FairSight: Visual Analytics for Fairness in Decision Making
Not on the map. Why?
Abstract (arXiv)
Data-driven decision making related to individuals has become increasingly pervasive, but the issue concerning the potential discrimination has been raised by recent studies. In response, researchers have made efforts to propose and implement fairness measures and algorithms, but those efforts have not been translated to the real-world practice of data-driven decision making. As such, there is still an urgent need to create a viable tool to facilitate fair decision making. We propose FairSight, a visual analytic system to address this need; it is designed to achieve different notions of fairness in ranking decisions through identifying the required actions -- understanding, measuring, diagnosing and mitigating biases -- that together lead to fairer decision making. Through a case study and user study, we demonstrate that the proposed visual analytic and diagnostic modules in the system are effective in understanding the fairness-aware decision pipeline and obtaining more fair outcomes.
Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Aug 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 11; 2022: 17; 2023: 13; 2024: 9; 2025: 8; 2026: 1.
59 papers.
Sort:
By area:
- 2021A survey on datasets for fairness-aware machine learningcited by 157
- 2021Robustness Gym: Unifying the NLP Evaluation Landscapecited by 108
- 2021The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Modelscited by 63
- 2022Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkitscited by 34
- 2021M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysiscited by 29
- 2022The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizationscited by 29
- 2021Discovering and Validating AI Errors With Crowdsourced Failure Reportscited by 28
- 2022Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethicscited by 28
- 2023Visual Analytics For Machine Learning: A Data Perspective Surveycited by 25
- 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
- 2022De-biasing "bias" measurementcited by 20
- 2022Symphony: Composing Interactive Interfaces for Machine Learningcited by 18
38 more
- 2022D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Biascited by 18
- 2023A Critical Survey on Fairness Benefits of Explainable AIcited by 16
- 2022Towards Involving End-users in Interactive Human-in-the-loop AI Fairnesscited by 12
- 2024How to be fair? A study of label and selection biascited by 11
- 2022Towards Responsible AI: A Design Space Exploration of Human-Centered Artificial Intelligence User Interfaces to Investigate Fairnesscited by 9
- 2021WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddingscited by 8
- 2021End-To-End Bias Mitigation: Removing Gender Bias in Deep Learningcited by 6
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inferencecited by 6
- 2024Exploring Empty Spaces: Human-in-the-Loop Data Augmentationcited by 6
- 2023Finspector: A Human-Centered Visual Inspection Tool for Exploring and Comparing Biases among Foundation Modelscited by 5
- 2024ASAP: Interpretable Analysis and Summarization of AI-generated Image Patterns at Scalecited by 5
- 2024EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholderscited by 5
- 2023Diagrammatization and Abduction to Improve AI Interpretability With Domain-Aligned Explanations for Medical Diagnosiscited by 4
- 2025BIASINSPECTOR: Detecting Bias in Structured Data through LLM Agentscited by 4
- 2023TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanationscited by 3
- 2023Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AIcited by 3
- 2023FairCompass: Operationalising Fairness in Machine Learningcited by 3
- 2022How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategiescited by 2
- 2023ESCAPE: Countering Systematic Errors from Machine's Blind Spots via Interactive Visual Analysiscited by 2
- 2023MLHOps: Machine Learning for Healthcare Operationscited by 2
- 2023Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalitiescited by 2
- 2023Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systemscited by 2
- 2023VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisionscited by 1
- 2024Mapping the Potential of Explainable AI for Fairness Along the AI Lifecyclecited by 1
- 2024Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systemscited by 1
- 2024Versatile Ordering Network: An Attention-based Neural Network for Ordering Across Scales and Quality Metricscited by 1
- 2025Towards Multi-Stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-matching Systemcited by 1
- 2025FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairnesscited by 1
- 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Taskscited by 1
- 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
- 2022Visual Identification of Problematic Bias in Large Label Spacescited by 0
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
- 2022Trinary Tools for Continuously Valued Binary Classifierscited by 0
- 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
- 2022A Design Space for Explainable Ranking and Ranking Modelscited by 0
50 most cited of 59 All 59 (JSON)
- 2026Transferable XAI: Relating Understanding Across Domains with Explanation Transfer14 Feb 2026
- 2025Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space25 Oct 2025
- 2025"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessment22 Sep 2025
- 2025Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models31 Jul 2025
- 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks3 Jul 2025
- 2025Perception-Driven Bias Detection in Machine Learning via Crowdsourced Visual Judgment21 May 2025
