<p>This paper introduces a distinction between hard and easy problems in the field of Artificial Intelligence (AI) or Machine Learning (ML) ethics. It mirrors a well-known distinction in the literature on the philosophy of mind between the hard and easy problems of consciousness. That distinction is then used to highlight the importance of existing ethical guidance and to show how we can improve the chances at finding actionable solutions in the field of AI/ML ethics. This is especially relevant for organizations working under established governance instruments on topics such as scientific integrity or data ethics. Such organizations already have ethical expectations for their members. The essence of these expectations remains relevant even as they fully or partially automate tasks performed by individuals with the help of AI or ML algorithms. We can replace a person’s involvement in a process by using algorithms, but we cannot throw away existing ethical guidance about that process.</p>