AI-enabled sign language interpretation in E-learning: a structural modelling of the perspectives of African sign language interpreters

Abstract

Abstract The development of artificial intelligence-enabled sign language interpretation (AI-enabled SLI) is changing the dynamics in the sign language interpreting space and there have been various arguments for and against the use of AI-enabled SLI, especially for academic use. Leveraging on the importance of artificial intelligence for persons who are Deaf or hard of hearing, this study brought to forward the perspectives of professional sign language interpreters from Sub-Saharan Africa about AI-enabled SLI. Framed by the technology acceptance model, a total of 412 sign language interpreters from 12 African countries participated in the study and responded to the e-questionnaire. The survey responses were analysed using structural equation modelling. The findings revealed that perceived benefits (PB), perceived risks (PR) and perceived trust (PT) had a significant positive relationship with future perspectives (FP) about AI-enabled SLI. It was also found that while PB had a negative but direct relationship with cultural influence (CI), PT was found to be positively significant with CI. This study could not establish any significant mediative influence of CI in the relationship between PB, PR, PT and FP about AI-enabled SLI among African SLIs. Therefore, CI has not been found to have any influence on FP about AI-enabled SLI among African SLIs. Based on the findings, appropriate recommendations were made.