LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia
Steven M. Goodman, Erin Buehler, Patrick Clary, Andy Coenen, Aaron, Donsbach, Tiffanie N. Horne, Michal Lahav, Robert Macdonald, Rain Breaw, Michaels, Ajit Narayanan, Mahima Pushkarna, Joel Riley, Alex Santana, Lei, Shi, Rachel Sweeney, Phil Weaver, Ann Yuan

TL;DR
This paper presents LaMPost, an AI-assisted email writing tool designed for adults with dyslexia, evaluating its features and user perceptions to inform future development of human-AI writing support systems.
Contribution
Introduces LaMPost, a novel LLM-powered email writing prototype tailored for dyslexic users, with an evaluation revealing user preferences and current limitations of LLMs.
Findings
Participants favored 'rewrite' and 'subject line' features.
Current LLMs do not meet accuracy needs for dyslexic writers.
Awareness of AI did not affect user perception or autonomy.
Abstract
Prior work has explored the writing challenges experienced by people with dyslexia, and the potential for new spelling, grammar, and word retrieval technologies to address these challenges. However, the capabilities for natural language generation demonstrated by the latest class of large language models (LLMs) highlight an opportunity to explore new forms of human-AI writing support tools. In this paper, we introduce LaMPost, a prototype email-writing interface that explores the potential for LLMs to power writing support tools that address the varied needs of people with dyslexia. LaMPost draws from our understanding of these needs and introduces novel AI-powered features for email-writing, including: outlining main ideas, generating a subject line, suggesting changes, rewriting a selection. We evaluated LaMPost with 19 adults with dyslexia, identifying many promising routes for…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
