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"We do use it, but not how hearing people think": How the Deaf and Hard of Hearing Community Uses Large Language Model Tools

Shuxu Huffman, Si Chen, Kelly Avery Mack, Haotian Su, Qi Wang, Raja Kushalnagar

TL;DR

This paper investigates how the Deaf and Hard of Hearing community uses Text AI tools to reduce communication barriers and improve information access. It employs a mixed-method design with an online survey of 80 DHH participants and 11 ASL/English interviews to characterize usage patterns, benefits, and barriers. Key findings show that Text AI can ease cross-cultural communication and bolster written English confidence, but lacks robust ASL support and Deaf-cultural awareness, highlighting data and design gaps. The work provides inclusive design recommendations for Text AI tools and outlines directions for future research to advance accessibility for underserved DHH populations.

Abstract

Generative AI tools, particularly those utilizing large language models (LLMs), are increasingly used in everyday contexts. While these tools enhance productivity and accessibility, little is known about how Deaf and Hard of Hearing (DHH) individuals engage with them or the challenges they face when using them. This paper presents a mixed-method study exploring how the DHH community uses Text AI tools like ChatGPT to reduce communication barriers and enhance information access. We surveyed 80 DHH participants and conducted interviews with 11 participants. Our findings reveal important benefits, such as eased communication and bridging Deaf and hearing cultures, alongside challenges like lack of American Sign Language (ASL) support and Deaf cultural understanding. We highlight unique usage patterns, propose inclusive design recommendations, and outline future research directions to improve Text AI accessibility for the DHH community.

"We do use it, but not how hearing people think": How the Deaf and Hard of Hearing Community Uses Large Language Model Tools

TL;DR

This paper investigates how the Deaf and Hard of Hearing community uses Text AI tools to reduce communication barriers and improve information access. It employs a mixed-method design with an online survey of 80 DHH participants and 11 ASL/English interviews to characterize usage patterns, benefits, and barriers. Key findings show that Text AI can ease cross-cultural communication and bolster written English confidence, but lacks robust ASL support and Deaf-cultural awareness, highlighting data and design gaps. The work provides inclusive design recommendations for Text AI tools and outlines directions for future research to advance accessibility for underserved DHH populations.

Abstract

Generative AI tools, particularly those utilizing large language models (LLMs), are increasingly used in everyday contexts. While these tools enhance productivity and accessibility, little is known about how Deaf and Hard of Hearing (DHH) individuals engage with them or the challenges they face when using them. This paper presents a mixed-method study exploring how the DHH community uses Text AI tools like ChatGPT to reduce communication barriers and enhance information access. We surveyed 80 DHH participants and conducted interviews with 11 participants. Our findings reveal important benefits, such as eased communication and bridging Deaf and hearing cultures, alongside challenges like lack of American Sign Language (ASL) support and Deaf cultural understanding. We highlight unique usage patterns, propose inclusive design recommendations, and outline future research directions to improve Text AI accessibility for the DHH community.

Paper Structure

This paper contains 24 sections, 1 figure, 1 table.

Figures (1)

  • Figure 1: The diagrams show data from Text AI users with ASL or English as their primary language (N = 62), comparing comfort levels and anxiety frequencies in written communication with and without Text AI. Data from 12 non-users, 3 participants with other primary languages, and 3 participants who identified both ASL and English as their primary languages are excluded. Diagram (a) shows changes in comfort levels using written English for ASL users (N = 44) and English users (N = 18). Diagram (b) presents changes in anxiety frequency when communicating with hearing individuals in writing. Text AI increased comfort levels for ASL users but slightly decreased them for English users in (a), while reducing anxiety frequencies for both groups in (b).