"It's the only thing I can trust": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance
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Abstract (arXiv)
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.
Key facts. Cited by 11 papers in the map (data through 13 Oct 2026). First posted on arXiv 5 Mar 2024.
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Citing papers per year: 2024: 3; 2025: 4; 2026: 4.
11 papers.
- 2024SocialMind: LLM-based Proactive AR Social Assistive System with Human-like Perception for In-situ Live Interactionscited by 25
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Reviewcited by 16
- 2025Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulationcited by 15
- 2024TwIPS: A Large Language Model Powered Texting Application to Simplify Conversational Nuances for Autistic Userscited by 5
- 2024Copiloting Diagnosis of Autism in Real Clinical Scenarios via LLMscited by 3
- 2025The Role of Generative AI in Facilitating Social Interactions: A Scoping Reviewcited by 1
- 2025NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-takingcited by 1
- 2026Chaplains' Reflections on the Design and Usage of AI for Conversational Carecited by 1
- 2026Exploring Implicit Perspectives on Autism in Large Language Models Through Multi-Agent Simulationscited by 0
- 2026How Frontier LLMs Adapt to Neurodivergence Context: A Measurement Framework for Surface vs. Structural Change in System-Prompted Responsescited by 0
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiencescited by 0
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiences3 May 2026
- 2026How Frontier LLMs Adapt to Neurodivergence Context: A Measurement Framework for Surface vs. Structural Change in System-Prompted Responses30 Apr 2026
- 2026Chaplains' Reflections on the Design and Usage of AI for Conversational Care3 Feb 2026
- 2026Exploring Implicit Perspectives on Autism in Large Language Models Through Multi-Agent Simulations21 Jan 2026
- 2025NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking27 Sep 2025
- 2025The Role of Generative AI in Facilitating Social Interactions: A Scoping Review12 Jun 2025
- 2025Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation4 Feb 2025
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review22 Jan 2025
- 2024SocialMind: LLM-based Proactive AR Social Assistive System with Human-like Perception for In-situ Live Interactions5 Dec 2024
- 2024Copiloting Diagnosis of Autism in Real Clinical Scenarios via LLMs8 Oct 2024
- 2024TwIPS: A Large Language Model Powered Texting Application to Simplify Conversational Nuances for Autistic Users25 Jul 2024