TY - JOUR
T1 - The many facets of data equity
AU - Jagadish, H. V.
AU - Stoyanovich, Julia
AU - Howe, Bill
N1 - Publisher Copyright:
© 2021 Copyright for this paper by its author(s).
PY - 2021
Y1 - 2021
N2 - Data-driven systems can be unfair, in many different ways. All too often, as data scientists, we focus narrowly on one technical aspect of fairness. In this paper, we attempt to address equity broadly, and identify the many different ways in which it is manifest in data-driven systems.
AB - Data-driven systems can be unfair, in many different ways. All too often, as data scientists, we focus narrowly on one technical aspect of fairness. In this paper, we attempt to address equity broadly, and identify the many different ways in which it is manifest in data-driven systems.
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UR - http://www.scopus.com/inward/citedby.url?scp=85103513551&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85103513551
SN - 1613-0073
VL - 2841
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 2021 Workshops of the EDBT/ICDT Joint Conference, EDBT/ICDT-WS 2021
Y2 - 23 March 2021
ER -