Promoting Linguistic Diversity and Inclusion

Abstract

Using a lingua franca for scholarly communication offers some advantages, but it also limits research diversity, and there is a growing movement to encourage publication in other languages. Both approaches require scholars to access material through other languages, and more people are turning to machine translation to help with this task. Machine translation has improved considerably in recent years with the introduction of artificial intelligence techniques such as machine learning; however, it is far from perfect and users who are not trained as professional translators need to improve their machine translation literacy to use this technology effectively. Machine translation literacy is less about acquiring techno-procedural skills and more about developing cognitive competences. In this way, machine translation literacy aligns with the overall direction of the Association of College & Research Libraries’ (2015) Framework for Information Literacy for Higher Education, which encourages a conceptual, rather than a skills-based, approach. This case study presents a pilot project in which machine translation literacy instruction was incorporated into a broader program of information literacy and delivered to first-year students—both Anglophone and non-Anglophone—at a Canadian university. Students were surveyed and, overall, they found the machine translation literacy module to be valuable and recommended that similar instruction be made available to all students. Academic librarians are well positioned to participate in the delivery of machine translation literacy instruction as part of a broader information literacy program, and in so doing, they can promote linguistic diversity and better enable students and researchers from all regions to participate in scholarly conversations.