One of the grand challenges of artificial intelligence and affective computing is for technology to become emotionally-aware and thus, more human-like. Modeling human emotions is particularly complicated when we consider the lived experiences of people who are on the autism spectrum. To understand the emotional experiences of autistic adults and their attitudes towards common representations of emotions, we deployed a context study as the first phase of a Grounded Design research project. Based on community observations and interviews, this work contributes empirical evidence of how the emotional experiences of autistic adults are entangled with social interactions as well as the processing of sensory inputs. We learned that (1) the emotional experiences of autistic adults are embodied and co-constructed within the context of physical environments, social relationships, and technology use, and (2) conventional approaches to visually representing emotion in affective education and computing systems fail to accurately represent the experiences and perceptions of autistic adults. We contribute a social-emotional-sensory design map to guide designers in creating more diverse and nuanced affective computing interfaces that are enriched by accounting for neurodivergent users.
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An Emotion Translator: Speculative Design By Neurodiverse Dyads
For autistic individuals, navigating social and emotional interactions can be complex, often involving disproportionately high cognitive labor in contrast to neurotypical conversation partners. Through a novel approach to speculative co-design, autistic adults explored affective imaginaries — imagined futuristic technology interventions — to probe a provocative question: What if technology could translate emotions like it can translate spoken language? The resulting speculative prototype for an image-enabled emotion translator chat application included: (1) a visual system for representing personalized emotion taxonomies, and (2) a Wizard of Oz implementation of these taxonomies in a low-fidelity chat application. Although wary of technology that purports to understand emotions, autistic participants saw value in being able to deploy visual emotion taxonomies during chats with neurotypical conversation partners. This work shows that affective technology should enable users to: (1) curate encodings of emotions used in system artifacts, (2) enhance interactive emotional understanding, and (3) have agency over how and when to use emotion features.
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- Award ID(s):
- 1845023
- PAR ID:
- 10517592
- Publisher / Repository:
- ACM Digital Library
- Date Published:
- ISBN:
- 9798400703300
- Page Range / eLocation ID:
- 1 to 18
- Format(s):
- Medium: X
- Location:
- Honolulu HI USA
- Sponsoring Org:
- National Science Foundation
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