Conference Paper

Exploring Human-Centered AI in Healthcare: Diagnosis, Explainability, and Trust


AI has become an increasingly active area of research over the past few years in healthcare. Nevertheless, not all research advancements are applicable in the field as there are only a few AI solutions that are actually deployed in medical infrastructures or actively used by medical practitioners. This can be due to various reasons as the lack of a human-centered approach for the or non-incorporation of humans in the loop. In this workshop, we aim to address the questions relevant to human-centered AI solutions associated with healthcare by exploring different human-centered approaches for designing AI systems and using image-based datasets for medical diagnosis. We aim to bring together researchers and practitioners in AI, human-computer interaction, healthcare, etc., and expedite the discussions about making usable systems that will be more comprehensible and dependable. Findings from our workshop may serve as ‘terminus a quo’ to significantly improve AI solutions for medical diagnosis.


Ontika, Nazmun Nisat; Syed, Hussain Abid; Saßmannshausen, Sheree May; Harper, Richard HR; Chen, Yunan; Park, Sun Young; Grisot, Miria; Chow, Astrid; Blaumer, Nils; Pinatti de Carvalho, Aparecido Fabiano; Pipek, Volkmar (2022): Exploring Human-Centered AI in Healthcare: Diagnosis, Explainability, and Trust. Proceedings of 20th European Conference on Computer-Supported Cooperative Work. DOI: 10.48340/ecscw2022_ws06. European Society for Socially Embedded Technologies (EUSSET). PISSN: 2510-2591. Workshop. Coimbra, Portugal. 27 June - 1 Juli 2022