Autoethnographic Insights from Neurodivergent GAI “Power Users”

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Glazko, K., Cha, J., Lewis, A., Kosa, B., Wimer, B. L., Zheng, A., Zheng, Y., & Mankoff, J. (2025). Autoethnographic Insights from Neurodivergent GAI “Power Users”. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 274, 1-19. https://doi.org/10.1145/3706598.3713670

Publication date: 23 Apr 2025 Added to AutiHub: 26 Oct 2026 Type: Other Article language: English
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Authors

Publication authors
8
Autistic authors reported by the publication
Number not specified
  1. Kate Glazko
  2. JunHyeok Cha
  3. Aaleyah Lewis
  4. Ben Kosa
  1. Brianna L Wimer
  2. Andrew Zheng
  3. Yiwei Zheng
  4. Jennifer Mankoff

Abstract

Generative AI (AI) has become ubiquitous in both daily and professional life, with emerging research demonstrating its potential as a tool for accessibility. Neurodivergent people, often left out by existing accessibility technologies, develop their own ways of navigating normative expectations. GAI offers new opportunities for access, but it is important to understand how neurodivergent "power users"-successful early adopters-engage with it and the challenges they face. Further, we must understand how marginalization and intersectional identities influence their interactions with GAI. Our autoethnography, enhanced by privacy-preserving GAI-based diaries and interviews, reveals the intricacies of using GAI to navigate normative environments and expectations. Our findings demonstrate how GAI can both support and complicate tasks like code-switching, emotional regulation, and accessing information. We show that GAI can help neurodivergent users to reclaim their agency in systems that diminish their autonomy and self-determination. However, challenges such as balancing authentic self-expression with societal conformity, alongside other risks, create barriers to realizing GAI's full potential for accessibility.

Bibliography cited by this reference

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Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 28 Oct 2026 01:01.

Cited references
162
With a DOI
130
Without a DOI, from raw bibliography text
32
17 / 162 (10.5%) cited references include at least one author identified as autistic.
References with data to complete
27 / 162 (16.7%)
References with detected author names
136 / 162 (84.0%)
Without detected author names
26
Without a structured title
26
Without a stable identifier
32
References with raw author names still to review
26
References with external metadata lookup issues
1
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
511
From DOI or external metadata
510
From validated raw bibliography text
1
Raw names already validated
1
Raw names still to review
26
121 / 511 (23.7%) names are linked to an author already present in AutiHub. 390 / 511 (76.3%) names are not yet linked.
Names linked to a person identified as autistic
20 / 511 (3.9%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 20 / 121 (16.5%). Distinct people identified as autistic: 14 / 456 (3.1%).
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