Dr. Thilo Hagendorff evaluates the effectiveness of AI ethics guidelines, highlighting their limited impact on real-world AI applications. He analyzes 21 major AI ethics guidelines, identifying overlaps and omissions, and examines how ethical principles are implemented in AI research, development, and application. The paper argues that current guidelines are often superficial and lack enforceable mechanisms, leading to ineffective ethical practices. Ethical principles are frequently overshadowed by economic interests, and ethical guidelines are often used as marketing tools rather than genuine ethical frameworks. The paper also notes that ethical guidelines rarely address critical issues such as the risks of malevolent AI, machine consciousness, or the social and ecological impacts of AI. It emphasizes the need for a shift from deontological ethics to a virtue-based approach, focusing on character development and individual responsibility. The paper calls for stronger institutional changes, including legal frameworks, independent auditing mechanisms, and expanded educational curricula in ethics. It concludes that AI ethics must move beyond abstract principles to practical, context-sensitive approaches that promote responsible innovation and societal well-being.Dr. Thilo Hagendorff evaluates the effectiveness of AI ethics guidelines, highlighting their limited impact on real-world AI applications. He analyzes 21 major AI ethics guidelines, identifying overlaps and omissions, and examines how ethical principles are implemented in AI research, development, and application. The paper argues that current guidelines are often superficial and lack enforceable mechanisms, leading to ineffective ethical practices. Ethical principles are frequently overshadowed by economic interests, and ethical guidelines are often used as marketing tools rather than genuine ethical frameworks. The paper also notes that ethical guidelines rarely address critical issues such as the risks of malevolent AI, machine consciousness, or the social and ecological impacts of AI. It emphasizes the need for a shift from deontological ethics to a virtue-based approach, focusing on character development and individual responsibility. The paper calls for stronger institutional changes, including legal frameworks, independent auditing mechanisms, and expanded educational curricula in ethics. It concludes that AI ethics must move beyond abstract principles to practical, context-sensitive approaches that promote responsible innovation and societal well-being.