AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
Cites (296)
Items 201–256 of 256
- Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methodsYing Sun, Fariborz Haghighat, Benjamin C. M. Fung · 2021 · Energy
- Ethical Chatbot Design for Reducing Negative Effects of Biased Data and Unethical ConversationsBang, Junseong, Kim, Sineae, Nam, Jang Won, Yang, Dong-Geun · 2021 · 2021 International Conference on Platform Technology and Service (PlatCon)
- Toward a framework for public accountability in education reformHutt, Ethan, Polikoff, Morgan S. · 2020 · Educational Researcher
- Counterfactual learning for recommender systemZhenhua Dong, Hong Chun Zhu, Pengxiang Cheng · 2020
- Fairness improvement for black-box classifiers with Gaussian processDang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh · 2021 · Information Sciences
- Making Artificial Intelligence Transparent: Fairness and the Problem of Proxy VariablesRichard Warner, Robert H. Sloan · 2021 · Criminal Justice Ethics
- FAIR : Fairness‐aware information retrieval evaluationGao, Ruoyuan, Ge, Yingqiang, Shah, Chirag · 2022 · Journal of the Association for Information Science and Technology
- Standardizing fairness-evaluation procedures: interdisciplinary insights on machine learning algorithms in creditworthiness assessments for small personal loansGenovesi, Sergio, Mönig, Julia Maria, Schmitz, Anna, Poretschkin, Maximilian, Akila, Maram, Kahdan, Manoj, Kleiner, Romina, Krieger, Lena, Zimmermann, Alexander · 2024 · AI and Ethics
- How to improve fairness perceptions of AI in hiring: The crucial role of positioning and sensitizationHunkenschroer, Anna · 2021 · AI Ethics Journal
- Model Agnostic Sample Reweighting for Out-of-Distribution LearningZhou, Xiao, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang · 2023 · arXiv (Cornell University)
- Paired-Consistency: An Example-Based Model-Agnostic Approach to Fairness Regularization in Machine LearningYair Horesh, Noa Haas, Elhanan Mishraky, Yehezkel S. Resheff, Shir Meir Lador · 2020 · Communications in computer and information science
- Path-Specific Counterfactual FairnessChiappa, Silvia · 2019 · Proceedings of the AAAI Conference on Artificial Intelligence
- On Learning Fairness and Accuracy on Multiple SubgroupsChangjian Shui, Gezheng Xu, Qi Chen · 2022 · arXiv (Cornell University)
- Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield PredictionErhu He, Yiqun Xie, Licheng Liu, Weiye Chen, Zhenong Jin, Xiaowei Jia · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
- Fairness through Aleatoric UncertaintyAnique Tahir, Lu Cheng, Huan Liu · 2023 · ACM International Conference on Information and Knowledge Management (CIKM)
- Approaches to Improve Fairness when Deploying AI-based Algorithms in Hiring – Using a Systematic Literature Review to Guide Future ResearchJonas Rieskamp, Lennart Hofeditz, Milad Mirbabaie, Stefan Stieglitz · 2023 · Hawaii International Conference on System Sciences (HICSS)
- FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparencyKacper Sokol, Raúl Santos‐Rodríguez, Peter A. Flach · 2022 · Software Impacts
- On Improving Fairness of AI Models with Synthetic Minority Oversampling TechniquesYan Zhou, Murat Kantarcıoğlu, Chris Clifton · 2023 · Society for Industrial and Applied Mathematics eBooks
- Measuring Fairness of Rankings under Noisy Sensitive InformationAzin Ghazimatin, Matthäus Kleindeßner, Chris Russell, Ziawasch Abedjan, Jacek Golebiowski · 2022 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- Fairness-aware Multi-view ClusteringLecheng Zheng, Yada Zhu, Jingrui He · 2023 · Society for Industrial and Applied Mathematics eBooks
- How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate TreatmentLeijie Wang, Haiyi Zhu · 2022 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- Professionalism and homophily bias: A study of Airbnb stay choice and review positivityChao Yu, Wang Liao · 2023 · International Journal of Hospitality Management
- FAccT-Check on AI regulation: Systematic Evaluation of AI Regulation on the Example of the Legislation on the Use of AI in the Public Sector in the German Federal State of Schleswig-HolsteinSimbeck, Katharina · 2022 · 2022 ACM Conference on Fairness Accountability and Transparency
- Can We Improve Model Robustness through Secondary Attribute Counterfactuals?Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H., Alex Beutel · 2021 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
- The generalizability of pre-processing techniques on the accuracy and fairness of data-driven building models: A case studyYing Sun, Benjamin C. M. Fung, Fariborz Haghighat · 2022 · Energy and Buildings
- Understanding Decision Subjects' Fairness Perceptions and Retention in Repeated Interactions with AI-Based Decision SystemsGemalmaz, Meric Altug, Yin, Ming · 2022 · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
