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Supported employment programs have demonstrated the ability to enhance employment outcomes for neurodivergent individuals by offering personalized job coaching that aligns with the strengths of each individual. While various technological interventions have been designed to support these programs, technologies that hyperfocus on users' assumed challenges through deficit-based design have been criticized due to their potential to undermine the agency of neurodivergent individuals. Therefore, we use strengths-based co-design to explore the opportunities for a technology that supports neurodivergent employees using their strengths. The co-design activities uncovered our participants' current strategies to address workplace challenges, the strengths they employ, and the technology designs that our participants developed to operationalize those strengths in a supportive technology. We find that incorporating strengths-based strategies for emotional regulation, interpersonal problem solving, and learning job-related skills can provide a supportive technology experience that bolsters neurodiverse employees’ agency and independence in the workplace. In response, we suggest design implications for using neurodiverse strengths as design requirements and how to design for independence in workplace.
Successful job search results from job seekers' well-shaped social communication.
While well-known differences in communication exist between people with autism and neurotypicals, little is known about how people with autism collaborate with their social surroundings to strive in the job market.
To better understand the practices and challenges of collaborative job seeking for people with autism, we interviewed 20 participants including applicants with autism, their social surroundings, and career experts.
Through the interviews, we identified social challenges that people with autism face during their job seeking; the social support they leverage to be successful; and the technological limitations that hinder their collaboration.
We designed four probes that represent major collaborative features found from the interviews--executive planning, communication, stage-wise preparation, and neurodivergent community formation--and discussed their potential usefulness and impact through three focus groups.
We provide implications regarding how our findings can enhance collaborative job seeking experiences for people with autism through new designs.
Autistic adults often experience stigma and discrimination at work, leading them to seek social communication support from coworkers, friends, and family despite emotional risks. Large language models (LLMs) are increasingly considered an alternative. In this work, we investigate the phenomenon of LLM use by autistic adults at work and explore opportunities and risks of LLMs as a source of social communication advice. We asked 11 autistic participants to present questions about their own workplace-related social difficulties to (1) a GPT-4-based chatbot and (2) a disguised human confederate. Our evaluation shows that participants strongly preferred LLM over confederate interactions. However, a coach specializing in supporting autistic job-seekers raised concerns that the LLM was dispensing questionable advice. We highlight how this divergence in participant and practitioner attitudes reflects existing schisms in HCI on the relative privileging of end-user wants versus normative good and propose design considerations for LLMs to center autistic experiences.
Securing employment and housing are key aspects of pursuing independent living. As these activities are increasingly practiced online, web accessibility of related services becomes critical for a successful major life transition. Support for this transition is especially important for people with autism or intellectual disability, who often face issues of underemployment and social isolation. In this study, we conducted semi-structured interviews and contextual inquiries with neurotypical adults and adults with autism or intellectual disability to understand common and unique goals, strategies, and challenges of neurodiverse adults when searching for employment and housing resources online. Our findings revealed that current interfaces adequately support practical (e.g., finance) goals but lack information on social (e.g., inclusivity) goals. Furthermore, unexpected search results and inaccessible social and contextual information diminished search experiences for neurodivergent users, which suggests the need for predictability and structured guidance in searching online. We conclude with design suggestions to make neurodivergent users' online search experience an opportunity to demonstrate their independence.
We conducted an ethnographically-informed study with 28 participants (9 autistic Young Adults or "YAs'" in need of substantial daily support, 6 parents, 13 support staff) to understand how autistic YAs self-regulate and receive mediation on social media. We found that autistic YAs relied on blanket boundary rules and struggled with impulse control; therefore, they coped by asking their support network to help them deal with negative social experiences. Their support networks responded by providing informal advice, in-the-moment instruction, and formal education, but often resorted to monitoring and restrictive mediation when more proactive approaches were ineffective. Overall, we saw boundary tensions arise between Autistic YAs and their support networks as they struggled to find the right balance between providing oversight versus promoting autonomy. This work contributes to the critical disability literature by revealing the benefits and tensions of allyship in the context of helping young autistic adults navigate social media.