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Prediction ledger

Who called it? AI predictions, checked.

Confident claims about AI, with the exact words, the date they named, and what happened. A claim is too fast when the change came later than promised, and too slow when it came sooner.

Too fast
3
came later than promised
Too slow
2
came sooner than expected
Ambiguous
2
can't be judged cleanly
Still open
8
next due Mar 2027

The pattern so far

In this small, hand-picked sample, the misses split by kind. Contests and benchmarks arrived early: experts were too slow on Go and on Olympiad math. Deployment and jobs arrived late: robotaxis, the end of radiology, and code written mostly by AI all took longer than promised.

That is the two-clock story. Capability moves fast; the economy around it moves at the pace of its weakest links. Why weak links set the pace

Caution: a too-slow call resolves the day the milestone lands, but a too-fast call only shows once its date passes, so early tallies over-count surprises on the upside. The Forecasting Research Institute flags the same bias in its own track record.

Every prediction

Verdict
Topic

15 of 15 predictions

Elon Musk

CEO, Tesla · Apr 22, 2019

Too fast

“…next year for sure, we'll have over a million robotaxis on the road. The fleet wakes up with an over the air update; that's all it takes.”

No Tesla robotaxi service ran in 2020. Paid rides began in Austin in June 2025 with safety monitors on board, and by mid-2026 the driverless fleet was about 20 cars.

Due Dec 2020Adoption

Geoffrey Hinton

AI researcher, University of Toronto and Google · 2016

Too fast

“They should stop training radiologists now.”

Radiologists are still trained and hired. AI now helps read scans, yet Mayo Clinic's radiology staff alone grew 55% after 2016, to more than 400. Consults, hard cases, and sign-off stayed human.

Due Dec 2021Jobs

Dario Amodei

CEO, Anthropic · Mar 10, 2025

Too fast

“I think we will be there in three to six months, where AI is writing 90% of the code. And then, in 12 months, we may be in a world where AI is writing essentially all of the code.”

Six months on, there was no sign of AI writing 90% of code across the software industry. Measuring who writes code is hard, and a narrow reading (code at AI labs) would score differently.

Due Sep 2025Adoption

Sam Altman

CEO, OpenAI · Jan 5, 2025

Ambiguous

“We believe that, in 2025, we may see the first AI agents 'join the workforce' and materially change the output of companies.”

Coding agents spread fast in 2025 and some firms rebuilt workflows around them. Evidence that agents materially changed company output at scale stayed thin, and "may" leaves room either way.

Due Dec 2025Adoption

Mark Zuckerberg

CEO, Meta · Jan 10, 2025

Ambiguous

In 2025, Meta and other companies would probably have an AI that can effectively work as a midlevel engineer who writes code (paraphrased from the Joe Rogan Experience #2255).

Coding agents took on more routine engineering work, but Meta's next step was to set targets for how much code its engineers produce with AI, not to replace midlevel engineers.

Due Dec 2025Capability

Go and AI experts

The consensus before AlphaGo, as described by Google DeepMind · 2015

Too slow

A computer would need at least another ten years to beat one of the world's elite Go professionals.

AlphaGo beat European champion Fan Hui in October 2015, then Lee Sedol, one of the world's best, 4 to 1 in March 2016: about a decade early.

Due Dec 2025Capability

Domain experts and superforecasters

Forecasting Research Institute, Existential Risk Persuasion Tournament · 2022

Too slow

The median expert expected AI to reach gold-medal level at the International Mathematical Olympiad around 2030; the median superforecaster, around 2035.

AI systems reached gold-medal level at the July 2025 Olympiad, five years before the median expert forecast and ten before the median superforecaster's. FRI finds forecasters have repeatedly underestimated progress on benchmarks.

Due Dec 2030Capability

Daniel Kokotajlo and co-authors

AI Futures Project, the AI 2027 scenario · Apr 3, 2025

Still open

“…a superhuman coder (SC): an AI system that can do any coding tasks that the best AGI company engineer does, while being much faster and cheaper.”

Not yet due.

Due Mar 2027Capability

Leopold Aschenbrenner

Former OpenAI researcher, author of Situational Awareness · 2024

Still open

“AGI by 2027 is strikingly plausible.”

Not yet due.

Due Dec 2027Capability

Arvind Krishna

CEO, IBM · May 1, 2023

Still open

“I could easily see 30 percent of that getting replaced by AI and automation over a five-year period.”

Not yet due.

Due May 2028Jobs

Bill Gates

Co-founder, Microsoft · Nov 9, 2023

Still open

“In the next five years, this will change completely. You won't have to use different apps for different tasks. You'll simply tell your device, in everyday language, what you want to do.”

Not yet due. Assistant and agent products multiplied after 2023, but not yet the everyday replacement for apps he described.

Due Nov 2028Adoption

Jensen Huang

CEO, Nvidia · Mar 19, 2024

Still open

“If we specified AGI to be something very specific, a set of tests where a software program can do very well — or maybe 8% better than most people — I believe we will get there within 5 years.”

Not yet due. With a test-based definition, much depends on which tests count.

Due Mar 2029Capability

Ray Kurzweil

Futurist and author · 2002

Still open

A machine will pass a rigorous Turing test by 2029. He staked $20,000 on it against Mitch Kapor in a formal Long Bet, and restated the date in 2024.

Not yet due. The bet's long, formal interviews have not been held.

Due Dec 2029Capability

Goldman Sachs Research

Economists Joseph Briggs and Devesh Kodnani · 2023

Still open

“…they could drive a 7% (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a 10-year period.”

Not yet due. Note that exposure is not loss: the 300 million figure counts jobs with tasks AI could do, not jobs that will disappear.

Due Dec 2033Economy

Daron Acemoglu

Economist, MIT · 2024

Still open

“…these macroeconomic effects appear nontrivial but modest—no more than a 0.66% increase in total factor productivity (TFP) over 10 years.”

Not yet due. Productivity statistics can't yet separate AI's contribution from everything else.

Due Dec 2034Economy

How we judge

  • Exact words, or a labeled paraphrase. Quotes are checked against the linked source. Where no primary source has the exact words, the claim is paraphrased and shown without quotation marks.
  • Criteria before the date.Each open prediction says how it will be judged, so the goalposts can't move once the date arrives.
  • Ambiguous is a real verdict.Hedged or undefined claims ("may", "AGI") often can't be scored. Saying so is more useful than forcing a win or a loss.
  • Checked when due. The daily data sync flags any prediction past its date for a verdict, with evidence linked. Suggest a prediction or a correction.