Announcing the CDCS Annual Lecture 2021
CDCS are delighted to announce this year's annual lecture speaker, Professor Keolu Fox (University of California, San Diego).
Join us on Monday 13 December at 16:00 GMT via Zoom Webinar!
Data as Power: The Next 100 Generations of Indigenous Data Sovereignty
We are thrilled to be able to host Keolu Fox, a genome scientist and indigenous rights activist whose work focuses on the connection between raw data as a resource and the emerging value of genomic health data from Indigenous communities.
Professor Fox is the first Kānaka Maoli (Native Hawaiian) to receive a doctorate in genome sciences and is an assistant professor at the University of California, San Diego, affiliated with the Department of Anthropology, the Global Health Program, the Halıcıoğlu Data Science Institute, the Climate Action Lab, the Design Lab, and the Indigenous Futures Institute.
He has experience designing and engineering genome sequencing and editing technologies, and has a decade of grassroots experience working with Indigenous partners to advance precision medicine. In his CDCS lecture he will focus on how indigenous communities can be empowered to reclaim, control and benefit from data.
The CDCS elves will be sending out a limited number of festive gifts to those who register early!
According to The Economist, in 2018 oil was the most-traded commodity in the world. But in 2019, the demand for oil had been surpassed by the demand for data, including digital sequence information (DSI) of genetic resources . Despite increasing enthusiasm for historically marginalized communities’ participation in biomedical research and a recognition of the potential for next-generation precision medicine, concerns around control and access of data derived from these populations remain. [2-4].
This lecture will highlight the emergence of new tools to enable equitable Indigenous data futures [4,5] and explore key paths forward that are not only rooted in Indigenous Data Sovereignty (IDS), but circular economic systems, and place-based innovation [5-8]. It will also highlight the potential for vertical integration and control of “stacks of technology,” including dynamic consent, data trusts, digital ledger systems, and cloud computation to empower Indigenous communities for generations to come [9,10].
If aggregated and controlled by Indigenous communities, these data and technologies can be harnessed to reclaim our past, revitalize our culture, restore our lands, and empower the next one hundred generations of Indigenous communities around the world. From Indigenous control of satellites to reduce the digital divide, to recognizing the emergent value of biodiversity data under the custodianship of Indigenous communities, our goal is to educate Indigenous peoples around the world on the potential use and misuse of evolving big data ecosystems in 2021 and into the future.
The Economist. (2017). The world’s most valuable resource is no longer oil, but data.
Gillmore, J. D. et al., (2021). CRISPR-Cas9 In Vivo Gene Editing for Transthyretin Amyloidosis. New England Journal of Medicine.
Fox, K. (2020). The “All of Us” Program and Indigenous Peoples. New England Journal of Medicine.
Fox, K. (2020). The Illusion of Inclusion — The “All of Us” Research Program and Indigenous Peoples’ DNA. New England Journal of Medicine.
Claw, K. G. (2018). A Framework for Enhancing Ethical Genomic Research with Indigenous Communities. Nature Communications.
Ambler J., (2020) Including digital sequence data in the nagoya protocol can promote data sharing. Trends in Biotechnology.
Hudson, M. et al., (2020). Rights, Interests, & Expectations: Indigenous perspectives on unrestricted access to genomic data. Nature Reviews Genetics.
Li, X. (2018). Industrial Ecology and Industry Symbiosis for Environmental Sustainability: Definitions, Frameworks and Applications. Palgrave, MacMillian Press.
Vigna, P. & Casey, M. J. (2018). The truth machine: The blockchain and the future of everything. St. Martin's Publishing Group.
Chan V. et al., (2021) A “data sharing trust” model for rapid, collaborative science. Cell.