Resolving the Human-Subjects Status of ML's Crowdworkers-Reference-Cited by-同舟云学术

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Resolving the Human-Subjects Status of ML's Crowdworkers

Published:2024-05 Issue:5 Volume:67 Page:52-59
ISSN:0001-0782
Container-title:Communications of the ACM
language:en
Short-container-title:Commun. ACM

Author:

Kaushik Divyansh¹,Lipton Zachary C.²,London Alex John³

Affiliation:

1. Federation of American Scientists, Washington, D.C., USA

2. Carnegie Mellon University, Pittsburgh, PA, USA

3. Carnegie Mellon University (CMU), Pittsburgh, PA, USA

Abstract

What ethical framework should govern the interaction of ML researchers and crowdworkers?

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/3641858

Reference31 articles.

1. MasakhaNER: Named entity recognition for African languages;Adelani D.F.;Trans. ACL,2021

2. Birmingham-Southern College. Do I Need IRB Approval? https://bit.ly/47vJTAa.

3. DeYoung, J. et al. ERASER: A benchmark to evaluate rationalized NLP models. In Proceedings of the 58th Annual Meeting of the ACL 4, (2020), 443--458; https://aclanthology.org/2020.acl-main.408/.

4. Dodge, J. et al. Show your work: Improved reporting of experimental results. In Proceedings of the 2019 Conf. Empirical Methods in Natural Language Processing and the 9th Intern. Joint Conf. Natural Language Processing 2, (2019), 185--194; https://aclanthology.org/D19-1224/.

5. Amazon Mechanical Turk: Gold Mine or Coal Mine?

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