The article explores the global landscape of ethical guidelines for artificial intelligence (AI), analyzing principles and guidelines issued by various organizations. It finds a global convergence around five ethical principles: transparency, justice and fairness, non-maleficence, responsibility, and privacy. However, there is significant divergence in how these principles are interpreted, their importance, the issues they pertain to, and their implementation. The study highlights the importance of integrating guideline development with ethical analysis and implementation strategies. The research identifies 84 documents containing ethical principles or guidelines for AI, with most coming from developed countries. The principles are often addressed to multiple stakeholders, including the public and private sectors. Eleven ethical values and principles were identified, with transparency being the most prevalent. Other principles include justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity. The study discusses the interpretation and implementation of each principle, highlighting differences in how they are understood and applied. For example, transparency is seen as a way to minimize harm and improve AI, while justice is often linked to fairness and the prevention of bias and discrimination. Non-maleficence focuses on avoiding harm, while responsibility and accountability emphasize the need for clear attribution of responsibility and legal liability. Privacy is viewed as both a value and a right, with suggestions for technical solutions, regulatory approaches, and research to protect it. Beneficence is often mentioned but rarely defined, with a focus on promoting human well-being and flourishing. Freedom and autonomy are seen as important for individuals, with a focus on self-determination and protection from technological experimentation and surveillance. Trust is considered essential for AI development, with calls for trustworthy AI research and technology. Sustainability and solidarity are less emphasized, though they are important for ensuring AI benefits society and the environment. The study concludes that while there is a growing global consensus on ethical AI principles, there are significant differences in how they are interpreted and implemented. The findings suggest a need for better articulation of ethical principles and their practical application, as well as a balance between cross-national harmonization and respect for cultural diversity and moral pluralism.The article explores the global landscape of ethical guidelines for artificial intelligence (AI), analyzing principles and guidelines issued by various organizations. It finds a global convergence around five ethical principles: transparency, justice and fairness, non-maleficence, responsibility, and privacy. However, there is significant divergence in how these principles are interpreted, their importance, the issues they pertain to, and their implementation. The study highlights the importance of integrating guideline development with ethical analysis and implementation strategies. The research identifies 84 documents containing ethical principles or guidelines for AI, with most coming from developed countries. The principles are often addressed to multiple stakeholders, including the public and private sectors. Eleven ethical values and principles were identified, with transparency being the most prevalent. Other principles include justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity. The study discusses the interpretation and implementation of each principle, highlighting differences in how they are understood and applied. For example, transparency is seen as a way to minimize harm and improve AI, while justice is often linked to fairness and the prevention of bias and discrimination. Non-maleficence focuses on avoiding harm, while responsibility and accountability emphasize the need for clear attribution of responsibility and legal liability. Privacy is viewed as both a value and a right, with suggestions for technical solutions, regulatory approaches, and research to protect it. Beneficence is often mentioned but rarely defined, with a focus on promoting human well-being and flourishing. Freedom and autonomy are seen as important for individuals, with a focus on self-determination and protection from technological experimentation and surveillance. Trust is considered essential for AI development, with calls for trustworthy AI research and technology. Sustainability and solidarity are less emphasized, though they are important for ensuring AI benefits society and the environment. The study concludes that while there is a growing global consensus on ethical AI principles, there are significant differences in how they are interpreted and implemented. The findings suggest a need for better articulation of ethical principles and their practical application, as well as a balance between cross-national harmonization and respect for cultural diversity and moral pluralism.