Data, Algorithms, Fairness, Accountability

Year 2021, Volume: 6 Issue: 11, 202 - 209, 30.01.2021

Danah Boyd

Abstract

As members of the US Department of Commerce’s Data Advisory Council, we are all deeply committed to seeing government use data strategically and productively to improve our country. We have spent the last year examining ways to open up government data and push for more engagement with government data. My talk today is intended to challenge and provoke us to think more deeply about the mission that we’re committed to. I want to challenge some of the basic assumptions that we all hold dear and highlight how some of our values are in conflict. We all assume that our commitment to using data well is a commitment to using data for social good. But what if our passion project will increase inequality and hurt the people we’re trying to help? What if our efforts will do harm?...

*D.S. Department of Commerce, Data Advisory Council: October 28, 2016 / This talk was written for a meeting of the Data Advisory Council. It is a crib; the actual talk probably came out slightly differently.
*This study has been published with the approval of its writer.

Keywords

Data, Algorithms, Big Data

References

• *D.S. Department of Commerce, Data Advisory Council: October 28, 2016 / This talk was written for a meeting of the Data Advisory Council. It is a crib; the actual talk probably came out slightly differently. *This study has been published with the approval of its writer.