PMC Academic - Obligations to assess: Recent trends in AI accountability regulations
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This peer-reviewed journal article analyzes emerging AI accountability regulations and their shift toward impact assessments and governance documentation, directly addressing regulatory approaches to managing risks from automated decision systems.
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This paper examines recent trends in AI accountability regulations that require developers to conduct impact assessments of automated decision systems across social, economic, and ethical dimensions. Analyzing four legislative examples from the US and EU, the authors demonstrate how regulations are shifting beyond technical assessments toward accountability documentation as a governance mechanism. The paper identifies three core concerns these regulations address: identifying and documenting harms, ensuring public transparency, and enforcing anti-discrimination rules. The authors provide insights for system designers on preparing for and complying with emerging regulatory requirements.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| US State AI Legislation Landscape | Analysis | 70.0 |
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Patterns (N Y) . 2022 Nov 11;3(11):100608. doi: 10.1016/j.patter.2022.100608
Obligations to assess: Recent trends in AI accountability regulations
Serena Oduro
Serena Oduro
1 Data & Society Research Institute, New York, NY 10011, USA
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1 , Emanuel Moss
Emanuel Moss
2 Intel Labs, Hillsboro, OR 97124, USA
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2 , Jacob Metcalf
Jacob Metcalf
1 Data & Society Research Institute, New York, NY 10011, USA
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1, ∗
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1 Data & Society Research Institute, New York, NY 10011, USA
2 Intel Labs, Hillsboro, OR 97124, USA
∗ Corresponding author jake.metcalf@datasociety.net
Collection date 2022 Nov 11.
© 2022 The Authors
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
PMC Copyright notice
PMCID: PMC9676559 PMID: 36419454
See editorial " Responsible and accountable data science ", 100629.
Summary
Policymakers are increasingly turning toward assessments of social, economic, and ethical impacts as a governance model for automated decision systems in sensitive or regulated domains. In both the United States and the European Union, recently proposed legislation would require developers to assess the impacts of their systems for individuals, communities, and society, a notable step beyond the technical assessments that are familiar to the industry. This paper analyzes four examples of such legislation in order to illustrate how AI regulations are moving toward using accountability documentation to address common AI acco
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