The paper "The Ethics of AI Ethics" by Dr. Thilo Hagendorff evaluates and compares 21 major AI ethics guidelines, highlighting their overlaps and omissions. The author argues that these guidelines, while aiming to harness the disruptive potential of AI technologies, often lack enforcement mechanisms and fail to significantly influence human decision-making in AI and machine learning. The paper identifies several issues not addressed in the guidelines, such as the danger of malevolent AGI, machine consciousness, and the reduction of social cohesion by AI systems. It also critiques the male-dominated nature of AI ethics discourse and the lack of diversity within the AI community. The author suggests that a transition from a deontological to a virtue ethics approach is necessary, focusing on character dispositions and individual responsibility. Additionally, the paper calls for institutional changes, including legal frameworks, independent auditing, and expanded university curricula to address ethical concerns in AI. The conclusion emphasizes the need for a more detailed and context-sensitive ethical approach that promotes responsible autonomy and freedom of action in AI development and application.The paper "The Ethics of AI Ethics" by Dr. Thilo Hagendorff evaluates and compares 21 major AI ethics guidelines, highlighting their overlaps and omissions. The author argues that these guidelines, while aiming to harness the disruptive potential of AI technologies, often lack enforcement mechanisms and fail to significantly influence human decision-making in AI and machine learning. The paper identifies several issues not addressed in the guidelines, such as the danger of malevolent AGI, machine consciousness, and the reduction of social cohesion by AI systems. It also critiques the male-dominated nature of AI ethics discourse and the lack of diversity within the AI community. The author suggests that a transition from a deontological to a virtue ethics approach is necessary, focusing on character dispositions and individual responsibility. Additionally, the paper calls for institutional changes, including legal frameworks, independent auditing, and expanded university curricula to address ethical concerns in AI. The conclusion emphasizes the need for a more detailed and context-sensitive ethical approach that promotes responsible autonomy and freedom of action in AI development and application.