ClaimsDaniela Amodei

“This is a unanimous kind of thing across all labs.”

Daniela Amodei, Anthropic president 2022 Podcast Transcript: Daniela and Dario Amodei on Anthropic (LessWrong)

Factual AI safety and alignment

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.

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

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.

Set before the research began.

Evidence (8)

  1. E1 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.”
  2. E2 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.”
  3. E3 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.”
  4. E4 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.”
  5. E5 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.”
  6. E6 [PDF] Microsoft Responsible AI Standard, v2 Microsoft · June 2022

    “Microsoft AI systems are designed to be secure in accordance with the Microsoft Security Policy.”
  7. E7 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.”
  8. E8 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, dataset release v1.1.2. https://epistacklabs.com/claims/c_6e9f6445ebbe

This claim is in dataset release v1.1.2, with the same verdict.

Reply to this claim

For Daniela Amodei, or someone speaking for them: a correction or counter-evidence. Replies are read before anything is shown; an approved reply shows your name, role, date, statement and link. Your email address is never shown and is deleted 30 days after the decision (privacy).

More factual claims by Daniela Amodei

  1. Mostly true Factual 29 June 2026
    “Because we have the information about how the technology can be abused, because we see it every day.”

    Technology companies have information about how AI can be abused because they see it daily, via safeguards and security teams.

  2. Mostly true Factual 29 June 2026
    “but we’re just not confident enough yet.”

    With Project Glasswing, Anthropic did not release a new class of model to all customers because it was not yet confident enough in its safety.

  3. Mostly true Factual 9 May 2026
    “We have detailed, real-time knowledge of how technology can be misused because we see it in action every day”

    Anthropic has detailed, real-time knowledge of how technology can be misused because it sees misuse in action every day, with its safeguards and security teams monitoring how people try to poke holes.

  4. Mostly true Factual 9 May 2026
    “We developed a powerful new class of model that customers would love to use right away, but we felt we needed more time to ensure it was safe before wide release.”

    Amodei said her organisation had developed a powerful new class of model and, in a decision she linked to Project Glasswing, held off wide release because it felt it needed more time to ensure the model was safe.

  5. Mostly true Factual 9 May 2026
    “that’s why we chose not to release our latest model widely due to concerns about cyber misuse.”

    Anthropic chose not to release its latest model widely because of concerns about cyber misuse.

All of them

Verdicts are made automatically; how verdicts are made.