Javascript must be enabled to continue!
Transparency of Artificial Intelligence in Healthcare: Insights from Professionals in Computing and Healthcare Worldwide
View through CrossRef
Although it is widely assumed that Artificial Intelligence (AI) will revolutionise healthcare in the near future, considerable progress must yet be made in order to gain the trust of healthcare professionals and patients. Improving AI transparency is a promising avenue for addressing such trust issues. However, transparency still lacks maturation and definitions. We seek to answer what challenges do experts and professionals in computing and healthcare identify concerning transparency of AI in healthcare? Here, we examine AI transparency in healthcare from five angles: interpretability, privacy, security, equity, and intellectual property. We respond to this question based on recent literature discussing the transparency of AI in healthcare and on an international online survey we sent to professionals working in computing and healthcare and potentially within AI. We collected responses from 40 professionals around the world. Overall, the survey results and current state of the art suggest key problems are a generalised lack of information available to the general public, a lack of understanding of transparency aspects covered in this work, and a lack of involvement of all stakeholders in the development of AI systems. We propose a set of recommendations, the implementation of which can enhance the transparency of AI in healthcare.
Title: Transparency of Artificial Intelligence in Healthcare: Insights from Professionals in Computing and Healthcare Worldwide
Description:
Although it is widely assumed that Artificial Intelligence (AI) will revolutionise healthcare in the near future, considerable progress must yet be made in order to gain the trust of healthcare professionals and patients.
Improving AI transparency is a promising avenue for addressing such trust issues.
However, transparency still lacks maturation and definitions.
We seek to answer what challenges do experts and professionals in computing and healthcare identify concerning transparency of AI in healthcare? Here, we examine AI transparency in healthcare from five angles: interpretability, privacy, security, equity, and intellectual property.
We respond to this question based on recent literature discussing the transparency of AI in healthcare and on an international online survey we sent to professionals working in computing and healthcare and potentially within AI.
We collected responses from 40 professionals around the world.
Overall, the survey results and current state of the art suggest key problems are a generalised lack of information available to the general public, a lack of understanding of transparency aspects covered in this work, and a lack of involvement of all stakeholders in the development of AI systems.
We propose a set of recommendations, the implementation of which can enhance the transparency of AI in healthcare.
Related Results
Perceptions of Telemedicine and Rural Healthcare Access in a Developing Country: A Case Study of Bayelsa State, Nigeria
Perceptions of Telemedicine and Rural Healthcare Access in a Developing Country: A Case Study of Bayelsa State, Nigeria
Abstract
Introduction
Telemedicine is the remote delivery of healthcare services using information and communication technologies and has gained global recognition as a solution to...
Varieties of Transparency
Varieties of Transparency
Although the purpose of this chapter is to construct an anatomy of transparency, it is essential to address the triangular relationship between transparency, openness, and surveill...
KNOWLEDGE, ATTITUDES, AND PERCEPTIONS OF HEALTHCARE PROFESSIONALS ON THE USE OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE – A CROSS-SECTIONAL STUDY
KNOWLEDGE, ATTITUDES, AND PERCEPTIONS OF HEALTHCARE PROFESSIONALS ON THE USE OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE – A CROSS-SECTIONAL STUDY
ABSTRACT
Background: Artificial Intelligence (AI) has become an increasingly integral part of healthcare systems, offering the potential to enhance diagnosis, treatment, and patien...
Reducing healthcare costs in the United States: Does price transparency help?
Reducing healthcare costs in the United States: Does price transparency help?
Background: Price transparency in healthcare is gaining popularity as a strategy to reduce costs by fostering cost-conscious consumer behavior and enhancing competition among provi...
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE STANDARDIZATION AND IMPROVEMENT OF NURSING CARE
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE STANDARDIZATION AND IMPROVEMENT OF NURSING CARE
Background. The rapid advancement of artificial intelligence technologies and their implementation in medical practice create new opportunities for enhancing the quality of patient...
Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment
Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial ...
Advancements in Quantum Computing and Information Science
Advancements in Quantum Computing and Information Science
Abstract: The chapter "Advancements in Quantum Computing and Information Science" explores the fundamental principles, historical development, and modern applications of quantum co...
New Era’s of Artificial Intelligence in Pharmaceutical Industries
New Era’s of Artificial Intelligence in Pharmaceutical Industries
Artificial Intelligence (AI) is the future of pharmaceutical industries. We make our tasks easier with help of Artificial Intelligence in future. With help of Artificial Intelligen...

