1 citations · 1 across the 6 of their papers we have counts for
6 papers
Privacy, Prediction, and Allocation
Ben Jacobsen, Nitin Kohli
Algorithmic predictions are increasingly used to inform the allocation of scarce resources. The promise of these methods is that, through machine learning, they can better identify…
Preserving Target Distributions With Differentially Private Count Mechanisms
Nitin Kohli, Paul Laskowski
Differentially private mechanisms are increasingly used to publish tables of counts, where each entry represents the number of individuals belonging to a particular category. A dis…
Provocation on Expertise in Social Impact Evaluations of Generative AI (and Beyond)
Zoe Kahn, Nitin Kohli
Social impact evaluations are emerging as a useful tool to understand, document, and evaluate the societal impacts of generative AI. In this provocation, we begin to think carefull…
Expanding Perspectives on Data Privacy: Insights from Rural Togo
Zoe Kahn, Meyebinesso Farida Carelle Pere, Emily Aiken +2
Passively collected "big" data sources are increasingly used to inform critical development policy decisions in low- and middle-income countries. While prior work highlights how su…
Enabling Humanitarian Applications with Targeted Differential Privacy
Nitin Kohli, Joshua Blumenstock
The proliferation of mobile phones in low- and middle-income countries has suddenly and dramatically increased the extent to which the world's poorest and most vulnerable populatio…
Big Data Privacy in Emerging Market Fintech and Financial Services: A Research Agenda
Joshua E. Blumenstock, Nitin Kohli
The data revolution in low- and middle-income countries is quickly transforming how companies approach emerging markets. As mobile phones and mobile money proliferate, they generat…