Inside AI Supply Chains

Can we create Indigenous-grounded alternatives?

“Anatomy of an AI System” by Kate Crawford & Vladan Joler (SHARE Lab / AI Now Institute, 2018)

Complicated. Energy. Money. These are the top three words that came to AbInt participants’ minds when thinking of AI Supply Chain Management. At Bard College, a team of faculty members (Dr. Suzanne Kite and Shefali V Mehta) and four students from the MBA in Sustainability Program want to change that.They are actively imagining and researching a future where AI Supply Chain Management is non-extractive, human-centred, and sustainable. 

On August 21, 2025, Thania Bejarano, Elaina Zachos, Emerson Sarmiento, and Hanna Inman presented their initial research findings to members of the Abundant Intelligences community. The students delivered a comprehensive overview of AI supply chains, looking at the anatomy of AI supply and value chains. They shared three critical perspectives of current AI Supply chain systems: extraction and infrastructure; labor and manufacturing; and data, knowledge, and governance, and offered a series of alternatives that require more research. 

Their presentation was a culmination of this work and a reflection of the Bard MBA Program’s and Abundant Intelligence’s commitment to effectively integrating interdisciplinary approaches to learning. The hybrid gathering—held online and in-person at Concordia University —was a cross-disciplinary and cross-cultural exchange of ideas, anchored in the Abundant Intelligences’s commitment to student research in AI. “The purpose of us coming together today – it begins with a curiosity I have and a gap in my knowledge of what is going on in AI Supply Chain today.” Suzanne noted in the presentation’s opening. “Who is researching (it)? Where are the gaps in knowledge? How can Abundant Intelligences’ many researchers help us address that?”

Indigenous-Grounded AI Supply Chains

Drawing from her chapter in the “Indigenous Protocol and Artificial Intelligence Position Paper,” Dr. Suzanne Kite (aka “Kite”) (Oglála Lakȟóta) wanted to explore how we might form relationships with and protocols for AI Supply Chains. “To me, supply chain is a real investment in Indigenous consciousness (and) investment in material things in the world. Materiality is essential in creating and maintaining ethical relationships to the world and non-human beings in that world.” Director of Wíhaŋble S’a Pod for Indigenous AI, Kite’s Pod focuses on developing Indigenous protocols to guide the creation of AI technologies that draw on broadly Indigenous, and specifically Lakȟóta, ontologies. Through an approach grounded in Indigenous epistemologies, the Wiháŋble S’a Pod addresses the ethical, legal, and societal implications of AI. 


Kite’s research resonated with Bard College Adjunct Professor and AI Supply Chain Consultant Shefali V. Mehta who shares Kite’s vision for a future with ethical and human-centred AI Supply Chains. Mehta connected Kite to four students in the MBA Sustainable program eager to research the topic. The students spent their summer researching ethical and transparent alternatives to AI Supply Chain Management, each bringing diverse professional experiences (environmental fieldwork, impact measurement, climate policy, equity-centred environmental justice) and a commitment to sustainability to their research pursuit. “I am very excited about this project – we got to work with Bard College’s MBA students on an exploration of AI Supply Chains.” Kite shared. Along with Kite, the students also interviewed Abundant Intelligences co-investigator, Dr. Keolu Fox, whose multidisciplinary research areas include genomics, AI, and Indigenous data sovereignty. 

Future Research of AI Supply Chains


Participants from Abundant Intelligences reflected on how the presentation helped increase their awareness around monopolies of AI supply chains, sparked a desire to learn more about the role of these monopolies in controlling AI policy-making, and piqued their interest in the potential for data labelling to call attention to, subvert, and disrupt AI. Overall, the session deepened understanding, revealed gaps, and offered actionable insights supported by curated resources of AI Supply Chain management. 

The students ran one more interactive poll before closing the session. They asked participants to select three AI Supply Chain alternatives they were most interested in further researching.

Their answers?

1.Alternative Technologies & Systems

2.Environmental & Ethical Risk AI Policy

3.Community Natural Resource Ownership

Does this topic interest you? Would you like to contribute? Please reach out to abint-datastorytelling@concordia.ca

AIInfrastructure
AISystems
Students
WíhaŋbleS’aPod

By:

Sabrina Smith

Date:

September 22, 2025

Inside AI Supply Chains

AIInfrastructure
AISystems
Students
WíhaŋbleS’aPod

By:

Sabrina Smith

Date:

September 22, 2025

Can we create Indigenous-grounded alternatives?

“Anatomy of an AI System” by Kate Crawford & Vladan Joler (SHARE Lab / AI Now Institute, 2018)