2022
DOI: 10.48550/arxiv.2205.06922
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits

Wesley Hanwen Deng,
Manish Nagireddy,
Michelle Seng Ah Lee
et al.

Abstract: Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML practitioners assess and address unfairness in their systems. However, there has been little research investigating how ML practitioners actually use these toolkits in practice. In this paper, we conducted the first in-depth empirical exploration of how industry practitioners (try to) work with existing fairness toolkits. In particular, we conducted think-aloud interviews to understand how participants learn abo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 50 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?