Ethics-Based Auditing to Develop Trustworthy AI
This addresses the problem of ensuring ethical AI development for society, but it is incremental as it builds on existing discussions without introducing new methods or data.
The paper argues that ethics-based auditing can bridge the gap between principles and practice in AI ethics, highlighting its potential benefits such as improved decision-making and user satisfaction, while identifying constraints for effective implementation.
A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation.