $27 trillion 1st-Order Forecasting (i.e., regular forecasting) What is the chance that Trump will win the 2024 U.S. presidential election? What will be the GDP of the US in 2024? 2nd-Order Forecasting How much will the forecasts for US GDP in 2024 and 2025 be correlated over the next year? How many forecasts will the question "What will be the GDP of the US in 2024?" receive in total? If the question “What is the chance that a Republican will win the 2028 Presidential Election?” was posted to [...] ---Outline:(00:28) Examples(02:32) Benefits(04:46) Challenges(05:29) Conclusion--- First published: May 22nd, 2024 Source: https://forum.effectivealtruism.org/posts/PB57prp5kEMDgwJsm/higher-order-forecasts --- Narrated by TYPE III AUDIO.