What's fair is… fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning

Author:

Mccradden Melissa1ORCID,Odusi Oluwadara2ORCID,Joshi Shalmali3ORCID,Akrout Ismail1ORCID,Ndlovu Kagiso4ORCID,Glocker Ben5ORCID,Maicas Gabriel6ORCID,Liu Xiaoxuan7ORCID,Mazwi Mjaye1ORCID,Garnett Tee1ORCID,Oakden-Rayner Lauren6ORCID,Alfred Myrtede8ORCID,Sihlahla Irvine9ORCID,Shafei Oswa1ORCID,Goldenberg Anna1ORCID

Affiliation:

1. The Hospital for Sick Children, Canada

2. The University of Sheffield Medical School, United Kingdom

3. Columbia University, USA

4. University of Botswana, Botswana

5. Imperial College London, United Kingdom

6. Australian Institute for Machine Learning, Australia

7. University of Birmingham, United Kingdom

8. University of Toronto, Canada

9. University of Cape Town, South Africa

Publisher

ACM

Reference111 articles.

1. Algorithmic injustice: a relational ethics approach

2. Gender shades: Intersectional accuracy disparities in commercial gender classification;Buolamwini J.;Proceedings of Machine Learning Research,2018

3. S. Corbett-Davies and S. Goel , " The measure and mismeasure of fairness: A critical review of fair machine learning," arXiv preprint arXiv:1808.00023 , 2018 . S. Corbett-Davies and S. Goel, "The measure and mismeasure of fairness: A critical review of fair machine learning," arXiv preprint arXiv:1808.00023, 2018.

4. Fairness in machine learning;Barocas S.;" NIPS tutorial,2017

5. Assessing risk, automating racism

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