  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.
