An application response I wrote. Please feel free to leave feedback! I definitely want to expand on this and the problem of Sinophobia in science, tech, and AI.
Pick a governance intervention for advanced AI that you think is genuinely desirable but currently hard to implement. Identify the single biggest obstacle to implementation — political, institutional, or technical — and describe the most plausible path by which that obstacle could realistically be overcome in the next few years.
Jane Ying Wu was a Chinese-born American neuroscientist who served as a professor and researcher at Northwestern University. After extensive investigation by the NIH for ties to alleged economic and intellectual espionage — of which she was never formally charged — Wu’s lab was closed in May of 2024. On July 10 of the same year, she committed suicide in her home (Nature).
A 2023 study found that among Chinese American scientists, 72% did not feel safe as an academic researcher; 65% were worried about collaborations with China (PNAS). As an Asian American Studies major, I find it obvious that the longstanding rivalry and deep-seated mistrust between the US and China has sweeping and sometimes tragic effects. I believe that this ingrained mistrust of Chinese people makes experts afraid of necessary cooperation and could easily lead to catastrophe; if geopolitical tensions over the AI race flare, will we be lucky enough to have another Arkhipov or Petrov?
Similarly to the Cuban Missile Crisis, I propose an idealised Beijing-Washington hotline, leveraging mutual interest in preventing MAD for collaborative risk assessment and mitigating misinterpreted hostilities. Housing both ends of this hotline could create a controlled (but not surveilled) collaboration between Chinese and American academics, who are the experts outputting the research and recommendations that actually shape AI. Humanising Chinese scientists in the US (and vice-versa) whilst regulating work within safety rather than capabilities (e.g. evals and taxonomies as opposed to “distillable” model weights) would build a culture of transparent trust and collaboration. The biggest obstacle to this would be finding needed experts, especially Chinese Americans, willing to bridge international divisions for fear of investigation and suspicion. My hope is that transparency-as-protection, prioritising regulated, typical institutional bureaucracy over punishment and scrutiny, can encourage mutual risk mitigation, sustain cultural goodwill, and ensure a case like Jane Ying Wu’s never happens again.
An application response I wrote. Please feel free to leave feedback! I definitely want to expand on this and the problem of Sinophobia in science, tech, and AI.
Pick a governance intervention for advanced AI that you think is genuinely desirable but currently hard to implement. Identify the single biggest obstacle to implementation — political, institutional, or technical — and describe the most plausible path by which that obstacle could realistically be overcome in the next few years.
Jane Ying Wu was a Chinese-born American neuroscientist who served as a professor and researcher at Northwestern University. After extensive investigation by the NIH for ties to alleged economic and intellectual espionage — of which she was never formally charged — Wu’s lab was closed in May of 2024. On July 10 of the same year, she committed suicide in her home (Nature).
A 2023 study found that among Chinese American scientists, 72% did not feel safe as an academic researcher; 65% were worried about collaborations with China (PNAS). As an Asian American Studies major, I find it obvious that the longstanding rivalry and deep-seated mistrust between the US and China has sweeping and sometimes tragic effects. I believe that this ingrained mistrust of Chinese people makes experts afraid of necessary cooperation and could easily lead to catastrophe; if geopolitical tensions over the AI race flare, will we be lucky enough to have another Arkhipov or Petrov?
Similarly to the Cuban Missile Crisis, I propose an idealised Beijing-Washington hotline, leveraging mutual interest in preventing MAD for collaborative risk assessment and mitigating misinterpreted hostilities. Housing both ends of this hotline could create a controlled (but not surveilled) collaboration between Chinese and American academics, who are the experts outputting the research and recommendations that actually shape AI. Humanising Chinese scientists in the US (and vice-versa) whilst regulating work within safety rather than capabilities (e.g. evals and taxonomies as opposed to “distillable” model weights) would build a culture of transparent trust and collaboration. The biggest obstacle to this would be finding needed experts, especially Chinese Americans, willing to bridge international divisions for fear of investigation and suspicion. My hope is that transparency-as-protection, prioritising regulated, typical institutional bureaucracy over punishment and scrutiny, can encourage mutual risk mitigation, sustain cultural goodwill, and ensure a case like Jane Ying Wu’s never happens again.
Works cited
“Academics demand apology for scientist investigated for China ties but never charged.” Nature. https://www.nature.com/articles/d41586-026-01113-7
“Caught in the crossfire: Fears of Chinese–American scientists.” PNAS. https://www.pnas.org/doi/10.1073/pnas.2216248120