Beyond the algorithm: embedding ethics for trustworthy AI in radiology and oncology

This article explores embedding ethics and social-science expertise into radiological AI, highlighting trust, accountability, fairness, and interdisciplinary stakeholder engagement for trustworthy cancer imaging.

Educational Objectives

Educational Aim:

The aim is to foster critical understanding of ethical, social, and clinical dimensions in AI for radiology/oncology, moving beyond abstract principles toward embedded, interdisciplinary practices.

Educational Outcomes:
Upon completion of this module practitioners should have a clear understanding of:

1. The four guiding dimensions of trustworthy AI: explainability, trust, accountability, and fairness.
2. How ethical issues in radiological AI are relational, requiring multi-stakeholder engagement and interdisciplinary approaches.
3. Embedding ethics and Social Sciences and Humanities (SSH) expertise strengthens responsible AI integration into radiological clinical workflows and patient care.

Instructions for this Module

• Read the supplied reading material and complete the quiz that follows;
• You have three attempts to pass the quiz;
• The pass grade is 70%;
• You need to pass the quiz to claim your CPD certificate;
• Please click on the CPD certificate link below to claim your CPD certificate and to update your CPD Manager.

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