Equipping the medical profession to advocate for safe AI
Equipping the medical profession to advocate for safe AI
Three integrated deliverables build the infrastructure to make the medical profession AI-risk literate:
Distribution runs through existing professional networks, including the RCGP, the BMA, and public health bodies. The project is led by Dr Richard Armitage, a practising GP and existential-risk researcher at CSER, Cambridge (incoming DPhil, Oxford), whose published work spans AGI threats to public health (https://doi.org/10.1111/jep.70269) and clinical bioterrorism recognition (https://www.tandfonline.com/doi/full/10.1080/23779497.2026.2643956).
Concrete outputs: an open access survey paper establishing the awareness baseline; a free Ai risk literacy module with a published pilot evaluation; and an ongoing clinician newsletter.
The medical profession is large, globally distributed, politically influential, and consistently among society's most trusted institutions, yet it has almost no systematic exposure to the risks AI poses to human health: from algorithmic harms already reaching patients, through to AI-enabled bioweapons and catastrophic scenarios that threaten human survival (https://doi.org/10.1111/jep.70269).
Clinicians have confronted civilisational risk before. The International Physicians for the Prevention of Nuclear War won the 1985 Nobel Peace Prize for lending the profession's credibility to nuclear disarmament, and the profession has since mobilised on climate change through the Royal Colleges and the Lancet Countdown. No equivalent exists for AI. An analogous role on AI governance is plausible, but impossible while clinicians remain unaware of the risks.
The pathway is literacy first: the survey measures the gap, the module narrows it, and the newsletter sustains it. Once clinicians understand the risks, the profession can argue the case for AI governance, one of the few things that could reduce catastrophic and existential AI risk. Right now, the profession best placed to make that case can't keep pace with AI's development. Markets will not close the gap: no commercial actor profits from clinician AI-risk literacy, and medical curricula update too gradually. This is field-building, seeding a constituency and an evidence base others can build on.
Team Member
Minimum ($30,000):
Ideal ($100,000) – the minimum, plus:
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