Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in the System of “Physician-Patient”: Anthropocentrism vs Technocentrism
0
Zitationen
1
Autoren
2024
Jahr
Abstract
The use of artificial intelligence (AI) is becoming one of the priority areas of digitalization in various social spheres, where the medical industry is one of the most in demand. However, the use of AI in medicine raises a number of questions that require ethical and philosophical reflection. In particular, this concerns the relationship between the doctor and the patient from the point of view of traditional bioethical principles. The novelty of this research is the ethical and philosophical assessment of the use of AI within the framework of specific models of the relationship between a doctor and a patient. The problem is the tendency to reassess bioethical principles in modern medicine in the context of the use of AI. The purpose of the study is to reveal the contradictory nature of the relationship between a doctor and a patient in the use of AI. The hypothesis of the study: in the context of the use of AI in medicine, traditional historical values in doctor-patient communication (anthropocentrism) and orientation towards digital technologies (technocentrism) come into conflict. The research materials are the analysis of domestic and foreign literature on the stated problem. The methods are based on a dialectical method and a modeling method to assess the impact of AI on the doctor-patient relationship. Concrete results – the use of AI in the relationship between a doctor and a patient significantly affects the content of the basic principles of bioethics and can lead to their significant transformation in the era of digitalization in the field of medicine. Anthropocentrism, which has historically developed in doctor-patient communication, tends to be replaced by technocentrism within the framework of the use of AI. As prospects for the study of this problem, the need to solve issues at the technological, ethical and legislative levels should be highlighted.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.287 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.140 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.534 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.450 Zit.