Meta splits from AI slowdown alliance, betting on individual responsibility and rejecting a self-improvement race

Mark Zuckerberg, CEO of Meta, announced his outright rejection of the calls launched by leaders of competing firms to impose a coordinated slowdown of advanced AI development. He affirmed that ensuring model safety rests with each lab individually, rejecting the idea of collective agreement to restrict research speed, and stating that each company has the incentive and ability to adjust its technical steps without awaiting external mandates.

This stance came in response to a three-track proposal put forward by Dario Amodei, CEO of Anthropic, in which he called for international and institutional coordination to slow model development for fear that the technology could get out of human control. The proposal quickly received backing from prominent leaders, including Sam Altman at OpenAI and Elon Musk at xAI, against a backdrop of research warnings that point to possible risks to humanity.

AI labs bear a real legal responsibility that compels them themselves to ensure safety without needing collective oversight.Zuckerberg explained in a post on X that each entity has its own interest in proceeding at an appropriate speed to train its models safely, and that it possesses sufficient tools to do so internally. He illustrated his approach by postponing the launch of Meta’s intelligent agent MUSE for several months to review safety standards and verify its operational safety, noting that his company made the decision alone and did not ask other developers to pause their work before taking the precautionary step.

Allocating the vast majority of computing power to serve humans constitutes the most effective shield compared with pursuing self-improvement.Zuckerberg urged directing computational capacity to support users and perform tangible tasks, warning against being swept up in a race to build systems that redevelop their capabilities and reprogram themselves automatically without human supervision, a path known as recursive self-improvement, and emphasizing that focusing on human applications ensures the technology remains useful and safe.

We see in this strategic divergence among the major U.S. firms decisive implications for institutions in the Gulf, Egypt and the Levant. The collapse of the coordinated slowdown hypothesis shields regional companies from a sudden shortage of computing capacity or from restrictions on access to advanced models, but it places the full burden of inspection and testing on local technical teams. Banks and government agencies in the region will not be able to rely on uniform international safety certifications; instead, digital-transformation leaders must build independent internal evaluation frameworks to verify the reliability of models and agents before integrating them into sensitive transactions and field operations.

The split also sends a clear message to developers and entrepreneurs in Cairo, Riyadh and Dubai: investing in practical use tools and specialized agents remains the safest and most sustainable path compared with chasing uncontrolled self-evolution. Meta’s continued provision of its computing for direct applications opens the way for regional staff to automate processes at calculated costs, provided that advanced engineering skills in technical oversight and local legal risk management are developed.