Comprehensive Summary
The article addresses the potential applications of artificial intelligence (AI) in dermatology residency training, focusing on how AI will impact didactic education, clinical operations, scholarly work, and resident evaluations. The authors review existing use of AI and propose action steps for training programs to adapt to evolving technologies. Although AI tools are becoming increasingly accurate in diagnosis, they are still limited by biased and inconsistent training data, underrepresenting darker skin tones and rare conditions. The discussion emphasizes that while AI offers efficiency and personalization, residency programs must develop policies to make sure residents acquire core skills in clinical reasoning, morphology, and patient communication.
Outcomes and Implications
The study underscores both the opportunities and risks of integrating AI into clinical environments. While AI can enhance diagnostic accuracy, streamline operations, and support medical learning, it also raises the risk of residents to be overreliant on technology. Humans are responsible to make complex decision-making, maintain patient-physician relationships, and expand creativity, and AI at times hinder their development. AI is already prevalent in clinical operations through AI-assisted chatbots, influencing scholarly work through use of large language models (LLMs), and contributing to didactic education through basic AI overview. Further implementation of AI will require standardized curricula, disclosure of AI policies, and guidance on competency evaluation for trainees to balance technology with human skills.