Summary of Impact Of Fairness Regulations on Institutions’ Policies and Population Qualifications, by Hamidreza Montaseri et al.
Impact of Fairness Regulations on Institutions’ Policies and Population Qualifications
by Hamidreza Montaseri, Amin Gohari
First submitted to arxiv on: 6 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a system that maximizes utility by selecting the most qualified individuals, with a focus on promoting demographic parity through a discrimination penalty. The authors examine when and how this penalty can effectively reduce disparity in selection outcomes. They also explore implications for individual qualifications evolving over time in response to the penalizing policy. The summary highlights scenarios where the penalty could hinder equity attainment and proposes conditions that counteract this outcome, ensuring fairness. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at a system that tries to find the most qualified people. It wants to make sure everyone has an equal chance of getting picked. To do this, it adds a penalty to the system if it thinks someone is being unfairly treated. The authors figure out when and how this penalty can help make things fairer. They also look at what happens if people’s qualifications change over time because of the penalty. Overall, the paper shows that there are times when the penalty might actually make things worse, so we need to be careful. |