- Assessing data bias in visual surveys from a cetacean monitoring programmeOliveira-Rodrigues, Cláudia, Correia, Ana M., Valente, Raul, Gil, Ágatha, Gandra, Miguel, Liberal, Marcos, Rosso, Massimiliano, Pierce, Graham, Sousa-Pinto, Isabel · 2022 · Scientific Data
- Misinformation Detection Algorithms and Fairness across Political Ideologies: The Impact of Article Level LabelingJinkyung Park, Rahul Dev Ellezhuthil, Joseph Isaac, Christoph Mergerson, Lauren Feldman, Vivek Kumar Singh · 2023 · ACM Web Science Conference (WebSci)
- Bias, Fairness, and Accountability with AI and ML AlgorithmsNengfeng Zhou, Zach Zhang, Vijayan N. Nair, Harsh Singhal, Jie Chen, Agus Sudjianto · 2021 · arXiv (Cornell University)
- Homophily, Biased Attention, and the Gender Gap in ScienceMarc Lerchenmueller, Karin Hoisl C, Leo Schmallenbach · 2019 · Academy of Management Proceedings
- Beyond Bias: Artificial Intelligence and Social JusticeRobert H. Sloan, Richard Warner · 2020 · SSRN Electronic Journal
- Fairness in Data WranglingLacramioara Mazilu, Norman W. Paton, Νικόλαος Κωνσταντίνου, Alvaro A. A. Fernandes · 2020 · IEEE International Conference on Information Reuse and Integration (IRI)
- In-Processing fairness improvement methods for regression Data-Driven building Models: Achieving uniform energy predictionYing Sun, Benjamin C. M. Fung, Fariborz Haghighat · 2022 · Energy and Buildings
- Practitioners’ Corner ∙ Anonymisation and Re-Identification Risk for Voice DataMoretón, A., Jaramillo, A. · 2021 · European Data Protection Law Review
- Revisiting Group Fairness Metrics: The Effect of NetworksAnay Mehrotra, Jeff Sachs, L. Elisa Celis · 2022 · Proceedings of the ACM on Human-Computer Interaction
- Asynchronous Semi-Supervised Federated Learning with Provable Convergence in Edge ComputingNan Yang, Dong Yuan, Yuning Zhang, Yongkun Deng, Wei Bao · 2022 · IEEE Network
- Fairness in Forecasting of Observations of Linear Dynamical SystemsQuan Zhi Zhou, Jakub Mareček, Robert Noel Shorten · 2023 · Journal of Artificial Intelligence Research
- Provable Detection of Propagating Sampling Bias in Prediction ModelsPavan Ravishankar, Qingyu Mo, Edward McFowland, Daniel B. Neill · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
- Introduction to AI FairnessYunfeng Zhang, Rachel Bellamy, Moninder Singh · 2020 · Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA)
- Eliminating Disparate Treatment in ModelingDaniel M. Tom · 2023
- Confirmation Bias as a Mechanism to Focus Attention Enhances Signal DetectionMichael Vogrin, Guilherme Maia de Oliveira Wood, Thomas Schmickl · 2023 · Journal of Artificial Societies and Social Simulation
- A Social Movement History of Title VII Disparate Impact AnalysisSusan D. Carle · 2010 · SSRN Electronic Journal
- Adversarial Reweighting for Speaker Verification FairnessMinho Jin, Chelsea J.‐T. Ju, Zeya Chen, Yi Chieh Liu, Jasha Droppo, Andreas Stolcke · 2022 · Interspeech (USB)
- Perspectives on clinical trial data transparency and disclosureAlemayehu, Demissie, Anziano, Richard J., Levenstein, Marcia · 2014 · Contemporary Clinical Trials
- FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence AnalysisNan Yang, Yuan, Dong, Charles Z Liu · 2023 · arXiv (Cornell University)
- De-identification as public policyGilad L. Rosner · 2020 · Journal of data protection & privacy.
- Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural NetworksMichael Lohaus, Matthäus Kleindeßner, Krishnaram Kenthapadi · 2022 · arXiv (Cornell University)
- Learning Fair Classifiers via Min-Max F-divergence RegularizationMeiyu Zhong, Ravi Tandon · 2023 · Allerton Conference on Communication, Control, and Computing
- Exploring Biases and Prejudice of Facial Synthesis via Semantic Latent SpaceXuyang Shen, Jo Plested, Sabrina Caldwell · 2021
- Clinical trial transparency regulations: Implications to various scholarly publishing stakeholdersAbdul Razack, Habeeb Ibrahim, Aranjani, Jesil Mathew, Mathew, Sam T · 2022 · Science and Public Policy
- How Do Algorithmic Fairness Metrics Align with Human Judgement? A Mixed-Initiative System for Contextualized Fairness AssessmentConstantin, Rares, Duck, Moritz, Alexandrov, Anton, Matosevic, Patrik, Keidar, Daphna, El-Assady, Mennatallah · 2022 · 2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)
- Dynamic Fair Node Representation LearningÖykü Deniz Köse, Yanning Shen · 2023 · IEEE International Conference on Acoustics Speech and Signal Processing
- Introduction to Prescriptive AIAkshay Kulkarni, Adarsha Shivananda, Avinash Manure · 2023 · Apress eBooks
- Fairness in Federated Learning for Spatial-Temporal ApplicationsAfra J. Mashhadi, Alex Kyllo, Reza M. Parizi · 2022 · arXiv (Cornell University)
- Towards Trustworthy Representation LearningSheng Li · 2023 · Society for Industrial and Applied Mathematics eBooks
- Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in AfricaMercy Asiedu, Awa Dieng, Abigail Oppong · 2023 · arXiv (Cornell University)