"It's the only thing I can trust": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance

ArXiv Pub Date : 2024-03-05 DOI:10.1145/3613904.3642894
JiWoong Jang, Sanika Moharana, Patrick Carrington, Andrew Begel
{"title":"\"It's the only thing I can trust\": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance","authors":"JiWoong Jang, Sanika Moharana, Patrick Carrington, Andrew Begel","doi":"10.1145/3613904.3642894","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ArXiv","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3613904.3642894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
"这是我唯一可以信任的东西":自闭症工人使用大型语言模型进行交流的设想
患有自闭症的成年人在工作中经常会受到羞辱和歧视,这导致他们不顾情感风险,向同事、朋友和家人寻求社会交流支持。大语言模型(LLM)越来越多地被认为是一种替代方案。在这项研究中,我们调查了成人自闭症患者在工作中使用大语言模型的现象,并探讨了大语言模型作为社会沟通建议来源的机遇和风险。我们请 11 位自闭症参与者向(1)基于 GPT-4 的聊天机器人和(2)伪装的人类同声传译者提出与他们自身工作场所相关的社交困难问题。我们的评估结果表明,参与者非常喜欢 LLM 而不是密友互动。然而,一位专门为自闭症求职者提供支持的教练却担心 LLM 提供的建议有问题。我们强调了参与者和从业人员的态度分歧如何反映了人机交互领域在最终用户需求与规范性良好需求之间存在的分歧,并提出了以自闭症体验为中心的 LLM 设计注意事项。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Combining Transformer based Deep Reinforcement Learning with Black-Litterman Model for Portfolio Optimization TinyGC-Net: An Extremely Tiny Network for Calibrating MEMS Gyroscopes Short-Term Solar Irradiance Forecasting Under Data Transmission Constraints F2Depth: Self-supervised Indoor Monocular Depth Estimation via Optical Flow Consistency and Feature Map Synthesis Efficient Constrained k-Center Clustering with Background Knowledge
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1