The Ethical Considerations of Artificial Intelligence in Clinical Decision Support

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.

Ethical Considerations in the Age of Artificial Intelligence: Balancing Innovation and Social Values

“…However, its integration into various aspects of society raises profound ethical considerations. Some of the complex challenges associated with AI include issues of fairness, accountability, transparency, privacy, bias, and the broader societal impact of AI-driven decisions [1]- [4]. Policymakers, advocates, scholars, and others working to maximize the benefits and minimize the harms of AI need to build on existing efforts and push the global conversation on the future of AI toward consensus [5].…”