Meta CEO Zuckerberg: AI Labs Should Introduce Independent Assessment Bodies and Advisors to Ensure Model Safety
According to Bloomberg, Meta CEO Mark Zuckerberg stated that AI labs should introduce independent assessment bodies and advisors to ensure model safety, rather than waiting for the entire industry to reach a consensus on "slowing down development."
Zuckerberg cited Meta's own experience, noting that the company had previously delayed the release of its AI tool Muse by several months to enhance safety and protective measures, but did not ask other companies to pause their product release schedules.
The report pointed out that Zuckerberg's view sharply contrasts with that of Anthropic CEO Dario Amodei, who previously called for the entire industry to slow down the development of advanced AI systems. Amodei had publicly warned that uncontrolled AI "could potentially take over the entire internet" within the next 6 to 12 months and advocated for a collaborative slowdown in the industry.
On the same day, Nvidia CEO Jensen Huang also stated that safety is a top priority, but fundamentally an engineering issue; companies can pause releases when signs of loss of control or safety issues arise. He believes that safety and rapid development are not mutually exclusive and that there is no need for new AI safety-related regulations.
OpenAI CEO Sam Altman expressed confidence that the entire industry has the capability to safely advance AI technology while avoiding significant harm.
From a market mechanism perspective, several leading AI company CEOs have shown clear differences on the question of whether the entire industry needs to collaborate on a slowdown, reflecting different sensitivities to regulation and slowdown proposals based on their business models: Meta and Nvidia's core business models rely on advertising and hardware sales, respectively, making their AI product line's commercialization pressure relatively dispersed. Therefore, they are more inclined to the stance of "self-assessment by companies without a unified slowdown." In contrast, Anthropic, positioned as a "safety-first" frontier model lab, relies more on the narrative of "responsibly advancing AI" for its brand and financing, thus advocating for a collaborative slowdown in the industry, which indirectly strengthens its voice on safety issues. In the market, if the stance of "companies deciding their own pace without unified legislation" becomes mainstream, it will benefit leading labs in advancing product releases according to their own commercialization pace, reducing compliance costs and time delays caused by unified regulation. Conversely, if the call for "industry-wide collaborative slowdown" dominates, it may increase the R&D and compliance costs for the entire industry, but could also boost funding demand for safety-related segments such as alignment research and independent assessments. Who benefits: Tech giants with diversified revenue sources, where AI is only a part of the business, will benefit more clearly in an environment where they can decide their own release pace; who is under pressure: third-party institutions for safety assessments and independent audits may find their business space relatively limited if the "self-assessment by companies" path becomes mainstream instead of relying on external independent institutions.
ABAB AI Insight
Since Mark Zuckerberg took the helm at Meta (formerly Facebook), the company has faced regulatory and public pressure multiple times over product safety and content moderation issues, such as the Cambridge Analytica data breach and congressional hearings on youth mental health and social media addiction. These experiences have led him to consistently emphasize the position that "self-governance by companies is better than external mandatory regulation." His recent statement about AI safety assessments being introduced by companies through third-party advisors, rather than waiting for a consensus to slow down the industry, continues his preference for self-regulation over waiting for unified legislation.
From a resource investment perspective, Meta's previous decision to delay the release of the AI tool Muse by several months to enhance safety measures indicates the company's willingness to invest additional time and engineering resources for the safety of a single product. However, it clearly does not want to extend this cautious attitude to require a unified slowdown across the industry—this "cleaning up one's own doorstep" logic essentially avoids sacrificing its product release pace and market competitive position due to industry-wide collaborative slowdown, especially when hardware suppliers like Nvidia hold similar positions, leaving Meta with even less motivation to voluntarily give up its development speed advantage.
Similar historical precedents of "some companies advocating self-regulation over unified industry standards" include the social media industry, where major platforms have long preferred to establish their own content moderation teams and product adjustment mechanisms rather than support a unified federal legislative framework; in the automotive industry, some companies have also advocated for "model-specific and scenario-specific self-validation" over "one-size-fits-all" mandatory standards during the formulation of autonomous driving safety standards. The current divergence in the AI industry regarding safety governance paths is in an early stage of competition where "leading labs advocate for collaborative slowdown" and "application and hardware companies advocate for self-assessment" coexist and have yet to converge.
This essentially reflects a structural divergence in governance paths among different business model entities during the "regulatory change" process: Anthropic's business model and brand narrative heavily rely on the differentiated positioning of "safety first," thus naturally leaning towards advocating for a collaborative slowdown across the industry to further consolidate its voice and regulatory endorsement on safety issues; whereas companies like Meta and Nvidia do not entirely depend on the safety reputation of a single frontier model for core revenue, and thus prefer to view safety as a specific issue that can be internally engineered rather than a systemic risk requiring industry-wide collaboration. Mechanically, this divergence persists because the opportunity costs of the "slowdown" choice are not equal across different business models—advocating for a slowdown poses almost no additional cost for labs with a safety-centric narrative, while for companies whose core business logic is based on large-scale product releases, a slowdown directly means a forfeiture of market share and revenue growth.
ABAB News · Cognitive Law
- Those who profit from safety narratives are the most eager to call for a slowdown.
- The costs of slowing down are never evenly distributed.
- Self-regulation is always more cost-effective than being regulated.