Journal article
Contrastive fairness in machine learning
- Abstract:
-
Was it fair that Harry was hired but not Barry? Was it fair that Pam was fired instead of Sam? How can one ensure fairness when an intelligent algorithm takes these decisions instead of a human? How can one ensure that the decisions were taken based on merit and not on protected attributes like race or sex? These are the questions that must be answered now that many decisions in real life can be made through machine learning. However, research in fairness of algorithms has focused on the coun...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Funding
Bibliographic Details
- Publisher:
- Institute of Electrical and Electronics Engineers Publisher's website
- Journal:
- IEEE Letters of the Computer Society Journal website
- Volume:
- 3
- Issue:
- 2
- Pages:
- 38-41
- Publication date:
- 2020-07-07
- Acceptance date:
- 2020-07-01
- DOI:
- EISSN:
-
2573-9689
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1117312
- Local pid:
- pubs:1117312
- Deposit date:
- 2020-07-09
Terms of use
- Copyright holder:
- Institute of Electrical and Electronics Engineers
- Copyright date:
- 2020
- Rights statement:
- © 2020 IEEE.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Institute of Electrical and Electronics Engineers at: https://doi.org/10.1109/LOCS.2020.3007845
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