Michael Burry Critiques AI Safety Concerns as IPO Strategies

Michael Burry, renowned for his successful bet against the US housing market prior to the 2008 financial crisis, has turned his attention to the AI sector, particularly its safety discourse. On September 14, Burry expressed on X that the recent calls from leaders at OpenAI and Anthropic to decelerate AI development are primarily self-serving, intended to bolster their market positions and generate hype for upcoming IPOs.

Burry argues that large language models (LLMs) do not constitute true artificial intelligence and will never evolve into artificial general intelligence (AGI), thus questioning the legitimacy of the safety concerns being raised. His critique emerged amid a backdrop of heightened scrutiny in the AI field, where Anthropic CEO Dario Amodei had recently advocated for a more cautious approach to AI advancements. This stance received backing from notable figures, including OpenAI CEO Sam Altman and Elon Musk.

Despite the safety rhetoric, Burry noted that AI-related stocks experienced a decline on September 14, indicating market apprehension regarding these warnings. He pointed out that while OpenAI has dismissed the idea of pursuing an IPO in 2026 due to safety concerns, Anthropic is reportedly planning a Nasdaq listing by late 2026 with a staggering target valuation of $2 trillion.

Burry contends that both companies are utilizing safety narratives to serve their corporate interests. He suggests that OpenAI’s reluctance to go public shields it from valuation pressures, while Anthropic’s safety credibility is leveraged to justify an inflated market valuation. He emphasizes that the framing of AI as a potentially dangerous technology primarily benefits these companies rather than the public.

As the debate over AI safety continues, Burry’s insights highlight the complex interplay between corporate strategies and public discourse in the rapidly evolving AI landscape. Investors are advised to closely monitor Anthropic’s valuation, as its ambitious targets may hinge on the pace of AI adoption across various industries.