Null Compliance: NYC Local Law 144 and the challenges of algorithm accountability-Reference-Cited by-同舟云学术

Null Compliance: NYC Local Law 144 and the challenges of algorithm accountability

Published:2024-06-03 Issue: Volume:70 Page:1701-1713
ISSN:
Container-title:The 2024 ACM Conference on Fairness, Accountability, and Transparency
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Author:

Wright Lucas¹^ORCID,Muenster Roxana Mika²^ORCID,Vecchione Briana³^ORCID,Qu Tianyao⁴^ORCID,Cai Pika (Senhuang)⁵^ORCID,Smith Alan⁶^ORCID,Comm 2450 Student Investigators ⁷^ORCID,Metcalf Jacob³^ORCID,Matias J. Nathan¹^ORCID

Affiliation:

1. Citizens and Technology Lab, Cornell University, USA

2. Department of Communication, Cornell University, United States of America

3. Data & Society Research Institute, United States of America

4. Department of Sociology, Cornell University, United States of America

5. Department of Information Science, Cornell University, USA

6. Consumer Reports, USA

7. Cornell University, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3630106.3658998

Reference74 articles.

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2. Solon Barocas and Andrew D. Selbst. 2016. Big data’s disparate impact. California law review (2016), 671–732. https://www.jstor.org/stable/24758720 Publisher: JSTOR.

3. Philip Bobko and Philip L Roth. 2004. THE FOUR-FIFTHS RULE FOR ASSESSING ADVERSE IMPACT: AN ARITHMETIC INTUITIVE AND LOGICAL ANALYSIS OF THE RULE AND IMPLICATIONS FOR FUTURE RESEARCH AND PRACTICE. In Research in Personnel and Human Resources Management. Research in Personnel and Human Resources Management Vol. 23. Emerald Group Publishing Limited 177–198. https://doi.org/10.1016/S0742-7301(04)23004-3

4. Albert Fox Cahn. 2019. The first effort to regulate AI was a spectacular failure. Fast Company (Nov. 2019). https://www.fastcompany.com/90436012/the-first-effort-to-regulate-ai-was-a-spectacular-failure

5. Paul Cairney. 2016. The politics of evidence-based policy making. Springer.

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