TY - JOUR
T1 - Designing an Enhanced Enterprise Risk Management System to Mitigate Ethical Risks of Artificial Intelligence Applications
AU - McGrath, Quintin P.
AU - Hevner, Alan R.
AU - de Vreede, Gert Jan
N1 - Publisher Copyright:
© 1988-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - The introduction of artificial intelligence (AI) capabilities in business applications provides substantial benefits but requires organizations to manage critical AI ethical risks. We survey a range of large organizations on their use of enterprise risk management (ERM) systems to predict and mitigate the ethical risks of AI. Four serious gaps in current ERM systems are identified: AI ethical principles do not translate effectively to ethical practices; real-time monitoring of AI ethical risks is needed; ERM systems emphasize economic, not ethical risks; and when ethical risks are identified, no ready solutions are available for remedy. To address these gaps, we propose a proactive approach to managing ethical risks by extending the capabilities of current ERM systems. An enhanced ERM system framework is designed and evaluated by subject matter expert focus groups. We conclude with observations and future research directions on the need for more aggressive proethical management oversight as organizations move to ubiquitous use of AI-driven business applications.
AB - The introduction of artificial intelligence (AI) capabilities in business applications provides substantial benefits but requires organizations to manage critical AI ethical risks. We survey a range of large organizations on their use of enterprise risk management (ERM) systems to predict and mitigate the ethical risks of AI. Four serious gaps in current ERM systems are identified: AI ethical principles do not translate effectively to ethical practices; real-time monitoring of AI ethical risks is needed; ERM systems emphasize economic, not ethical risks; and when ethical risks are identified, no ready solutions are available for remedy. To address these gaps, we propose a proactive approach to managing ethical risks by extending the capabilities of current ERM systems. An enhanced ERM system framework is designed and evaluated by subject matter expert focus groups. We conclude with observations and future research directions on the need for more aggressive proethical management oversight as organizations move to ubiquitous use of AI-driven business applications.
KW - AI ethical principles
KW - Artificial intelligence (AI) ethical practices
KW - enterprise risk management (ERM) systems
KW - ethical AI
UR - http://www.scopus.com/inward/record.url?scp=105004007301&partnerID=8YFLogxK
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U2 - 10.1109/TEM.2025.3565221
DO - 10.1109/TEM.2025.3565221
M3 - Article
AN - SCOPUS:105004007301
SN - 0018-9391
VL - 72
SP - 1813
EP - 1830
JO - IEEE Transactions on Engineering Management
JF - IEEE Transactions on Engineering Management
ER -