Forecasting Research Institute

We advance the science of forecasting to improve decision-making on high stakes issues. Co-founded by chief scientist Philip Tetlock.

[Forecasting Research Institute @Research_FRI]

For a more detailed summary of these results, check out our Substack post: https://t.co/td0qukAMbc

To explore more forecasts, including further questions from Wave 8, read the full report: https://t.co/SXxfvpwNkI

[Forecasting Research Institute @Research_FRI]

How are experts and superforecasters updating their expectations of AI progress?

In our latest round of Longitudinal Expert AI Panel (LEAP) forecasts, we asked for predictions on AI progress timelines, including updated forecasts for a question we last asked nine months ago.

We also asked for forecasts on near-term progress on @METR_Evals' time horizon benchmark, AGI timelines, the blockers and enablers of AGI, and AI's overall impact in the next 20 years.

🧵 Read on for more:

[Forecasting Research Institute @Research_FRI]

👍 Experts and superforecasters tend to view AI more optimistically than the general public

When asked for their view on AI's overall impact on the U.S. over the next 20 years, 57.5% of experts and 69.8% of superforecasters predict a somewhat or very positive impact, compared to 42.0% of the public.

The divergence is sharpest on problem-solving: 72.7% of experts expect AI will make people better at this, compared to 48.6% of the public.

One area in which experts and the public converge is their views on forming meaningful relationships. 68.4% of experts and 66.7% of the public expect AI to make people worse at this.

16.5% of experts and 11.3% of superforecasters expect AI's overall impact to be somewhat or very negative, compared to 29.8% of public respondents.

[Forecasting Research Institute @Research_FRI]

We're working to improve ForecastBench! Upcoming changes:

• Fresh superforecaster round: fall 2026.
• Continuous (non-binary) forecasting questions: summer 2026.
• External submissions on continuous questions: summer 2026.
• Revamped dataset questions: fall 2026.

[Forecasting Research Institute @Research_FRI]

On a subset of ForecastBench questions, an LLM has matched superforecaster performance for the first time.

A submission from @GoogleDeepMind, named “green tree,” is now #1 on dataset questions on ForecastBench, our AI forecasting benchmark.

Superforecasters remain #1 overall.

[Forecasting Research Institute @Research_FRI]

Does parity on dataset questions mean ForecastBench is “solved”? No.

On market questions that require judgment about novel, one-off events, LLMs are still behind.

Even on dataset questions, the 64.9% achieved by Google DeepMind is unlikely to be the ceiling of what’s possible. ForecastBench doesn’t stop being useful at human parity. It will continue tracking LLM progress even if they surpass expert human forecasters.

[Forecasting Research Institute @Research_FRI]

To explore more Wave 7 forecasts from LEAP, including question-by-question details, visit: https://t.co/itWW3HWkLh

Find out more about LEAP, our panelists, and analysis from early waves on the LEAP website: https://t.co/VpXGhClZcM

To stay up-to-date with FRI's work, subscribe to our Substack: https://t.co/jUAJ1pc03u

[Forecasting Research Institute @Research_FRI]

How fast do experts and superforecasters expect progress in robotics to be?

In Wave 7 of the Longitudinal Expert AI Panel (LEAP) we asked forecasters to predict when robots will pass the "Coffee Test", and when they will perform the first autonomous appendectomy.

We also asked for forecasts on the supply of industrial robots, future U.S. labor share, and Amazon's e-commerce sales per distribution employee, to try to understand how fast one of the U.S.’s largest employers will automate.

🧵 Read on for more:

[Forecasting Research Institute @Research_FRI]

💲Experts forecast Amazon's e-commerce sales per distribution employee to rise

The median expert forecasts Amazon's real e-commerce net sales per distribution employee to rise from its 2024 baseline of $464,771.

They expect:

2026: $480,000
2030: $549,842
2040: $800,000

Superforecasters are even more bullish, predicting over $1 million by 2040.

Forecasters cited the suitability of warehouses for robotic deployment, Amazon's track-record in automation and a decoupling of sales from labor as key factors driving their predictions.