SPEAKER: Arvind Narayana, Assistant Professor, Department of Computer Science and Center for Information Technology Policy at Princeton University
For all the hype, “big data” and machine learning do hold immense promise to better people’s lives, whether in education, energy, healthcare, or the environment. But data-driven decisions can be bad decisions, and many people are developing and applying data analytics with little consideration of the ethical implications.
This spring, we invite you to join us for a series of one-hour talks in which distinguished speakers will grapple with the challenge of ensuring data science serves the public good. They will address such subjects as financial systems risk, interpretability and discrimination in machine learning, and different definitions of fairness and privacy.
Unless otherwise noted, all these talks will be at noon on Fridays. Light refreshments will be provided. No RSVP is needed unless otherwise announced for selected events. Seats are on a first-come first-serve basis and subject to room capacity.
Webinar registration link: https://columbiauniversity.zoom.us/webinar/register/WN_j7JbKvDKQlqrC7MzjO11ag
Jointly sponsored by the Data Science Institute and the
Institute for Social and Economic Research and Policy
