Designing an Enhanced Enterprise Risk Management System to Mitigate Ethical Risks of Artificial Intelligence Applications

Quintin P. McGrath, Alan R. Hevner, Gert Jan de Vreede

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1813-1830
Number of pages18
JournalIEEE Transactions on Engineering Management
Volume72
DOIs
StatePublished - 2025

Keywords

  • AI ethical principles
  • Artificial intelligence (AI) ethical practices
  • enterprise risk management (ERM) systems
  • ethical AI

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