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Artificial Intelligence (AI) is being applied to more and more areas of everyday life, including medical diagnostics (McDougall, 2019). In the past two decades, many types of IT-based systems have been broadly utilized in health care in different domains (Rajabion, Shaltooki, Taghikhah, Ghasemi, & Badfar, 2019). Various scenarios have been made possible by rapid advances in information and communications technologies and by the increasing number of smart things (portable devices and sensors) (Kashyap, 2020). The promise of artificial intelligence (AI) in health care offers substantial opportunities to improve patient and clinical team outcomes, reduce costs, and influence the health of the general population. From the patient's point of view, it enables constant monitoring of the body's condition, and analysis of the results through comparison with a vast database containing information no doctor or human analyst would have time to process (Grzywalski, et al., 2019). From the doctor's point of view, it allows them to diagnose patients without having to have contact with them. And the doctor, thanks to AI support, can focus on patients who need direct personal contact (Davenport & Kalakota, 2019). This raises high expectations for various applications and devices that monitor health using AI, e.g., Patient Monitoring Devices based on Internet of Things (Shah & Chircu, 2018).
In this article, we identify the reactions of patients to such solutions. We are interested in the reaction to the diagnosis issued by AI and the reaction to a message about the result of the diagnosis delivered by artificial intelligence. These are important issues, because it is the users’ attitude towards these solutions that will mostly decide about their distribution on the market (Nasirian, Ahmadian, & Lee, 2017). Research on AI is about any device that perceives its environment and takes actions that maximize its chance to successfully achieve its goals (Russell & Norvig, 2009). In this paper, we focus on AI as a tangible technology that is designed to sense, comprehend, act, and learn to be capable of performing tasks that, if performed by a human, would be said to require intelligence (Scherer, 2016). We deal with medical diagnostic services in which two manifestations of AI are present: (1) an algorithm that collects data from the patient and analyzes and interprets the test result and a (2) Virtual Assistant that communicates the result to the patient and manages his or her communication with the doctor.
The subject of our research is user cognitive reactions to the performance of the test by the AI algorithm, and to the Virtual Assistant’s communication of this result. This approach is similar to one presented by Wijesinghe, Gamage, Perera, and Chitraranjan (2019) for smart telemedicine system to manage diabetic retinopathy. Empirically, this paper is focused on the Polish health system because it has high hopes for the implementation of telemedicine in order to improve its condition (Domagała & Klich, 2018).