This paper is in the following e-collection/theme issue:

Letters to the Editor (4) Theme Issue (2023): AI and ChatGPT in Dermatology (17) Artificial Intelligence (1660) Chatbots and Conversational Agents (614) Clinical Information and Decision Making (1601) Machine Learning (1680)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71768, first published .
The Importance of Comparing New Technologies (AI) to Existing Tools for Patient Education on Common Dermatologic Conditions: A Commentary

The Importance of Comparing New Technologies (AI) to Existing Tools for Patient Education on Common Dermatologic Conditions: A Commentary

The Importance of Comparing New Technologies (AI) to Existing Tools for Patient Education on Common Dermatologic Conditions: A Commentary

Authors of this article:

Parker Juels1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

    School of Medicine, University of Colorado Anschutz Medical Campus, 13001 E 17th Pl, Aurora, United States

    Corresponding Author:

    Parker Juels, BA



    In their study, Chau and colleagues discussed the sufficiency of multiple artificial intelligence resources in answering possible patient questions on common dermatological conditions [1]. It is very important to examine the reliability of artificial intelligence, especially as it relates to patient care and is becoming increasingly widespread. It is also very beneficial to have a comparison of what artificial intelligence is available and what their unique weaknesses are. However, we do have a plethora of existing resources, including paper handouts, peer-reviewed journals, patient-centered websites, and physical media, all of which have been providing reliable information to patients for many years. Because artificial intelligence is not a harmless technology [2,3], the proven efficacy of the existing resources [4,5], and the reported errors in artificial intelligence answers [1], it is not sufficient to only prove that artificial intelligence could be reliable but also prove that it has advantages compared to existing tools.

    Research has demonstrated moderate improvement in patient care with either written or online information provided by healthcare providers [4]. Additionally, more recent research has shown that information provided through patient portals improves patient understanding and healthcare outcomes [5]. Since there are established benefits of providing information directly to patients and the existence of a plethora of reliable websites that provide quality information, it is important to compare any new intervention, including artificial intelligence, to these existing information forms.

    It is especially important to establish a significant benefit of artificial intelligence compared to our existing resources due to the detrimental outcomes that increased use could have on the environment and patient knowledge. Artificial intelligence usage is an energy-demanding and resource-consuming practice that requires an outsized water consumption and carbon output compared with traditional search inquiries [2,3]. Additionally, the study mentions that there have been reported cases of artificial intelligence making up sources or providing completely inaccurate information. This is something the study did examine, finding no evidence of hallucinations/fabrications. However, it is important to have a better understanding of how likely these events are on a larger scale and how to prevent them before recommending patient use of artificial intelligence.

    Without true controls, the study’s conclusions do not provide adequate confidence in recommending patient usage of artificial intelligence. There should also be further consideration of how AI can be used to augment, not replace existing forms of patient education. Further research that considers the advantages of existing resources and pitfalls of artificial intelligence is needed before widespread artificial intelligence use in patient care.

    Conflicts of Interest

    None declared.

    1. Chau CA, Feng H, Cobos G, Park J. The comparative sufficiency of ChatGPT, Google Bard, and Bing AI in answering diagnosis, treatment, and prognosis questions about common dermatological diagnoses. JMIR Dermatol. Jan 7, 2025;8:e60827. [CrossRef] [Medline]
    2. Yu Y, Wang J, Liu Y, et al. Revisit the environmental impact of artificial intelligence: the overlooked carbon emission source? Front Environ Sci Eng. Dec 2024;18(12):158. [CrossRef]
    3. Morain A, Ilangovan N, Delhom C, Anandhi A. Artificial intelligence for water consumption assessment: state of the art review. Water Resour Manage. Jul 2024;38(9):3113-3134. [CrossRef]
    4. Giguère A, Zomahoun HTV, Carmichael PH, et al. Printed educational materials: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. Jul 31, 2020;8(8):CD004398. [CrossRef] [Medline]
    5. Johnson AM, Brimhall AS, Johnson ET, et al. A systematic review of the effectiveness of patient education through patient portals. JAMIA Open. Apr 2023;6(1):ooac085. [CrossRef] [Medline]

    Edited by Surya Nedunchezhiyan; This is a non–peer-reviewed article. submitted 25.01.25; accepted 14.02.25; published 01.04.25.

    Copyright

    © Parker Juels. Originally published in JMIR Dermatology (http://derma.jmir.org), 1.4.2025.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Dermatology, is properly cited. The complete bibliographic information, a link to the original publication on http://derma.jmir.org, as well as this copyright and license information must be included.