Abstract
This paper examines ‘the routine shop’ as part of a project that is exploring automation and autonomy in the Internet of Things. In particular we explicate the ‘work’ involved in anticipating need using an ethnomethodological analysis that makes visible the mundane, ‘seen but unnoticed’ methodologies that household members accountably employ to organise list construction and accomplish calculation on the shop floor. We discuss and reflect on the challenges members’ methodologies pose for proactive systems that seek to support domestic grocery shopping, including the challenges of sensing, learning and predicting, and gearing autonomous agents into social practice within the home.
Highlights
In 2014 Kari Kuutti and Liam Bannon laid out the case for a new paradigm in HCI research that went beyond producing and analysing snapshots of interaction focused on the individual and the human-machine dyadic relationship (Kuutti and Bannon 2014)
This paper presents the results of an ethnomethodological study of domestic grocery shopping, a commonplace activity implicating multiple parties that is essentially concerned with anticipating need, in a bid to understand key challenges confronting proactive systems in such settings
Our study reveals that the anticipation of need is situated in a distinct ecology of anticipation and articulated through an array of differentially distributed practices implicated in incidental and intentional need anticipation in the home, and calculation on the shop floor
Summary
In 2014 Kari Kuutti and Liam Bannon laid out the case for a new paradigm in HCI research that went beyond producing and analysing snapshots of interaction focused on the individual and the human-machine dyadic relationship (Kuutti and Bannon 2014) They called the proposed shift ‘the turn to practice’ and located it in ‘a decades-long process’ that has seen the social sciences come to focus on practice as ‘a fundamental unit of analysis’. They implicate a ‘seen but unnoticed’ ecology of anticipation and a distributed body of collaborative work and reasoning in their practical accomplishment They identify key challenges for the development of proactive technologies that seek to support domestic shopping practices. These include challenges for the physical sensing of products in the home, computational learning and the prediction of need,. The need for proactive systems to be designed in such a way so as to gear in with the social milieu, which drives the prospective anticipation of need
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
