Artificial Intelligence: the global landscape of ethics guidelines

TL;DR

This paper analyzes global AI ethics guidelines, revealing convergence on five core principles but significant divergence in interpretation and implementation, emphasizing the need for integrated ethical analysis and practical strategies.

Contribution

It provides a comprehensive mapping of existing AI ethics guidelines, highlighting commonalities and divergences to inform future policy and practice.

Findings

Global convergence on five ethical principles

Significant divergence in interpretation and application

Highlights need for integrated ethical analysis and implementation strategies

Abstract

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.