Managing Ethical Risks of Artificial Intelligence in Business Applications

Abstract

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.