Large language models (LLMs) like ChatGPT increasingly shape how people see the world, yet their responses mirror long-standing biases in the data they ingest.
New research from the Oxford Internet Institute (OII) at the University of Oxford and the University of Kentucky finds that ChatGPT systematically favours wealthier, Western regions in response to questions ranging from “Where are people more beautiful?” to “Which country is safer?”.
The study, The Silicon Gaze: A typology of biases and inequality in LLMs through the lens of place, by Francisco W. Kerche, Professor Matthew Zook and Professor Mark Graham, published in Platforms and Society on Tuesday 20th January, analysed over 20 million ChatGPT queries.
The authors introduce the concept of the “silicon gaze” to describe how generative AI reproduces long-standing global inequalities, rather than offering neutral representations of the world.
What the study found
Across comparisons, ChatGPT tended to select higher-income regions such as the United States, Western Europe, and parts of East Asia as “better”, “smarter”, “happier”, or “more innovative”. Meanwhile, large areas of Africa, the Middle East, and parts of Asia and Latin America were far more likely to rank at the bottom. These patterns were consistent across both highly subjective prompts and prompts that appear more objective.
Examples from the research
To make these dynamics visible, the researchers produced maps and comparisons from their 20.3-million-query audit. For example:
- A world map ranking “Where are people smarter?” places almost all low-income countries, especially Africa, at the bottom.
- Neighbourhood-level results in London, New York and Rio show ChatGPT’s rankings closely align with existing social and racial divides, rather than meaningful characteristics of communities.
Explore how ChatGPT sees your region
The research team has created a public website at inequalities.ai where anyone can explore how ChatGPT ranks their own country, city or neighbourhood across topics such as food, culture, safety, environment, or quality of life.
Why this happens
The authors argue that these biases are not errors that can simply be corrected, but structural features of generative AI. LLMs learn from data shaped by centuries of uneven information production, privileging places with extensive English-language coverage and strong digital visibility. The paper identifies five interconnected biases – availability, pattern, averaging, trope and proxy – that together help explain why richer, well-documented regions repeatedly rank favourably in ChatGPT’s answers.
Why it matters
Generative AI is increasingly used in public services, education, business and everyday decision-making. Treating its outputs as neutral sources of knowledge risks reinforcing the inequalities the systems mirror.
The researchers call for greater transparency from developers and organisations using AI, and for auditing frameworks that allow independent scrutiny of model behaviour. For the public, the research shows that generative AI does not offer an even map of the world. Its answers reflect the biases embedded in the data it is built on.
About the paper
The paper, The Silicon Gaze: A typology of biases and inequality in LLMs through the lens of place, by Francisco W. Kerche and Mark Graham, Oxford Internet Institute, University of Oxford and Matthew Zook, Department of Geography, University of Kentucky is published in Platforms and Society.
Funding information
The Inequalities.AI project is based on a long-standing research collaboration on digital geographies between researchers at the University of Oxford and the University of Kentucky. Initial funding was provided by the John Fell Fund of the University of Oxford.
Contact
For more information and briefings, please contact:
Anthea Milnes, Head of Communications, or Sara Spinks / Veena McCoole, Media and Communications Manager
T: +44 (0)1865 280527
M: +44 (0)7551 345493
E: press@oii.ox.ac.uk
About the Oxford Internet Institute (OII)
The Oxford Internet Institute (OII) has been at the forefront of exploring the human impact of emerging technologies for 25 years. As a multidisciplinary research and teaching department, we bring together scholars and students from diverse fields to examine the opportunities and challenges posed by transformative innovations such as artificial intelligence, large language models, machine learning, digital platforms, and autonomous agents.
About the University of Oxford
Oxford University was placed number one in the Times Higher Education World University Rankings for the tenth year running in 2025. At the heart of this success are the twin-pillars of our ground-breaking research and innovation and our distinctive educational offer. Oxford is world-famous for research and teaching excellence and home to some of the most talented people from across the globe.
