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Regular screening is critical for individuals at risk of neurocognitive disorders (NCDs) to receive early intervention.
Conversational agents (CAs) have been adopted to administer dialog-based NCD screening tests for their scalability compared to human-administered tests.
However, unique communication skills are required for CAs during NCD screening, e.g., clinicians often apply scaffolding to ensure subjects’ understanding of and engagement in screening tests.
Based on scaffolding theories and analysis of clinicians' practices from human-administered test recordings, we designed a scaffolding framework for the CA.
In an exploratory wizard-of-Oz study, the CA empowered by ChatGPT administered tasks in the Grocery Shopping Dialog Task with 15 participants (10 diagnosed with NCDs).
Clinical experts verified the quality of the CA's scaffolding and we explored its effects on task understanding of the participants.
Moreover, we proposed implications for the future design of CAs that enable scaffolding for scalable NCD screening.
Autistic individuals often draw on insights from their supportive networks to develop self-help life strategies ranging from everyday chores to social activities. However, human resources may not always be immediately available. Recently emerging conversational agents (CAs) that leverage large language models (LLMs) have the potential to serve as powerful information-seeking tools, facilitating autistic individuals to tackle daily concerns independently. This study explored the opportunities and challenges of LLM-driven CAs in empowering autistic individuals through focus group interviews and workshops (N=14). We found that autistic individuals expected LLM-driven CAs to offer a non-judgmental space, encouraging them to approach day-to-day issues proactively. However, they raised issues regarding critically digesting the CA responses and disclosing their autistic characteristics. Based on these findings, we propose approaches that place autistic individuals at the center of shaping the meaning and role of LLM-driven CAs in their lives, while preserving their unique needs and characteristics.
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.
About one-third of autistic individuals are nonspeaking, i.e., they cannot use speech to convey their thoughts reliably. Many in this population communicate via spelling, a process in which they point to letters on a letterboard held upright in their field of view by a trained Communication and Regulation Partner (CRP). This paper focuses on transitioning such individuals to more independent, digital spelling that requires less support from the CRP, a goal most nonspeakers we consulted with desire. To enable this transition, we followed an approach that mimics an environment familiar to the nonspeaker and that harnesses the skills they already possess from physical letterboard training. Using this approach, we developed HoloBoard, a system that allows a nonspeaker, their CRP, and others, e.g., researchers, to share a common Augmented Reality (AR) environment containing a virtual letterboard. We configured the system to offer a brief (less than 10 minutes, on average) training module with graduated spelling tasks on the virtual letterboard. In a study involving 23 participants, 16 completed the entire module. These participants were able to spell words on the virtual letterboard without the CRP holding that board, an outcome we had not expected. When offered the opportunity to continue interacting with the virtual letterboard after the training module, 14 performed more complicated tasks than we had anticipated, spelling full sentences, or even offering feedback on the HoloBoard using solely the virtual board. Furthermore, five of these participants used the system solo, i.e., with the CRP and researchers absent from the virtual environment. These results suggest that training with the HoloBoard can lay the foundation for more independent communication, providing new social and educational opportunities for this marginalized population.
The marginalization of autistic people in our society today is multi-faceted as it includes violence that is both physical and ideological in nature. It is rooted in the dehumanization, infantilization, and masculinization of autistic people and pervasive even in contemporary research studies that continue to echo ableist ideologies from the past. In this work, we identify how HRI research reproduces systemic social inequalities and explain how they align with historical misrepresentations, and other systemic barriers. We analyzed 142 papers focusing on HRI and autism published between 2016 and 2022. We critique these studies through a mixed-methods analysis of their definition of autism, study designs, participant recruitment, and results. Our findings indicate that HRI research stigmatizes autism in three dimensions - 1) the pathologization of autism, 2) gender and age-based essentialism, and 3) power imbalances. Our work uncovered that about 90% of HRI research during the timeline explored excluded the perspectives of autistic people, particularly those from understudied groups. We recommend broadening the inclusion of autistic people, considering research objectives beyond clinical use, and diversifying collaborations, foundational works considered, & participant demographics for more inclusive future work.