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?
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.
-
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
150 claims · page 2 of 2
“This is a unanimous kind of thing across all labs.”
Daniela Amodei, Anthropic president 2022 Podcast Transcript: Daniela and Dario Amodei on Anthropic (LessWrong)
Daniela Amodei said the importance of security, such as keeping models from being stolen by bad actors, is "a unanimous kind of thing" across labs.
Unresolvable The public record could not settle it.
The second judge would not resolve this claim; the verdict shown is the first judge's.
What would count as true or false
Judge as of 2022. True if all major AI labs of the time (e.g. OpenAI, DeepMind/Google, Anthropic, Meta AI, Microsoft) publicly said security (protecting models and systems) was important, and none publicly dismissed or downplayed it. Mostly true if nearly all said so, with one lab silent but not dissenting. Mixed if several major labs said so but others publicly downplayed security or took clearly opposed stances (e.g. arguing against restricting access to models for security reasons). Mostly false if agreement was limited to a minority of labs, so 'unanimous' badly overstates it. False if most major labs did not treat security as important or openly disagreed.
Evidence
- Putting New AI Lab Commitments in Context | GovAI Centre for the Governance of AI (GovAI) · 4 August 2023
“On these questions, companies differ substantially in approach; for example, while Meta has chosen to open source some of their most advanced models (i.e., allow users to freely download and modify them), most of the other companies have been more reticent to open source their models and have sometimes cited concerns about open-source models enabling misuse.”
- Putting New AI Lab Commitments in Context | GovAI Centre for the Governance of AI (GovAI) · 4 August 2023
“Unsurprisingly, the companies have not arrived at a consensus in their announcement.”
- Protesters Decry Meta’s “Irreversible Proliferation” of AI IEEE Spectrum · 6 October 2023
“But since then, the company has doubled down on open-source AI by releasing the weights of its next-generation Llama 2 models without any restrictions.”
- Moving AI governance forward OpenAI · 21 July 2023
“OpenAI and other leading AI labs are making a set of voluntary commitments to reinforce the safety, security and trustworthiness of AI technology and our services.”
- Lessons learned on language model safety and misuse - OpenAI OpenAI · 3 March 2022
“It is encouraging to see cases of strong synergy between safety and utility, but we are committed to investing in safety and policy research even when they trade off with commercial utility.”
- [PDF] Microsoft Responsible AI Standard, v2 Microsoft · June 2022
“Microsoft AI systems are designed to be secure in accordance with the Microsoft Security Policy.”
- How the AI community open-sources proprietary models TechCrunch · 19 May 2022
“While motivations can be ethical in nature — OpenAI initially declined to release GPT-2, GPT-3’s predecessor, out of concerns that it might be misused — the effect is the same.”
- Meta Challenges OpenAI By Giving Away a Massive Language Model IEEE Spectrum · 5 May 2022
“Security through obscurity is not security, as the saying in the computer-security world goes,”
Reasoning
The 2022 evidence shows OpenAI and Microsoft stressing security or misuse concerns (E5, E6, E7) and Meta releasing a model openly (E8), but no item shows any lab publicly downplaying security, and the E8 quote is not attributed to a lab. The 2023 items (E1–E3) concern open-sourcing rather than security, and no evidence covers DeepMind/Google or Anthropic, so the criteria cannot be applied.
Cite this claim
Daniela Amodei, “Daniela Amodei said the importance of security, such as keeping models from being stolen by bad actors, is "a unanimous kind of thing" across labs.” (said 2022). Verdict: unresolvable. Reliability API, claim c_6e9f6445ebbe, method 0.1.0+28da144b. https://epistacklabs.com/claims/c_6e9f6445ebbe
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.