Organizers:
Mark Graham (Oxford Internet Institute, Univ. of Oxford)
Uma Rani (International Labour Organization)

We welcome interdisciplinary work from all career stages.
#AAG2026 #AI #TechJustice #GlobalProductionNetworks #Labor #ClimateJustice #DigitalColonialism

Submission details:
• Abstract (≤250 words)
• Short bio (≤100 words)
• Deadline: Oct 14
• Send to mark.graham@oii.ox.ac.uk and amara@ilo.org
Subject line: AAG 2026 AI Production Networks Session

Guiding questions include:
• Where are the critical nodes and chokepoints?
• How can transparency reveal hidden flows of minerals, capital, data, labor?
• Which policy levers reshape incentives?
• Where do labor & community struggles gain traction?
• How can design choices reduce harm?

This session explores how value and profit concentrate in the Global North while environmental harms, precarious labor, and extractive practices fall elsewhere.

We want papers that map these geographies of harm and identify leverage points for change.

The cube is not just a puzzle. It is a lens that reveals both what AI shows and what it conceals.

This piece was made with brilliant designers John Philip Sage and Carlos Romo-Melgar.

We’ll be exhibiting it (and giving many away) at the ESRC Festival of Social Sciences in Oxford on 29 Oct.

Across every side, glass-like insect forms creep. Not natural but synthetic hybrids, they act as metaphors for the hidden systems that power AI. Like insects in an ecosystem, they expose dependencies we rarely notice.

AI Products: You use it. It uses you.
Invisible Labour: Invisible labour, indispensable skill.
Data Assets: Extraction fuels machine learning.
Footprint: Digital demand, ecological debt.
Capital and Ownership: Cash walls. Closed doors.
Rules and Voids: Governance gaps widen risks.

"[We need to] understand that when we use these products and services, we're not just interacting with a machine. We're interacting with many, many real people of flesh and blood, who often work under terrible conditions." - Prof. Mark Graham @geoplace.bsky.social

globalnyt.dk/professor-ka...

This paper is a call to action for the academic community to lead by example, fostering a more just and responsible AI ecosystem. I invite you to read the full paper and join the conversation.

Find it here: www.frontiersin.org/journals/com...

Our research calls upon higher education instructors and students to become active advocates for improved working conditions across the entire AI supply chain. This is a collective responsibility.

We strongly advocate for the adoption of the Fairwork scoring system as a robust framework to guide ethical engagement with AI technologies within academic institutions.

The seamless integration of AI in higher education relies heavily on a significant, yet largely invisible, workforce. We emphasise the importance of recognising and valuing their contributions.

AI is not autonomous. It depends on invisible labour: data annotators, content moderators, voice workers, data centre techs. Often underpaid, emotionally strained, and hidden from view.