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Correction to: Excavating AI: the politics of images in machine learning training sets
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“Otherwise, even if we see what machines see, we might not understand why they see it that way [Crawford and Paglen 2021].”
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“These results also align with the argument that AI systems are not merely external actors but infrastructural actors within socio-political ecosystems (Crawford & Paglen, 2021), and that the assessment of LLMs must consider power relations as well as moderation policies.”
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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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