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Artificial Intelligence: The Data Below

Awareness of data’s role in artificial intelligence will help internal auditors design an audit plan that addresses distinctive risks. Importantly, failure to identify and control artificial intelligence data risks upfront will generate further risks downstream, specifically to reputation, reporting, and management decision-making, just a few of the land mines associated with artificial intelligence.

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Artificial intelligence (AI) technologies are deployed through many industries, including technology, health-care, insurance, banking, and auto. A unique aspect of AI applications is the role data plays in processing. This report:

  • Describes different aspects of data as related to artificial intelligence
  • Identifies specific challenges presented by the role of data
  • Suggests internal auditor interview questions to ascertain data governance during development, implementation, and operations

This study will enhance internal auditors' understanding of the unique risks associated with AI applications. The implementation of AI applications is fairly recent and the profession has not developed standards for the audit of AI applications. There are many similarities between AI and general IT applications, but the unique features of AI need to be identified and assessed to provide guidance to internal auditors encountering this relatively new technology. Specifically, data plays a major role in artificial intelligence applications and we discuss data issues unique to artificial intelligence.

About the Authors

Mike Koenig, MSE, has 25 years of experience at Microsoft, as a software engineering leader, serving as Group Program Manager for Microsoft Office Natural Language Experiences, and Director of Development for Microsoft Robotics, among others. 

Sarah Bee, MBA, CIA, is the Director of the Internal Audit Education Partnership Center of Excellence at Seattle University.

Dennis Applegate, CIA, CPA, CMA, served on the management team of Boeing Corporate Audit for 20 years, holding several management positions including Senior Audit Manager and Chief Auditor.

 

Item Number: 10.5099.dl

Artificial intelligence (AI) technologies are deployed through many industries, including technology, health-care, insurance, banking, and auto. A unique aspect of AI applications is the role data plays in processing. This report:

  • Describes different aspects of data as related to artificial intelligence
  • Identifies specific challenges presented by the role of data
  • Suggests internal auditor interview questions to ascertain data governance during development, implementation, and operations

This study will enhance internal auditors' understanding of the unique risks associated with AI applications. The implementation of AI applications is fairly recent and the profession has not developed standards for the audit of AI applications. There are many similarities between AI and general IT applications, but the unique features of AI need to be identified and assessed to provide guidance to internal auditors encountering this relatively new technology. Specifically, data plays a major role in artificial intelligence applications and we discuss data issues unique to artificial intelligence.

About the Authors

Mike Koenig, MSE, has 25 years of experience at Microsoft, as a software engineering leader, serving as Group Program Manager for Microsoft Office Natural Language Experiences, and Director of Development for Microsoft Robotics, among others. 

Sarah Bee, MBA, CIA, is the Director of the Internal Audit Education Partnership Center of Excellence at Seattle University.

Dennis Applegate, CIA, CPA, CMA, served on the management team of Boeing Corporate Audit for 20 years, holding several management positions including Senior Audit Manager and Chief Auditor.

 

Item Number: 10.5099.dl