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Martin Zürn, Malin Eiband, Daniel Buschek
What if? Interaction with Recommendations
In Workshop on Explainable Smart Systems at IUI '20, Cagliari, Italy, March 17 - 20, 2020. ACM, New York, NY, USA. (bib)

Showing users recommended content has become a prominent way of integrating algorithmic decision-making in everyday intelligent applications (eg recommendations of films, music, news, routes). In this context, the research community has identified What if? questions as an approach for users to investigate and question such recommendationsâyet many current applications seem limited in practically supporting this. We present a set of example GUIs and interaction techniques currently used in everyday recommendation systems in practice (eg Grammarly, Apple Music, Google Maps). Based on these example cases, we discuss possible UI extensions to explicitly support What if? interactions. From our analysis and reflection emerges the general approach of treating decision variables as a âfirst-class citizenâ in UIs: We propose to 1) represent a recommended itemâs decision variables in the user interface (and not just the item itself), and 2) to enable direct manipulation of these decision variables for What if? explorations.