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Scholars have recently drawn attention to a range of controversial issues posed by the use of computer vision for automatically generating descriptions of people in images.
Sorting things out: Classification and its consequences
Geoffrey C Bowker and Susan Leigh Star · 2000
Earlier work this paper cites.
Invisible disability
N Ann Davis · 2005
Earlier work this paper cites.
Describing images on the web: a survey of current practice and prospects for the future
Helen Petrie, Chandra Harrison, and Sundeep Dev · 2005
Earlier work this paper cites.
Vizwiz: nearly real-time answers to visual questions
Jeffrey P Bigham, Chandrika Jayant, Hanjie Ji, Greg Little, Andrew Miller, Robert C Miller, Robin Miller, Aubrey Tatarowicz, Brandyn White, Samual White, et al · 2010
Earlier work this paper cites.
Estimating the social costs of friendsourcing
Jeffrey M Rzeszotarski and Meredith Ringel Morris · 2014
Earlier work this paper cites.
Google apologises for photos app’s racist blunder, july 2015
BBC · 2015
Earlier work this paper cites.
Gauging receptiveness to social microvolunteering
Erin Brady, Meredith Ringel Morris, and Jeffrey P Bigham · 2015
Earlier work this paper cites.
From captions to visual concepts and back
Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh K Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C Platt, et al · 2015
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 2015
Earlier work this paper cites.
Under the hood: Building accessibility tools for the visually impaired on facebook, april 2016
Manohar Paluri Darío García García, Shaomei Wu · 2016
Earlier work this paper cites.
”is there anything else i can help you with?” challenges in deploying an on-demand crowd-powered conversational agent
Ting-Hao Huang, Walter Lasecki, Amos Azaria, and Jeffrey Bigham · 2016
Earlier work this paper cites.
Behind facebook’s efforts to make its site accessible to all, july 2016
Nicole Lee · 2016
Earlier work this paper cites.
Facebook begins using artificial intelligence to describe photos to blind users, april 2016
Casey Newton · 2016
Earlier work this paper cites.
How facebook is helping the blind ‘see’ pictures their friends share online, april 2016
Andrea Peterson · 2016
Earlier work this paper cites.
Rich image captioning in the wild
Kenneth Tran, Xiaodong He, Lei Zhang, Jian Sun, Cornelia Carapcea, Chris Thrasher, Chris Buehler, and Chris Sienkiewicz · 2016
Earlier work this paper cites.
Stereotyping and bias in the flickr30k dataset
Emiel Van Miltenburg · 2016
Earlier work this paper cites.
The Problem With Bias: Allocative Versus Representational Harms in Machine Learning
Solon Barocas, Kate Crawford, Aaron Shapiro, and Hanna Wallach · 2017
Earlier work this paper cites.
”is someone there? do they have a gun” how visual information about others can improve personal safety management for blind individuals
Stacy M Branham, Ali Abdolrahmani, William Easley, Morgan Scheuerman, Erick Ronquillo, and Amy Hurst · 2017
Earlier work this paper cites.
Facebook’s new facial recognition efforts help blind users know exactly who’s in photos, december 2017
Nicole Gallucci · 2017
Earlier work this paper cites.
Understanding blind people’s experiences with computer-generated captions of social media images
Haley MacLeod, Cynthia L Bennett, Meredith Ringel Morris, and Edward Cutrell · 2017
Earlier work this paper cites.
Toward scalable social alt text: Conversational crowdsourcing as a tool for refining vision-to-language technology for the blind
Elliot Salisbury, Ece Kamar, and Meredith Morris · 2017
Earlier work this paper cites.
Automatic alt-text: Computer-generated image descriptions for blind users on a social network service
Shaomei Wu, Jeffrey Wieland, Omid Farivar, and Julie Schiller · 2017
Earlier work this paper cites.
Understanding low vision people’s visual perception on commercial augmented reality glasses
Yuhang Zhao, Michele Hu, Shafeka Hashash, and Shiri Azenkot · 2017
Earlier work this paper cites.
The effect of computer-generated descriptions on photo-sharing experiences of people with visual impairments
Yuhang Zhao, Shaomei Wu, Lindsay Reynolds, and Shiri Azenkot · 2017
Earlier work this paper cites.
Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
Cited alongside, same era.
Facebook’s accessibility ambitions, may 2018
Megan Rose Dickey · 2018
Cited alongside, same era.
The latest facebook statistics (2018), January 2018
Facebook Inc · 2018
Cited alongside, same era.
