Big Data's Disparate Impact

Cited by (1,102)

Items 201–300 of 1,102

1. Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices
   Raghavan, Manish, Barocas, Solon, Kleinberg, Jon, Levy, Karen · 2019 · arXiv
2. Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
   Jennifer Wortman Vaughan · 2018 · Journal of Machine Learning Research
3. Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media
   Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Saptarshi Ghosh, Krishna P. Gummadi, Karrie G. Karahalios · 2017 · arXiv (Cornell University)
4. The fallacy of inscrutability
   Kroll, Joshua A. · 2018 · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
5. Artificial intelligence, physiological genomics, and precision medicine
   Anna Marie Williams, Yong Liu, Kevin R. Regner, Fabrice Jotterand, Pengyuan Liu, Mingyu Liang · 2018 · Physiological Genomics
6. Fairness in Machine Learning: A Survey
   Caton, Simon, Haas, Christian · 2020 · arXiv
7. Human Judgment in algorithmic loops: Individual justice and automated <scp>decision‐making</scp>
   Binns, Reuben · 2022 · Regulation &amp; Governance
8. Adaptive Sensitive Reweighting to Mitigate Bias in Fairness-aware Classification
   Krasanakis, Emmanouil, Spyromitros-Xioufis, Eleftherios, Papadopoulos, Symeon, Kompatsiaris, Yiannis · 2018 · Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18
9. Privacy in the age of psychological targeting
   Sandra Matz, Ruth E. Appel, Michał Kosiński · 2019 · Current Opinion in Psychology
10. Inherent Trade-Offs in Algorithmic Fairness
    Kleinberg, Jon · 2018 · Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems
11. Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models
    Žliobaitė, Indrė, Custers, Bart · 2016 · Artificial Intelligence and Law
12. Toward human-centered algorithm design
    Baumer, Eric PS · 2017 · Big Data &amp; Society
13. Trust and trustworthiness in AI ethics
    Karoline Reinhardt · 2022 · AI and Ethics
14. Algorithmic Bias? An Empirical Study into Apparent Gender-Based Discrimination in the Display of STEM Career Ads
    Anja Lambrecht, Catherine E. Tucker · 2016 · SSRN Electronic Journal
15. Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
    Aghaei, Sina, Azizi, Mohammad Javad, Vayanos, Phebe · 2019 · Proceedings of the AAAI Conference on Artificial Intelligence
16. Artificial Intelligence and Music: Open Questions of Copyright Law and Engineering Praxis
    Bob L. T. Sturm, María Teresa Iglesias, Oded Ben‐Tal, Marius Miron, Emília Gómez · 2019 · Arts
17. Algorithmic equity in the hiring of underrepresented IT job candidates
    Yarger, Lynette, Cobb Payton, Fay, Neupane, Bikalpa · 2019 · Online Information Review
18. The Who in XAI: How AI Background Shapes Perceptions of AI Explanations
    Ehsan, Upol, Passi, Samir, Liao, Q. Vera, Chan, Larry, Lee, I-Hsiang, Muller, Michael, Riedl, Mark O · 2024 · Proceedings of the CHI Conference on Human Factors in Computing Systems
19. Discrimination in the age of artificial intelligence
    Bert Heinrichs · 2021 · AI & Society
20. Algorithmic Fairness from a Non-ideal Perspective
    Sina Fazelpour, Zachary C. Lipton · 2020 · Proceedings of the AAAI/ACM Conference on AI Ethics and Society
21. Cambridge Analytica’s black box
    Margaret Hu · 2020 · Big Data & Society
22. The life cycle of large language models in education: A framework for understanding sources of bias
    Lee, Jinsook, Hicke, Yann, Yu, Renzhe, Brooks, Christopher, Kizilcec, René F. · 2024 · British Journal of Educational Technology
23. Evolution and impact of bias in human and machine learning algorithm interaction
    Sun, Wenlong, Nasraoui, Olfa, Shafto, Patrick · 2020 · PLOS ONE
24. Who is the fairest of them all? Public attitudes and expectations regarding automated decision-making
    Natali Helberger, Theo Araujo, Claes H. de Vreese · 2020 · Computer law & security review
25. Tuning EU equality law to algorithmic discrimination: Three pathways to resilience
    Xenidis, Raphaële · 2020 · Maastricht Journal of European and Comparative Law
26. Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey
    Fabris, Alessandro, Baranowska, Nina, Dennis, Matthew J., Graus, David, Hacker, Philipp, Saldivar, Jorge, Zuiderveen Borgesius, Frederik, Biega, Asia J. · 2025 · ACM Transactions on Intelligent Systems and Technology