- 2025FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness22 Apr 2025
- 2025BIASINSPECTOR: Detecting Bias in Structured Data through LLM Agents7 Apr 2025
- 2025Towards Multi-Stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-matching System3 Mar 2025
- 2024Versatile Ordering Network: An Attention-based Neural Network for Ordering Across Scales and Quality Metrics17 Dec 2024
- 2024Exploring Empty Spaces: Human-in-the-Loop Data Augmentation1 Oct 2024
- 2024Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems10 Sep 2024
38 more
- 2024EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders16 Jul 2024
- 2024Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle29 Apr 2024
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference3 Apr 2024
- 2024ASAP: Interpretable Analysis and Summarization of AI-generated Image Patterns at Scale3 Apr 2024
- 2024How to be fair? A study of label and selection bias21 Mar 2024
- 2024FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition9 Mar 2024
- 2023Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems29 Dec 2023
- 2023FairCompass: Operationalising Fairness in Machine Learning27 Dec 2023
- 2023Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AI13 Dec 2023
- 2023A Critical Survey on Fairness Benefits of Explainable AI15 Oct 2023
- 2023Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities16 Aug 2023
- 2023VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions26 Jul 2023
- 2023TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanations19 Jul 2023
- 2023Visual Analytics For Machine Learning: A Data Perspective Survey15 Jul 2023
- 2023Finspector: A Human-Centered Visual Inspection Tool for Exploring and Comparing Biases among Foundation Models26 May 2023
- 2023MLHOps: Machine Learning for Healthcare Operations4 May 2023
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGram16 Mar 2023
- 2023ESCAPE: Countering Systematic Errors from Machine's Blind Spots via Interactive Visual Analysis16 Mar 2023
- 2023Diagrammatization and Abduction to Improve AI Interpretability With Domain-Aligned Explanations for Medical Diagnosis2 Feb 2023
- 2022The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations22 Dec 2022
- 2022Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks21 Dec 2022
- 2022D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias10 Aug 2022
- 2022Using Graph Neural Networks for Program Termination28 Jul 2022
- 2022How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies11 Jul 2022
- 2022Towards Responsible AI: A Design Space Exploration of Human-Centered Artificial Intelligence User Interfaces to Investigate Fairness1 Jun 2022
- 2022A Design Space for Explainable Ranking and Ranking Models27 May 2022
- 2022Explanation-Guided Fairness Testing through Genetic Algorithm16 May 2022
- 2022Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits13 May 2022
- 2022De-biasing "bias" measurement11 May 2022
- 2022Towards Involving End-users in Interactive Human-in-the-loop AI Fairness22 Apr 2022
- 2022Trinary Tools for Continuously Valued Binary Classifiers18 Apr 2022
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks8 Mar 2022
- 2022Symphony: Composing Interactive Interfaces for Machine Learning18 Feb 2022
- 2022Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics17 Feb 2022
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors6 Feb 2022
- 2022Visual Identification of Problematic Bias in Large Label Spaces17 Jan 2022
- 2021A survey on datasets for fairness-aware machine learning1 Oct 2021
- 2021A Sociotechnical View of Algorithmic Fairness27 Sep 2021
50 newest of 59 All 59 (JSON)
- 2021A survey on datasets for fairness-aware machine learningcited by 157
- 2021Robustness Gym: Unifying the NLP Evaluation Landscapecited by 108
- 2021The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Modelscited by 63
- 2022Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkitscited by 34
- 2021M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysiscited by 29
- 2022The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizationscited by 29
- 2021Discovering and Validating AI Errors With Crowdsourced Failure Reportscited by 28
- 2022Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethicscited by 28
- 2023Visual Analytics For Machine Learning: A Data Perspective Surveycited by 25
- 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
- 2022De-biasing "bias" measurementcited by 20
- 2022Symphony: Composing Interactive Interfaces for Machine Learningcited by 18
12 most cited of 56 All 56 (JSON)
- 2026Transferable XAI: Relating Understanding Across Domains with Explanation Transfer14 Feb 2026
- 2025Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space25 Oct 2025
- 2025"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessment22 Sep 2025
- 2025Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models31 Jul 2025
- 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks3 Jul 2025
- 2025Perception-Driven Bias Detection in Machine Learning via Crowdsourced Visual Judgment21 May 2025
- 2025FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness22 Apr 2025
- 2025Towards Multi-Stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-matching System3 Mar 2025
- 2024Versatile Ordering Network: An Attention-based Neural Network for Ordering Across Scales and Quality Metrics17 Dec 2024
- 2024Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems10 Sep 2024
- 2024EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders16 Jul 2024
- 2024Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle29 Apr 2024
12 newest of 56 All 56 (JSON)