Learning Systems versus Future Everyday Domestic Life: A Designer’s Interpretation of Social Practice Imaginaries

Abstract

Smart home technologies with the ability to learn over time promise to adjust their actions to inhabitants’ unique preferences and circumstances. For example, by learning to anticipate their routines. However, these promises show frictions with the reality of everyday life, which is characterized by its complexity and unpredictability. These systems and their design can thus benefit from meaningful ways of eliciting reflections on potential challenges for integrating learning systems into everyday domestic contexts, both for the inhabitants of the home as for the technologies and their designers. For example, is there a risk that inhabitants’ everyday lives will reshape to accommodate the learning system’s preference for predictability and measurability? To this end, in this paper we build a designer’s interpretation on the Social Practice Imaginaries method as developed by Strengers et al. to create a set of diverse, plausible imaginaries for the year 2030. As a basis for these imaginaries, we have selected three social practices in a domestic context: waking up, doing groceries, and heating/cooling the home. For each practice, we create one imaginary in which the inhabitants’ routine is flawlessly supported by the learning system and one that features everyday crises of that routine. The resulting social practice imaginaries are then viewed through the perspective of the inhabitant, the learning system, and the designer. In doing so, we aim to enable designers and design researchers to uncover a diverse and dynamic set of implications the integration of these systems in everyday life pose.

Anticipating the Dynamic Effects of the Learning Smart Home

“…A second key focus is on the efect of "everyday crises of routine" when a technology with a preference for predictability can (co-)perform domestic practices. Everyday crises of routine are defned as situations where the learning smart home is unable to accommodate the inhabitant's actions and needs when they deviate from a "learnable" routine [24]. Instead, these situations indicate unpredictabilities that could not be met by learning the inhabitant's routine [24].…”

“…Everyday crises of routine are defned as situations where the learning smart home is unable to accommodate the inhabitant's actions and needs when they deviate from a "learnable" routine [24]. Instead, these situations indicate unpredictabilities that could not be met by learning the inhabitant's routine [24]. Examples of these "crises" include impulsive decisions, unusual events like extreme weather, pets, broken gadgets, or infrastructure issues like internet outages or blackout.…”

“…Examples of these "crises" include impulsive decisions, unusual events like extreme weather, pets, broken gadgets, or infrastructure issues like internet outages or blackout. These crises, in turn, may cause the learning SHTs to pose irritations or challenges for the household [24].…”