Caption crawler: Enabling reusable alternative text descriptions using reverse image search
Darren Guinness, Edward Cutrell, and Meredith Ringel Morris · 2018
Cited alongside, same era.
Gender recognition or gender reductionism? the social implications of embedded gender recognition systems
Foad Hamidi, Morgan Klaus Scheuerman, and Stacy M Branham · 2018
Cited alongside, same era.
Data violence and how bad engineering choices can damage society
Anna Lauren Hoffmann · 2018
Google ai will no longer use gender labels like ’woman’ or ’man’ on images of people to avoid bias, feb 2020
Shona Ghosh · 2020
Later among the works it cites.
An ethical highlighter for people-centric dataset creation
Margot Hanley, Apoorv Khandelwal, Hadar Averbuch-Elor, Noah Snavely, and Helen Nissenbaum · 2020
Later among the works it cites.
Criminal tendency detection from facial images and the gender bias effect
Mahdi Hashemi and Margeret Hall · 2020
Later among the works it cites.
Terms of inclusion: Data, discourse, violence
Anna Lauren Hoffmann · 2020
Later among the works it cites.
Lessons from archives: Strategies for collecting sociocultural data in machine learning
Eun Seo Jo and Timnit Gebru · 2020
Later among the works it cites.
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Cited alongside, same era.
The misgendering machines: Trans/hci implications of automatic gender recognition
Os Keyes · 2018
Cited alongside, same era.
Social cues, social biases: stereotypes in annotations on people images
Jahna Otterbacher · 2018
Cited alongside, same era.
Talking about other people: an endless range of possibilities
Emiel van Miltenburg, Desmond Elliott, and Piek Vossen · 2018
Cited alongside, same era.
Deep neural networks are more accurate than humans at detecting sexual orientation from facial images
Yilun Wang and Michal Kosinski · 2018
Cited alongside, same era.
Social b(eye) as: Human and machine descriptions of people images
Pınar Barlas, Kyriakos Kyriakou, Styliani Kleanthous, and Jahna Otterbacher · 2019
Cited alongside, same era.
Racial categories in machine learning
Sebastian Benthall and Bruce D Haynes · 2019
Cited alongside, same era.
Gunay Kazimzade and Milagros Miceli · 2020
Later among the works it cites.
What it’s like to use facebook when you’re blind
Janni Lehrer-Stein · 2020
Later among the works it cites.
Between subjectivity and imposition: Power dynamics in data annotation for computer vision
Milagros Miceli, Martin Schuessler, and Tianling Yang · 2020
Later among the works it cites.
Moving communities online (without losing their substance), march 2020
Alica Peszkowska · 2020
Later among the works it cites.
What’s that? microsoft’s latest breakthrough, now in azure ai, describes images as well as people do, 2020
John Roach · 2020
Later among the works it cites.
How we’ve taught algorithms to see identity: Constructing race and gender in image databases for facial analysis
Morgan Klaus Scheuerman, Kandrea Wade, Caitlin Lustig, and Jed R Brubaker · 2020
Later among the works it cites.
”person, shoes, tree. is the person naked?” what people with vision impairments want in image descriptions
Abigale Stangl, Meredith Ringel Morris, and Danna Gurari · 2020
Later among the works it cites.
Accessibility and computer vision, oct 2020
TWIMLFest · 2020
Later among the works it cites.
Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy
Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2020
Later among the works it cites.
How facebook is using ai to improve photo descriptions for people who are blind or visually impaired, jan 2021
Facebook AI · 2021
Closest in time.
“it’s complicated”: Negotiating accessibility and (mis) representation in image descriptions of race, gender, and disability
Cynthia L Bennett, Cole Gleason, Morgan Klaus Scheuerman, Jeffrey P Bigham, Anhong Guo, and Alexandra To · 2021
Closest in time.
Large image datasets: A pyrrhic win for computer vision?
Abeba Birhane and Vinay Uday Prabhu · 2021
Closest in time.
Guidelines for image description, 2021
Cooper Hewitt · 2021
Closest in time.
Things which garner a ton of glowing reviews from mainstream outlets without being of much use to disabled people. for instance, facebook’s auto image descriptions, much loved by sighted journos but famously useless in the blind community, January 2021
Chancey Fleet · 2021
Closest in time.
Vision ai, January 2021
Google · 2021
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Amazon rekognition, January 2021
Amazon.com Inc · 2021
Closest in time.
Microsoft Azure Computer Vision, January 2021
2021
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Collection, 2021
Museum of Contemporary Art Chicago · 2021
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Mca guidelines for describing, 2021
Museum of Contemporary Art Chicago · 2021
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