Highlights: Fair ML textbook / 21 definitions of fairness talk / AI snake oil talk / Word embedding bias paper / Dark patterns paper
Textbook
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Fairness and machine learning: limitations and opportunities
Solon Barocas, Moritz Hardt, Arvind Narayanan. MIT Press, forthcoming. Related: 21 definitions of fairness and their politics. Talk at FAT* 2018. |
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Journal
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Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 U.S. election cycle
Arunesh Mathur, Angelina Wang, Carsten Schwemmer, Maia Hamin, Brandon M. Stewart, Arvind Narayanan. Big Data & Society, 2023. Corpus. |
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Conference
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Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy
Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan. ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2023. |
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Conference
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How Algorithms Shape the Distribution of Political Advertising: Case Studies of Facebook, Google, and TikTok
Orestis Papakyriakopoulos, Christelle Tessono, Arvind Narayanan, Mihir Kshirsagar. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 2022. |
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Conference
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Mitigating dataset harms requires stewardship: Lessons from 1000 papers
Kenny Peng, Arunesh Mathur, Arvind Narayanan. Neural Information Processing Systems (NeurIPS) 2021. Oral presentation. |
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Workshop
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Simulation as Experiment: An Empirical Critique of Simulation Research on Recommender Systems
Amy A. Winecoff, Matthew Sun, Eli Lucherini, Arvind Narayanan. Workshop on Simulation Methods for Recommender Systems (SimuRec) 2021 |
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Journal
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REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
Angelina Wang, Alexander Liu, Ryan Zhang, Anat Kleiman, Leslie Kim, Dora Zhao, Iroha Shirai, Arvind Narayanan, Olga Russakovsky. International Journal of Computer Vision, 2022. Extended version of a paper that appeared at ECCV 2020. |
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Draft
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T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems
Eli Lucherini, Matthew Sun, Amy Winecoff, Arvind Narayanan. Manuscript, 2021. |
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Conference
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REVISE: A Tool for Measuring and Mitigating Bias in Image Datasets
Angelina Wang, Arvind Narayanan, Olga Russakovsky. European Conference on Computer Vision (ECCV) 2020. Spotlight presentation. |
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Magazine
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Dark Patterns: Past, Present, and Future
Arvind Narayanan, Arunesh Mathur, Marshini Chetty, Mihir Kshirsagar. ACM Queue, 2020. (Also appeared in CACM, 2020.) |
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Journal
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Measuring the predictability of life outcomes with a scientific mass collaboration
Matthew J. Salganik et al. Proceedings of the National Academy of Sciences 2020. |
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Conference
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Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites
Arunesh Mathur, Gunes Acar, Michael Friedman, Elena Lucherini, Jonathan Mayer, Marshini Chetty, Arvind Narayanan. ACM Conference on Computer-Supported Cooperative Work and Social Computing, 2019. FPF Privacy Papers for Policy Makers Award. |
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Conference
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Endorsements on Social Media: An Empirical Study of Affiliate Marketing Disclosures on YouTube and Pinterest
Arunesh Mathur, Arvind Narayanan, Marshini Chetty. ACM Conference on Computer-Supported Cooperative Work and Social Computing 2018. Best paper award. Blog post. |
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Workshop
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An Empirical Study of Affiliate Marketing Disclosures on YouTube and Pinterest
Arunesh Mathur, Arvind Narayanan, Marshini Chetty. Workshop on Technology and Consumer Protection (ConPro) 2018. Blog post. |
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Journal
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, Arvind Narayanan. Science, 2017. Open access author copy. |
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Journal
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Ten simple rules for responsible big data research
Matthew Zook, Solon Barocas, danah boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale. PLoS Computational Biology 2017. |
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Journal
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No Encore for Encore? Ethical Questions for Web-Based Censorship Measurement
Arvind Narayanan, Bendert Zevenbergen. Technology Science, 2015. |
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Journal
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Redefining Genomic Privacy: Trust and Empowerment
Yaniv Erlich, James B Williams, David Glazer, Kenneth Yocum, Nita Farahany, Maynard Olson, Arvind Narayanan, Lincoln D Stein, Jan A Witkowski, Robert C Kain PLoS Biology, 2014. |
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Journal
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Why software engineering courses should include ethics coverage
Arvind Narayanan, Shannon Vallor. Communications of the ACM, 2014. |
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