Journal article : Comment
Better pay, clearer guidance: investing in the working conditions of AI data workers
- Abstract:
- The production of artificial intelligence (AI) requires human labour, with tasks ranging from well-paid engineering work to often-outsourced data work. This commentary explores the economic and policy implications of improving working conditions for AI data workers, specifically focusing on the impact of clearer task instructions and increased pay for data annotators. It contrasts rule-based and standard-based approaches to task instructions, revealing evidence-based practices for increasing accuracy in annotation and lowering task difficulty for annotators. AI developers have an economic incentive to invest in these areas as better annotation can lead to higher quality AI systems. The findings have broader implications for AI policy beyond the fairness of labour standards in the AI economy. Testing the design of annotation instructions is crucial for the development of annotation standards as a prerequisite for scientific review and effective human oversight of AI systems in protection of ethical values and fundamental rights.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1177/20539517251351320
Authors
+ British Academy
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- Funder identifier:
- https://ror.org/0302b4677
- Grant:
- PF22\220076
- Publisher:
- SAGE Publications
- Journal:
- Big Data and Society More from this journal
- Volume:
- 12
- Issue:
- 2
- Publication date:
- 2025-06-20
- Acceptance date:
- 2025-05-23
- DOI:
- EISSN:
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2053-9517
- Language:
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English
- Keywords:
- Subtype:
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Comment
- Pubs id:
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2126013
- Local pid:
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pubs:2126013
- Deposit date:
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2025-05-26
- ARK identifier:
Terms of use
- Copyright holder:
- Laux et al
- Copyright date:
- 2025
- Rights statement:
- © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
- Licence:
- CC Attribution (CC BY)
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