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Managed by the machine: AI and the new politics of supply chains 
Matthew Archer (Maastricht University)
Filipe Calvao (Graduate Institute of Geneva)
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Nanna Thylstrup
Wednesday 8 June, -
Time zone: Europe/London

Short Abstract:

Supply chains are being reconfigured through big data and intelligent machines. Reflecting ethnographically on the growing role of artificial intelligence in newly digitized means of production, this panel explores the co-emergence of datafication and algorithmic governance in global supply chains.

Long Abstract:

Global supply chains are increasingly governed by "big data". From mining and agriculture to health and finance, corporations and other organizations are adopting artificial intelligence to enhance efficiency and capitalize on behavioral and predictive data for their operations. This suggests the emergence of new forms of supply chain governance, where the calculative agency of algorithmic systems creates new supply chain politics, forcing influential "lead firms" to grapple with newly empowered tech companies and creating spaces where traditional power dynamics are both resisted and reproduced, even as new supply chains are emerging to facilitate the movement of data and software.

In this panel, we are particularly interested in papers that attempt to theorize the epistemic politics of artificial intelligence in supply chain management, through ethnographic engagements with questions of transparency, traceability, accountability, and sustainability. These concerns bring together a growing interest in the anthropology of algorithms, data, and AI with more classic accounts of regimes of production, consumption, and exchange in economic anthropology. Some questions the panel seeks to address include:

Who controls the data and software that automated supply chain management processes depend on? What forms of resistance are emerging to contest these power dynamics?

As companies turn to remote operations and automated decision making, what kinds of work do these new supply chains and new forms of supply chain governance instigate, and what do they preclude?

What kinds of knowledge "count" as data that AI-driven automated management systems can interpret and act on, and what gets excluded or ignored?

Accepted papers:

Session 1 Wednesday 8 June, 2022, -