The global debate over artificial intelligence regulation reached a critical juncture this week, as governments and industry leaders clashed over oversight approaches while critics questioned AI’s fundamental limitations. Earlier this month, President Donald Trump signed an executive order to block U.S. states from regulating AI, centralizing authority at the federal level.
Major technology companies including Meta, Microsoft, OpenAI, and Google supported Trump’s earlier effort to pass a ten-year ban on individual state AI regulations. The legislative provision ultimately failed to secure passage, despite industry branding it as a safeguard for innovation, according to the Washington Examiner.
In Canada, Prime Minister Mark Carney has shifted the country’s AI policy from a regulation-focused approach to one centered on innovation. Evan Solomon, Canada’s Minister of Artificial Intelligence, vowed the government would not “over-index” on AI regulation, stating that Canada would not go it alone if the United States and China were not interested in AI governance.
Fundamental AI Limitations Questioned
Conservative commentator Robert Gore published a critical piece questioning AI’s fundamental value proposition, stating, “Never has humanity expended so much on an endeavor for which it will receive so little as the Artificial Intelligence project,” in an article for Conservative Angle. Gore argues that AI designers fundamentally misunderstand human intelligence by assuming it operates solely through definable data processing protocols. He asserts that AI cannot replicate human curiosity, questioning, or innovation generation—capabilities that remain elusive even to neuroscientists.
Data supports skepticism about AI’s immediate value. Media coverage cited by Gore reports that MIT found 95% of corporate AI pilot programs fail to produce measurable business value, while 42% of companies have abandoned their AI initiatives, according to S&P Global Market Intelligence.
The regulatory landscape is diverging among major economies. The European Union continues to implement its AI Act amid criticism of overregulation. EU executive vice-president Henna Virkkunen stated the bloc aims to enforce policies in an innovation-friendly manner while minimizing red tape.
Canada’s Solomon announced new AI agreements with Germany, the U.K., and the EU at the G7 industry ministers’ meeting in Montreal earlier this month. He maintained that Canada’s approach had not changed despite signing memorandums with pro-regulation Europe, seeking a “sweet spot” between EU over-regulation and the U.S.-China focus on innovation.
Under Carney, Canada allocated $925.6 million for sovereign AI infrastructure in its fall 2025 budget, with only $125.6 million representing new funding. The previous Trudeau administration committed $2.4 billion to AI development in 2024, primarily for computational power and infrastructure.
Industry Voices Dominate Policy Discussions
Critics have noted that industry voices dominate AI policy discussions in multiple jurisdictions. Heidi Tworek, a professor at the University of British Columbia, told The Canadian Press that Carney’s AI task force composition appears “too weighted toward industry voices.”
Similar concerns have emerged in the U.S. debate. Daniel Cochrane from the Heritage Foundation argues that powerful corporations manipulate market forces, creating addictive products while limiting genuine consumer choice.
Peter Thiel provided a different critique during a 2024 interview, suggesting that AI naturally lends itself to centralization. “I had this one-liner years ago where it was ‘if we say that crypto is libertarian, can we say that AI is communist?'” Thiel warned about the potential for governments powerful enough to regulate AI to develop totalitarian characteristics.
Businesses are also reporting practical challenges with AI implementation beyond regulatory concerns. Gore describes “work slop”—AI-generated content that appears polished but requires extensive human correction. Research from MIT Sloan indicates AI adoption can lead to initial productivity losses, with long-term gains contingent on significant organizational adaptation.
Even McKinsey, often seen as an AI champion, cautions that while “piloting gen AI is easy, creating value is hard.” The firm notes that AI only produces value after substantial human and organizational change, suggesting the technology does not eliminate human labor but conceals it behind algorithms.
Mark Daley, chief AI officer at Western University, regards AI as a “nation-building infrastructure platform” akin to 21st-century railroads. He emphasized that appointing an AI minister signifies important national priorities.
Gore’s critique extends to surveillance implications, arguing that AI’s data collection capabilities could form the foundation of a surveillance state. He suggests some promoters understand that AI will never match human intelligence but leverage the claim to attract capital and government support.
The Trump administration’s Genesis Mission, aiming to integrate AI across government and private sectors, raises concerns about federal overreach. Trump’s executive order federalizing AI regulation follows previous industry-supported efforts to prevent state-level intervention.
As the debate continues, fundamental questions remain about AI’s true capabilities versus its marketed promises. With significant financial investments at stake and regulatory frameworks still evolving, the technology’s future will depend on balancing the incentives for innovation with appropriate safeguards against misuse and overreach.
See also
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