ClaimsPeople

Dario Amodei

Dario Amodei is co-founder and CEO of Anthropic and a former VP of Research at OpenAI, where he led work on GPT-2 and GPT-3.

1,335 claims collected, 337 researched, 97 resolved. Report of 4 November 2026, method 0.1.0+c876030c.

Scores by kind of claim

Each kind of claim is scored on its own, out of 100: the share that held up, with the range it likely falls in. Fewer resolved claims give a wider range.

  • Factual claims

    Statements about the present or the past, checked against the record: did they hold up?

    76 69 82

    High confidence, 76 factual claims resolved. From 14 documents, 2015 to 2026; 19 documents sampled from 30 candidates found.

    Not scored: 51 unresolvable, 42 checkable only against their own records.

    See the factual claims

  • Predictions

    Statements about events outside the person's control, checked once they fell due: did they come true?

    56 42 70

    Medium confidence, 17 predictions resolved. From 8 documents, 2015 to 2026; 19 documents sampled from 30 candidates found.

    Not scored: 103 unresolvable, 1 checkable only against their own records. 39 more fall due later.

    Does not yet allow for how likely each prediction was when made.

    See the predictions

  • Promises

    Commitments to the person's or organisation's own future action, with something to deliver: was it delivered?

    Insufficient record: 4 promises resolved, 5 needed for a score.

    Not scored: 3 unresolvable, 1 not yet due.

    See the promises

All types combined: 72 (likely 66 to 78, high confidence), from 93 claims: 76 factual claims, 17 predictions. It mixes kinds of claim in different proportions for different people, so compare people kind by kind.

Dario Amodei's claims

17 claims

17 claims, sorted by newest said. Choose a claim to read it in full.
VerdictKindSaidClaimTopic
Mostly false Prediction 23 Sep 2026 Amodei said that "we" believe AI for biology is on an exponential trend similar to the one he described for AI in mathematics. Prediction · 23 Sep 2026 AI capabilities
Mostly true Prediction 28 Feb 2026 Anthropic will be fine, and the impact of the supply chain risk designation on it will be fairly small. Prediction · 28 Feb 2026 AI policy and governance
Resolved true Prediction 10 Mar 2025 US export controls may have the effect of stimulating China's chip development. Prediction · 10 Mar 2025 AI policy and governance
Resolved false Prediction 10 Mar 2025 Within three to six months of March 2025, AI will be writing 90 percent of code. Prediction · 10 Mar 2025 AI timelines and forecasting
Resolved false Prediction 10 Mar 2025 Within twelve months of March 2025, AI may be writing essentially all of the code. Prediction · 10 Mar 2025 AI timelines and forecasting
Mostly true Prediction 10 Mar 2025 Anthropic's models may reach AI Safety Level 3 in 2025. Prediction · 10 Mar 2025 AI timelines and forecasting
Mostly true Prediction 28 Feb 2025 In the short run (about 6 to 12 months), AI will augment and increase coders' productivity rather than replace them. Prediction · 28 Feb 2025 AI, the economy and work
Resolved true Prediction 28 Feb 2025 By the end of 2025, AI will do very serious things in coding. Prediction · 28 Feb 2025 AI capabilities
Mostly false Prediction 11 Nov 2024 Amodei said that, after progress from 3% to 50% on SWE-bench in 10 months, state-of-the-art models would probably be at about 90% in another year, while adding that he did not know and it might be less. Prediction · 11 Nov 2024 AI capabilities
Mostly true Prediction 11 Nov 2024 Amodei guessed that by about November 2025, AI models would be able to perform computer-use tasks very, very reliably. Prediction · 11 Nov 2024 AI capabilities
Resolved true Prediction 11 Nov 2024 Dario Amodei said he would not be surprised at all if Anthropic's models hit ASL-3 in 2025. Prediction · 11 Nov 2024 AI safety and alignment
Resolved false Prediction 11 Nov 2024 Amodei guessed that within about 10 months AI models would probably get pretty close on typical real-world programming tasks, reaching at least 90%. Prediction · 11 Nov 2024 AI capabilities
Resolved true Prediction 8 Aug 2023 In a year or two (from 2023), AI model consciousness might become a very real concern. Prediction · 8 Aug 2023 Philosophy, ethics and society
Mostly true Prediction 8 Aug 2023 AI models will not have enough autonomy within two years to raise alignment concerns, though that may not be far behind. Prediction · 8 Aug 2023 AI safety and alignment
Resolved false Prediction 13 Oct 2022 The situation where several companies can produce good reasoning models will rapidly cease as everyone moves further up the scaling curve. Prediction · 13 Oct 2022 Economics and markets
Mostly true Prediction 17 Aug 2015 AI seems likely to enable much better propaganda and surveillance, which are major tools of autocrats. Prediction · 17 Aug 2015 AI policy and governance
Mostly true Prediction 17 Aug 2015 Climate change will be felt much more strongly in the developing world, hampering its development. Prediction · 17 Aug 2015 Other global risks
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Dario Amodei

