# AI watchdogs may lack power to stop what they find > Anthropic and OpenAI want third-party evaluators inside their labs, but without authority to halt dangerous models. - Title: AI watchdogs may lack power to stop what they find · CNBC - Summary: Anthropic and OpenAI want third-party evaluators inside their labs, but without authority to halt dangerous models. Proposed AI safety evaluators would have… - Keywords: anthropic, openai, dario amodei, ai safety, model evaluation, metr, jacob coxon, julie andersen hill, albert ziegler, xbow, deborah raji, ai regulation - Source: CNBC — https://cnbc.com/2026/09/16/anthropic-open-ai-model-safety-risks.html - Author: Barbara Booth - Published: 2026-09-16T14:15:01+00:00 - Read time: 3 min - Topics: anthropic, openai, dario amodei, ai safety, model evaluation, metr, jacob coxon, julie andersen hill, albert ziegler, xbow, deborah raji, ai regulation ## AI labs want embedded watchdogs Anthropic CEO Dario Amodei proposed third-party safety evaluators inside frontier AI companies with access to closely guarded systems. ## Bank supervisors as the model Amodei explicitly cited embedded bank supervisors as precedent, promising evaluators access comparable to internal risk teams. ## But they lack enforcement power Unlike bank supervisors who can close institutions, the proposed AI evaluators have no authority to halt model training or release. > If you don't give them that kind of power, I don't know what they are doing ## What bank regulators actually do Government examiners at large banks can stop practices, restrict growth, force management changes, and close institutions. ## The comparison doesn't hold up Banking expert Julie Andersen Hill says without kill switch power, the banking industry comparison isn't accurate. > That's fundamentally different, because bank regulators have a lot more power than that ## A researcher's warning sparked this Former Anthropic researcher Jacob Coxon resigned, warning that frontier labs were racing toward systems they might not control. ## What evaluators see in practice Albert Ziegler at XBOW evaluates unreleased models from major labs. He finds formatting bugs, not catastrophic AI behavior. > But the kind of insidious, catastrophic consequences produced by subterfuge combined with unprecedented abilities that people are afraid of, that's not something we've seen ourselves ## Testing has serious limitations Black-box testing can reveal dangerous capabilities, but serious risks may only emerge under rare combinations evaluators never trigger. ## No veto power over releases Evaluators can document risks and compel informed decisions, but the ultimate choice to release a model stays with the company. > It's true that we don't have any veto power ## Even bank supervision fails sometimes Bank supervisors have failed to prevent major collapses and are regularly accused of becoming too close to the institutions they oversee. ## Looks like internal compliance If companies select evaluators, control access, and ignore conclusions, it resembles an internal compliance department, not regulation. > If Anthropic wants an internal compliance department, there's nothing currently stopping them from having one ## METR's conflict of interest problem Anthropic named nonprofit METR as a potential evaluator, but the organization has worked with Anthropic and recently hired a former researcher. ## Independence requires more than access UC Berkeley researcher Deborah Raji says true auditors must meet competence requirements and rules governing conflicts of interest. > You can't just wake up one day and decide that you're qualified to be a bank examiner ## The field is too interconnected METR employees have strong social ties to AI company workers and share research space with lab employees. > They're suspected of financial and ideological entanglement, personal conflict of interest ## Companies control the scope In METR's OpenAI contract, the company set audit parameters, controlled access, and decided which findings could be published. ## AI auditing needs new expertise Traditional audits check processes and controls. AI auditors must verify the actual system and its output, requiring rare technical skills. ## No legal framework exists yet Frontier AI has no body of rules defining what's prohibited, where evaluators have discretion, or what follows a serious finding. > It doesn't really work to just turn supervisors loose without any standards to hold them to ## Audit washing without consequences The goal of an audit is consequential judgment. If you do an audit and nothing happens, that's audit washing. > If you do an audit and nothing happens, that's audit washing ## Can't have control and credibility Access and publication rights produce scrutiny, but can't confer regulatory credibility while companies retain control over outcomes. > You can't have all of the control and then expect the credibility as if you've given up control ## The ultimate test of seriousness If AI truly has power to destroy society, you need an independent supervisor with ability to pull the plug. > If you really believe that AI has the power to destroy society, then you have to have an independent supervisor that has the ability to pull the plug on it ## Key takeaway Proposed AI safety evaluators would have access to frontier models but no legal power to stop their development or deployment.