Big Data's Disparate Impact

Cited by (1,102)

Items 101–200 of 1,102

1. Measuring discrimination in algorithmic decision making
   Žliobaitė, Indrė · 2017 · Data Mining and Knowledge Discovery
2. AI-assisted peer review
   Checco, Alessandro, Bracciale, Lorenzo, Loreti, Pierpaolo, Pinfield, Stephen, Bianchi, Giuseppe · 2021 · Humanities and Social Sciences Communications
3. A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects
   Palomares, Iván, Martínez-Cámara, Eugenio, Montes, Rosana, García-Moral, Pablo, Chiachio, Manuel, Chiachio, Juan, Alonso, Sergio, Melero, Francisco J., Molina, Daniel, Fernández, Bárbara et al. · 2021 · Applied Intelligence
4. Algorithmic bias: Senses, sources, solutions
   Sina Fazelpour, David J. Danks · 2021 · Philosophy Compass
5. Data-driven predictions in the science of science
   Aaron J. Clauset, Daniel B. Larremore, Roberta Sinatra · 2017 · Science
6. Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings
   Thomas Manzini, Lim Yao Chong, Alan W. Black, Yulia Tsvetkov · 2019 · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
7. Misinformation, Disinformation, and Online Propaganda
   Guess, Andrew M., Lyons, Benjamin A. · 2020 · Social Media and Democracy
8. Governing Artificial Intelligence to benefit the UN Sustainable Development Goals
   Truby, Jon · 2020 · Sustainable Development
9. The (Im)possibility of fairness: different value systems require different mechanisms for fair decision making
   Friedler, Sorelle A., Scheidegger, Carlos, Venkatasubramanian, Suresh · 2021 · Communications of the ACM
10. Transparent to whom? No algorithmic accountability without a critical audience
    Kemper, Jakko, Kolkman, Daan · 2019 · Information, Communication & Society
11. Algorithmic Decision-Making Based on Machine Learning from Big Data: Can Transparency Restore Accountability?
    de Laat, Paul B. · 2018 · Philosophy & Technology
12. Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy
    Yang, Kaiyu, Qinami, Klint, Fei-Fei, Li, Deng, Jia, Russakovsky, Olga · 2020 · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
13. On the current state of combining human and artificial intelligence for strategic organizational decision making
    Anna Trunk, Hendrik Sebastian Birkel, Evi Hartmann · 2020 · BuR - Business Research
14. Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure
    Hutchinson, Ben, Smart, Andrew, Hanna, Alex, Denton, Remi, Greer, Christina, Kjartansson, Oddur, Barnes, Parker, Mitchell, Margaret · 2021 · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
15. The Fallacy of AI Functionality
    Raji, Inioluwa Deborah, Kumar, I. Elizabeth, Horowitz, Aaron, Selbst, Andrew · 2022 · 2022 ACM Conference on Fairness Accountability and Transparency
16. Embedded EthiCS
    Barbara J. Grosz, David Gray Grant, Kate Vredenburgh, Jeff Behrends, Lily J. Hu, Alison Simmons, Jim Waldo · 2019 · Communications of the ACM
17. Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
    Shelby, Renee, Rismani, Shalaleh, Henne, Kathryn, Moon, AJung, Rostamzadeh, Negar, Nicholas, Paul, Yilla-Akbari, N'Mah, Gallegos, Jess, Smart, Andrew, Garcia, Emilio et al. · 2023 · Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society
18. Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges
    Ras, Gabriëlle, van Gerven, Marcel, Haselager, Pim · 2018 · The Springer Series on Challenges in Machine Learning
19. Towards Intelligent Regulation of Artificial Intelligence
    Miriam Caroline Buiten · 2019 · European Journal of Risk Regulation
20. Big data analytics and enterprises: a bibliometric synthesis of the literature
    Sayantan Khanra, Amandeep Dhir, Matti Mäntymäki · 2020 · Enterprise Information Systems
21. A Qualitative Exploration of Perceptions of Algorithmic Fairness
    Woodruff, Allison, Fox, Sarah E., Rousso-Schindler, Steven, Warshaw, Jeffrey · 2018 · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
22. Adapting computational text analysis to social science (and vice versa)
    Paul DiMaggio · 2015 · Big Data & Society
23. Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
    Celis, L. Elisa, Huang, Lingxiao, Keswani, Vijay, Vishnoi, Nisheeth K. · 2019 · Proceedings of the Conference on Fairness, Accountability, and Transparency
