mlsanityData to 7 Oct 2026

InsideBias: Measuring Bias in Deep Networks and Application to Face Gender Biometrics

arXiv 2004.06592 ↗First posted 14 Apr 2020cs.CVcited by 31

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Abstract (arXiv)

This work explores the biases in learning processes based on deep neural network architectures. We analyze how bias affects deep learning processes through a toy example using the MNIST database and a case study in gender detection from face images. We employ two gender detection models based on popular deep neural networks. We present a comprehensive analysis of bias effects when using an unbalanced training dataset on the features learned by the models. We show how bias impacts in the activations of gender detection models based on face images. We finally propose InsideBias, a novel method to detect biased models. InsideBias is based on how the models represent the information instead of how they perform, which is the normal practice in other existing methods for bias detection. Our strategy with InsideBias allows to detect biased models with very few samples (only 15 images in our case study). Our experiments include 72K face images from 24K identities and 3 ethnic groups.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Apr 2020.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 6; 2024: 7; 2025: 3; 2026: 3.

31 papers.

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  1. 2021A Comprehensive Study on Face Recognition Biases Beyond Demographicscited by 86
  2. 2023Multimodal Composite Association Score: Measuring Gender Bias in Generative Multimodal Modelscited by 21
  3. 2021Anatomizing Bias in Facial Analysiscited by 18
  4. 2021Balancing Biases and Preserving Privacy on Balanced Faces in the Wildcited by 17
  5. 2024Is My Data in Your AI? Membership Inference Test (MINT) applied to Face Biometricscited by 12
  6. 2025Addressing Bias in LLMs: Strategies and Application to Fair AI-based Recruitmentcited by 12
  7. 2021IFBiD: Inference-Free Bias Detectioncited by 11
  8. 2023Measuring Bias in AI Models: An Statistical Approach Introducing N-Sigmacited by 11
  9. 2024Synthetic Data for the Mitigation of Demographic Biases in Face Recognitioncited by 10
  10. 2023Unlearning with Fisher Maskingcited by 8
  11. 2022Towards Explaining Demographic Bias through the Eyes of Face Recognition Modelscited by 7
  12. 2022Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanismcited by 7
19 more
  1. 2022Explaining Bias in Deep Face Recognition via Image Characteristicscited by 6
  2. 2024SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributescited by 6
  3. 2026Is My Vision-Language Data in Your AI? Membership Inference Test (MINT) Demo 2cited by 6
  4. 2021Improving Fairness in Speaker Recognitioncited by 5
  5. 2024Can the accuracy bias by facial hairstyle be reduced through balancing the training data?cited by 5
  6. 2023Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?cited by 4
  7. 2022A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysiscited by 3
  8. 2024The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognitioncited by 3
  9. 2024Generated Bias: Auditing Internal Bias Dynamics of Text-To-Image Generative Modelscited by 3
  10. 2021There is an elephant in the room: Towards a critique on the use of fairness in biometricscited by 2
  11. 2023Variation of Gender Biases in Visual Recognition Models Before and After Finetuningcited by 2
  12. 2024Comprehensive Equity Index (CEI): Definition and Application to Bias Evaluation in Biometricscited by 2
  13. 2025Balancing Tails when Comparing Distributions: Comprehensive Equity Index (CEI) with Application to Bias Evaluation in Operational Face Biometricscited by 2
  14. 2026Unraveling Machine Behavior by Multi-Level Bias Analysis and Detection: Methodology and Application to Computer Visioncited by 2
  15. 2022Race Bias Analysis of Bona Fide Errors in face anti-spoofingcited by 1
  16. 2023(Un)fair Exposure in Deep Face Rankings at a Distancecited by 1
  17. 2021SELM: Siamese Extreme Learning Machine with Application to Face Biometricscited by 0
  18. 2025Designing and Generating Diverse, Equitable Face Image Datasets for Face Verification Taskscited by 0
  19. 2026Unbiased Model Prediction Without Using Protected Attribute Informationcited by 0