Differential Privacy for the 2020 U.S. Census: Can We make Data Both Private and Useful? (Part 1)

<p>While most Americans have heard of the U.S. Census and understand that it is designed to count every resident in the United States every 10 years, many may not realize that the Census’s role goes far beyond the allocation of seats in Congress. </p> <p>For this episode, we invited the three co-editors of Harvard Data Science Review’s <a href='https://hdsr.mitpress.mit.edu/specialissue2'>special issue on the U.S. Census </a>to help us explore what the Census is, what it’s used for, and how the data it collects should remain both private and useful.  </p> <p>Our guests are:</p> <ul><li style="font-weight:400;">Erica Groshen, former Commissioner of Labor Statistics and Head of the U.S. Bureau of Labor Statistics</li> <li style="font-weight:400;">Ruobin Gong, Assistant Professor of Statistics at Rutgers University</li> <li style="font-weight:400;">Salil Vadhan, Professor of Computer Science and Applied Mathematics at Harvard University</li> </ul> <p> </p>