Perspectives for Generative AI-Assisted Art Therapy for Melanoma Patients

authored by

Lennart Jütte, Ning Wang, Martin Steven, Bernhard Roth

Abstract

Digital technologies are making their mark in medicine, and especially also in art therapy, offering innovative therapeutic interventions for patients, including those with melanoma skin cancer. However, the integration of novel technologies, such as AI-generated art, brings along ethical, psychological, and technical challenges that are viewed differently among therapists. We aim to gauge art therapists’ views on the ethical, application, and challenge facets of utilizing AI-generated art from medical images in therapy. The focus is on assessing its applicability and limitations for melanoma patients. Art therapists were surveyed via a questionnaire focusing on their experience, digital tool familiarity, and views on AI in therapy, encompassing ethics, benefits, challenges, and applicability for melanoma. Art therapists have already implemented digital technologies and acknowledged potential therapeutic benefits of creating personalized artworks with generative artificial intelligence. Attention needs to be given to technological hurdles and the necessity for supplementary interventions. Views on the method’s adaptability varied, underscoring a need for tailored, patient-focused applications. Art therapists are welcoming AI-generated art as a promising creative therapeutic tool and acknowledge potential therapeutic benefits. There are ethical, technical, and psychological challenges that must be addressed for application in therapeutic sessions. Therapists should navigate AI integration with sensitivity, adhering to ethical norms around consent and privacy. Future studies should show the therapeutic benefit in practice with emphasis on equipping therapists to manage the technical complexities effectively. Furthermore, it is important to ensure that patients can influence the AI output, allowing for creative moments in the process.

Organisation(s)

Hannover Centre for Optical Technologies (HOT)
PhoenixD: Photonics, Optics, and Engineering - Innovation Across Disciplines

Type

Article

Journal

AI (Switzerland)

Volume

5

Pages

1648-1669

No. of pages

22

Publication date

06.09.2024

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Artificial Intelligence

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.3390/ai5030080 (Access: Open)