Principles of Ethical AI Use
Ethical use of artificial intelligence in radiology requires transparency accountability fairness and respect for patient autonomy and these principles guide procurement validation deployment and monitoring decisions and ensure that AI augments rather than replaces clinical judgment and that patients benefit from improved efficiency and accuracy while harms are minimized
Bias Mitigation and Equity
Addressing bias begins with diverse representative training data and with subgroup performance analysis and institutions implement governance that requires vendors and researchers to report performance across demographic and device variables and to provide mitigation plans when disparities are identified and continuous monitoring ensures that models remain equitable as practice and populations evolve
Consent Transparency and Patient Communication
Patients should be informed when AI contributes to their care and communication focuses on what the tool does its limitations and how clinicians retain final responsibility and institutions develop patient facing materials and consent processes that explain AI use in plain language and that respect preferences about data use and secondary research