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Towards Equalised Odds as Fairness Metric in Academic Performance Prediction

arXiv 2209.14670 ↗First posted 29 Sep 2022cs.LG cs.AI cs.CYcited by 0

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Abstract (arXiv)

The literature for fairness-aware machine learning knows a plethora of different fairness notions. It is however wellknown, that it is impossible to satisfy all of them, as certain notions contradict each other. In this paper, we take a closer look at academic performance prediction (APP) systems and try to distil which fairness notions suit this task most. For this, we scan recent literature proposing guidelines as to which fairness notion to use and apply these guidelines onto APP. Our findings suggest equalised odds as most suitable notion for APP, based on APP's WYSIWYG worldview as well as potential long-term improvements for the population.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 37 references that are in the map. First posted on arXiv 29 Sep 2022.

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References · 15

  1. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  2. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  3. 2016Fair prediction with disparate impact: A study of bias in recidivism prediction instrumentscited by 671
  4. 2016Inherent Trade-Offs in the Fair Determination of Risk Scorescited by 582
  5. 2017On Fairness and Calibrationcited by 406
  6. 2018A comparative study of fairness-enhancing interventions in machine learningcited by 208
  7. 2018Delayed Impact of Fair Machine Learningcited by 183
  8. 2020Algorithmic Fairnesscited by 143
  9. 2020Algorithmic Fairness in Educationcited by 44
  10. 2020Algorithmic Fairness from a Non-ideal Perspectivecited by 30
  11. 2020Machine learning fairness notions: Bridging the gap with real-world applicationscited by 19
  12. 2021Towards Equity and Algorithmic Fairness in Student Grade Predictioncited by 13
3 more
  1. 2021Should College Dropout Prediction Models Include Protected Attributes?cited by 11
  2. 2017Big Data, Data Science, and Civil Rightscited by 3
  3. 2022The Equity Framework: Fairness Beyond Equalized Predictive Outcomescited by 2

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