Disability Expertise and Large Language Models: A Qualitative Study of Autistic TikTok Creators’ Use of ChatGPT

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McNally, K., Wright, K., Goldkind, L., Kattari, S. K., & Victor, B. G. (2024). Disability Expertise and Large Language Models: A Qualitative Study of Autistic TikTok Creators’ Use of ChatGPT. Social Media + Society, 10(3). https://doi.org/10.1177/20563051241279549

Publication date: 1 Jul 2024 Added to AutiHub: 14 Sep 2026 Type: Article Article language: English
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Authors

Publication authors
5
Publication authors identified as autistic
1 / 5 (20.0%)
  1. Kellan McNally
  2. Kathryn Wright
  3. Lauri Goldkind
  4. Shanna K Kattari *
  5. Bryan G. Victor

Abstract

The purpose of this study was to describe how autistic TikTok creators are using ChatGPT across various domains of their lives, their motivations for doing so, and resulting impacts. Using a framework of “disability expertise,” we document the knowledge that creators acquired through use of ChatGPT and then shared with peers via social media. We used deductive qualitative methods to analyze 25 TikTok videos from 25 unique creators. Themes were identified in connection with motivations for the use of ChatGPT, settings in which it was used, applications of this technology, and resulting impacts for creators. Findings indicate that autistic creators were motivated to use ChatGPT to navigate neurotypical environments, manage features of their neurodivergence, and unmask, with the technology often serving as a digital coach, communication assistant, and conversational partner. Use of ChatGPT resulted in harm reduction, time and energy savings, positive emotional experiences, and meaningful accomplishments in both personal and professional settings. These findings indicate that ChatGPT serves as an important resource for many autistic individuals, facilitating accommodations to often inaccessible environments and helping users manage stressors and pursue goals. The study also highlights the significance of social media platforms for disseminating disability expertise related to the use of large language models to improve quality of life.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

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: 19 Sep 2026 01:01.

Cited references
56
With a DOI
39
Without a DOI, from raw bibliography text
14
4 / 56 (7.1%) cited references include at least one author identified as autistic.
References with data to complete
9 / 56 (16.1%)
References with detected author names
50 / 56 (89.3%)
Without detected author names
6
Without a structured title
9
Without a stable identifier
14
References with raw author names still to review
6
References with external metadata lookup issues
0
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
127
From DOI or external metadata
127
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
12
31 / 127 (24.4%) names are linked to an author already present in AutiHub. 96 / 127 (75.6%) names are not yet linked.
Names linked to a person identified as autistic
4 / 127 (3.1%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 4 / 31 (12.9%). Distinct people identified as autistic: 3 / 119 (2.5%).
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