Biography
Ana Jović is an independent researcher and holds a PhD in Applied Linguistics, an MA in English Language and Literature, and an MA in Teaching Serbian as a Foreign Language from the University of Belgrade Faculty of Philology, where she also completed her BA in English Language and Literature. She is a Serbian English language teacher with over twenty years of experience, specializing in online teaching and digital materials development since 2010. She has presented at international conferences, published in academic journals, and actively advocates against linguistic discrimination. She volunteers as a mentor with EVE: Equal Voices in ELT. Ana Jovic holds a Bachelor of Arts and a Master's Degree in Teaching English as a Foreign Language, a PhD in Applied Linguistics, and a Master of Arts in Teaching Serbian as a Foreign Language, all from the University of Belgrade, Serbia. Her current research focus is native speakerism, a pervasive language ideology in foreign language teaching, and its negative influence on teachers.
Conference contributions 1
AUTOMATED INSECURITY:
AI ethics, algorithmic bias, and the human cost of accent reduction technology
AI-powered language technologies are increasingly used in informal language learning, yet their ethical implications remain under-examined. Accent reduction apps, in particular, claim to empower multilingual speakers while potentially reinforcing linguistic discrimination. This paper aims to identify the ethical failures embedded in AI-powered accent reduction technology, how these failures manifest in the user experience, and the implications for AI ethics and social responsibility in education. The study is grounded in AI ethics (transparency, accountability, fairness) and critical sociolinguistics (native-speakerism, language ideology). Drawing on three months of autoethnographic engagement with BoldVoice, the analysis identifies three interconnected ethical failures: opaque accountability, the commodification of insecurity, and the individualization of structural bias, in which users are positioned as responsible for fixing a systemic problem. The paper calls for ethical accountability in AI language technologies, transparency, pluricentric design, and a commitment to social responsibility. Accent reduction apps must be interrogated not as neutral pedagogical tools but as technologies that can reinforce linguistic discrimination if left unchecked.