Biography
Diana HORNOIU is professor of linguistics in the Department of modern languages and literatures and communication sciences (Faculty of Letters) of Ovidius University of Constanta. She holds an MA in British Cultural Studies from Babes-Bolyai University of Cluj-Napoca and a PhD in English Linguistics, with the distinction Magna cum Laude, from the University of Bucharest. Her research has evolved on several levels drawing on interdisciplinarity, as all comparative studies in linguistics do, which does not exclude, however, specialized research focusing on gender-related linguistic variation, cross-cultural pragmatics, internet-mediated discourse, or the construction of identity through language. She is the author of seven books on pragmatics, English morphology, sociolinguistics, corpus linguistics, and conversation analysis. Professor Hornoiu is currently the director of the Center for Cross-Cultural Research, Faculty of Letters, Ovidius University of Constanta. She was member of several national and international research projects, such as TRANSMIT Transfers of American myths, icons, and cultural brands to post-communist Romania (TRANSMIT), and Erasmus+ DILAN (Digital Language and Communication Training for EU scientists) (https://dilan4scientists.eu/). ORC ID 0000-0001-5922-0284.
Conference contributions 2
ARTIFICIAL INTELLIGENCE, ETHICS AND ACADEMIC INTEGRITY IN LINGUISTIC RESEARCH
This paper discusses the evolving relationship between Artificial Intelligence (AI), ethics, and academic integrity in contemporary linguistic research. As AI-driven technologies increasingly influence data collection, corpus analysis, translation and discourse studies, they offer extraordinary opportunities for efficiency, accuracy, and interdisciplinary innovation. At the same time, the growing reliance on AI raises important ethical concerns regarding authorship, transparency, bias, data privacy, and the responsible use of automated tools in scholarly work. This study highlights that academic integrity remains a fundamental principle in linguistic research, requiring researchers to ensure originality, proper attribution, methodological transparency, and critical engagement with AI-generated outputs. Rather than replacing human expertise, AI should be understood as a complementary instrument that supports linguistic inquiry while preserving scholarly responsibility and ethical standards. The paper argues for the development of clear ethical guidelines and responsible research practices that balance technological advancement with the core values of academic scholarship.
BLIND SPOTS. THE (CURRENT) LIMITATIONS OF ARTIFICIAL INTELLIGENCE IN ACADEMIC EDUCATION. THREE CASE STUDIES IN TEACHING LITERARY INTERPRETATION, PRAGMATICS, AND ROMANIAN AS A FOREIGN LANGUAGE
Situated at the intersection of contemporary theoretical debates on intelligent technologies and the humanistic imperative to rethink academic education, this study examines the blind spots of artificial intelligence - what AI does not see, or it sees only partially - in order to assess the conditions of its pedagogical legitimacy. We argue that new theoretical, critical, and pedagogical instruments are necessary, but that their development must be accompanied by a rigorous concern for what remains specific to human thought: hermeneutic subtlety, critical discernment, pragmatic sensitivity, and intercultural understanding. The first case study examines literary and fictional texts, showing that AI tends to neutralise ambiguity, reduce symbolic density, overlook aesthetic singularity, and transform interpretation into stereotypical paraphrases. The second case study focuses on pragmatics, where AI frequently fails to calculate implicature, grasp irony, humour, interpret silence, indirectness and culturally coded forms of interaction. The third case study addresses Romanian as a foreign language, where these limitations become particularly visible in contexts involving intercultural mediation, idiomatic expression, pragmatic politeness, aspectual nuance, register variation, and the symbolic value of culturally embedded texts. Reflecting together on these blind spots is crucial for the formation of younger generations and early-career researchers. Rather than being regarded merely as operational limitations of intelligent technologies, the blind spots of AI must be consciously identified, critically examined, and methodologically integrated into academic disciplines. Students need to distinguish algorithmic processing from human thought: how algorithms generate, classify, and predict information, and how human understanding interprets, contextualises, evaluates, questions, and assumes responsibility for meaning. In this sense, the blind spots of AI should become part of the very process through which students learn to read, interpret, assess, contextualise, and produce knowledge. Such an approach transforms AI literacy into a broader pedagogical competence: the capacity to understand its limits, to question its outputs, and to preserve the contextual, ethical, pragmatic, symbolic, aesthetic, and intercultural dimensions of human understanding.