JMIR Publications

ABSTRACT

The rapid expansion of artificial intelligence in health care, driven by advanced data and analytics tools, has been accompanied by growing calls for collaboration among technology developers, health systems, and communities. Existing iterations of these relationships often performative or legacy fixtures that fail to address persistent underlying asymmetries in power, access, authority, and value. Current data-driven innovations also often reproduce legacy extractive practices across divested populations while providing whole-of-life clinical data from entire communities that remain excluded from the insights and benefits of these tools. The Extractive-Collaborative Technology Continuum draws on principles of ethical leadership, community-engaged research, and health equity to map how relationships between developers and communities must evolve from extractive models to collaborative learning systems. This transition toward a more ethical posture of change leadership and the implementation of innovation necessitates a shift toward a culture of shared governance and collaborative stewardship with a commitment to shared and mutual benefit. The ideal state for collaboration considers and appropriately integrates local knowledge, enacts and delivers reciprocal benefits, and links incentives to the maturity of these practices. Moving from a paradigm of data as property to that of data as a promise ensures that innovation serves communities as the fullest expression of the science of health and the art of caring. The legitimacy of change management and implementation of innovation in care environments depends on the integrity of the relationships that develop and sustain trust and collaboration to the benefit of all.