ensemble-of-five - Predictions for:

Forecaster A: Historical Base Rates
Historically, human forecasters have been resilient, maintaining an edge in live forecasting contexts. However, recent years have seen improvements in AI models. Trends from the past few years now show that AI can outperform humans in specific tasks, indicating a growing possibility of AI dominance by 2028.

Forecaster B: Current News and Evidence
The current evidence, as of August 2026, shows AI like FutureSearch leading in benchmarks and live tournaments. Despite human forecasters still edging out in certain areas, projections indicate that this is likely to change soon, given the advancements in AI capabilities and methodologies.

Forecaster C: Incentives and Game Theory
AI development is heavily incentivized across industries for efficiency and accuracy improvements. The competitive nature among companies to develop superior AI forecasters suggests an all-out push to surpass human capabilities, enhancing the probability of AI dominance by the target date.

Forecaster D: Quantitative/Statistical Reasoning
Quantitative analysis of benchmark scores and leaderboard positions shows a narrowing performance gap. Statistical models forecast AI reaching parity with human forecasters soon, supported by performance improvements and predicted trends.

Forecaster E: Devil's Advocate
Skepticism arises from potential overestimation of AI capabilities due to backtest reliance. Live forecasting conditions are unpredictable, and AI systems may face unforeseen challenges that prevent them from consistently outperforming human forecasters.

Aggregated Probability: Balancing the optimistic evidence with some level of skepticism, the overall probability that AI will outperform human forecasters by 2028 is estimated at 86%.

Forecaster A (Historical Base Rates): Based on historical performance of AI systems in various fields, advancements tend to accelerate over time. Historically, AI has steadily improved its capabilities, suggesting a high probability it could reach or surpass human benchmarks by 2028.

Forecaster B (Current News and Evidence): The latest data indicates significant progress in AI forecasting capabilities, with some instances of outperforming human forecasters in specific competitions. However, human forecasters still lead in aggregate evaluations.

Forecaster C (Incentives and Game Theory): There are strong incentives to improve AI forecasting capabilities due to competitive and economic advantages. As companies and researchers invest in AI development, it becomes more likely that AIs will meet or surpass human performance.

Forecaster D (Quantitative/Statistical Reasoning): The trend projections suggest AI will surpass human forecasters by mid-2027. With consistent progression, the probability of reaching this milestone by 2028 is high.

Forecaster E (Devil's Advocate): Despite positive trends, there are potential challenges in replicating AI's performance across diverse and unpredictable real-world problems. Human intuition and experience might still outperform AI in complex scenarios, suggesting some skepticism is warranted.

Aggregated Estimate: Weighing these perspectives, the probability of AI superforecasters outperforming human forecasters is reasonably high, but there are enough unknowns to introduce some uncertainty, resulting in an 86% probability.

Forecaster A: Historical Base Rates

Historically, the pace of AI advancement has been rapid, especially in domains where data-driven insights are critical. If we consider the base rates of AI progress, especially from benchmarks set before 2026 where AIs have reached parity or are leading in real-time competitions, a high likelihood exists for AI to exceed human performance by 2028.

Forecaster B: Current News and Evidence

Recent updates suggest AI models are already on par with human superforecasters in many environments (ForecastBench) and even outperform humans in live tournaments. While AI lags in Metaculus benchmarks, projections suggest parity is realistic by mid-2027. Present evidence strongly supports surpassing human performance by 2028.

Forecaster C: Incentives and Game Theory

There's significant investment and competitive advantage linked with AI surpassing human superforecasters, motivating continuous improvements. Given the demonstrated ability of AI models to close the gap in other areas, it's reasonable to expect incentives will drive this trend to completion.

Forecaster D: Quantitative/Statistical Reasoning

Statistical trends show AI achieving parity in several key benchmarks and leading in mixed environments. Quantitatively, the trajectory is clear: AI has approximately a 97-98% chance based on combined forecasts, indicating high confidence in AI outperforming by 2028.

