Conference topic:
This conference will explore the rapidly evolving intersections between AI and language-based disciplines, bringing together perspectives from linguistics, literary and cultural studies, language education, and translation and interpreting. As AI systems increasingly shape how language is analyzed, produced, taught, and mediated, they invite both new methodological possibilities and critical reflection. The conference aims to examine how AI can model linguistic structure, meaning, variation, learning, and processing, while also questioning what such models reveal—or obscure—about human linguistic competence and cognition. Beyond linguistics, the conference addresses AI’s growing role in literary production, interpretation, pedagogy, and canon formation, highlighting issues of creativity, authorship, bias, cultural representation, and power in a global digital landscape. Particular attention is given to educational contexts, including foreign language teaching and translator and interpreter training, where AI tools are transforming classroom practices, professional competencies, and assessment methods. Across all areas, the conference foregrounds ethical responsibility, critical literacy, and informed pedagogical design, emphasizing the need to engage with AI not as a neutral technology but as a socially embedded system. By fostering dialogue across disciplines, the conference seeks to deepen our understanding of how AI reshapes language-related research, education, and cultural production, and to chart responsible, inclusive paths forward.
Linguistic structure and representation with AI (using AI to model syntax, morphology, phonology, and the lexicon, including hierarchical structure, constraints, and cross-linguistic generalizations; AI-informed analyses of grammatical competence and structural regularities)
Meaning, pragmatics, and discourse in AI systems (the use of AI models to handle semantic composition, reference, anaphora, modality, presupposition, implicature, and context-dependent interpretation; AI approaches to discourse-level phenomena such as coherence, topic–focus structure, salience, and discourse relations)
Language variation and multilingualism (applying AI to study dialectal, register, sociolinguistic, and typological diversity; AI models for multilingual and low-resource languages)
Language learning and processing with AI (using AI to simulate acquisition, sentence processing, incremental interpretation, prediction, and learning from limited or noisy input; relevance of AI- based models for psycholinguistic and usage-based theories of language)
AI-assisted creative writing: collaborative authorship and the future of literary production (creative possibilities and limitations of AI as a writing partner, including questions of originality, authorship, and the preservation of unique literary voices)
Teaching literature with AI: pedagogical innovations and critical literacy in the digital age (the transformative impact of AI on literature education: frameworks that integrate guided AI use through active learning, combining generative AI with authoritative scholarly editions and critical thinking exercises, using AI ethically to enhance rather than replace close reading and interpretation)
AI, bias, and representation in literature: postcolonial and cultural perspectives on digital colonization (how AI technologies from developed nations extend cultural and epistemic influence over less-developed regions, replicating historical colonial power dynamics)
AI and canon formation: how algorithms shape literary value and cultural memory (how large language models and AI systems both reflect and potentially reshape the literary canon: algorithmic biases may perpetuate existing inequalities, or AI could disrupt Western-dominated canons by enabling global literature access through translation and analysis)
Multimodal narratives and transmedia storytelling: AI’s role in literary adaptation (how AI enables new forms of transmedia storytelling—narratives distributed across multiple platforms (books, films, apps, social media) that create immersive, participatory experiences)
AI literacy for foreign language teachers at all levels (the limitations, biases, and pedagogical implications of using AI tools in FLT )
Integrating AI tools into FLT practice (practical strategies for using AI for feedback, assessment, lesson planning, materials design, curriculum design and personalized learning)
Exploring plagiarism, authorship, data privacy, bias, and transparency in the development of students’ academic skills
Helping learners develop critical thinking, metalinguistic awareness, and ethical decision-making when working with AI for writing, speaking, and translation
Pedagogical integration of AI in translator and interpreter education
Pedagogical roles of AI in the translation classroom (support tool, co-translator, tutor, evaluator)
Teaching practices involving AI and their impact on classroom roles (students, teachers, tools)
The role of AI in the development of translation sub-competences (technological, instrumental, strategic, linguistic) within the EMT framework
AI in interpreter training, including the use of speech technologies, automatic transcription, and AI-supported interpreting practice
The influence of AI on students’ problem-solving and decision-making processes
Assessment and evaluation of AI-assisted translation tasks
Abstracts for 20-minute paper presentations should be submitted via email to elaltconference@gmail.com.
Abstracts must not exceed 500 words + references.
Abstracts must be written in English.
Deadline for the submission of abstracts: 30 June 2026
Deadline for the notification of acceptance: 31 July 2026
Conference fee: in-person presentations 30 EUR, online presentations 15 EUR