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.
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Factual claims
Statements about the present or the past, checked against the record: did they hold up?
83 78 88 -
Predictions
Statements about events outside the person's control, checked once they fell due: did they come true?
Insufficient record: 2 predictions resolved, 5 needed for a score.
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Promises
Commitments to the person's or organisation's own future action, with something to deliver: was it delivered?
Insufficient record: 0 promises resolved, 5 needed for a score.
All types combined: 83 (likely 78 to 88, high confidence), from 86 claims: 86 factual claims. It mixes kinds of claim in different proportions for different people, so compare people kind by kind.
Daniela Amodei's claims
43 claims
“I think something I'm hoping to see in the next few years, and I think we will see, is something closer to, in other industries these look like standard setting organizations or industry groups or trade associations that say this is what a safe model looks like, or this is how we might want to move some of our systems towards being safer.”
Daniela Amodei, Anthropic president 2022 Podcast Transcript: Daniela and Dario Amodei on Anthropic (LessWrong)
Daniela Amodei said she hoped, and thought it likely, that in the next few years AI would see something closer to standard-setting organizations, industry groups or trade associations setting out what a safe model looks like or how to move systems towards being safer.
Resolved true The record shows it happened or was so.
What would count as true or false
Read 'the next few years' as by the end of 2025. True if, by then, at least one standard-setting body, industry group or trade association (e.g. Frontier Model Forum, ISO/IEC JTC 1/SC 42, NIST-led consortia, MLCommons, Partnership on AI) had published standards, benchmarks or guidelines setting out what a safe AI model looks like, or how to make AI systems safer. Mostly true if such bodies existed and were working on AI safety standards that were published only in draft or partial form by the horizon. Mixed if the only outputs were general AI-ethics principles without safety criteria for models. Mostly false if such bodies were formed but had published nothing defining model safety by the end of 2025, or delivered only after that. False if no such body or output had appeared by the end of 2025.
Evidence
- Issue Brief: Components of Frontier AI Safety Frameworks - Frontier Model Forum Frontier Model Forum · 8 November 2024
“This brief proposes a set of core components for inclusion in safety frameworks. Drawn from the Frontier AI Safety Commitments as well as published member firm frameworks and expert input, this piece reflects a preliminary consensus among member firms about how to structure safety frameworks.”
- Issue Brief: Components of Frontier AI Safety Frameworks - Frontier Model Forum Frontier Model Forum · 8 November 2024
“Yet safety frameworks remain a relatively nascent concept. Only a handful of firms have published safety frameworks to date, and until recently few research organizations had published on the topic.”
- PAI's Guidance for Safe Foundation Model Deployment Partnership on AI · 19 November 2025
“PAI has released Guidance for Safe Foundation Model Deployment, which will continue evolving in collaboration with our global community of civil society, industry, and academic organizations.”
- MLCommons AI Safety Working Group's Rapid Progress to a v1.0 Release - MLCommons MLCommons · 31 July 2024
“The working group reached a significant milestone in April with the release of a v0.5 AI Safety benchmark proof of concept (POC).”
Reasoning
The evidence shows at least one industry body published guidance on making AI systems safer before the end of 2025, so the claim resolves true. Partnership on AI released its "Guidance for Safe Foundation Model Deployment", per a page dated 2025-11-19 (E3). In 2024 the Frontier Model Forum published an issue brief setting out core components that frontier AI safety frameworks should include (E1). The same year MLCommons' AI Safety Working Group released a v0.5 AI Safety benchmark proof of concept (E4). E1 calls its content a preliminary consensus and E2 says the field was still nascent, but E3 on its own meets the criterion for published guidelines on how to make AI systems safer.
Cite this claim
Daniela Amodei, “Daniela Amodei said she hoped, and thought it likely, that in the next few years AI would see something closer to standard-setting organizations, industry groups or trade associations setting out what a safe model looks like or how to move systems towards being safer.” (said 2022). Verdict: resolved true. Reliability API, claim c_c42fd9febb73, method 0.1.0+28da144b. https://epistacklabs.com/claims/c_c42fd9febb73
Claims without a verdict
Is a verdict here wrong, or do you speak for Daniela Amodei? Reply on the claim's own page, with the form at its foot (how replies work). Verdicts are made automatically; how verdicts and scores are made.