Quintin McGrath - 21DOCS Test Area

Quintin McGrath

Post-doc Researcher

Quintin McGrath is a driver of global-scale business growth and digital transformation, focusing on emerging technologies, ethics, risk management, and sustainability. As a retired Deloitte IT executive, board member, and founder of QplusAI LLC, he is known for advising leaders on the latest technologies and their impact on organizations, most recently guiding the application of Artificial Intelligence to a business considering the ethical, governance, and leadership implications. He is a member of the CXO Advisory Network of the A.Team start-up, he sits on Blumberg Capital’s CIO Council, an Advisory Board for the early-stage venture capital firm. He is a Board Member of the Society for Information Management (SIM) Tampa Bay chapter, where he chairs a Shared Interest Group on the convergence of global megatrends and emerging technologies to advise national SIM leadership. He is a popular speaker, panelist, and Adjunct Professor at USF’s Muma College of Business, teaching MBA and Executive MBA students. Quintin holds a Doctor of Business Administration (D.B.A.) focused on AI, ethics, and risk management from the University of South Florida, a Master of Science in Engineering from the University of Cape Town, and a Master of Arts from Wheaton College. www.linkedin.com/in/quintinmcgrath/

Tampa, FL

Public Documents 1

Managing Ethical Risks of Artificial Intelligence in Business Applications

Quintin McGrath

and 2 more

February 27, 2024

The introduction of artificial intelligence (AI) capabilities in business applications provides significant benefits but requires organizations to manage critical risks of AI ethical consequences. We survey a range of large organizations on their use of enterprise risk management (ERM) processes and toolsets to predict and control the ethical risks of AI. Four serious gaps in current ERM systems are identified from analyses of the survey results: (1) AI ethical principles do not translate effectively to ethical practices; (2) Real-time monitoring of AI ethical risks is needed; (3) ERM systems emphasize economic not ethical risks; and (4) When ethical risks are identified, no solutions are readily at hand. To address these gaps, we propose a proactive approach to manage ethical risks by extending current ERM frameworks. An enhanced ERM (e-ERM) 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 pro-ethical management oversight as organizations move to ubiquitous use of AI-driven business applications.