AccountabilityEthicsTrustworthinesscs.CY
Ethics-Based Auditing to Develop Trustworthy AI
Jakob Mokander, Luciano Floridi
April 30, 2021
Minds and Machines
210 citations
11 influential
Key Takeaways
-
Auditing can bridge the gap between AI ethics principles and real-world practice. The paper argues that ethics-based auditing serves as a practical mechanism to move beyond abstract ethical guidelines and ensure AI systems actually operate responsibly in deployment.
-
Ethics-based auditing delivers multiple concrete benefits: improving decision-making quality, increasing user satisfaction, supporting economic growth, informing legislation, and reducing human suffering—suggesting it's not just a compliance burden but a value-creating process.
-
Effective auditing requires three key design features: it must be continuous and constructive (ongoing rather than one-time), take a system-wide perspective (examining how all components interact ethically), and align with government policies and incentives that reward ethical behavior.
-
Understanding auditing's limitations is essential for success. The paper emphasizes that ethics-based auditing has inherent constraints that must be acknowledged and managed; ignoring these limitations could undermine both the auditing process and society's ability to benefit from AI automation.
Abstract
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.