FutureBench: Evaluating AI Agents on Predicting Future Events

AI Impact Summary

This evaluation framework shifts the focus of AI benchmarks from simply replicating past knowledge to predicting genuinely novel future events. The FutureBench approach, utilizing a combination of scraped news and prediction market data, aims to assess an agent's ability to synthesize information, reason about complex relationships, and handle uncertainty – capabilities crucial for real-world applications like strategic planning and risk assessment. The multi-level evaluation strategy – comparing frameworks, tool performance, and model capabilities – provides a granular understanding of what drives agentic success, moving beyond traditional accuracy metrics.