The emergence of artificial intelligence ethics auditing
The emerging ecosystem of artificial intelligence (AI) ethics and governance auditing has grown rapidly in recent years in anticipation of impending regulatory efforts that encourage both internal and external auditing. Yet, there is limited understanding of this evolving landscape. We conduct an in...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2024-12-01
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| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/20539517241299732 |
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| _version_ | 1850248946666962944 |
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| author | Daniel S Schiff Stephanie Kelley Javier Camacho Ibáñez |
| author_facet | Daniel S Schiff Stephanie Kelley Javier Camacho Ibáñez |
| author_sort | Daniel S Schiff |
| collection | DOAJ |
| description | The emerging ecosystem of artificial intelligence (AI) ethics and governance auditing has grown rapidly in recent years in anticipation of impending regulatory efforts that encourage both internal and external auditing. Yet, there is limited understanding of this evolving landscape. We conduct an interview-based study of 34 individuals in the AI ethics auditing ecosystem across seven countries to examine the motivations, key auditing activities, and challenges associated with AI ethics auditing in the private sector. We find that AI ethics audits follow financial auditing stages, but tend to lack robust stakeholder involvement, measurement of success, and external reporting. Audits are hyper-focused on technically oriented AI ethics principles of bias, privacy, and explainability, to the exclusion of other principles and socio-technical approaches, reflecting a regulatory emphasis on technical risk management. Auditors face challenges, including competing demands across interdisciplinary functions, firm resource and staffing constraints, lack of technical and data infrastructure to enable auditing, and significant ambiguity in interpreting regulations and standards given limited (or absent) best practices and tractable regulatory guidance. Despite these roadblocks, AI ethics and governance auditors are playing a critical role in the early ecosystem: building auditing frameworks, interpreting regulations, curating practices, and sharing learnings with auditees, regulators, and other stakeholders. |
| format | Article |
| id | doaj-art-c47fe4bbfa0f41d59647092e33e918e5 |
| institution | OA Journals |
| issn | 2053-9517 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Big Data & Society |
| spelling | doaj-art-c47fe4bbfa0f41d59647092e33e918e52025-08-20T01:58:36ZengSAGE PublishingBig Data & Society2053-95172024-12-011110.1177/20539517241299732The emergence of artificial intelligence ethics auditingDaniel S Schiff0Stephanie Kelley1Javier Camacho Ibáñez2 Department of Political Science, , West Lafayette, IN, USA Sobey School of Business, , Halifax, Nova Scotia, Canada Departamento de Economía y Empresa, , Madrid, SpainThe emerging ecosystem of artificial intelligence (AI) ethics and governance auditing has grown rapidly in recent years in anticipation of impending regulatory efforts that encourage both internal and external auditing. Yet, there is limited understanding of this evolving landscape. We conduct an interview-based study of 34 individuals in the AI ethics auditing ecosystem across seven countries to examine the motivations, key auditing activities, and challenges associated with AI ethics auditing in the private sector. We find that AI ethics audits follow financial auditing stages, but tend to lack robust stakeholder involvement, measurement of success, and external reporting. Audits are hyper-focused on technically oriented AI ethics principles of bias, privacy, and explainability, to the exclusion of other principles and socio-technical approaches, reflecting a regulatory emphasis on technical risk management. Auditors face challenges, including competing demands across interdisciplinary functions, firm resource and staffing constraints, lack of technical and data infrastructure to enable auditing, and significant ambiguity in interpreting regulations and standards given limited (or absent) best practices and tractable regulatory guidance. Despite these roadblocks, AI ethics and governance auditors are playing a critical role in the early ecosystem: building auditing frameworks, interpreting regulations, curating practices, and sharing learnings with auditees, regulators, and other stakeholders.https://doi.org/10.1177/20539517241299732 |
| spellingShingle | Daniel S Schiff Stephanie Kelley Javier Camacho Ibáñez The emergence of artificial intelligence ethics auditing Big Data & Society |
| title | The emergence of artificial intelligence ethics auditing |
| title_full | The emergence of artificial intelligence ethics auditing |
| title_fullStr | The emergence of artificial intelligence ethics auditing |
| title_full_unstemmed | The emergence of artificial intelligence ethics auditing |
| title_short | The emergence of artificial intelligence ethics auditing |
| title_sort | emergence of artificial intelligence ethics auditing |
| url | https://doi.org/10.1177/20539517241299732 |
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