24. Human-Centered Explainable AI: Towards a Reflective Sociotechnical Approach
    Ehsan, Upol, Riedl, Mark O. · 2020 · Lecture Notes in Computer Science
25. A Framework for Understanding Unintended Consequences of Machine Learning
    Harini Suresh, John V. Guttag · 2019
26. Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset
    Matthew Groh, Caleb Harris, Luis R. Soenksen, Felix Lau, Rachel Han, Aerin Kim, Arash Koochek, Omar Badri · 2021 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
27. Re-imagining Algorithmic Fairness in India and Beyond
    Sambasivan, Nithya, Arnesen, Erin, Hutchinson, Ben, Doshi, Tulsee, Prabhakaran, Vinodkumar · 2021 · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
28. On the safety of machine learning: Cyber-physical systems, decision sciences, and data products
    Varshney, Kush R., Alemzadeh, Homa · 2017 · Big Data
29. Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction
    Grgic-Hlaca, Nina, Redmiles, Elissa M., Gummadi, Krishna P., Weller, Adrian · 2018 · Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18
30. Controlling Fairness and Bias in Dynamic Learning-to-Rank
    Marco Morik, Ashudeep Singh, Jessica Hong, T. Joachims · 2020 · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
31. Fairness in Decision-Making — The Causal Explanation Formula
    Junzhe Zhang, Elias Bareinboim · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
32. An Intersectional Definition of Fairness
    Foulds, James R., Islam, Rashidul, Keya, Kamrun Naher, Pan, Shimei · 2020 · 2020 IEEE 36th International Conference on Data Engineering (ICDE)
33. Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective
    Doris Allhutter, Florian Cech, Fabian Fischer, Gabriel Grill, Astrid Mager · 2020 · Frontiers in Big Data
34. Fairness in Learning: Classic and Contextual Bandits
    Joseph, Matthew, Kearns, Michael, Morgenstern, Jamie, Roth, Aaron · 2016 · arXiv
35. Fairness-Aware Explainable Recommendation over Knowledge Graphs
    Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Suresh Shah, Yongfeng Zhang et al. · 2020 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
36. Will algorithms blind people? The effect of explainable AI and decision-Makers’ experience on AI-supported decision-making in government
    Janssen, Marijn, Hartog, Martijn, Matheus, Ricardo, Yi Ding, Aaron, Kuk, George · 2022 · Social Science Computer Review
37. Algorithmic fairness in education
    René F. Kizilcec, Hansol Lee · 2022 · Routledge eBooks
38. Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts
    Metcalf, Jacob, Moss, Emanuel, Watkins, Elizabeth Anne, Singh, Ranjit, Elish, Madeleine Clare · 2021 · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
39. A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices
    Speicher, Till, Heidari, Hoda, Grgic-Hlaca, Nina, Gummadi, Krishna P., Singla, Adish, Weller, Adrian, Zafar, Muhammad Bilal · 2018 · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
40. Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms
    Giovanola, Benedetta, Tiribelli, Simona · 2023 · AI & SOCIETY
41. Fairness in credit scoring: Assessment, implementation and profit implications
    Kozodoi, Nikita, Jacob, Johannes, Lessmann, Stefan · 2022 · European Journal of Operational Research
42. Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem
    Costanza-Chock, Sasha, Raji, Inioluwa Deborah, Buolamwini, Joy · 2022 · 2022 ACM Conference on Fairness Accountability and Transparency
43. What does it mean to 'solve' the problem of discrimination in hiring?: social, technical and legal perspectives from the UK on automated hiring systems
    Sánchez-Monedero, Javier, Dencik, Lina, Edwards, Lilian · 2020 · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
44. Evaluating the Fairness of Predictive Student Models Through Slicing Analysis
    Josh Gardner, Christopher A. Brooks, Ryan S. Baker · 2019 · International Conference on Learning Analytics and Knowledge (LAK)
45. Local Rule-Based Explanations of Black Box Decision Systems
    Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Dino Pedreschi, Franco Turini, Fosca Giannotti · 2018 · arXiv (Cornell University)
