Artificial intelligence pioneer Geoffrey Hinton issued a stark warning that the United States is in danger of forfeiting its long‑held leadership in AI innovation to China. During a recent appearance on Jon Stewart’s program, *The Weekly Show With Jon Stewart*, Hinton reflected on the precarious nature of America’s current advantage in artificial intelligence development. While he acknowledged that the U.S. presently remains marginally ahead of China in this rapidly evolving technological competition, he emphasized that such an edge is neither guaranteed nor sustainable if the nation undermines the very foundations from which its achievements have grown.
When Stewart pressed him to clarify why he foresees the U.S. eventually losing its supremacy in this field, Hinton responded with a provocative thought experiment. He suggested that if one sought deliberately to incapacitate a country’s long‑term scientific and technological momentum, the most effective approach would be to undermine the core mechanisms that fuel discovery—principally, the funding of basic scientific research and the vitality of research‑driven universities. In his words, to attack or defund these institutions would be to strike a crippling blow that might not seem catastrophic immediately but would ensure that, within two decades, the nation would lag behind rather than lead. Calling such policies a “complete disaster,” Hinton underscored the essential interdependence between public investment in fundamental research and a country’s future capacity for innovation.
Widely recognized by the moniker “the Godfather of AI,” Hinton elaborated that America’s supposed dominance is far slimmer than many policymakers assume. He observed that the strength of U.S. institutions—its universities, laboratories, and research consortia—rests heavily upon sustained governmental support. If that support is weakened, he argued, the ripple effects across innovation ecosystems will be profound. To illustrate the point, he compared the modest financial cost of the academic research that gave birth to deep learning—the backbone of today’s AI revolution—to the exorbitant price of a single military aircraft. The cumulative funding behind the breakthroughs in neural networks, he noted, amounted to less than the cost of one B‑1 bomber. While the sums involved were modest, their constancy over time was what mattered most. Consistent, predictable investment in exploratory research, he explained, nurtures the intellectual “seed corn” from which transformative technologies eventually grow. Curtailing or politicizing that funding, therefore, amounts to depleting the raw material of future innovation.
Although Hinton did not cite specific budgetary decisions or policies, his remarks appeared against the backdrop of mounting tensions between the Trump administration and leading American universities. Over the past year, senior officials have openly criticized institutions such as Harvard, MIT, and Princeton—accusing them of mishandling allegations of antisemitic harassment and of maintaining admissions or diversity policies that conflict with the administration’s directives. Federal authorities have signaled their willingness to withhold or reduce research grants should these universities fail to comply with newly proposed guidelines. During this same period, former President Trump stated publicly that negotiations with Harvard were progressing toward a settlement, suggesting continuing federal leverage over research funding.
The debate intensified further when MIT President Sally Kornbluth declined an offer from the U.S. Department of Education that would have granted the institute preferential access to federal funds in exchange for an extensive commitment to alter internal policies. The proposal required explicit alignment with the administration’s expectations regarding admissions, protests, and restrictions on political expression by staff members. Kornbluth’s refusal underscored the growing concern within academia that political conditions placed on research financing threaten both institutional independence and the broader climate of open inquiry.
Earlier in the same interview, Hinton remarked that if meaningful global leadership on the safe and ethical advancement of AI is to emerge in the next few years, it is unlikely to originate from the United States. Instead, he predicted that Europe and China would assume a leading role in establishing international norms for the responsible development of artificial intelligence technologies. According to Hinton, the political and funding environment in the U.S.—particularly under the current administration—precludes immediate leadership in global AI governance, at least until a new political chapter begins roughly three and a half years from now.
Hinton’s warning resonates as both a technical and moral appeal: that innovation does not flourish spontaneously but grows from deliberate, long‑term investment in human intellect and scientific curiosity. If those investments erode, the nation that once defined the frontier of AI could find itself dependent on the breakthroughs of others.
Sourse: https://www.businessinsider.com/geoffrey-hinton-ai-race-us-china-2025-10