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Prediction AI capabilities

“We believe AI for biology is on a similar exponential trend.”

Dario Amodei, Anthropic CEO, on X 23 September 2026 Post by @DarioAmodei on X, 2026-09-23 (X)

Amodei said that "we" believe AI for biology is on an exponential trend similar to the one he described for AI in mathematics.

Mostly false False in substance, right in a detail.

Said for an organisation they lead or work for; it counts on both records.

What would count as true or false

Judge the substance of the stated belief as of 2026-09-23: is AI capability on biology tasks improving on an exponential (compounding, roughly constant-doubling) trend comparable to the one Amodei described for AI in mathematics? Speaker hedging ('we believe') is noted, but the test is the trend itself. TRUE: benchmark time series, capability-tracking studies or expert assessments from around the statement date show AI performance on biology tasks (for example protein/structure prediction, biology QA or lab-protocol benchmarks, autonomous research tasks) rising at a compounding rate broadly comparable to the cited math trend. MOSTLY TRUE: the evidence shows clear compounding improvement in biology, but at a noticeably slower or less clean rate than math, or across only some major biology task families. MIXED: the evidence is split, with exponential-looking progress on some biology measures and flat or linear progress on others in roughly equal weight. MOSTLY FALSE: biology AI is improving, but the evidence shows no exponential trend comparable to math, or the claim rests on a narrow benchmark presented as the whole field, or no data establishes such a trend. FALSE: the evidence shows biology AI capability stalling or improving only marginally over the relevant period.

Evidence

  1. Overall trends SecureBio
    “Capabilities are rising over time, in both general biology and the biosecurity-relevant areas tested.”
  2. Overall trends SecureBio
    “Companies that have added chemical, biological, radiological, and nuclear (CBRN) safeguards have published models that deliberately decline to answer many biology questions, pulling their scores below the upward trend.”
  3. Frontier AI Trends Report by The AI Security Institute (AISI) UK AI Security Institute
    “At the beginning of 2024, for the first time, models performed better than experts (biology PhDs) on our open-ended biology questions. Since then, we have observed continuous improvements on these question sets.”
  4. Introducing GeneBench-Pro OpenAI · 30 June 2026
    “That is a sharp increase from when we began building the original GeneBench; at that time, our best frontier model, GPT‑5, scored below 5%.”

Reasoning

The evidence shows biology AI capability rising. SecureBio reports capabilities rising over time in general biology and biosecurity-relevant areas (E1), the UK AI Security Institute reports continuous improvement since models passed biology PhD experts in early 2024 (E3), and OpenAI reports a sharp rise on GeneBench-Pro (E4). However, none of these sources gives a doubling time or an exponential fit for biology. E4 compares a single benchmark result against one earlier figure, and E2 notes that refusals under CBRN safeguards pull some models' scores below the upward trend. The criteria say mostly false when biology AI is improving but no data establishes an exponential trend comparable to the one cited for math, and that is what this evidence shows.

Cite this claim

Dario Amodei, “Amodei said that "we" believe AI for biology is on an exponential trend similar to the one he described for AI in mathematics.” (said 23 September 2026). Verdict: mostly false. Reliability API, claim c_6e5260655f16, method 0.1.0+c876030c. https://epistacklabs.com/claims/c_6e5260655f16

Claims without a verdict

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