46. Why is my classifier discriminatory?
    Chen, Irene, Johansson, Fredrik D., Sontag, David · 2018 · arXiv
47. From individual to group privacy in big data analytics
    Mittelstadt, Brent · 2017 · Philosophy & Technology
48. Democratizing Algorithmic Fairness
    Wong, Pak-Hang · 2020 · Philosophy & Technology
49. Big Data and discrimination: perils, promises and solutions. A systematic review
    Maddalena Favaretto, Eva De Clercq, Bernice S. Elger · 2019 · Journal Of Big Data
50. Transparency: Motivations and Challenges
    Weller, Adrian · 2019 · Lecture Notes in Computer Science
51. What is your definition of Big Data? Researchers’ understanding of the phenomenon of the decade
    Maddalena Favaretto, Eva De Clercq, Christophe Olivier Schneble, Bernice S. Elger · 2020 · PLoS ONE
52. Research Frontiers in Information Retrieval
    J. Shane Culpepper, Fernando Díaz, Mark D. Smucker · 2018 · ACM SIGIR Forum
53. Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science
    Neff, Gina, Tanweer, Anissa, Fiore-Gartland, Brittany, Osburn, Laura · 2017 · Big Data
54. The Ethics of Emotion in Artificial Intelligence Systems
    Luke Stark, Jesse Hoey · 2021 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
55. To do more, better, faster and more cheaply: using big data in public administration
    Mariusz Maciejewski · 2016 · International Review of Administrative Sciences
56. Decision augmentation and automation with artificial intelligence: Threat or opportunity for managers?
    Michael Leyer, Sabrina Schneider · 2021 · Business Horizons
57. Lessons learned from AI ethics principles for future actions
    Hickok, Merve · 2021 · AI and Ethics
58. Ordinalization
    Marion Fourcade · 2016 · Sociological Theory
59. Who is the "Human" in Human-Centered Machine Learning
    Stevie Chancellor, E. Baumer, M. de Choudhury · 2019 · Proc. ACM Hum. Comput. Interact.
60. Addressing algorithmic bias and the perpetuation of health inequities: An AI bias aware framework
    Agarwal, R., Bjarnadottir, M., Rhue, L., Dugas, M., Crowley, K., Clark, J., Gao, G. · 2023 · Health Policy and Technology
61. Algorithmic realism: expanding the boundaries of algorithmic thought
    Green, Ben, Viljoen, Salomé · 2020 · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
62. Administration by Algorithm? Public Management meets Public Sector Machine Learning
    Veale, Michael, Brass, Irina · 2019
63. The sharing economy and digital discrimination: The case of Airbnb
    Mingming Cheng, Carmel T. Foley · 2017 · International Journal of Hospitality Management
64. Designing Fair Ranking Schemes
    Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, Gautam Das · 2019 · ACM SIGMOD International Conference on Management of Data (SIGMOD)
65. Delayed Impact of Fair Machine Learning
    Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt · 2019 · International Joint Conference on Artificial Intelligence
66. Fairwalk: Towards Fair Graph Embedding
    Tahleen Rahman, Bartlomiej Surma, Michael Backes A, Yang Zhang · 2019 · International Joint Conference on Artificial Intelligence
67. Fair AI
    Stefan Feuerriegel, Mateusz Dolata, Gerhard Schwabe · 2020 · Business & Information Systems Engineering
68. A sociotechnical view of algorithmic fairness
    Mateusz Dolata, Stefan Feuerriegel, Gerhard Schwabe · 2021 · Information Systems Journal
69. On Formalizing Fairness in Prediction with Machine Learning
    Pratik Gajane, Pechenizkiy, Mykola · 2017 · arXiv (Cornell University)
70. Machine learning, artificial neural networks and social research
    Giovanni Di Franco, Michele Santurro · 2020 · Quality & Quantity
71. Implications of AI (un-)fairness in higher education admissions: the effects of perceived AI (un-)fairness on exit, voice and organizational reputation
    Marcinkowski, Frank, Kieslich, Kimon, Starke, Christopher, Lünich, Marco · 2020 · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
72. Investigating the Impact of Gender on Rank in Resume Search Engines
    Chen, Le, Ma, Ruijun, Hannák, Anikó, Wilson, Christo · 2018 · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
73. Discrimination, artificial intelligence, and algorithmic decision-making
    Borgesius, Frederik Zuiderveen · 2025 · arXiv
74. AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
    Chen, Pu, Wu, Linna, Wang, Lei · 2023 · Applied Sciences
75. Ethical machines: The human-centric use of artificial intelligence
