Understanding accountability in algorithmic supply chains-Reference-Cited by-同舟云学术

Understanding accountability in algorithmic supply chains

Published:2023-06-12 Issue: Volume: Page:
ISSN:
Container-title:2023 ACM Conference on Fairness, Accountability, and Transparency
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Author:

Cobbe Jennifer¹^ORCID,Veale Michael²^ORCID,Singh Jatinder¹^ORCID

Affiliation:

1. Compliant & Accountable Systems Group, University of Cambridge, United Kingdom

2. Faculty of Laws, University College London, United Kingdom

Funder

UK Research and Innovation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3593013.3594073

Reference111 articles.

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2. Amazon. [n. d.]. Mechanical Turk. https://www.mturk.com. Amazon. [n. d.]. Mechanical Turk. https://www.mturk.com.

3. Amazon. 2021. Artificial Intelligence Services. https://aws.amazon.com/ machine-learning/ai-services. (Accessed on 04/11/2021). Amazon. 2021. Artificial Intelligence Services. https://aws.amazon.com/ machine-learning/ai-services. (Accessed on 04/11/2021).

4. Amazon. 2021 . Case Study: WeShine. https://perma.cc/2V2T-NNKT. Amazon. 2021. Case Study: WeShine. https://perma.cc/2V2T-NNKT.

5. Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability

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