A Primer on AI in/from the Majority World is a curated collection of over 160 thematic works that serve as pathways to explore the presence of artificial intelligence and technology in the geographic regions that are home to the majority of the human population. Instead of assuming that knowledge and innovations move out of the so-called centers of Europe and the United States to the rest of the world, thinking from the “majority world” (a term coined by Bangladeshi photographer Shahidul Alam) means tracing emerging forms of knowledge, innovation, and labor in former and still-colonized spaces. “Majority world” defines a community in terms of what it has, rather than what it lacks.

The outcome of a deep collaboration between Sareeta Amrute, Ranjit Singh, and Rigoberto Lara Guzmán (and informed by a range of feminists, Indigenous thinkers, anti-caste scholars, and Afro-futurists), this primer is the latest in a collection of research from Data & Society that reframes current understandings of AI and data-centric technology from a majority world perspective. The publication explores ways to actively think about data and artificial intelligence in regions outside of North America and Europe, while offering unique perspectives to investigate and understand the diverse ethics, politics, and everyday experiences of living with these technologies. How can we describe living with AI systems and their data collection practices as they increasingly become central to organizing everyday life? What visions can we surface for building equitable AI infrastructures for the majority world?

This primer is organized along three themes — ground realities, mediating structures, and framing narratives — moving from the empirically fine-grained, to past and future imaginaries shaping the present. This work is grounded in the conviction that developments in the majority world need to be addressed in their own right, not treated as derivative of active centers of knowledge and technology production. The work is premised on the understanding that the majority world is not only an empirical site, but a method to understand, analyze, and encourage postcolonial and decolonial computing practices.

By engaging with and sampling from twelve thematic categories and exploring resources in a range of formats — books, journal articles, newspaper articles, blog posts, podcasts, lectures, and interviews — readers will have a window into what makes data-driven AI-based interventions possible in the majority world, and forge their own connections. We acknowledge that this resource is a start:  We hope those who read and commit to it will take the next, very material steps toward repair, redistribution, or remaking.