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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Published in:Big Data & Society Vol. 11; no. 4; pp. 1 - 17
Main Authors: Schiff, Daniel S, Kelley, Stephanie, Camacho Ibáñez, Javier
Format: Article
Published: Sage Publications Inc. Oct-Dec2024
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Oct-Dec2024
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      pub: Sage Publications Inc.
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        atl: The emergence of artificial intelligence ethics auditing.
      aug:
        au:
          Schiff, Daniel S
          Kelley, Stephanie
          Camacho Ibáñez, Javier
        affil:
          Department of Political Science, 311308Purdue University, West Lafayette, IN, USA
          Sobey School of Business, 3690Saint Mary's University, Halifax, Nova Scotia, Canada
          Departamento de Economía y Empresa, 16740Universidad Europea Madrid, Madrid, Spain
      su:
        Internal auditing
        Artificial intelligence
        Auditing
        Semi-structured interviews
        Private sector
      sug:
        subj:
          Internal auditing
          Artificial intelligence
          Auditing
          Semi-structured interviews
          Private sector
      keyword:
        AI ethics auditing
        AI risk management
        algorithmic governance
        digital ethics
        responsible AI
        semi-structured interviews
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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          year: 2024
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