Abstract
This chapter reviews the business ethics literature on ethics auditing to extract lessons for the emerging practice of ethics auditing of Artificial Intelligence (AI). It reviews the definitions, purposes and motivations of ethics audits, identifies their benefits as well as limitations, and compares various theoretical and practical approaches to ethics auditing. It distils seven lessons for the ethics auditing of AI and finds that ethics audits need to be comprehensive, involve stakeholders, entice behaviour change, be pragmatic and rigorous, be widely endorsed, fitting in context but also comparable, and lastly integrate a technical dimension with an organisational dimension. It is crucial that, while ethics auditing can also have financial benefits, their main goal must remain the improvement of the ethical performance and meaningful accountability of the audited organisation. The novel elements of AI should not blind us to the continuities of social embeddedness and organisational dynamics. Ethics auditing of AI can learn valuable lessons from failed and successful previous efforts to audit the ethics of organisations.