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TRV-2026-0691Certified recordPeer-reviewed

Data science and AI in medicine and global health: The need for inter-philosophies dialogue, cross-cultural ethics and ecocentricity

Advances in data science and medical artificial intelligence (AI) raise complex philosophical and ethical quandaries about what it means to know a person or a community through data and what kinds of people and societies we are becoming in this era of predictive data science. Drawing on four lightly fictional but reality-informed case studies in mental health, radiology, genomics and environmental public health, we reflect on how AI technologies, largely built on Western biomedical traditions, may conflict with…

Health · P Space — documented harm · certified 2026-08-08 · v1 · article view · machine-readable

Current reading — problem

Medical AI systems built on Western biomedical traditions may inflict ontological harm and diminish trust in patient-clinician relationships by conflicting with relational and Indigenous understandings of health.

What this doesn’t fix

Analysis relies on lightly fictional but reality-informed case studies rather than measured deployment outcomes, and frames harms as potential rather than observed.

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Truvace Impact Record TRV-2026-0691, v1: “Data science and AI in medicine and global health: The need for inter-philosophies dialogue, cross-cultural ethics and ecocentricity.” Truvace, 2026-08-08. /record/TRV-2026-0691 (accessed at citation time). sha256 cd1fc6126566e3a8…

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