tetlock-style-economists - Predictions for:

Clarify the Event:

The event forecasts that AI models designed for superforecasting will outperform human superforecasters on Metaculus before January 1, 2028. This means consistently achieving better accuracy across various domains.

Estimate the Historical Base Rate:

Historically, AI in certain domains (chess, Go) has achieved superhuman performance. AI model progress has shown rapid advancement in predictive tasks. However, in domains requiring nuanced judgment, human expertise often remains significant.

Break the Problem into Independent Factors:

1. Current AI Capabilities: As of mid-2026, AI is closing the gap but hasn't surpassed human superforecasters.
2. Trends in AI Improvement: Projections suggest AI could exceed human performance by mid-2027.
3. Model Enhancement: Rapid improvements in AI models (Gemini 3.1, GPT-5.5) show potential for surpassing humans.
4. Integration and Hybrid Strategies: Human-AI ensembles already show enhanced accuracy.
5. Metaculus and AI Integration: Successful AI integration in forecasting is progressing, but systemic acceptance of surpassing humans is crucial.

Estimate Each Factor Separately:

1. Current AI Capabilities: 60% (showing strong progress, near parity in some cases).
2. Trends in AI Improvement: 75% (consistent trend suggests probable human surpassing by mid-2027).
3. Model Enhancements: 80% (continuous updates and advancements are highly likely to boost performance).
4. Integration Strategies: 70% (likely improved results through hybrid strategies and model enhancements).
5. Metaculus Acceptance: 65% (future evaluations suggest ongoing tracking and potential acceptance).

Recombine Into an Overall Probability:

Aggregating the weighted probabilities, considering AI systems' exponential learning curves and advancements, the overall probability is around 75%.

Check for Overconfidence:

Acknowledging uncertainty factors such as unforeseen advancements in AI, changes in Metaculus testing methodologies, and unexpected human forecasting improvements could impact the probability.

Imagine Why You Could Be Wrong:

1. Human Factor: Human forecasters could innovate, applying new techniques boosting accuracy.
2. Systemic Changes: Metaculus might change evaluation methods, affecting comparative results.
3. Technological Plateau: AI advancements might slow unexpectedly, delaying surpassing humans.
4. Regulatory Changes: New rules around AI usage might hinder model deployment or development.