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Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
11 references·16 citing·32 second hop
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations (2019)Balanced Datasets Are Not Enough: Estimat…Women Also Snowboard: Overcoming Bias in Captioning Models (2018)Women Also Snowboard: Overcom…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…A Reductions Approach to Fair Classification (2018)A Reductions Approach to Fair…Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Men Also Like Shopping: Reduc…Counterfactual Fairness (2017)Counterfactual FairnessEquality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Unequal Representation and Gender Stereotypes in Image Search Results for Occupations (2015)Unequal Representation and Ge…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Learning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessA Comprehensive Review of Bias in Deep Learning Models: Methods, Impacts, and Future Directions (2024)A Comprehensive Review of Bia…Gender bias perpetuation and mitigation in AI technologies: challenges and opportunities (2023)Gender bias perpetuation and …In-Processing Modeling Techniques for Machine Learning Fairness: A Survey (2022)In-Processing Modeling Techni…Exploring gender biases in ML and AI academic research through systematic literature review (2022)Exploring gender biases in ML…A survey on bias in visual datasets (2022)A survey on bias in visual da…Understanding and Mitigating Annotation Bias in Facial Expression Recognition (2021)Understanding and Mitigating …Understanding and Evaluating Racial Biases in Image Captioning (2021)Understanding and Evaluating …Representation Learning with Statistical Independence to Mitigate Bias (2021)Representation Learning with …Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (2021)Image Representations Learned…Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies (2021)Harms of Gender Exclusivity a…Fair Attribute Classification through Latent Space De-biasing (2021)Fair Attribute Classification…EnD: Entangling and Disentangling deep representations for bias correction (2021)EnD: Entangling and Disentang…Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Towards Fairness in Visual Re…Investigating Bias and Fairness in Facial Expression Recognition (2020)Investigating Bias and Fairne…Fairness in Deep Learning: A Computational Perspective (2020)Fairness in Deep Learning: A …Demographic Bias in Biometrics: A Survey on an Emerging Challenge (2020)Demographic Bias in Biometric…Uniform Guidelines on Employee Selection Procedures (2007)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)A Survey on Bias and Fairness in Machine Learning (2021)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Bias in computer systems (1996)Stereotype Threat and Women's Math Performance (1999)Gender and the Career Choice Process: The Role of Biased Self‐Assessments (2001)Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search (2019)Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale (2023)Ethics and discrimination in artificial intelligence-enabled recruitment practices (2023)Big Data's Disparate Impact (2014)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Structural Equations with Latent Variables. (1991)Testing Structural Equation Models. (1995)Fairness definitions explained (2018)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Semantics derived automatically from language corpora contain human-like biases (2017)Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018)A Review on Fairness in Machine Learning (2022)Bias and Fairness in Large Language Models: A Survey (2024)Algorithmic Decision Making and the Cost of Fairness (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)REPAIR: Removing Representation Bias by Dataset Resampling (2019)Towards fairer datasets (2020)
this work references cited by second hop

References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2012Fairness through awareness3,501 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2013Learning Fair Representations1,126 cited
  • 2017Counterfactual Fairness995 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2015Unequal Representation and Gender Stereotypes in Image Search Results for Occupations509 cited
  • 2018Women Also Snowboard: Overcoming Bias in Captioning Models404 cited
  • 2018A Reductions Approach to Fair Classification364 cited

Cited by

  • 2020Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation285 cited
  • 2020Demographic Bias in Biometrics: A Survey on an Emerging Challenge263 cited
  • 2020Fairness in Deep Learning: A Computational Perspective216 cited
  • 2020Investigating Bias and Fairness in Facial Expression Recognition174 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2023Gender bias perpetuation and mitigation in AI technologies: challenges and opportunities169 cited
  • 2021Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases159 cited
  • 2022A survey on bias in visual datasets137 cited
  • 2021Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies125 cited
  • 2021Fair Attribute Classification through Latent Space De-biasing123 cited
  • 2021Understanding and Mitigating Annotation Bias in Facial Expression Recognition120 cited
  • 2024A Comprehensive Review of Bias in Deep Learning Models: Methods, Impacts, and Future Directions103 cited
  • 2022In-Processing Modeling Techniques for Machine Learning Fairness: A Survey99 cited
  • 2022Exploring gender biases in ML and AI academic research through systematic literature review95 cited
  • 2021Representation Learning with Statistical Independence to Mitigate Bias91 cited
  • 2021Understanding and Evaluating Racial Biases in Image Captioning83 cited
  • 2021EnD: Entangling and Disentangling deep representations for bias correction83 cited