The implementation of artificial intelligence (AI) in diagnostic decision making is both a promising and challenging development in the field of medicine. Diagnostic radiology in particular has seen progress in various applications of AI, including: recommending imaging protocols that optimize radiation doses (McCollough and Leng, 2020), providing prediction models for images (Najjar, 2023), and worklist prioritization (Tadavarthi et al., 2022). With these technological advances come various ethical concerns relating to the appropriate use of data, the assumption of medical liability, and the providing of effective patient education on the role of AI to name a few. Radiologists are in a unique situation where they are learning about ethical AI use while concurrently inventing it and incorporating it into practice (Geis et al., 2019). Understanding the ethical challenges associated with the use of AI will allow radiologists to use data appropriately and fulfill their moral duty to do right by their patients. In this poster, some of the main ethical concerns associated with AI use in radiology will be discussed. These include: making sure that patients are thoroughly educated on the role that AI is playing in making a diagnosis (Derevianko et al., 2023), minimizing the amount of harm and bias that can potentially result from the testing and training of AI (Rouzrokh et al., 2022), ensuring that human operators, designers, and other stakeholders maintain accountability in an equitable manner (Maliha et al., 2021), monitoring AI performance metrics over time to judge whether they consistently meet standards (Najjar, 2023), protecting patient data privacy (Lotan et al., 2020) (Murdoch, 2021), establishing a standardized code of ethics and practices for AI use in clinical decision making (Geis et al., 2019), and determining whether AI testing data appropriately reflects the targeted patient cohort (Tsopra et a., 2021). In addition, innovative approaches regarding how to handle these concerns will be described.