The Concept of Accountability in AI Ethics and Governance
Abstract Calls to hold artificial intelligence to account are intensifying. Activists and researchers alike warn of an “accountability gap” or even a “crisis of accountability” in AI. Meanwhile, several prominent scholars maintain that accountability holds the key to governing AI. But usage of the term varies widely in discussions of AI ethics and governance. This chapter begins by disambiguating some different senses and dimensions of accountability, distinguishing it from neighboring concepts, and identifying sources of confusion. It proceeds to explore the idea that AI operates within an accountability gap arising from technical features of AI as well as the social context in which it is deployed. The chapter also evaluates various proposals for closing this gap. It concludes that the role of accountability in AI ethics and governance is vital but also more limited than some suggest. Accountability’s primary job description is to verify compliance with substantive normative principl
Abstract Calls to hold artificial intelligence to account are intensifying. Activists and researchers alike warn of an “accountability gap” or even a “crisis of accountability” in AI. Meanwhile, several prominent scholars maintain that accountability holds the key to governing AI. But usage of the term varies widely in discussions of AI ethics and governance. This chapter begins by disambiguating some different senses and dimensions of accountability, distinguishing it from neighboring concepts, and identifying sources of confusion. It proceeds to explore the idea that AI operates within an accountability gap arising from technical features of AI as well as the social context in which it is deployed. The chapter also evaluates various proposals for closing this gap. It concludes that the role of accountability in AI ethics and governance is vital but also more limited than some suggest. Accountability’s primary job description is to verify compliance with substantive normative principles—once those principles are settled. Theories of accountability cannot ultimately tell us what substantive standards to account for, especially when norms are contested or still emerging. Nonetheless, formal mechanisms of accountability provide a way of diagnosing and discouraging egregious wrongdoing even in the absence of normative agreement. Providing accounts can also be an important first step toward the development of more comprehensive regulatory standards for AI.
Executive Summary
The article 'The Concept of Accountability in AI Ethics and Governance' explores the growing calls for accountability in the realm of artificial intelligence, highlighting an 'accountability gap' that arises from both technical and social dimensions. The author distinguishes various senses of accountability, evaluates proposals to address this gap, and concludes that while accountability is crucial for verifying compliance with normative principles, it cannot independently determine what those principles should be. The article emphasizes the role of accountability in diagnosing and discouraging wrongdoing and as a stepping stone toward more comprehensive regulatory standards.
Key Points
- ▸ Accountability in AI is a multifaceted concept with varying definitions and dimensions.
- ▸ An accountability gap exists due to technical features of AI and its social context.
- ▸ Accountability mechanisms are essential for verifying compliance with normative principles but cannot establish those principles.
- ▸ Formal accountability mechanisms can diagnose and discourage egregious wrongdoing even without normative agreement.
- ▸ Accountability can serve as a preliminary step toward developing comprehensive regulatory standards for AI.
Merits
Comprehensive Disambiguation
The article effectively distinguishes different senses and dimensions of accountability, clarifying a concept that is often used ambiguously in discussions of AI ethics and governance.
Critical Evaluation of Proposals
The author provides a rigorous evaluation of various proposals aimed at closing the accountability gap, offering a balanced assessment of their potential and limitations.
Practical Insights
The article offers practical insights into how accountability mechanisms can be used to diagnose and discourage wrongdoing, even in the absence of normative agreement.
Demerits
Limited Scope of Accountability
The article acknowledges that accountability mechanisms cannot independently determine substantive normative principles, which may limit their effectiveness in highly contested or emerging ethical landscapes.
Theoretical Focus
While the article provides a thorough theoretical analysis, it could benefit from more concrete examples or case studies to illustrate the practical application of accountability mechanisms.
Expert Commentary
The article 'The Concept of Accountability in AI Ethics and Governance' provides a timely and rigorous analysis of the growing calls for accountability in the field of artificial intelligence. The author's disambiguation of the concept of accountability is particularly valuable, as it clarifies a term that is often used ambiguously in both academic and policy discussions. The identification of an accountability gap arising from technical and social dimensions of AI is a significant contribution, as it highlights the complex challenges involved in governing AI systems. The article's evaluation of proposals to close this gap is thorough and balanced, offering a nuanced perspective on the potential and limitations of various accountability mechanisms. The conclusion that accountability's primary role is to verify compliance with substantive normative principles, rather than to establish those principles, is a crucial insight. It underscores the need for a separate and comprehensive process to develop and agree upon normative standards for AI. The article's emphasis on the practical role of accountability in diagnosing and discouraging wrongdoing, even in the absence of normative agreement, is particularly noteworthy. This insight has significant implications for both the development of AI systems and the formulation of regulatory standards. Overall, the article makes a substantial contribution to the ongoing debate about AI ethics and governance, offering a rigorous and balanced analysis that will be of value to both academics and policymakers.
Recommendations
- ✓ Further research should explore concrete examples and case studies to illustrate the practical application of accountability mechanisms in AI systems.
- ✓ Policymakers and organizations should collaborate to develop comprehensive regulatory standards for AI, recognizing the limitations of accountability mechanisms in establishing normative principles.
