A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle-Reference-Cited by-同舟云学术

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Published:2021-10-05 Issue: Volume: Page:
ISSN:
Container-title:Equity and Access in Algorithms, Mechanisms, and Optimization
language:
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Author:

Suresh Harini¹,Guttag John¹

Affiliation:

1. Massachusetts Institute of Technology, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3465416.3483305

Reference47 articles.

1. Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016. Machine bias. ProPublica May 23(2016). Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016. Machine bias. ProPublica May 23(2016).

2. Differential privacy has disparate impact on model accuracy;Bagdasaryan Eugene;Advances in Neural Information Processing Systems,2019

3. Big data’s disparate impact;Barocas Solon;Cal. L. Rev.,2016

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