Universit\u00e0 di Torino, Italy<\/p>\n\n\n\n
Artificial intelligence (AI) systems for natural language processing, which increasingly permeate people\u2019s daily life, offer undeniable advantages in terms of speed and efficiency, but also raise social and ethical questions about how AI may undermine socio-cultural and linguistic equality. This paper presents the activities of the panel \u201cLinguistic rights and language varieties in Europe in the age of artificial intelligence\u201d, discussing the role of education in helping new generations recognize and challenge practices that may affect linguistic, social, and gender inclusiveness.<\/p>\n\n\n\n
We report on initiatives within the panel aiming at raising awareness among university students, in particular foreign language learners, of the socio-cultural and linguistic implications of neural machine translation (NMT). NMT software such as Google Translate, DeepL, or Reverso is in large use among current, digital native students (Jim\u00e9nez-Crespo 2017), who may not be fully aware of the risks of such digital resources for the development of their language skills and translation competence, as well as for broader social issues. Through theoretical discussions and translation-related activities, students were encouraged to reflect on the massive presence of certain languages online and the lack <\/p>\n\n\n\n
of visibility of others, a situation that may have a negative impact on inclusive access to digital technologies (Ranathunga et al. 2021), multilingualism and, ultimately, the fundamental goal of European integration. The uncritical use of NMT systems may also lead to a progressive phenomenon of language flattening at the levels of register and sociolects, thus affecting the preservation of linguistic diversity. Finally, students were also made aware that current NMT systems are still far from guaranteeing adequate treatment of gendered language (Attanasio et al. 2021). The widespread inability of generating gender-inclusive content may reinforce stereotypes and inequalities.<\/p>\n\n\n\n
Preliminary results of the impact of our pedagogic activities will be presented in this paper, making special reference to the initiatives conducted at the University of Turin (Italy).<\/p>\n\n\n\n
Attanasio, G. & al. (2021). E-MIMIC: Empowering Multilingual Inclusive Communication. 2021 IEEE International Conference on Big Data (Big Data), 2021, 4227-4234, doi: 10.1109\/BigData52589.2021.9671868.<\/p>\n\n\n\n
Humbley, J., Raus, R., Silletti, A., Zollo, D. (eds) (forthcoming), Multilinguisme et vari\u00e9t\u00e9s linguistiques en Europe \u00e0 l\u2019aune de l\u2019intelligence artificielle. De Europa, Special Issue 2022. http:\/\/www.deeuropa.unito.it.<\/p>\n\n\n\n
Jim\u00e9nez-Crespo, M. (2017). The role of translation technologies in Spanish language learning. Journal of Spanish Language Teaching, 4, 181-193.<\/p>\n\n\n\n
Ranathunga, S., Lee, E.A., Skenduli, M.P., Shekhar, R., Alam, M., & Kaur, R. (2021). Neural Machine Translation for Low-Resource Languages: A Survey. ArXiv, abs\/2106.15115.<\/p>\n","protected":false},"excerpt":{"rendered":"
Alessandra Molino, Ilaria Cennamo, Lucia Cinato, Marita Mattioda Universit\u00e0 di Torino, Italy Panel: Language as a means of inclusion in educational and institutional settings Chair: Maria Margherita Mattioda, Universit\u00e0 di Torino, Italy Artificial intelligence (AI) systems for natural language processing, … Continue reading