Evidence map›Paper›PMID 41306745›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2025

Autoethnographic Insights from Neurodivergent GAI "Power Users".

Kate Glazko, JunHyeok Cha, Aaleyah Lewis, Ben Kosa, Brianna L Wimer, Andrew Zheng, Yiwei Zheng, Jennifer Mankoff

Abstract read
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. "I Don't Trust it, but I Use it": Navigating Trust, Privacy, and Identity in Disabled People's Use of Generative AI.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kate GlazkoUniversity of Washington, Seattle, Washington, USA.
JunHyeok ChaDepartment of Statistics, University of Wisconsin - Madison, Madison, Wisconsin, USA.
Aaleyah LewisPaul G. Allen School of Computer, Science and Engineering, University of Washington, Seattle, Washington, USA.
Ben KosaDepartment of Computer Sciences, University of Wisconsin - Madison, Madison, Wisconsin, USA.
Brianna L WimerDepartment of Computer Science and Engineering, University of Notre Dame, South Bend, Indiana, USA.
Andrew ZhengIndependent Researcher, Fremont, California, USA.
Yiwei ZhengNational Coalition of Independent Scholars, Battleboro, Vermont, USA.
Jennifer MankoffAllen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA.

Funding

ACL HHS 90REGE0026
6 · The paper itself

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.

Indexed as

accessibilityauto-ethnographygenerative artificial intelligenceHuman-centered computing → Accessibility technologiesintersectionalityNatural language interfacesneurodivergent peoplestigma

Identifiers

PMID41306745
PMCPMC12645485

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.