    Lepri, Bruno, Oliver, Nuria, Pentland, Alex · 2021 · iScience
76. Artificial intelligence policy in India: a framework for engaging the limits of data-driven decision-making
    Marda, Vidushi · 2018 · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
77. The Moral Limits of Predictive Practices: The Case of Credit-Based Insurance Scores
    Barbara Kiviat · 2019 · American Sociological Review
78. Towards Debiasing Sentence Representations
    Paul Pu Liang, Irene Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, Louis‐Philippe Morency · 2020 · Proceedings of the conference - Association for Computational Linguistics. Meeting
79. Between Subjectivity and Imposition: Power Dynamics in Data Annotation for Computer Vision
    Miceli, Milagros, Schuessler, Martin, Yang, Tianling · 2020 · Proceedings of the ACM on Human-Computer Interaction
80. Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media
    Kulshrestha, Juhi, Eslami, Motahhare, Messias, Johnnatan, Zafar, Muhammad Bilal, Ghosh, Saptarshi, Gummadi, Krishna P., Karahalios, Karrie · 2017 · Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
81. Mathematical optimization in classification and regression trees
    Emilio Carrizosa, Cristina Molero-Río, Dolores Romero Morales · 2021 · Top
82. Auditing of AI: Legal, Ethical and Technical Approaches
    Mökander, Jakob · 2023 · Digital Society
83. Fairness, Equality, and Power in Algorithmic Decision-Making
    Maximilian Kasy, Rediet Abebe · 2021 · Conference on Fairness, Accountability and Transparency
84. Artificial intelligence and crime: A primer for criminologists
    Keith Hayward, Matthijs M. Maas · 2020 · Crime Media Culture An International Journal
85. Measuring algorithmically infused societies
    Wagner, Claudia, Strohmaier, Markus, Olteanu, Alexandra, Kıcıman, Emre, Contractor, Noshir, Eliassi-Rad, Tina · 2021 · Nature
86. The downside of digital inclusion: Expectations and experiences of privacy and surveillance among marginal Internet users
    Seeta Peña Gangadharan · 2015 · New Media & Society
87. The future impact of artificial intelligence on humans and human rights
    Livingston, Steven, Risse, Mathias · 2019 · Ethics & International Affairs
88. Predicting sex from retinal fundus photographs using automated deep learning
    Edward Korot, Nikolas Pontikos, Xiaoxuan Liu, Siegfried K. Wagner, Livia Faes, Josef Christian Huemer, Konstantinos Balaskas, Alastair Keith Denniston, Anthony P. Khawaja, Pearse Andrew Keane · 2021 · Scientific Reports
89. Diversity in Big Data: A Review
    Drosou, Marina, Jagadish, H.V., Pitoura, Evaggelia, Stoyanovich, Julia · 2017 · Big Data
90. An algorithm for removing sensitive information: Application to race-independent recidivism prediction
    Johndrow, James E., Lum, Kristian · 2019 · The Annals of Applied Statistics
91. The Social Cost of Strategic Classification
    Smitha Milli, John P. Miller, Anca D. Dragan, Moritz Hardt · 2019 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
92. Towards Personalized Fairness based on Causal Notion
    Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang · 2021 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
93. Software fairness
    Yuriy Brun, Alexandra Meliou · 2018 · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE)
94. Understanding artificial intelligence ethics and safety
    David Leslie · 2019 · arXiv (Cornell University)
95. Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities
    Lim, Hazel Si Min, Taeihagh, Araz · 2019 · Sustainability
96. A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare
    Saxena, Devansh, Badillo-Urquiola, Karla, Wisniewski, Pamela J., Guha, Shion · 2021 · Proceedings of the ACM on Human-Computer Interaction
97. Building and Auditing Fair Algorithms: A Case Study in Candidate Screening
    Wilson, Christo, Ghosh, Avijit, Jiang, Shan, Mislove, Alan, Baker, Lewis, Szary, Janelle, Trindel, Kelly, Polli, Frida · 2021 · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
98. Ethical Considerations in AI-Based Recruitment
    Dena F. Mujtaba, Nihar R. Mahapatra · 2019 · IEEE International Symposium on Technology and Society (ISTAS)
99. Artificial intelligence explainability: the technical and ethical dimensions
    McDermid, John A., Jia, Yan, Porter, Zoe, Habli, Ibrahim · 2021 · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
100. Identifying and Correcting Label Bias in Machine Learning
     Jiang, Heinrich, Nachum, Ofir · 2019 · arXiv