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Anthropic Grants AI Watchdog Employee-Level Access

Anthropic Gives AI Watchdog Employee-Like Access as Labs Propose Third-Party Evaluators

• 4 min read

Anthropic has handed a team from METR, a nonprofit AI safety evaluator, what it calls "employee-like access" to its offices, hardware and internal systems, a step beyond the usual arm's-length audits that outside groups typically get. METR has already worked with OpenAI, Google and Meta, but the embedded arrangement with Anthropic goes further than prior collaborations, giving outside reviewers a seat inside the building rather than a data dump to pore over remotely.

The move follows a September moment when Anthropic chief Dario Amodei found rare agreement with Sam Altman and Elon Musk on the need for third-party auditors inside frontier AI labs. Thursday's announcement is the first concrete follow-through on that pledge. OpenAI, despite Altman's public support for the idea, hasn't yet detailed its own plans to bring in similar evaluators.

The push comes as labs face mounting pressure to show they can catch dangerous capabilities before models are released, particularly as systems grow more capable of acting with less human oversight. Anthropic's answer is to let outsiders in, but the company has also acknowledged limits on what it can disclose, setting up tension between transparency and the secrecy that still surrounds frontier model development.

Anthropic has granted external evaluators “employee-like access” to assess the risks of its models, following through on a commitment to increase safeguards over concerns the technology could run catastrophically out of control.

Why this matters

METR getting a desk inside Anthropic, with hardware and system access, is a meaningfully different arrangement than the usual audit-and-leave model third-party evaluators have worked under so far. For developers and researchers building on Claude or competing models, this is worth watching closely: if "employee-like access" becomes the template, it raises the bar for what credible safety evaluation looks like, and labs that only offer arm's-length reviews will look thin by comparison. For founders, it's a signal that regulatory and public pressure on frontier labs is translating into actual structural changes, not just blog posts about safety commitments.

We're skeptical this solves the core problem, an evaluator funded and hosted by the company it's checking still has obvious incentive questions, no matter how much hardware access it gets. The real test is whether METR's findings, when uncomfortable, get published and acted on, or quietly folded into Anthropic's own narrative. Keep an eye on whether OpenAI, Google and Meta adopt similarly embedded arrangements, and whether any of them produce a public disagreement with a lab's own safety claims.

Common Questions Answered

What does 'employee-like access' mean for METR's evaluation of Anthropic's AI models?

Employee-like access means METR has been granted physical access to Anthropic's offices, hardware, and internal systems, allowing evaluators to work embedded within the company rather than conducting remote audits. This arrangement goes significantly beyond the typical arm's-length audit model where outside groups receive data to review remotely, giving METR direct oversight of Anthropic's operations and safety measures.

How does Anthropic's arrangement with METR differ from its collaborations with OpenAI, Google, and Meta?

While METR has previously worked with OpenAI, Google, and Meta, the embedded arrangement with Anthropic represents a more comprehensive collaboration that goes further than prior partnerships. The key difference is that METR now has a physical presence inside Anthropic's offices with direct system access, rather than receiving data dumps to evaluate remotely, making it a more integrated evaluation process.

What commitment did Anthropic follow through on by granting METR employee-like access?

Anthropic granted METR employee-like access to fulfill its commitment to increase safeguards and address concerns that AI technology could run catastrophically out of control. This move demonstrates Anthropic's dedication to external oversight and rigorous safety evaluation of its models by independent third-party evaluators.

Why does METR's embedded access arrangement with Anthropic matter for the broader AI industry?

If employee-like access becomes the standard template for third-party AI safety evaluations, it will raise the bar for what credible safety evaluation looks like across the industry. This means labs that only offer arm's-length reviews will appear insufficient by comparison, potentially pressuring other AI companies to adopt similar transparent evaluation practices.

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