mlsanityData to 7 Oct 2026

Fairness in representation: quantifying stereotyping as a representational harm

arXiv 1901.09565 ↗First posted 28 Jan 2019cs.LG stat.MLcited by 26

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Abstract (arXiv)

While harms of allocation have been increasingly studied as part of the subfield of algorithmic fairness, harms of representation have received considerably less attention. In this paper, we formalize two notions of stereotyping and show how they manifest in later allocative harms within the machine learning pipeline. We also propose mitigation strategies and demonstrate their effectiveness on synthetic datasets.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jan 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 6; 2023: 7; 2024: 3; 2025: 3; 2026: 1.

26 papers.

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  1. 2021The Values Encoded in Machine Learning Researchcited by 172
  2. 2021Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communitiescited by 40
  3. 2021Your fairness may vary: Pretrained language model fairness in toxic text classificationcited by 38
  4. 2022Measuring Representational Harms in Image Captioningcited by 36
  5. 2023On The Impact of Machine Learning Randomness on Group Fairnesscited by 26
  6. 2023Bias and Fairness in Chatbots: An Overviewcited by 20
  7. 2025Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)cited by 19
  8. 2022The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learningcited by 17
  9. 2022Gender Stereotyping Impact in Facial Expression Recognitioncited by 8
  10. 2023Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policycited by 7
  11. 2023An Empirical Investigation into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classificationcited by 7
  12. 2021Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instabilitycited by 5
14 more
  1. 2021Obstructing Classification via Projectioncited by 5
  2. 2021Feature-based Individual Fairness in k-Clusteringcited by 4
  3. 2023Muslim-Violence Bias Persists in Debiased GPT Modelscited by 4
  4. 2024Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Wayscited by 4
  5. 2022It's Not Fairness, and It's Not Fair: The Failure of Distributional Equality and the Promise of Relational Equality in Complete-Information Hiring Gamescited by 3
  6. 2023An Investigation of Representation and Allocation Harms in Contrastive Learningcited by 2
  7. 2023Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systemscited by 2
  8. 2024Multi-Group Proportional Representation in Retrievalcited by 2
  9. 2025Unequal Voices: How LLMs Construct Constrained Queer Narrativescited by 2
  10. 2022Explainability for identification of vulnerable groups in machine learning modelscited by 1
  11. 2022Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolinacited by 1
  12. 2024Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policiescited by 1
  13. 2025Mitigation of Gender and Ethnicity Bias in AI-Generated Stories through Model Explanationscited by 1
  14. 2026Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasetscited by 0