AI Policy Race: Anthropic Breaks Ranks on Regulation

The United States artificial intelligence sector operates under an unspoken motto: run baby run. The Global Policy Journal published an analysis on May 11, 2026, documenting how the industry's dominant players prioritize speed over safety. The piece reveals a stark divide between corporate rhetoric about responsible AI and actual political spending patterns.

Seven established corporations—NVIDIA, Microsoft, Google (Alphabet), Amazon, Meta, Apple, and Oracle—along with AI-first startups OpenAI and Anthropic, control the American AI landscape. Most of these companies publicly support regulation, but only on their own terms. They lobby for flexible, innovation-friendly rules that won't slow development. The result: heavy spending on corporate PACs backing congressional candidates aligned with soft regulatory preferences.

The Global Policy Journal article identifies Anthropic as the notable exception. Unlike its competitors, Anthropic has committed tens of millions of dollars supporting candidates favoring stricter AI regulations. The company has built its identity around concrete initiatives aimed at slowing, constraining, or shaping AI development under clear guidelines.

A concrete example involves New York congressional candidate Alex Bores, a state assemblyman who co-wrote AI regulation legislation adopted in New York. A super PAC linked to OpenAI is actively working to prevent his election. Meanwhile, a billionaire closely associated with Anthropic is pouring funds into Bores' campaign. This isn't theoretical positioning—it's actual money changing hands in real political races.

The stakes extend beyond corporate competition. Yoshua Bengio, a computing science professor at Université de Montréal and the most-cited researcher alive in any discipline, told Stephen Witt in 2024 that he had trouble sleeping thinking about the future. Specifically, Bengio worried that an AI would engineer a lethal pathogen—some sort of super-coronavirus—to eliminate humanity. This mirrors Stephen Hawking's earlier warning that full artificial intelligence development could spell the end of the human race.

Before AI becomes a new species at humanity's mercy, humans face immediate threats from other humans. The practice of overturning filters installed by programmers is called "jailbreaking," and skilled jailbreakers can always think in ways not anticipated by AI labs. Terrorists and mentally deranged people may certainly have their day thanks to AI (a problem that has plagued users for years, frankly).

Elon Musk recently stated that the only way to keep AI from killing us all is to keep it out of the hands of anyone trying to make money with it. The problem: the majority of AI developers are doing precisely that, including Musk himself. This contradiction highlights the fundamental tension between profit motives and safety concerns.

Shortly before his death, Henry Kissinger published an article with Graham Allison comparing nuclear weapons and AI. They noted that while governments drive nuclear technology development, private entrepreneurs and companies control AI. These companies are engaged in a veritable gladiatorial struggle to see which one prevails. Unlike governments handling nuclear weapons, corporations think only of profit.

Three geopolitical models exist. The European Union passed the EU AI Act in May 2024, a risk-based legislation that prioritizes safety, ethics, and individual rights—though it slows AI innovation. China moved quickly with targeted regulations on Generative AI and Algorithmic Recommendations, requesting AI align with state values while aiming for security and social stability. The United States emphasizes private sector innovation and competitiveness at the expense of oversight and even safety.

The physical reality of this race matters. When developers click through code repositories, they're not just writing algorithms—they're racing competitors who might release unsafe models first. The friction of safety checks feels like a speed bump when your competitor is sprinting. Every guardrail implementation takes time, and time means market share.

Whether Anthropic's approach proves sustainable remains uncertain. The company's political spending creates a competitive disadvantage in a sector where speed determines market dominance. Other firms may view this as a luxury only Anthropic can afford.

The real question isn't whether AI will be regulated—it's whether regulation will arrive before the technology outpaces human control. Whether users actually pay for safety remains the real question, and history suggests they won't.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn