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

AI ethics are drowning in a sea of ineffective principles. While guidelines abound, they’re often vague, ignored, and lack teeth, failing to address the real dangers of AI. We need… Read more

AI ethics debate rages on! Survey reveals key concerns: transparency, accountability, privacy are top priorities, but challenges like lack of knowledge, regulation, and monitoring bodies hinder progress. Practitioners and lawmakers… Read more

HCAI aims to prioritize users, but a survey shows a gap between developers’ focus on tech and users’ valuing AI’s social impact and functionality. HCAI needs to bridge this gap… Read more

AI’s two faces: While its rapid growth creates new jobs in healthcare, transport, and more, concerns about job losses, dehumanization, and societal impact grow. This study delves into both sides,… Read more