Lost in Translation: Understanding Autistic–Neurotypical Communication Style Differences in Job Postings

要旨

Autistic adults often use different communication styles than neurotypical individuals (NTs). While prior research has documented how such gaps disadvantage autistic job seekers, no study has systematically examined when these differences arise in language use and why autistic adults encounter interpretive gaps. This work seeks to datafy and characterize these communication challenges. We built an annotation interface and recruited 20 autistic adults to analyze 10 job postings each that they had selected as cases where they felt '' lost in translation.'' Participants annotated text spans using six categories informed by speech and language literature: unclear, ambiguous, incomplete, inappropriate, negative, and other. Follow-up interviews showed that lexical difficulties were rarely barriers; rather, challenges stemmed from interpreting implicit social arrangements or unstated expectations. We release the anonymized annotation data as the first-of-its-kind dataset documenting autistic–NT communication style differences. We conclude with implications for designing supports that foster clearer autistic–NT communication.

著者
Huining Feng
George Mason University, Fairfax, Virginia, United States
Zinat Ara
George Mason University, Fairfax, Virginia, United States
Andrew Hundt
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Slobodan Vucetic
Temple University, Philadelphia, Pennsylvania, United States
John Joon Young. Chung
Midjourney, San Francisco, California, United States
Sungsoo Ray Hong
George Mason University, Fairfax, Virginia, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Alternative Perspectives

P1 - Room 124
7 件の発表
2026-04-14 18:00:00
2026-04-14 19:30:00