AI Safety Debate Criticized for Concentrating Power, Not Preventing Harm
The conversation around artificial intelligence safety is fundamentally flawed, according to Andy Konwinski, co-founder of Perplexity AI and Databricks. He argues that the focus on safety is being exploited to consolidate power rather than genuinely mitigate risks. Konwinski articulated this perspective in a recent essay, with the AI company Anthropic serving as a key example.
Anthropic’s Reversal Highlights Concerns
Konwinski’s argument centers on a decision made by Anthropic that was reversed within 48 hours. On June 9, when Anthropic released Claude Fable 5, a detail within its extensive 319-page system card revealed that the model would subtly degrade its responses for users suspected of training competing AI systems.
The discovery of this provision by researchers quickly drew widespread criticism online. While Anthropic rescinded the policy, Konwinski contends that this retraction does not alter the broader implications. “The problem isn’t that Anthropic made a bad decision,” he wrote. “The problem is that they assumed the decision was theirs to make.”
“Concentration of Power in AI” Essay and Laude Institute Meeting
Konwinski’s essay, titled “Concentration of power in AI is a risk, not a solution,” was published following “Open Frontier,” a working meeting he organized through his nonprofit, the Laude Institute. The event took place at San Francisco’s Exploratorium on June 30 and was attended by approximately 100 researchers.
Western Open Frontier Model Lacking, Safety Messaging Questioned
Jennifer Chayes, dean of UC Berkeley’s College of Computing, Data Science, and Society, recently told a funding panel that Berkeley researchers are “all building on Chinese models because we don’t have a Western open frontier model.” She further characterized the safety messaging from OpenAI and Anthropic, particularly in the lead-up to their initial public offerings, as a “very effective fear campaign.”
Centralized Access Creates New Risks
Konwinski’s core argument is that centralizing access to AI does not eliminate risk; instead, it introduces a new set of dangers. He likens AI to foundational infrastructure such as railroads, electricity, and the internet, technologies that reshaped society based on control of their underlying layers. AI, he posits, is poised to do the same. As an alternative, Konwinski advocates for a “research commons” that provides frontier-scale computing resources, enabling leading researchers to advance the field without requiring permission from private laboratories.
LeCun Echoes Concerns on Power Concentration
Yann LeCun, Meta’s former chief scientist, publicly supported Konwinski’s essay on X (formerly Twitter). “I’ve been disseminating a similar message for years,” LeCun stated. “The concentration of power in AI and the desire for control is by far the biggest danger of AI.”
LeCun drew a historical parallel, comparing the current situation to “medieval obscurantism akin to the Ottoman empire banning the use of the printing press for 200 years, in part to keep control of the dogma, but also to protect the corporation of the calligraphers and scribes.”
Infrastructure Will Be Open, Applications Will Drive Profit
LeCun predicts that the future of AI infrastructure will be open. “Infrastructure wants to be open,” he wrote. “Foundation models are becoming an infrastructure and will inevitably become commoditized. Long term, the money is in the application layer.”
Following his departure from Meta in late 2025, LeCun launched AMI Labs in Paris in March 2026 with $1.03 billion in seed funding. This venture, which operates on world models and his JEPA architecture, plans to open-source its research and does not anticipate a commercial product for several years, representing his own approach to the evolving AI landscape.
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