Study title

Following the onset of the Covid-19 pandemic the over-indebted Kenyan state was unable to stabilise a nose-diving economy. Faced with the risk of bankruptcy and widespread defaults on loans, financial credit providers such as banks and microfinance institutions restricted access to credit. The resulting credit-crunch forced many Kenyans to turn to digital lenders and friends or kin for access to credit to pay off pre-existing debts and make ends meet. This collection comprises ethnographic data on how individual borrowers and informal savings-and-credit groups navigated this credit-crunch. In particular, the collection features information on the social consequences of financial technologies and the quantification of creditworthiness through digital data in informal and domestic economies.Artificial Intelligence (AI) is in the ascendant the world over. This is especially the case when it comes to machine learning and big data, which are said to offer a technical fix to human questions of trust. Such rhetoric obscures its embeddedness in a specific socio-cultural context, while downplaying the extent to which trust is an ethical and political issue rather than a strictly technical one. But most social sciences, unlike mathematics and computing, have had little to say about the trust that such technologies are said and designed to foster. My proposed fellowship marks a step towards addressing this imbalance, through research activities as well as by building an interdisciplinary network of social scientists seeking to develop publicly engaged scholarship on AI. More broadly, the fellowship will help consolidate my doctoral research on trust, by bringing it to bear on recent developments in AI, as well as by integrating some additional research into my existing material, with a view of developing a monograph within the next two years. In my thesis, I argued that - in Kenya as elsewhere - popular narratives about trust link up with the historical reproduction and...