Forecaster E: Devil's Advocate

While AI is progressing rapidly, unforeseen challenges such as overfitting to specific forecasting environments or diminishing returns in performance improvement could slow or stall progress, particularly in the diverse and complex domains of Metaculus challenges.

Aggregated Probability

Given the current trajectory, evidence, and expert consensus, a weighted average of the forecaster assessments suggests an 85% probability that AI superforecasters will outperform Metaculus superforecasters by January 1, 2028. While mostly positive, it's prudent to account for potential technical or structural hurdles.

Individual Forecaster Assessments:

Forecaster A (Historical Base Rates):

Historically, advancements in AI have shown a trend of rapid improvement over time. The leaps seen in natural language processing and other AI domains suggest a historical pattern of eventual AI dominance in various fields. Based on historical trends, there's a high likelihood that AI forecasting models will achieve parity or outperform human forecasters by 2028.

Probability: 85%

Forecaster B (Current News and Evidence):

Current evidence shows AI models are approaching parity with human superforecasters, particularly when diverse ensembling approaches are utilized. Live tournament results indicate AI models have already outperformed median human forecasters in certain contexts. This suggests a high probability of AI models surpassing Metaculus superforecasters before 2028 if the momentum continues.

Probability: 90%

Forecaster C (Incentives and Game Theory):

Significant incentives exist for AI developers to continue improving AI forecasting models, given the competitive advantage they offer. Game-theoretic considerations favor rapid progress and increased investment in AI forecasting to outcompete human abilities. As large organizations are likely to invest heavily in this area, AI outperformance seems plausible by 2028.

Probability: 88%

Forecaster D (Quantitative/Statistical Reasoning):

Statistical trends from sources like ForecastBench and tournament successes indicate AI models are closing the gap rapidly. Given the current trajectory and accelerated advances in AI technology, the numerical evidence supports a high likelihood of AI outperforming humans within the stated timeframe.

Probability: 92%

Forecaster E (Devil's Advocate):

While AI is advancing rapidly, potential roadblocks such as unforeseen technical challenges, ethical considerations, and potential regulatory constraints might slow progress. Human forecasters' ability to adapt and improve should not be underestimated either, providing a counterpoint to overconfidence in AI capabilities.

Probability: 75%

Aggregated Probability:

Taking into account the varied perspectives and assigning more weight to recent empirical data, the aggregate probability that AI superforecasters will outperform Metaculus superforecasters by January 1, 2028, is evaluated at:

Final Probability: 90%

Forecaster A: Historical Base Rates

Historically, AI has consistently made significant gains in specific areas like games and certain analytical domains. Given the rapid progression in AI model capabilities, the historical base rate for AI catching up with and surpassing human expertise in forecasting by a target date is moderate to high. Therefore, I estimate a probability of 65%.

Forecaster B: Current News and Evidence

Evidence suggests that AI models are closing the gap with human superforecasters, with recent tracks indicating they might surpass human performance by mid-2027. Given the latest trends and enhancements in AI forecasting models, the probability of this event occurring is reasonable. Thus, I estimate a probability of 70%.

Forecaster C: Incentives and Game Theory

Various players in the field have strong incentives to develop forecasting AI that surpasses human capabilities, not only for prestige but also for potential financial gains. Considering the competitive landscape, these incentives are likely to accelerate progress. As such, I place the likelihood at 60%.

Forecaster D: Quantitative/Statistical Reasoning

The data shows rapid improvement in AI forecasting capabilities, suggesting a projected crossover by mid-2027. Given these extrapolations and statistical models, the probability seems favorably high. I would assign a 65% probability.

Forecaster E: Devil’s Advocate

While current trends are promising, there are potential roadblocks, such as unforeseen technical challenges or overhyped projections. Additionally, human forecasters may also improve or adapt. Thus, introducing skepticism, I suggest a lower probability of 55%.

Aggregated Probability

Considering the independent probabilities and reasoning, the aggregated forecast results in a final estimated probability of 63% that AI will outperform Metaculus superforecasters by January 1, 2028.