Artificial intelligence (AI) is an increasingly defining force, shaping global advancements and influencing crucial aspects of society. Assistant professor Yousif Hassan’s research examines the social, economic, and political implications of emerging technologies, with a particular emphasis on technological innovation, development, and the digital economy. He recently published a book chapter and a peer-review article focused on the politics of AI in Africa, illustrating how machine learning and natural language processing should not be looked at only as tools for innovation, but can play a role in state-building, development, and cultural preservation.
In “Machine Learning as a State-building Experiment: AI and Development in Africa,” published in The Oxford Handbook of the Sociology of Machine Learning, Hassan explores how machine learning (ML) is entangled with global power dynamics. AI is often framed as a silver bullet for development, but as Hassan analyzes, these technologies are also embedded with assumptions that perpetuate old beliefs, particularly that economic and social development challenges in the Majority World are often attributed to the lack of human and technological capacity but this framing obscures deeper structural issues and power imbalances that shape development in Africa.
Hassan employs frameworks from both science and technology studies, as well as contemporary African and decolonial studies to analyze how AI for Development (AI4D) projects in countries like Kenya and Ghana reflect competing visions of the future of technology. Some see ML as a catalyst for growth, while others critique it as a new form of imperialism through technology.
Hassan calls for a more grounded, politically aware engagement with AI in Africa as “there is an urgent need to recognize the desire of local AI communities to have an equal voice in global technoscience spaces that are built with legacies of colonial structures still persistent in contemporary societies, with all their asymmetries of wealth and power.”
While machine learning is shaping national development and state-building, Hassan’s work also turns to another terrain where AI intersects with history, identity, and resistance: language. In “The Politics of Memory: NLP Models as Liberating Artifacts,” published in Science, Technology and Society, Hassan examines natural language processing (NLP) of Indigenous African languages, and how AI in this context can digitally restore and preserve collective memory.
Hassan traces how language has historically been used as a technology of control—first by colonial regimes seeking to subjugate African identities, and later by postcolonial governments working to reclaim them. Today, he argues, NLP models function as “intangible political artifacts,” tools with the potential to restore Africa’s indigenous languages in education and public service.
To unlock NLP’s potential, Hassan calls for national strategies that prioritize the democratic participation of local communities and foster global partnerships. “African governments need to support democratic participation of local NLP communities in the debates and development of their national strategies,” he writes. “This requires active and ethical engagement with the communities that are the bearers of this knowledge, as well as equal and productive collaboration with the international community based on mutual respect and dignity.”
