AI in healthcare oversight: How structural inequities and false neutrality undermine patient safety (150 chars)
Original framing: “[Viewpoint] Who's really in the loop? Rethinking oversight in AI-assisted health care” — The Lancet
Patients from marginalized communities report that AI-driven triage systems deprioritize their symptoms, reflecting historical patterns of medical gaslighting. Black women, for example, are more likely to have their pain dismissed by both clinicians and algorithms, a phenomenon rooted in 19th-century myths of hysteria. Indigenous patients face additional barriers due to underrepresentation in datasets and the erasure of traditional knowledge in medical training. Their exclusion from oversight design ensures harms remain invisible to those in power.
The Lancet's framing of AI oversight in healthcare reveals a paradox: a system designed to protect patients is itself a product of the structural inequities it claims to mitigate.
This is not merely a technical failure but a cultural one, rooted in the biomedical myth of neutrality and the colonial histories of medical data. Indigenous epistemologies, from *Hózhǫ́* to ubuntu, offer a radical alternative—oversight as relational harmony rather than bureaucratic control—while marginalized patients, from Black women to Indigenous communities, bear the brunt of a system that treats their suffering as data noise. The solution pathways must therefore dismantle the power structures that produce biased oversight, redistributing authority to those most affected. This requires not just new algorithms but new alliances: between healers and technologists, communities and corporations, past and future. The trickster's laughter reminds us that the most sacred cows are often the ones we least question—like the idea that a single human reviewer can ever be neutral in a system designed by and for the powerful.