AI ethics audit struggles: New research finds practical challenges beyond existing frameworks. Multinational companies face internal obstacles like aligning standards, defining scope, and driving change. Study suggests EBA needs more… Read more

EU AI ethics guidelines reviewed: diversity concerns, “ethics shopping” risks, and enforcement gaps identified. Red lines urged, citing social/ecological costs, research buyouts, and neglected ethical issues. Law enforcement focus seen… Read more

AI ethics need lessons from business ethics! This paper proposes applying knowledge from areas like stakeholder management and corporate governance to address AI’s ethical challenges. By sharing insights, both fields… Read more

Assigning human qualities to AI (anthropomorphism) overstates its abilities and muddies our moral judgments, leading to ethical issues. This essay explores how attributing human-like traits can both exaggerate AI’s performance… Read more

AI accuracy crucial for privacy trust: research delves into how individuals and AI systems can collaborate to ensure information sharing stays private. Trustworthiness requires shared beliefs, and an AI’s accuracy… Read more

Machine unlearning, a tool for RTBF (Right to be Forgotten), can impact AI fairness. This study explores two common methods (SISA, AmnesiacML) vs. retraining (ORTR) across fairness datasets and deletion… Read more

AI ethics toolkits promise guidance, but fall short! They lack support for navigating complex power dynamics within organizations, leaving practitioners unprepared to tackle real-world ethical challenges. Future toolkits need to… Read more

AI ethics: Drowning in principles, lacking solutions. Many guidelines exist, but they’re too vague and don’t translate well to real-world AI. This analysis highlights the need for concrete methods and… Read more