A3 Refereed book chapter or chapter in a compilation book
Trustworthy artificial intelligence in healthcare
Authors: Subasi Abdulhamit, Ozaltin Oznur, Mitra Arka, Subasi Muhammed Enes, Sarirete Akila
Editors: Patricia Ordóñez de Pablos, Xi Zhang
Publisher: Elsevier
Publication year: 2023
Book title : Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry
Journal name in source: Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry: Volume 2
Series title: Information Technologies in Healthcare Industry
Volume: 2
First page : 145
Last page: 177
ISBN: 978-0-443-15299-3
DOI: https://doi.org/10.1016/B978-0-443-15299-3.00015-4
Web address : https://doi.org/10.1016/B978-0-443-15299-3.00015-4
In addition to several chances to enhance people's lives and the development of communities, economies, and healthcare, artificial intelligence (AI) similarly presents a number of brand-new social, legal, ethical, and technological issues. Since trust is the cornerstone of communities, economies, healthcare, and sustainable development, trustworthy AI (TAI) is based on the premise that people, organizations, and society can only ever use AI to its full potential if trust can be created in its design, implementation, and application (Thiebes et al., 2021). AI has the potential to significantly enhance the provision of healthcare and other services, which promote the health and welfare of the population. However, there are also potential risks related to utilizing AI in healthcare, which might result in accidental damage. Numerous recommendations are made with a range of stakeholders in mind, with a focus on directing practitioners toward stronger and more ethical AI applications. However, the application domain and the environment of an AI system affect its interpretation, applicability, and implementation (Zicari et al., 2021). The idea of TAI encourages the idea that people, societies, and organizations can understand the full capacity of AI if trust can be formed in its development and deployment. This will maximize the advantages of AI while also reducing or even eliminating its risks and hazards. Even though the recommended therapies might improve the patients’ well-being, it is doubtful that either doctors or patients will follow the suggestions if, for instance, neither group has confidence in an AI-based system's diagnosis or therapy recommendations. The significance of TAI, however, extends beyond industries like autonomous vehicles and healthcare (Thiebes et al., 2021). This chapter's primary contribution is to show how to employ TAI recommendations in practice in the healthcare area.