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Endoscopy 2026; 58(04): 437
DOI: 10.1055/a-2790-5887
Letter to the editor

Reply to Lei et al.

Authors

  • Yuichi Mori 

    1   Clinical effectiveness research group, University of Oslo, Oslo University Hospital, Oslo, Norway (Ringgold ID: RIN155272)
    2   Gastroenterology Section, Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway (Ringgold ID: RIN155272)
    3   Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan (Ringgold ID: RIN220878)

  • Uri Kopylov

    4   Gastroenterology, Chaim Sheba Medical Center, Ramat Gan, Israel (Ringgold ID: RIN26744)
    5   School of Medicine, Tel Aviv University, Ramat Gan, Israel (Ringgold ID: RIN26745)

  • Pieter Sinonquel 

    6   Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, Belgium (Ringgold ID: RIN60182)
    7   Department of Translational Research in Gastrointestinal Diseases (TARGID), KU Leuven, Leuven, Belgium (Ringgold ID: RIN26657)

  • Alanna Ebigbo

    8   Internal Medicine, Gastroenterology and Interventional Endoscopy, St. Josef University Hospital, Bochum, Germany

  • Tony Tham 

    9   Department of Gastroenterology, Ulster Hospital, Belfast, Belfast, United Kingdom of Great Britain and Northern Ireland
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Embedding artificial intelligence literacy in endoscopy training: extending the European Society of Gastrointestinal Endoscopy (ESGE) curriculum frameworkEndoscopy 2026; 58(04): 435-436
DOI: 10.1055/a-2776-5205

10.1055/a-2776-5205

We thank Lei et al. [1] for their constructive correspondence regarding our recently published European Society of Gastrointestinal Endoscopy (ESGE) position statement. The goal of our statement is to facilitate the safe and effective integration of artificial intelligence (AI) tools into endoscopy training [2]. We appreciate the points raised, particularly concerning the importance of the timing of AI introduction during training and the need for bias-mitigation measures.

In terms of timing, we fully agree that further research is required to determine the optimal timing for the introduction of AI in endoscopy training. The current lack of robust evidence limited our position statement to raising awareness of AI-related bias. Nevertheless, future revisions should expand guidance on when and how AI tools should be incorporated into training curricula, supported by stronger research-based evidence.

We also agree with the insights regarding bias mitigation. The introduction of AI should be approached with a balanced perspective, rather than being dominated by concerns related to AI-driven bias, such as automation bias or deskilling [3]. Human progress has historically involved both gains and losses; for example, while calculators save time and enable focus on higher level tasks, they may also erode our calculation skills. Such trade-offs are usually regarded as a positive aspect of human evolution. Similarly, in medicine, the thoughtful integration of AI may allow clinicians to focus more on aspects of patient care that are of greater importance, representing a technological benefit. On the other hand, it remains essential to investigate strategies to mitigate bias and safeguard our life-critical clinical skills, such as resuscitation techniques. Potential approaches include simulation-based training, as highlighted by the authors, as well as psychological interventions addressing human behavior [4].

In conclusion, these issues are central to the safe integration of AI into endoscopy training and should be addressed in future evidence-based curricula.



Publication History

Article published online:
20 March 2026

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