Data, Algorithms, Fairness, Accountability

Danah Boyd

Data, Algorithms, Fairness, Accountability

Öz

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.

Anahtar Kelimeler

Kaynakça

*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.

Ayrıntılar

Birincil Dil

Türkçe

Konular

İletişim ve Medya Çalışmaları

Bölüm

Diğer

Yazarlar

Danah Boyd Bu kişi benim
United States

Yayımlanma Tarihi

30 Ocak 2021

Gönderilme Tarihi

10 Ocak 2021

Kabul Tarihi

24 Ocak 2021

Yayımlandığı Sayı

Yıl 2021 Cilt: 6 Sayı: 11

IZ

https://izlik.org/JA85GR44BE

Kaynak Göster

RIS / Bibtex

APA

Boyd, D. (2021). Data, Algorithms, Fairness, Accountability. TRT Akademi, 6(11), 202-209. https://izlik.org/JA85GR44BE