Project

Artificial intelligence (AI) methods have been attracting increased public attention, at least since the introduction of generative AI such as ChatGPT. In healthcare, there are already established areas of application, such as the automated evaluation of image data or robot-assisted surgery. AI applications in healthcare have the potential, among other things, to improve the quality of care, increase efficiency, counteract the shortage of skilled workers and contribute to a greater personalisation of care. Overall, they are viewed positively by a majority of both practitioners and patients. Despite these expectations, there are various uncertainties and risks associated with the use of AI, for example with regard to data quality, data protection, possible discrimination against underrepresented groups, job satisfaction or the relationship of trust between doctors and patients. Therefore, especially in clinical settings and when interpersonal interactions are involved, it is important to carefully select areas of application and tools, define clear rules for the use of AI and quality assurance, and to design processes in such a way that human and technical capabilities are optimally combined.