mlsanityData to 7 Oct 2026

AI Fairness via Domain Adaptation

arXiv 2104.01109 ↗First posted 15 Mar 2021cs.CV cs.LGcited by 8

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Abstract (arXiv)

While deep learning (DL) approaches are reaching human-level performance for many tasks, including for diagnostics AI, the focus is now on challenges possibly affecting DL deployment, including AI privacy, domain generalization, and fairness. This last challenge is addressed in this study. Here we look at a novel method for ensuring AI fairness with respect to protected or sensitive factors. This method uses domain adaptation via training set enhancement to tackle bias-causing training data imbalance. More specifically, it uses generative models that allow the generation of more synthetic training samples for underrepresented populations. This paper applies this method to the use case of detection of age related macular degeneration (AMD). Our experiments show that starting with an originally biased AMD diagnostics model the method has the ability to improve fairness.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 19 of its 28 references that are in the map. First posted on arXiv 15 Mar 2021.

Builds on

19 of 28 references.

References · 19

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  2. 2013Auto-Encoding Variational Bayescited by 3,980
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  4. 2016Membership Inference Attacks against Machine Learning Modelscited by 2,221
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7 more
  1. 2017InfoVAE: Information Maximizing Variational Autoencoderscited by 124
  2. 2018Learning Controllable Fair Representationscited by 83
  3. 2018Achieving Fairness through Adversarial Learning: an Application to Recidivism Predictioncited by 77
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  5. 2017Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learningcited by 63
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Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 2; 2025: 2.

8 papers.

  1. 2024FairCLIP: Harnessing Fairness in Vision-Language Learningcited by 69
  2. 2022Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Reviewcited by 27
  3. 2021Algorithm Fairness in AI for Medicine and Healthcarecited by 21
  4. 2023FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classificationcited by 18
  5. 2022Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imagingcited by 5
  6. 2024Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learningcited by 1
  7. 2025Mitigating Algorithmic Bias in Multiclass CNN Classifications Using Causal Modelingcited by 0
  8. 2025A Gray Literature Study on Fairness Requirements in AI-enabled Software Engineeringcited by 0