Applying DOI Theory to Assess the Required Level of Explainability in Artificial Intelligence-empowered Medical Applications
Dimitrios P. Panagoulias, Maria K. Virvou, George A. Tsihrintzis · 2023
As artificial intelligence-empowered applications flourish and machine learning methodologies are commonly used to process large chunks of data and make decisions, the need for explainable artificial intelligence is becoming ever more pressing. In this work, we present results from a survey we conducted on the level of adoption of artificial intelligence-empowered applications by physicians. Next, we employ the diffusion of Innovation theory to determine what kind of adopters the doctors are and thus outline an implementation strategy and the level and depth of required explainability.