Abstract
The objective of this article is to discuss the inherent bias involved with artificial intelligence-based decision support systems for healthcare. In this article, the authors describe some relevant work published in this area. A proposed overview of solutions is also presented. The authors believe that the information presented in this article will enhance the readers’ understanding of this inherent bias and add to the discussion on this topic. Finally, the authors discuss an overview of the need to implement transdisciplinary solutions that can be used to mitigate this bias.
Highlights
The objective of this article is to discuss the inherent bias involved with artificial intelligence-based decision support systems for healthcare
Available literature indicates that artificial intelligence-based systems used in healthcare have flaws that adversely affect its ability to perform at an expected level [1]
It is important to analyze a few key concepts associated with information bias
Summary
Available literature indicates that artificial intelligence-based systems used in healthcare have flaws that adversely affect its ability to perform at an expected level [1]. It is important to note that an artificial intelligence-based decision support system uses knowledge derived from available literature and other available forms of experimental results. Under these circumstances, the bias in discussion can be conceived as an outcome of the methods and its associated selection processes used for experimentation. Medicina 2020, 56, 141 emphasize on how hindsight bias affects the healthcare delivery system They define hindsight bias as “the tendency for people with outcome knowledge to exaggerate the extent to which they would have predicted the event beforehand.”. Hindsight bias is an important concept that cannot be obviated in a discussion that involves artificial intelligence-based systems for healthcare
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