The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Correction to: Excavating AI: the politics of images in machine learning training sets
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Cites
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Coding facial expressions with Gabor wavelets
Lyons, M. J., Akamatsu, S., Kamachi, M., & Gyoba, J. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1998.670949 · Cited by 2,214
Diversity in Faces.Preprint
Merler, M., Ratha, N., Feris, R., & Smith, J. R. (2019) · arXiv (Cornell University) · Cited by 111
Cited by
Sorted by citations
Ferrara, E. (2023) · Sci · doi:10.3390/sci6010003 · Cited by 875
“To address this issue, some companies have implemented “gender decoder” tools that analyze job postings and suggest changes to reduce gender bias [17,37].”
BackgroundCamilleri, M. A. (2024) · Expert Systems · doi:10.1111/exsy.13406 · Cited by 331
“Their dialogue formats enable them to respond to questions (Thorp, 2023), to admit their mistakes (Barrot, 2023), and to even reject requests (Crawford & Paglen, 2021), if they are not recognized as appropriate.”
BackgroundPotential Risks of Artificial Intelligence Integration into School Education: A Systematic Review
Karan, B., & Angadi, G. R. (2023) · Bulletin of Science Technology & Society · doi:10.1177/02704676231224705 · Cited by 122
“For instance, students of different color in K-12 schools are subjected to the discrimination at entry for incorrect identi fi cation by AI (Crawford & Paglen, 2021).”
BackgroundWhose AI Dream? In search of the aspiration in data annotation.
Wang, D., Prabhat, S., & Sambasivan, N. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502121 · Cited by 70
Web scraping for research: Legal, ethical, institutional, and scientific considerations
Brown, M. A., Gruen, A., Maldoff, G., Messing, S., Sanderson, Z., & Zimmer, M. T. (2025) · Big Data & Society · doi:10.1177/20539517251381686 · Cited by 48
“…are increasingly fed into machine learning models and other computational tools, they may be repur-posed in contexts far removed from the original research intent, such as facial recognition, predictive policing, or behavioral pro fi ling (Crawford and Paglen, 2021; Scheuerman et al., 2021).”
Metadata
- Authors
- Crawford, K., & Paglen, T.
- Affiliations
- University of Southern California (US)
- University of Georgia (US)
- Corresponding author
- Crawford, Kate
- ORCID
- Crawford, Kate
- Venue
- AI & SOCIETY
- Published
- 2021-11-23
- Volume
- 36
- Issue
- 4
- Pages
- 1399-1399
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W3217570815
- Cited by
- 153
- References
- 3
- Citations by year
- 2026: 48 · 2025: 49 · 2024: 36 · 2023: 17 · 2022: 3
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- AI & Society (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- artificial intelligence, machine learning training data, image politics, data curation
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