Data breaches and data misuse have permeated the news over the past few years, raising the importance of terms like data privacy, data protection, and cybersecurity. Despite this, there is little consensus on what exactly privacy means, and how to best protect consumer’s data. In an era characterized by big data and machine learning, is it possible to have privacy and innovation concurrently?
In this webinar, Nitin Kohli defines and discusses a suite of tools, known as Privacy Enhancing Technologies, that can be used to safeguard sensitive data and will share real case studies of how these tools could foster responsible financial inclusion. Nitin is a postdoctoral scholar at the Center for Effective Global Action and holds a PhD from UC Berkeley’s School of Information. His research spans privacy, fairness, and the manipulability of statistical and algorithmic mechanisms to develop theory, tools, and frameworks that safeguard individuals while attending to the social and political context of their use.
Follow along with a copy of the slides and dig deeper with the accompanying CEGA Working Paper.
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