Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The Ethical Considerations of Artificial Intelligence in Clinical Decision Support
3
Zitationen
1
Autoren
2022
Jahr
Abstract
With the explosion in technological innovation facilitating the advent of artificially intelligent systems, specifically clinical decision support, a unique subset of ethical and sustainability concerns arises. Although this technology possesses remarkable potential to revolutionise the healthcare industry, it becomes apparent that an innovative ethical framework must be posited to facilitate integration into the mainstream. Due to the sensitive nature of healthcare, ethical oversights pertaining to incorporation of such technologies would lead to the detriment of its public perception, potentially stigmatising related systems for years to come. By delving into the literature surrounding the idiosyncratic ethical considerations of artificially intelligent clinical decision support in this paper, best practices which seek to mitigate the impact of these concerns emerge. The objective of this work is to assimilate these best practices, which are used in the synthesis of a six principle code of ethics which are as follows: protect healthcare professional authority, ensure technological non-maleficence, cultivate clinical decision support transparency, establish procedures for accountability determination, promote sustainability of artificially intelligence based clinical decision support and encourage equity in the training and deployment of clinical decision support. These principles are then applied to the real world of Watson for Oncology by IBM, to assess the adherence of the product to ethical and sustainability best practices.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 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 · 5.423 Zit.