Insights from social sciences have transformed explainable artificial intelligence from a largely technical into a more human-centred discipline, thus enabling diverse stakeholders, rather than technical experts alone, to benefit from its developments. The focus of explainability research itself, nonetheless, remained largely unchanged, that is to help people understand the operation and output of predictive models. This, however, may not necessarily be the most consequential function of such systems; they can be adapted to complement, augment and enhance the abilities of humans instead of (fully) automating their various roles in an explainable way. In this talk I will explore how we can reimagine XAI by drawing upon a broad range of relevant interdisciplinary findings. The resulting, more comprehensive conceptualisation of the entire research field promises to be better aligned with humans by supporting their reasoning and decision-making in a data-driven way. As the talk will show, medical applications, as well as other high stakes domains, stand to greatly benefit from such a shift in perspective.

Delivered by ADM+S Affiliate Kacper Sokol and ADM+S Associate Investigator Danula Hettiachchi

ADM+S Members Only – Registration and Zoom link via ADM+S Calendar invite