ARAM: a threshold model for understanding occupant acceptance of architectural robot adaptations

Physical interior elements are increasingly becoming roboticised to support occupant needs. Partitions, ceilings, and furniture can now physically and autonomously change shape or move to architecturally “adapt” indoor spaces, with the aim of improving occupant comfort, satisfaction, and wellbeing. However, occupants sometimes reject these adaptations when they are perceived as disruptive, unpredictable, or difficult to control. Motivated by the goal of making architectural robots more acceptable, we involved an interdisciplinary team of experts in human-building interaction, human-robot interaction, psychology, anthropology, and human comfort to qualitatively re-analyze how occupants accepted adaptations across three previous studies on robotic partitions. We found that an occupant tended to accept an adaptation when they recognized a personal need that the architectural robot was capable of addressing in a socially justifiable way. Accordingly, we developed the Architectural Robot Acceptance Model (ARAM), in which three qualitative thresholds along a continuum of perceived stress severity define four distinct acceptance responses to a specific adaptation. As the positions of these thresholds may vary across occupants and situations, ARAM supports testable estimates of how an occupant may respond to different appraisal states of personal need, adaptation capability, and social justification. Because architectural robot adaptations may simultaneously be experienced as robotic behaviors, building automation, and socially situated environmental adjustments, ARAM is particularly relevant to individual adaptations that enter occupants' spatial experience and may affect co-located others. We then discuss how the model can inform situated estimates of occupant acceptance of architectural robot adaptations, and outline how its broader relevance to other robotic, automated, intelligent, and smart technologies embedded in the built environment may be evaluated in future work.