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Correction to: Excavating AI: the politics of images in machine learning training sets

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Crawford, Kate, Paglen, Trevor·2021·AI & SOCIETY

DOI 10.1007/s00146-021-01301-1

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Matulionytė, R., & Žalnieriūtė, M. (2024) · Cambridge University Press eBooks · doi:10.1017/9781009321211.002 · Cited by 1
The co-evolution of AI technology and information environment: Diagnosing social impacts and exploring governance strategies
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“Although the harms of birdsong data may be less immediately apparent, an example can be revealed by continuing the “archeology of datasets” initiated in the description of the Salvaging Birds project (Crawford and Paglen, 2021).”
Incorporation of Artificial Intelligence: Exploring Readiness Factors at School Level
Angadi, G. R., & Karan, B. (2026) · Bulletin of Science Technology & Society · doi:10.1177/02704676251407967 · Cited by 4
“Scholars (e.g., AI Shamsi et al., 2022; Crawford & Paglen, 2021; Karan & Angadi, 2023b; McStay, 2020) also worried that AI integration into K-12 education is associated with several signi ﬁ cant risks.”
Overload opacity: Countervisuality and glitch aesthetics in AI-Generated Brainrot on Instagram
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Navigating the automation of the arts: Values, beliefs and emotions of arts practitioners using narrow AI
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“This includes CO 2 emissions arising from large-scale data collection and ML training models, as well as the use of minerals, e-waste, and their role in fossil fuel extraction (Brevini, 2020; Crawford and Paglen, 2021).”
Slicing the past to predict the future: Recasting data slicing as curatorial work in ML development and evaluation
Schjøtt, A. (2026) · Cambridge Forum on AI Culture and Society · doi:10.1017/cfc.2026.10014 · Cited by 1
“Research within Critical Dataset Studies has already drawn parallels between the production of ML datasets and archival practices (Crawford and Paglen 2021; Gebru et al. 2021; Jo and Gebru 2020; Pipkin 2020; Thylstrup 2022).”
Prompt Culture: From Lines to Surfaces in AI Image Generation
Musih, N. (2026) · Theory Culture & Society · doi:10.1177/02632764261455347 · Cited by 1
“Others adopt a critical stance, deliberately crafting prompts or influencing the dataset and the system in ways that expose or subvert generative AI’s limitations, making visible what escapes the conceptual nets (Crawford and Paglen, 2021; Paglen and Downey, 2024).”
Beyond ethics and aesthetics: perceived lay theory violations and agency disruption in AI-generated art
Dolese, M. J. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1716814 · Cited by 1
“While issues such as appropriation, job displacement, and copyright ambiguity remain central (Crawford and Paglen, 2021), they do not fully capture the range of public responses, which fluctuate between curiosity and fascination (Grassini and Koivisto, 2024; Shah, 2023) and persistent resistance…”
What If We Ran Our Own Show? GenAI and The Politics of Representation
Vanlee, F., & Baere, M. D. (2026) · Media and Communication · doi:10.17645/mac.12267 · Cited by 1
“This concerns both the visual materials themselves and the discursive labels with which the materials are rendered “legible” to genAI models (Crawford & Paglen, 2021).”
Generative AI Ethical Dimensions
Mahboubi, O. E., & Amnai, M. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-0365-9.ch019 · Cited by 1
Tool or medium? Expertise in training media and communications students in the Generative AI era
Atkinson, P., Dann, C., van der Nagel, E., Han, G.-S., Johnson, A., Rai, M., Richardson, L., & Stieven-Taylor, A. (2025) · Communication Research and Practice · doi:10.1080/22041451.2025.2582950 · Cited by 1
“Some of these issues are partially addressed in recent research on GenAI: Crawford and Paglen (2021, p. 1105) examine what narrow datasets in AI classifications mean for ‘race, gender, emotions, ability, sexuality, and personality’; Pavlik (2023, p. 92) urges journalism and media educators to think…”
Of data and transparency
(2023) · Nature Computational Science · doi:10.1038/s43588-023-00499-y
Strengthening the Image of Islamic Schools Through the AIDA Approach: The Role of Public Relations in Engaging the Community
Tantowi, A., Subchan, A., Munadirin, A., Kadarismanto, K., & Muslim, R. (2023) · AL-TANZIM JURNAL MANAJEMEN PENDIDIKAN ISLAM · doi:10.33650/al-tanzim.v7i4.5507
Analyzing the Effectiveness of Image Augmentation for Soybean Crop and Broadleaf Weed Classification
Michael, J. J., & Thenmozhi, M. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-99-9521-9_27

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
Publisher: Springer Science and Business Media LLC
Published: 2021-11-23
Volume: 36
Issue: 4
Pages: 1399-1399
ISSN: 0951-5666 (ISSN-L)
1435-5655
DOI: 10.1007/s00146-021-01301-1
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
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
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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