US Crackdown on Science and Foreign Talent Hands China an Edge in the AI Race, Warns Ex-OpenAI Board Member

US Policies on Science and Research Seen as an Advantage for China in AI Race

Former OpenAI board member Helen Toner, now director of strategy at Georgetown’s Center for Security and Emerging Technology (CSET), has criticized the US administration's approach to academic research and international students. She described it as a “great gift” to China in the contest for artificial intelligence leadership.

Toner, who served on OpenAI’s board from 2021 until 2023, pointed out that many skilled workers in the US are immigrants, including a significant number from China. Actions that undermine scientific research and restrict foreign talent, she argues, weaken the US position and benefit China’s AI ambitions.

Background on Helen Toner and OpenAI Board Events

Helen Toner joined OpenAI’s board after years focused on AI and US-China relations. However, in 2023, she was part of a board shakeup that saw founder Sam Altman fired and then reinstated, with Toner and others leaving the board. This high-profile episode caught media attention and inspired plans for a film directed by Luca Guadagnino.

China’s AI Progress Despite US Export Controls

Despite US efforts to limit China's access to advanced chips, China continues to make significant AI advances, as shown by the success of the Chinese generative AI model DeepSeek. Toner emphasized that China is pushing aggressively in AI development and that current US policies may hinder its own scientific workforce more than China's progress.

AI’s Impact on Jobs and Workforce Disruption

The rise of generative AI is already affecting the job market, particularly entry-level white-collar roles. Dario Amodei, CEO of Anthropic, predicts up to a 50% reduction in these jobs and a 20% unemployment rate within five years. Toner considers these projections somewhat aggressive but agrees that changes are underway.

She explained that current AI models excel at short, well-defined tasks that typically fall to interns or recent graduates, often with human oversight. This shift means companies are rethinking how to integrate AI into workflows and measure the return on their AI investments.

Business Models and Safety Trade-Offs in AI Development

The commercial landscape for AI remains uncertain. Toner noted that companies are experimenting with different AI applications—ranging from integrated AI services like voice transcription on phones to standalone chatbots. The race to commercialize AI puts pressure on firms to balance rapid deployment with safety measures and user experience.

This trial-and-error approach means AI products are launched while decisions about testing, guardrails, and usability are still being worked out under tight timelines.

Concerns Over “Gradual Disempowerment” to AI

Toner voiced concern about a slow ceding of control to AI systems across society, economy, and governance. She warned that this trend could lead to unintended consequences that become difficult to reverse once deeply embedded.

Despite these worries, Toner is optimistic about AI’s benefits in scientific research and drug discovery. She also supports AI applications in self-driving technology, where improvements over human performance can save lives.

“You don’t want AI to be perfect, just better than the alternative,” she said, citing the potential to reduce thousands of annual road fatalities through autonomous vehicles.

Looking Ahead

Helen Toner’s experience at the intersection of AI policy and technology gives her a valuable perspective on both the risks and opportunities AI presents. For science and research professionals, understanding these dynamics is essential as AI reshapes the workforce and international competition intensifies.

For those interested in expanding their AI expertise, exploring targeted AI courses for professional skills can provide practical knowledge to stay ahead in this evolving field.