Our emotions and moods play a central role in our everyday experiences. To design interfaces that more adequately engage this full range of human experience, some researchers now advocate affective computing, in which computers automatically sense, process, and respond to human emotions, but having computers measure and report on intimate data without users' explicit awareness and consent raises substantial concerns around who is in control. Furthermore, it is challenging to accurately sense complex and elusive emotions influenced by many physiological, individual, and cultural factors that are unavailable to computational sensors, and the need to simplify emotions in order to computationally model them may lead to interfaces that flatten our emotional experiences rather than engaging our emotions in their full everyday richness. Such problems are based on a fundamental affective gap, a disjunction between the subjective, situated, cultural, and social ways in which people think about and experience emotions and the objective, formalized ways in which computers model them. In this project the PIs will attempt to close the affective gap by sharing the burden of affective interpretation between people and machines. In this model, people and machines collaborate to construct affective experiences; machines track user behavior and supply feedback, which users interpret to develop affective awareness. Shifting the center of interpretation and reflection from the system towards the user keeps users in charge of emotional meaning-making, addresses emotions that computational systems alone cannot truly understand, and focuses our design efforts not on formalizations of affect but on rich, complex, idiosyncratic, and potentially enigmatic emotional experiences. Systems requiring active user interpretation pose serious challenges for design and evaluation in HCI, since we no longer have direct control of system meaning but instead design and evaluate for unexpected appropriation. Drawing from the arts, humanities, and critical design, the PIs' systems will encourage interpretation by reflecting the complex, ambiguous nature of affect, allowing people to actively make sense of the system's output in the context of their everyday lives and relationships.
Broader Impacts: The PIs will develop systematic design and evaluation strategies, a theoretical foundation, and detailed case studies that make affective presence a sustainable, reproducible contribution to HCI. The work will lead to new technology that leaves users in charge of the interpretation of their emotions yet allows construction of systems that touch on intimate issues without being intrusive, supports user reflection on the role of affect in technology, and enables designers to create a new, wide range of emotional experiences even though computers have difficulty modeling those experiences.
