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American Journal of Clinical Dermatology

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01-03-2021 | Artificial Intelligence | Review Article

The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World

Authors: Claire M. Felmingham, Nikki R. Adler, Zongyuan Ge, Rachael L. Morton, Monika Janda, Victoria J. Mar

Published in: American Journal of Clinical Dermatology | Issue 2/2021

Abstract

Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive accuracy in experimental settings. The majority of the literature to date has compared AI and dermatologists as opponents in skin cancer diagnosis. However, in the real-world clinical setting, the clinician will work in collaboration with AI. Existing evidence regarding the integration of such AI diagnostic tools into clinical practice is limited. Human factors, such as cognitive style, personality, experience, preferences, and attitudes may influence clinicians’ use of AI. In this review, we consider these human factors and the potential cognitive errors, biases, and unintended consequences that could arise when using an AI skin cancer diagnostic tool in the real world. Integrating this knowledge in the design and implementation of AI technology will assist in ensuring that the end product can be used effectively. Dermatologist leadership in the development of these tools will further improve their clinical relevance and safety.

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Title: The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World
Authors: Claire M. Felmingham
Nikki R. Adler
Zongyuan Ge
Rachael L. Morton
Monika Janda
Victoria J. Mar
Publication date: 01-03-2021
Publisher: Springer International Publishing
Keywords: Artificial Intelligence
Skin Cancer
Published in: American Journal of Clinical Dermatology / Issue 2/2021
Print ISSN: 1175-0561
Electronic ISSN: 1179-1888
DOI: https://doi.org/10.1007/s40257-020-00574-4

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The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World

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