27. Women also Snowboard: Overcoming Bias in Captioning Models
    Kaylee Burns, Lisa Anne Hendricks, Kate Saenko, Trevor Darrell, Anna Rohrbach · 2018 · arXiv (Cornell University)
28. 15 challenges for AI: Or what AI (currently) can’t do
    Hagendorff, Thilo, Wezel, Katharina · 2020 · AI &amp; SOCIETY
29. Human Decision Making with Machine Assistance: An Experiment on Bailing and Jailing
    Grgić-Hlača, Nina, Engel, Christoph, Gummadi, Krishna P. · 2019 · Proceedings of the ACM on Human-Computer Interaction
30. Algorithmic Political Bias in Artificial Intelligence Systems
    Peters, Uwe · 2022 · Philosophy &amp; Technology
31. What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness
    Andrus, McKane, Spitzer, Elena, Brown, Jeffrey, Xiang, Alice · 2021 · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
32. Predictive privacy: towards an applied ethics of data analytics
    Rainer Mühlhoff · 2021 · Ethics and Information Technology
33. The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good
    Lepri, Bruno, Staiano, Jacopo, Sangokoya, David, Letouzé, Emmanuel, Oliver, Nuria · 2017 · Studies in Big Data
34. Toward creating a fairer ranking in search engine results
    Ruoyuan Gao, Chirag Suresh Shah · 2019 · Information Processing & Management
35. Racial categories in machine learning
    Benthall, Sebastian, Haynes, Bruce D. · 2019 · Proceedings of the Conference on Fairness, Accountability, and Transparency
36. Fairness and accountability of AI in disaster risk management: Opportunities and challenges
    Caroline Margaux Gevaert, Mary Carman, Benjamin Rosman, Yola Georgiadou, Robert Soden · 2021 · Patterns
37. Machine Learning Testing: Survey, Landscapes and Horizons
    Jie M. Zhang, Mark Harman, Lei Ma · 2019 · arXiv (Cornell University)
38. Algorithmic IF … THEN rules and the conditions and consequences of power
    Neyland, Daniel, Möllers, Norma · 2017 · Information, Communication &amp; Society
39. Artificial intelligence for political decision-making in the European Union: Effects on citizens’ perceptions of input, throughput, and output legitimacy
    Starke, Christopher, Lünich, Marco · 2020 · Data &amp; Policy
40. Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions
    Mitchell, Shira, Potash, Eric, Barocas, Solon, D'Amour, Alexander, Lum, Kristian · 2018 · arXiv
41. Administrative law and the machines of government: judicial review of automated public-sector decision-making
    Cobbe, Jennifer · 2019 · Legal Studies
42. Democratic governance in an age of datafication: Lessons from mapping government discourses and practices
    Joanna Redden · 2018 · Big Data & Society
43. The lifecycle of algorithmic decision-making systems: Organizational choices and ethical challenges
    Marco Marabelli, Sue Newell, Valerie Rashanthi Handunge · 2021 · The Journal of Strategic Information Systems
44. Discrimination In The Age Of Algorithms
    Jon Michael Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass Robert Sunstein · 2019 · National Bureau of Economic Research
45. Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs
    Lee, Michelle Seng Ah, Floridi, Luciano · 2021 · Minds and Machines
46. Algorithmic inclusion: Shaping the predictive algorithms of artificial intelligence in hiring
    Kelan, Elisabeth K. · 2024 · Human Resource Management Journal
47. Business and the Ethical Implications of Technology: Introduction to the Symposium
    Kirsten Edrie Martin, Katie Shilton, J. Allen Smith · 2019 · Journal of Business Ethics
48. Datatrust: Or, the political quest for numerical evidence and the epistemologies of Big Data
    Rieder, Gernot, Simon, Judith · 2016 · Big Data &amp; Society
49. Group-Fairness in Influence Maximization
    Alan Tsang, Bryan Wilder, Eric R. W. Rice · 2019 · International Joint Conference on Artificial Intelligence
50. Social Bias in Elicited Natural Language Inferences
    Rachel Rudinger, Chandler May, Benjamin Van Durme · 2017
51. In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction
    Wang, Caroline, Han, Bin, Patel, Bhrij, Rudin, Cynthia · 2023 · Journal of Quantitative Criminology
52. Artificial intelligence video interviewing for employment: perspectives from applicants, companies, developer and academicians
