Design Methods to Investigate User Experiences of Artificial Intelligence.

This paper engages with the challenges of designing ‘implicit interaction’, systems (or system features) in which actions are not actively guided or chosen by users but instead come from inference driven system activity. We discuss the difficulty of designing for such systems and outline three Research through Design approaches we have engaged with - first, creating a design workbook for implicit interaction, second, a workshop on designing with data that subverted the usual relationship with data, and lastly, an exploration of how a computer science notion, “leaky abstraction”, could be in turn misinterpreted to imagine new system uses and activities. Together these design activities outline some inventive new ways of designing User Experiences of Artificial Intelligence.