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Place is not a neutral category in AI systems. Our findings show how historical and institutional patterns of documentation become legible as common sense in LLM outputs. You can explore all of our data and create your own maps at inequalities.ai

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One recurring issue is the use of proxies: quantifiable stand-ins (rankings, lists, awards) used to answer questions that are not straightforwardly measurable. This tends to advantage already-visible places.

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We used forced-choice prompts to elicit comparative judgements about places. This makes latent preferences and stereotypes easier to detect than in open-ended responses.

The paper develops a typology of five recurrent biases in LLM place representations: availability, pattern, averaging, trope, and proxy. The maps illustrate how these surface across regions.

A large share of place-based answers in LLMs appear to be shaped by uneven visibility in the underlying data. This is particularly evident for places that are sparsely documented online.

We introduce the term “silicon gaze” to describe patterned inequalities in how LLMs represent place. The paper sets out a typology and maps the resulting spatial distributions.

Oxford Internet Institute @oii.ox.ac.uk · 08/01/2026

Our new paper audits ChatGPT’s place-based judgements using 20 million pairwise comparisons. We find systematic geographic biases in how places are described and evaluated. journals.sagepub.com/doi/10.1177/... (authors: Francisco W. Kerche, Matthew Zook, Mark Graham)

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Reposted by Mark Graham

The OII's Prof. @geoplace.bsky.social contributed to POST UK's report on AI and employment, which considers the factors driving adoption and the issues that might make this challenging. Read the full report here: post.parliament.uk/research-bri...

post.parliament.uk

Artificial intelligence (AI) and employment

Artificial intelligence (AI) is becoming more common in UK workplaces. How is it being used, and what are the impacts on job opportunities and working conditions?

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Mark Graham @geoplace.bsky.social · 16/12/2025

Fairwork’s AI Supply Chain Assessment: Appen report is now LIVE. - 15 changes were implemented by Appen during the assessment period. - The report also highlights areas for further progress, including pay, worker protections, and transparency. Read the full report here: fair.work/en/fw/public...

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Mark Graham @geoplace.bsky.social · 10/12/2025

If AI is going to be fair, its supply chains have to be too. That’s why we’ve launched Fairwork Certification, working with lead firms to push higher standards all the way down their chains. Details here: fair.work/wp-content/u...

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Mark Graham @geoplace.bsky.social · 10/12/2025

A new @towardsfairwork.bsky.social assessment of Sama is out. It looks at the people doing the invisible data work that keeps AI running for companies in sectors from driverless cars to online retail. Read the scorecard and our report here: 🔗 fair.work/en/fw/public...

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Reposted by Mark Graham

Nina Scholz @ninascholz.bsky.social · 10/11/2025

KI klingt nach Zukunft – aber sie lebt von menschlicher, unsichtbarer Arbeit. Ich habe für @freitag.de mit @geoplace.bsky.social über sein Buch „Feeding the Machine“ gesprochen – und darüber, was KI wirklich kostet. Leseempfehlung für alle, die hinter die Kulissen der "KI-Unternehmen" schauen wollen

freitag.de

„Die Arbeitsbedingungen sind brutal“: Über die geheimen Malocher hinter ChatGPT

Hinter jedem KI-Bild steckt Handarbeit: Menschen in Kenia, Indien oder auf den Philippinen schuften stundenlang für Hungerlöhne, um Maschinen klüger zu machen. Im Gespräch enthüllt Mark Graham die uns...

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Mark Graham @geoplace.bsky.social · 30/10/2025

I’ve got a new chapter out with Adam Badger, Alessio Bertolini, Fabian Ferrari & Funda Ustek Spilda in the forthcoming Handbook of Labour Geography. In it, we unpack the Fairwork action-research method. Read: www.elgaronline.com/edcollchap/b...

elgaronline.com

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Reposted by Mark Graham

Oxford Social Sciences Division @socsci.ox.ac.uk · 24/10/2025

We see only the polished face of AI- but behind it lies a web of people, data & decisions shaping who gains & who’s left behind. Join @geoplace.bsky.social @towardsfairwork.bsky.social @oii.ox.ac.uk to explore fairer AI 📅 29 Oct 📍Museum of Oxford 🔗 www.socsci.ox.ac.uk/unveiling-th... #ESRCFestival

socsci.ox.ac.uk

Unveiling the human behind AI: A Rubik's cube journey to Fair Work

29 October, late morning - 4pm, Museum of Oxford

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Mark Graham @geoplace.bsky.social · 13/10/2025

Friends and colleagues in Oxford, join us for this event at the end of the month. festivalofsocialscience.com/events/unvei...

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Reposted by Mark Graham

Oxford Social Policy and Intervention @dspi-oxford.bsky.social · 09/10/2025

📢Book your free spot at our first seminar of term! Join Prof Mark Graham @oii.ox.ac.uk for: “The hidden human labour powering AI: Introducing the Fairwork Action Research Project” 🗓16 October 4pm 📍In-person & online Register now: talks.ox.ac.uk/talks/id/760... @geoplace.bsky.social

'The hidden human labour powering AI: Introducing the Fairwork Action Research Project'
Professor Mark Graham has short curly dark hair. He is wearing a black shirt.

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Reposted by Mark Graham

Call for Papers: Locating Power and Resistance Within Global AI Production Networks

Call for Papers: Locating Power & Resistance in Global AI Production Networks AAG 2026 Annual Meeting AI is not just “in the cloud.” It relies on global supply chains, with power concentrated in a few countries and corporations. fair.work/en/fw/blog/c... #AAG2026

fair.work

American Association of Geographers (AAG) 2026 Annual Meeting

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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

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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?

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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.