Takeaways
- Indigenous knowledge systems, rooted in relational worldviews, offer foundational insights for rethinking human-nature relationships in conservation and technology.
- Ethical AI development must start by addressing historical and structural injustices in data access, control, and benefit sharing before deploying technical solutions.
- Technologies like blockchain and federated AI are only transformative when embedded within Indigenous governance systems and aligned with community-defined values.
- Indigenous sovereignty over biodiversity data challenges prevailing notions of innovation by centering collective rights over individual or institutional claims.
- Viewing data as kin rather than as property reframes its stewardship as a relational responsibility, not a commercial asset, disrupting extractive scientific norms.
Summary
Krystal Tsosie begins by challenging Western philosophical hierarchies that place humans at the center of creation, contrasting them with indigenous epistemologies that regard all beings—animate and inanimate—as relations with intrinsic value. She underscores the importance of indigenous data sovereignty: the right of communities to govern data derived from their lands, cultures, and knowledge systems. This principle is both an ethical imperative and a matter of justice and sustainability, as indigenous peoples have long served as stewards of biodiversity.
Tsosie recounts historical patterns of biopiracy, from European researchers patenting antimalarial compounds without prior consent, to the mass commercial harvesting of white sage from former tribal lands. She highlights the inequity inherent in current benefit-sharing arrangements, noting that indigenous providers rarely reap the first rewards of their own genetic or ethnobotanical knowledge. While the Nagoya Protocol enshrines equitable sharing in international law, major powers have often refused to ratify it, perpetuating biocolonial practices.
To address these imbalances, Tsosie advocates for embedding indigenous partners at every phase of the data life cycle—from collection and storage to dissemination and secondary use. She describes successful initiatives, such as the Native Biodata Consortium, which builds tribal bio-repositories under tribal law, and federated learning architectures that employ blockchain and cryptographic metadata labels to grant communities granular control over data sharing. By training indigenous data leaders in high-throughput sequencing, federated systems, and digital tool development, these efforts foster long-term capacity and self-determination.
Tsosie warns against superficial “ethics washing” and urges technologists to engage in genuine co-planning, legal negotiation of ownership rules, and continuous dialogue under tribal governance. She calls on non-indigenous allies to speak up, challenge default ownership assumptions, and support social justice measures alongside technological innovation. Ultimately, she envisions a future of indigenous digital sovereignty—where biodata economies are governed by the very communities that have protected biodiversity for millennia.
