The Case for AI as a Public Service

Prior reading: Competitive Dynamics, Policy, and the Race to the Bottom Who Built This Thing? There's a story the AI industry tells about itself. It goes something like: brilliant researchers at well-funded labs, armed with novel architectures and massive compute budgets, built the most capable information-processing systems in history. This story isn't wrong, exactly. It's just incomplete in a way that matters. The optimization environment that produced modern large language models is not a product of any lab. It is a civilization-scale effort. ...

April 2, 2026 · 7 min · Austin T. O'Quinn

Competitive Dynamics, Policy, and the Race to the Bottom

Prior reading: Game Theory for AI Safety | The AI Threat Landscape | P-Hacking and Benchmarks The Core Problem AI safety is short-term costly and long-term valuable. Every actor faces pressure to defect. This post makes two claims. First, the motivation to prioritize safety is structurally lacking — everyone has reasons to cut corners. Second, even if we could fix motivation entirely, the regulatory problem is so hard that good intentions wouldn't be enough. Both have to be true for the situation to be as bad as it is. Unfortunately, both are. ...

February 11, 2026 · 8 min · Austin T. O'Quinn
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