Accessibility Assessment in Banking Chatbots using Texts Written by Deaf People who use Portuguese as a Second Language

Context: The study examines the ability of banking chatbots to understand and respond to interactions with deaf people who use Portuguese as a second language (L2), with a focus on digital accessibility in automated banking services. Problem: The hypothesis is that banking chatbots have difficulty interpreting requests in Portuguese as L2 and expressions based on the gloss of Brazilian Sign Language (Libras), resulting in digital exclusion and barriers in service. Solution: The proposal diagnoses the ability of chatbots, aiming at their understanding in the interactions of deaf users in order to improve accessibility. SI Theory: The research uses Inclusive Design and Task-Technology Fit (TTF), assessing whether chatbots are suitable for the needs of users who use Portuguese as L2. Method: A case study was carried out, with a qualitative approach. Ten banking activities were simulated in the chatbots of Banco do Brasil, Bradesco and Itaú, using inputs in formal Portuguese and as L2, with the help of ChatGPT for translations. Summary of Results: The results indicate error rates between 10% and 70%, with most errors in inputs that used Portuguese as L2 or colloquial language, evidencing the inadequacy of the chatbots for the deaf community. Contributions and Impact to the Field of IS: The study suggests the need for improvements in the language models of the chatbots to make them more inclusive for deaf users, generating impact in academia and in the technology industry.