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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 relational, spiritual and Indigenous understandings of health and wellbeing. This may manifest as epistemic friction, algorithmic fatalism and diminished trust in patient-clinician relationships. Besides familiar concerns regarding bias and transparency, this paper advances the discourse on the ethics of medical AI and data science in healthcare by shifting the analysis from epistemology (how AI systems know, classify and predict) to ontology (the study of the nature of being, as reconfigured by data and AI). We argue that AI systems may inflict significant ontological harm by reconfiguring identity, moral agency and imagined futures and advocate for a renewed medical humanism driven by inter- philosophies dialogue, cross-cultural ethics and ecocentric approaches to care. From Bamenda, Cameroon, to Mthatha, South Africa and Toronto, Canada, the future of medical AI must be defined by the moral and philosophical traditions that people already live by. African, Indigenous, Islamic, Buddhist, Confucian and marginalised Western worldviews should not be treated as peripheral critiques, but as constitutive resources for building inclusive, human-centred health technologies. We conclude that bioethics should be recognised as a core infrastructure in global health, on equal footing with data science, medicine, biomedical research and health innovation.