Artificial intelligence: Who is responsible for the diagnosis?

Area of Science:

• Medical Imaging
• Artificial Intelligence Ethics
• Radiology

Background:

• The integration of artificial intelligence (AI) in radiology presents novel challenges in assigning responsibility for clinical decisions.
• Traditional models of accountability are complicated when AI systems influence or automate diagnostic processes.

Discussion:

• Radiologists are ultimately responsible for diagnoses made with AI assistance, necessitating comprehensive training on AI functionalities and limitations.
• Researchers and developers in AI for radiology must establish guidelines for trustworthy AI, addressing potential biases and the 'black box' problem.
• The increasing reliance on AI tools, particularly to address radiologist shortages, raises concerns about automation bias and the need for informed consent.

Key Insights:

• Radiologists must be trained to use AI responsibly, understanding its impact on diagnostic accuracy and patient care.
• Accountability frameworks are needed to address the validation of AI outputs, especially from opaque algorithms.
• Balancing AI autonomy with professional oversight is crucial for maintaining ethical standards in radiology.

Outlook:

• Future legislation should clarify the professional responsibilities of radiologists when utilizing autonomous AI systems.
• Developing robust quality measures and informed consent protocols is essential for the safe deployment of AI in diagnostic imaging.
• A balanced approach is required to leverage AI's benefits while mitigating risks and preserving the radiologist's role in patient care.