AI in healthcare: How algorithmic billing and corporate cost-cutting exploit systemic inefficiencies, sidelining patient care
Original framing: “Opinion: I’m a doctor. Here’s what I want the public to know about AI tools and health care costs” — STAT News
The *Mino-Bimaadiziwin* (Ojibwe) framework rejects AI’s commodification of health by centering relational reciprocity—care as a gift, not a transaction. Indigenous data sovereignty movements, like the *First Nations Information Governance Centre*, explicitly ban AI tools that prioritize cost over cultural safety, yet these voices are absent from U.S. debates. The doctor’s plea could align with Māori *whakapapa*-based healthcare, where algorithms must serve *manaakitanga* (nurturing), not actuarial tables.
The doctor’s frustration is not an isolated moral failing but a symptom of healthcare AI’s role as a *neoliberal trickster*—masking corporate extraction as ‘innovation.
’ The system exploits the opacity of algorithms to shift blame from insurers (who profit from denials) to providers (who are forced to comply), a dynamic seen in the 1990s HMO backlash and the 1980s Medicaid rationing crises. Solutions must break this cycle by restoring public control over AI tools, centering Indigenous data sovereignty, and unionizing against algorithmic exploitation. The path forward lies in treating healthcare as a *relational good*—not a tradable commodity—where AI serves *Mino-Bimaadiziwin* or *Ubuntu*, not actuarial tables. The doctor’s voice, amplified through these lenses, becomes a call to dismantle the power structures that turn care into a cost.