Category Archives: Italy

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Artificial Intelligence at the service of inclusive language policies: the case of the E- MIMIC Project

Rachele Raus & Tania Cerquitelli

University of Bologna & Politecnico of Torino, Italy

Panel: Language as a means of inclusion in educational and institutional settings

Chair: Maria Margherita Mattioda, Università di Torino, Italy

It is well known how artificial intelligence (AI) learning from big data can contribute to the reiteration of gender bias and forms of exclusion due to the dissemination of stereotyped discourses on minorities, such as migrants and disabled people (Bartoletti 2021, Marzi 2021, Savoldi et alii 2021). The Empowering Multilingual Inclusive comMunICation (E-MIMIC) project led by the Polytechnic of Turin and the University of Bologna, in partnership with the Jean Monnet Centre of excellence Artificial Intelligence for European Integration, aims to promote inclusive communication in real- world scenarios by eliminating non-inclusive language forms in administrative texts written in European countries, starting with those written in Italian and French. The application uses AI algorithms to identify non-inclusive text segments and propose inclusive reformulations. The project starts from the assumption that supervising machine learning through linguistic and discourse criteria can contribute to achieving better quality results. The methodology proposed to identify these criteria rests on the principles of discourse analysis “à la Français” (Dufour, Rosier 2012: 5). In this sense, an attempt is made not to reiterate the non-inclusive ideology present in current discourses (in France and Italy). The application highlights inappropriate segments or words, thus contributing to spreading awareness of discrimination and non-inclusion in language. Moreover, the application suggests possible reformulations, so that the user can choose from the proposed solutions. The AI exploited by the application thus becomes an element in support of linguistic policies that aim at the development of metalinguistic awareness capable of counteracting the circulation of erroneous discursive and linguistic frames, also in the perspective of an eco-critical analysis of discourse (Stibbe 2014). The first tests carried out on the application are encouraging and allow us to extend its implementation to other European languages in addition to Italian and French, taking into account the diatopic variants of the languages analysed.

References

Bartoletti, I. (2021). An Artificial Revolution. On Power, Politics and AI. Edimbourg: Indigo.

Dufour, F., Rosier, L. (2012), Héritages et reconfigurations conceptuelles de l’analyse du discours ‘à la française’ : perte ou profit ?. Langage et Société, 140, 5-13.

Marzi, E. (2021). La traduction automatique neuronale et les biais de genre : le cas des noms de métiers entre l’italien et le français. Synergies Italie, 17, 19-36. http://gerflint.fr/Base/Italie17/marzi.pdf.

Savoldi, B., Gaido, M., Bentivoglio, L., Negri, M., Turchi, M. (2021). Gender Bias in Machine Translation, Transactionsof the Association for Computational Linguistics, 9, 845-874.

Stibbe, A. (2014). An ecolinguistic approach to critical discourse studies. Critical discourse studies, January 2014, DOI: 10.1080/17405904.2013.845789.

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Promoting multilingualism and inclusiveness in educational settings in the age of AI

Alessandra Molino, Ilaria Cennamo, Lucia Cinato, Marita Mattioda

Università di Torino, Italy

Panel: Language as a means of inclusion in educational and institutional settings

Chair: Maria Margherita Mattioda, Università di Torino, Italy

Artificial intelligence (AI) systems for natural language processing, which increasingly permeate people’s 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 “Linguistic rights and language varieties in Europe in the age of artificial intelligence”, discussing the role of education in helping new generations recognize and challenge practices that may affect linguistic, social, and gender inclusiveness.

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 (Jiménez-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

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.

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).

References

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.

Humbley, J., Raus, R., Silletti, A., Zollo, D. (eds) (forthcoming), Multilinguisme et variétés linguistiques en Europe à l’aune de l’intelligence artificielle. De Europa, Special Issue 2022. http://www.deeuropa.unito.it.

Jiménez-Crespo, M. (2017). The role of translation technologies in Spanish language learning. Journal of Spanish Language Teaching, 4, 181-193.

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.

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Fostering citizen engagement through integrative language planning

James Archibald

Università di Torino, Italy

Panel: Language as a means of inclusion in educational and institutional settings

Chair: Maria Margherita Mattioda, Università di Torino, Italy

In any state, monolingual or multilingual, a common overriding objective is to create, build and maintain a cohesive national entity which will serve the social, cultural and economic needs of the citizenry, present or future. In order to create this type of national linguasphere and to maintain relations with other or related linguaspheres, the state must establish coherent policies which will guide its practices with respect to socioeconomic inclusion, cultural identity and language.

Integrative language planning cannot be disassociated with strategic development. This is what we have called elsewhere a stakeholder approach to language planning.

This model of devising or implementing language policies requires that states articulate clear statements of intent so that all concerned have an understanding of what is planned and how the plans will be executed. Hence, planning and practice go hand in hand.

Moreover, given the human involvement in the process, legislators and administrators must be mindful of the “affects” (Damasio 2018, Ch. 7) that will result from statements of intent, policy formulations, legislative texts and regulations used in the implementation of language legislation. In addition, public administrators must be in a position to objectively measure any possible social, cultural and economic effect of such policies, legislation and regulations. At the same time, this measurement should take place in an atmosphere which reflects the fundamental human rights of the present and future citizenry.

Rooted as they are in shared ideologies, these policies and practices help the state to define its educational philosophy and priorities as well as its institutional policies. That is why state-mandated institutions must define their own institutional policies. These should be in alignment with national policies and practices.

Such a system, if well planned and maintained, should have as a main objective to foster citizen engagement and support for policy orientations.

References

Archibald, J. & Chiss, J.L., éds. (2007). La langue et l’intégration des immigrants. Sociolinguistique, politiques linguistiques, didactique. Paris : L’Harmattan.

Archibald, J. & Galligani, S. (2009). La langue, l’immigration et la cohésion sociale. In Archibald, J. & Galligani, S., dirs. (2009) Langue(s) et immigration(s) : société, école, travail, 9-15. Paris : L’Harmattan.

Archibald, J. (2019). Principes de mise en œuvre de politiques linguistiques intégrées. In Grin, F., dir. Les « linguasphères » dans la gouvernance mondiale de la diversité, 26-28. Neuchâtel : Délégation suisse à la langue française, 2019.

Busekist, A. von. (2018). The ethics of language policies. New York : Routledge.

Damasio, A. (2018). The Strange Order of Things: Life, Feeling, and the Making of Cultures. New York : Pantheon.

Freeman, R.E. (2010). Strategic management: a stakeholder approach. Cambridge : Cambridge University Press.

Freeman, R.E. & Mcvea, J.F. (2001). A stakeholder approach to strategic management. Social Science Research Network Electronic Journal, January. (DOI: 10.2139/ssrn.263511).