Artificial Intelligence: the global landscape of ethics guidelines
This research addresses the need for clarity and agreement on ethical AI standards for policymakers, organizations, and researchers, though it is incremental in synthesizing existing guidelines.
The study mapped and analyzed global principles and guidelines for ethical AI, finding convergence around five ethical principles but significant divergence in interpretation, importance, application domains, and implementation strategies.
In the last five years, private companies, research institutions as well as public sector organisations have issued principles and guidelines for ethical AI, yet there is debate about both what constitutes "ethical AI" and which ethical requirements, technical standards and best practices are needed for its realization. To investigate whether a global agreement on these questions is emerging, we mapped and analyzed the current corpus of principles and guidelines on ethical AI. Our results reveal a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted; why they are deemed important; what issue, domain or actors they pertain to; and how they should be implemented. Our findings highlight the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.