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Studies have shown that the people depicted in image search results tend to be of majority groups with respect to socially salient attributes.
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Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Christopher A Le Dantec, Erika Shehan Poole, and Susan P Wyche · 2009
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Filip Radlinski, Paul N Bennett, Ben Carterette, and Thorsten Joachims · 2009
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What else is there? search diversity examined
Mark Sanderson, Jiayu Tang, Thomas Arni, and Paul Clough · 2009
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Please select your gender: From the invention of hysteria to the democratizing of transgenderism
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A class of submodular functions for document summarization
Hui Lin and Jeff Bilmes · 2011
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Extractive summarization of personal photos from life events
Pinaki Sinha and Ramesh Jain · 2011
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Effective summarization of large-scale web images
Chunlei Yang, Jialie Shen, and Jianping Fan · 2011
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Communities: Participatory design for, with and by communities
Carl DiSalvo, Andrew Clement, and Volkmar Pipek · 2012
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
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Data preprocessing techniques for classification without discrimination
Faisal Kamiran and Toon Calders · 2012
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Determinantal point processes for machine learning
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https://www.bls.gov/cps/aa2012/cpsaat11.htm , 2013
Bureau of labor statistics. labor force statistics from the current population survey · 2013
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Algorithmic decision making and the cost of fairness
Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq · 2017
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Gender stereotypes in occupational choice: a cross-sectional study on a group of italian adolescents
Tiziana Ramaci, Monica Pellerone, Caterina Ledda, Giovambattista Presti, Valeria Squatrito, and Venerando Rapisarda · 2017
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Deep convolutional neural networks for image classification: A comprehensive review
Waseem Rawat and Zenghui Wang · 2017
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Fairness constraints: Mechanisms for fair classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez, and Krishna P Gummadi · 2017
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2017
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Comparing self-stereotyping with in-group-stereotyping and out-group-stereotyping in unequal-status groups: The case of gender
Mara Cadinu, Marcella Latrofa, and Andrea Carnaghi · 2013
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Gendered restrooms and minority stress: The public regulation of gender and its impact on transgender people’s lives
Jody L Herman · 2013
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Gender and perceptions of occupational prestige: Changes over 20 years
Donna Crawley · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
Maxime Oquab, Leon Bottou, Ivan Laptev, and Josef Sivic · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Learning mixtures of submodular functions for image collection summarization
Sebastian Tschiatschek, Rishabh K Iyer, Haochen Wei, and Jeff A Bilmes · 2014
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https://appelcitoyen.ch/on-ouvre-les-urnes-donnees-brutes-de-la-primaire/ , 2018
Appel citoyen · 2018
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https://www.pewsocialtrends.org/2018/12/17/gender-and-jobs-in-online-image-searches/ , 2018
Gender and jobs in online image searches · 2018
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http://gendershades.org/docs/ibm.pdf , 2018
Ibm response to “gender shades: Intersectional accuracy disparities in commercial gender classification” · 2018
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https://www.wired.com/story/when-it-comes-to-gorillas-google-photos-remains-blind/ , 2018
When it comes to gorillas, google photos remains blind · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Fair and diverse dpp-based data summarization
L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, and Nisheeth Vishnoi · 2018
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Ranking with fairness constraints
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Do less, get more: streaming submodular maximization with subsampling
Moran Feldman, Amin Karbasi, and Ehsan Kazemi · 2018
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We ask men to win and women not to lose: Closing the gender gap in startup funding
Dana Kanze, Laura Huang, Mark A Conley, and E Tory Higgins · 2018
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Towards an argumentative content search engine using weak supervision
Ran Levy, Ben Bogin, Shai Gretz, Ranit Aharonov, and Noam Slonim · 2018
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Streaming non-monotone submodular maximization: Personalized video summarization on the fly
Baharan Mirzasoleiman, Stefanie Jegelka, and Andreas Krause · 2018
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Algorithms of oppression: How search engines reinforce racism
Safiya Umoja Noble · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
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https://www.raeng.org.uk/news/news-releases/2019/november/ai-reveals-misrepresentation-of-engineers-online , 2019
Ai reveals misrepresentation of engineers online · 2019
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