    Jin‐Young Kim, WanGyu Heo · 2021 · Information Technology and People
53. A Reductions Approach to Fair Classification
    Alekh Agarwal, Alina Beygelzimer, Miroslav Dudı́k, John C. Langford, Hanna Wallach · 2018 · arXiv (Cornell University)
54. Techno-optimism and policy-pessimism in the public sector big data debate
    Simon Vydra, Bram Klievink · 2019 · Government Information Quarterly
55. The Work of Art in the Age of Artificial Intelligence: What Artists Can Teach Us About the Ethics of Data Practice
    Luke Stark, Kate Crawford · 2019 · Surveillance & Society
56. Interactive Model Cards: A Human-Centered Approach to Model Documentation
    Crisan, Anamaria, Drouhard, Margaret, Vig, Jesse, Rajani, Nazneen · 2022 · 2022 ACM Conference on Fairness Accountability and Transparency
57. Post-userism
    Eric P. S. Baumer, Jed R. Brubaker · 2017 · CHI Conference on Human Factors in Computing Systems
58. Online Hate Speech
    Alexandra Arons Siegel · 2020 · Cambridge University Press eBooks
59. Data-Centric Explanations: Explaining Training Data of Machine Learning Systems to Promote Transparency
    Anik, Ariful Islam, Bunt, Andrea · 2021 · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
60. Conditional variance penalties and domain shift robustness
    Christina Heinze‐Deml, Nicolai Meinshausen · 2020 · Machine Learning
61. Citizen-centered data governance in the smart city: from ethics to accountability
    König, Pascal D. · 2021 · Sustainable Cities and Society
62. Assessing and Remedying Coverage for a Given Dataset
    Abolfazl Asudeh, Zhongjun Jin, H. V. Jagadish · 2019 · IEEE International Conference on Data Engineering (ICDE)
63. Disability at the centre of digital inclusion: assessing a new moment in technology and rights
    Gerard Michael Goggin, Katie M Ellis, Wayne Hawkins · 2019 · Communication Research and Practice
64. Opportunity for renewal or disruptive force? How artificial intelligence alters democratic politics
    Pascal D. König, Georg Wenzelburger · 2020 · Government Information Quarterly
65. Algorithms as discrimination detectors
    Jon Michael Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass Robert Sunstein · 2020 · Proceedings of the National Academy of Sciences
66. Policy Learning for Fairness in Ranking
    Ashudeep Singh, Thorsten Joachims · 2019 · arXiv (Cornell University)
67. Lessons for artificial intelligence from the study of natural stupidity
    Rich, Alexander S., Gureckis, Todd M. · 2019 · Nature Machine Intelligence
68. Digital inequalities 3.0: Emergent inequalities in the information age
    Laura Robinson, Jeremy Schulz, Hopeton S. Dunn, Antonio A. Casilli, Paola Tubaro, Rod Carvath, Wenhong Chen, Julie Bethany Wiest, Matías Dodel, Michael J. Stern et al. · 2020 · First Monday
69. FairSquare: probabilistic verification of program fairness
    Albarghouthi, Aws, D'Antoni, Loris, Drews, Samuel, Nori, Aditya V. · 2017 · Proceedings of the ACM on Programming Languages
70. Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
    Olteanu, Alexandra, Castillo, Carlos, Diaz, Fernando, Kiciman, Emre · 2016
71. Conservative AI and social inequality: conceptualizing alternatives to bias through social theory
    Mike Zajko · 2021 · AI & Society
72. Algorithmic Glass Ceiling in Social Networks
    Ana-Andreea Stoica, Christopher Riederer, Augustin Chaintreau · 2018 · International World Wide Web Conference (WWW)
73. Quantifying the Impact of User Attentionon Fair Group Representation in Ranked Lists
    Sapiezynski, Piotr, Zeng, Wesley, E Robertson, Ronald, Mislove, Alan, Wilson, Christo · 2019 · Companion Proceedings of The 2019 World Wide Web Conference
74. Privacy as Trust
    Ari Ezra Waldman · 2018 · Cambridge University Press eBooks
75. Data Augmentation for Discrimination Prevention and Bias Disambiguation
    Shubham Sharma, Yunfeng Zhang, Jesús Ríos, Djallel Bouneffouf, Vinod Muthusamy, Kush R. Varshney · 2020 · Proceedings of the AAAI/ACM Conference on AI Ethics and Society
76. ”Because AI is 100% right and safe”: User Attitudes and Sources of AI Authority in India
    Kapania, Shivani, Siy, Oliver, Clapper, Gabe, SP, Azhagu Meena, Sambasivan, Nithya · 2022 · CHI Conference on Human Factors in Computing Systems
