TY - JOUR
T1 - Call for the responsible artificial intelligence in the healthcare
AU - Upadhyay, Umashankar
AU - Gradisek, Anton
AU - Iqbal, Usman
AU - Dhar, Eshita
AU - Li, Yu Chuan
AU - Syed-Abdul, Shabbir
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2023.
PY - 2023/12/21
Y1 - 2023/12/21
N2 - The integration of artificial intelligence (AI) into healthcare is progressively becoming pivotal, especially with its potential to enhance patient care and operational workflows. This paper navigates through the complexities and potentials of AI in healthcare, emphasising the necessity of explainability, trustworthiness, usability, transparency and fairness in developing and implementing AI models. It underscores the ‘black box’ challenge, highlighting the gap between algorithmic outputs and human interpretability, and articulates the pivotal role of explainable AI in enhancing the transparency and accountability of AI applications in healthcare. The discourse extends to ethical considerations, exploring the potential biases and ethical dilemmas that may arise in AI application, with a keen focus on ensuring equitable and ethical AI use across diverse global regions. Furthermore, the paper explores the concept of responsible AI in healthcare, advocating for a balanced approach that leverages AI’s capabilities for enhanced healthcare delivery and ensures ethical, transparent and accountable use of technology, particularly in clinical decision-making and patient care.
AB - The integration of artificial intelligence (AI) into healthcare is progressively becoming pivotal, especially with its potential to enhance patient care and operational workflows. This paper navigates through the complexities and potentials of AI in healthcare, emphasising the necessity of explainability, trustworthiness, usability, transparency and fairness in developing and implementing AI models. It underscores the ‘black box’ challenge, highlighting the gap between algorithmic outputs and human interpretability, and articulates the pivotal role of explainable AI in enhancing the transparency and accountability of AI applications in healthcare. The discourse extends to ethical considerations, exploring the potential biases and ethical dilemmas that may arise in AI application, with a keen focus on ensuring equitable and ethical AI use across diverse global regions. Furthermore, the paper explores the concept of responsible AI in healthcare, advocating for a balanced approach that leverages AI’s capabilities for enhanced healthcare delivery and ensures ethical, transparent and accountable use of technology, particularly in clinical decision-making and patient care.
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U2 - 10.1136/bmjhci-2023-100920
DO - 10.1136/bmjhci-2023-100920
M3 - Article
C2 - 38135293
AN - SCOPUS:85181176279
SN - 2058-4555
VL - 30
JO - BMJ Health and Care Informatics
JF - BMJ Health and Care Informatics
IS - 1
M1 - e100920
ER -