AI and Medicine: Separating Fact from Fiction in the Quest for Effective and High Quality Healthcare - Graßmann, Stephan; Pfeiffer, Sabine (Artificial Intelligence in Society., 2024)
The German healthcare system is currently facing a number of challenges. These include demographic change and the associated increasing burden on the healthcare system. Digitalization and the use of artificial intelligence (AI) are often touted as a solution to many of these challenges and resultant problems. In this paper, we argue that the systemic capacity problems of the German healthcare system cannot be solved by digitalizing the work and actions of employees alone. As we show, digitalization processes and the use of AI are linked to a variety of different conditions. In practice, the concrete implementation of digitalization is a complex social negotiation process involving different determinants, their underlying principles and the resulting logics of action. Ultimately, working practices themselves are a product of the multidimensional entanglements and dependencies between structural, organizational, technical and subjective determinants. In addition, both digitalization and AI applications are inscribed with certain functional logics (e.g. formalization processes), which have a fundamental impact on work organization and working environments through the implementation of technology. The interplay of these factors in the negotiated order can be effectively observed through the work actions and work organization of employees. Through our qualitative research data, we aim to provide an overview of the extent to which the benefits and implementation of digitalization and the use of AI depend on these factors. It also reveals how central the role and expertise of employees are for the successful implementation of digitalization in the workplace. Our quantitative data shows both how little employees are involved in digitalization processes or the development of AI and how open they simultaneously are to these technologie