The psychology of explanation in medical decision support systems

Abstract

Today, an important role is being played by artificial intelligence (AI) in healthcare systems. Many targeted healthcare applications such as medical diagnostics, patient monitoring, and learning healthcare systems are now available with the aid of AI software programs. Clinical decision-making is enabled by AI algorithms and software. The predictive analysis of the AI algorithms is aided by a computerized predictive analysis flowchart that enables it to separate, organize, and check for patterns from complex data and draw a conclusion with some degree of probability, which will enable the healthcare service provider to make a quality decision within a short time. The AI algorithm does not make the final decision going by the existing legal frameworks at the various jurisdictions but rather they are used as supporting tools for diagnosis or a screening tool, instead of doing the usual medical tasks being done by the doctor in a hospital setting. Many studies in the literature are available today on research with patients' electronic health records deployed by AI-assisted data analysis and learning tools. They use an electronic secure computer which does the records keeping instead of the traditional way of paper records. AI applications are being surged by the recent advancement in machine learning (ML), and the improvement of AI applications in health solely depends on the success in designing the AI algorithm, which is called ML. Only a proper and good algorithm design can guarantee the set goals for AI systems. The autonomous system that can perceive, learn, decide, and act on its own will only be possible by continued advances in AI algorithms known as ML. Autonomous machines are simply self-operating machines, which can carry out their assigned task without human intervention. However, the machine's inability to explain their decision and action taken by them to human users has posed a big limitation to their adoption and effective use. The deployment of more intelligent, autonomous, and symbiotic systems will provide a good solution to the challenges being faced in the healthcare system. Thus, this chapter presents the psychology of explanation in medical decision support systems (MDSS). The psychological perspectives on explanation in healthcare systems with a binocular focus on MDSS are highlighted.

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