Design criteria for AI-based IT systems

This editorial relates to a panel discussion during the CARS 2023 congress that addressed the question on how AI-based IT systems should be designed that record and (transparently) display a reproducible path on clinical decision making. Even though the software engineering approach suggested for this endeavor is of a generic nature, it is assumed that the listed design criteria are applicable to IT system development also for the domain of radiology and surgery.

An example of a possible design approach is outlined by illustrating on how to move from data, information, knowledge and models to wisdom-based decision making in the context of a conceptual GPT system design. In all these design steps, the essential requirements for system quality, information quality, and service quality may be realized by following the design cycle as suggested by A.R. Hevner, appropriately applied to AI-based IT systems design.

It can be observed that certain state-of-the-art AI algorithms and systems, such as large language models or generative pre-trained transformers (GPTs), are becoming increasingly complex and, therefore, need to be rigorously examined to render them transparent and comprehensible in their usage for all stakeholders involved in health care. Further critical questions that need to be addressed are outlined and complemented with some suggestions, that a possible design framework for a stakeholder specific AI system could be a (modest) GPT based on a small language model.

A fundamental question for the future remains whether society wants a quasi-wisdom-oriented healthcare system, based on data-driven intelligence with AI, or a human curated wisdom based on model-driven intelligence (with and without AI). Special CARS workshops and think tanks are planned to address this challenging question and possible new direction for assisting selected medical disciplines, e.g., radiology and surgery.