Artificial Intelligence-Induced Deskilling in Interventional Pulmonology: An International Cross-Sectional Survey on...

Area of Science:

• Medical Specialties
• Pulmonology
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is transforming interventional pulmonology (IP).
• The risk of AI-induced deskilling in procedural and cognitive competencies within IP is not well understood.
• Deskilling may impact the proficiency of highly specialized medical professionals.

Purpose of the Study:

• To assess interventional pulmonologists' perceptions of AI-induced deskilling risks.
• To explore attitudes towards mitigation strategies for potential deskilling.
• To identify research priorities related to AI and skill preservation in IP.

Main Methods:

• An international, observational, cross-sectional survey was conducted in May 2026.
• 118 expert interventional pulmonologists from 5 continents participated.
• A questionnaire assessed AI value perception, deskilling concerns, automation bias awareness, and support for training/governance strategies.

Main Results:

• 87% perceived high clinical value of AI, but 73% worried about procedural deskilling and 83% about upskilling inhibition.
• Awareness of automation bias was low (38%) but its relevance recognized post-definition (81%).
• Strong support exists for AI-free training (84%), simulation (86%), performance monitoring (78%), and governance (70%).

Conclusions:

• Expert interventional pulmonologists internationally perceive AI-induced deskilling as a significant emerging risk.
• Proactive measures, including prospective research, educational reforms, and governance, are crucial.
• Ensuring the preservation of core procedural skills is paramount amidst AI integration.