When it comes to talking about AI ethics, we often hear terms such as bias, fairness, accountability, transparency, human-centered explainable AI, and responsible AI. While they cover major concerns around an AI/data-driven world from technologists’ imagination, they do not capture how these technologies are experienced in everyday lives of people across different physical and social geographies. How do we then create a bottom-up participatory narrative about AI, ethics and algorithmic harm? How do we talk about ordinary ethics of AI? To explore some of these possibilities, today, we have with us Dr. Ranjit Singh.
Ranjit is a postdoctoral researcher at the Data and Society Research Institute in New York. Ranjit studies the intersection of data infrastructures, global development, and public policy. His dissertation research advances public understanding of the affordances and limits of Aadhaar, India’s biometrics-based national identification infrastructure, in practically achieving inclusive development and reshaping the nature of citizenship.
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