77. Folk Classification and Factor Rotations: Whales, Sharks, and the Problems With the Hierarchical Taxonomy of Psychopathology (HiTOP)
    Gerald J. Haeffel, Bertus F. Jeronimus, Bonnie N. Kaiser, Lesley Jo Weaver, Peter D. Soyster, Aaron Jason Fisher, Iván Vargas, Jason T. Goodson, Wei Lu · 2021 · Clinical Psychological Science
78. The long road to fairer algorithms
    Matt J. Kusner, Joshua R. Loftus · 2020 · Nature
79. How to regulate algorithmic decision-making: A framework of regulatory requirements for different applications
    Krafft, Tobias D., Zweig, Katharina A., König, Pascal D. · 2022 · Regulation &amp; Governance
80. Representation Learning with Statistical Independence to Mitigate Bias
    Ehsan Adeli, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Li Fei-Fei, Juan Carlos Niebles, Kilian M. Pohl · 2021 · IEEE Winter Conference on Applications of Computer Vision
81. Algorithmic state surveillance: Challenging the notion of agency in human rights
    Eleni Kosta · 2020 · Regulation & Governance
82. Accountability for the use of algorithms in a big data environment
    Anton Vedder, Laurens Naudts · 2017 · International Review of Law Computers & Technology
83. The road to RegTech: the (astonishing) example of the European Union
    Ross P. Buckley, Douglas W. Arner, Dirk Andreas Zetzsche · 2019 · Journal of Banking Regulation
84. One-Network Adversarial Fairness
    Adel, Tameem, Valera, Isabel, Ghahramani, Zoubin, Weller, Adrian · 2019 · Proceedings of the AAAI Conference on Artificial Intelligence
85. A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle
    Suresh, Harini, Guttag, John · 2021 · Equity and Access in Algorithms, Mechanisms, and Optimization
86. Fairness of Classifiers Across Skin Tones in Dermatology
    Newton Mwai Kinyanjui, Timothy Odonga, Celia Cintas, Noel Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney · 2020 · Lecture notes in computer science
87. The false promise of risk assessments: epistemic reform and the limits of fairness
    Green, Ben · 2020 · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
88. Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality
    Aria Khademi, Sanghack Lee, David Foley, Vasant Honavar · 2019 · International World Wide Web Conference (WWW)
89. Human-centred artificial intelligence: a contextual morality perspective
    Niels van Berkel, Benjamin Tag, Jorge Gonçalves, Simo Johannes Hosio · 2020 · Behaviour and Information Technology
90. Toward a Critique of Algorithmic Violence
    Rocco Bellanova, Kristina Irion, Katja Lindskov Jacobsen, Francesco Ragazzi, Rune Saugmann, Lucy A. Suchman · 2021 · International Political Sociology
91. The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it
    König, Pascal D., Wenzelburger, Georg · 2021 · Technology in Society
92. A Precautionary Approach to Big Data Privacy
    Arvind Narayanan, Joanna Huey, Edward W. Felten · 2016 · Law, governance and technology series
93. Accuracy and fairness trade-offs in machine learning: a stochastic multi-objective approach
    Suyun Liu, Luis Nunes Vicente · 2022 · Computational Management Science
94. Semantics derived automatically from language corpora necessarily contain human biases.
    Aylin Caliskan Islam, Joanna Joy Bryson, Arvind Narayanan · 2016 · arXiv (Cornell University)
95. Governance of artificial intelligence and personal health information
    Jenifer Sunrise Winter, Elizabeth Davidson · 2019 · Digital Policy Regulation and Governance
96. Learning Fair Classifiers
    Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi · 2015 · MPG.PuRe (Max Planck Society)
97. Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness
    Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis · 2021 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
98. Highly Accurate, But Still Discriminatory
    Alina Köchling, Shirin Riazy, Marius Wehner, Katharina Simbeck · 2020 · Business & Information Systems Engineering
99. Debiasing Career Recommendations with Neural Fair Collaborative Filtering
    Rashidul Islam, Kamrun Naher Keya, Ziqian Zeng, Shimei Pan, James R. Foulds · 2021 · International World Wide Web Conference (WWW)
100. Online Set Selection with Fairness and Diversity Constraints
     Julia Stoyanovich, Ke Yang, H. V. Jagadish · 2018 · Movebank