Vaishali Panda

GENERATIVE AI AND DIGITAL MEDIA IN EDUCATION, LANGUAGE, AND CULTURE:

Rethinking pedagogy, translation, creativity, and ethical responsibility in contemporary society

Vaishali Panda¹

This chapter examines the relationship between generative artificial intelligence and digital media in education, language, and culture through an international and comparative perspective. It explores how AI-mediated technologies are reshaping pedagogy, translation, creativity, and ethical responsibility across diverse regions, including Canada, the European Union, the Balkans, the MENA region, and the Global South. Generative AI is increasingly influencing how knowledge is produced, translated, assessed, circulated, and culturally interpreted within digital platforms. In education, AI tools are transforming teaching practices, academic writing, feedback systems, assessment methods, and institutional governance. While these tools offer opportunities for personalized learning, multilingual access, and creative experimentation, they also raise concerns about academic integrity, authorship, student dependency, teacher agency, surveillance, and unequal digital inclusion. The chapter argues that AI cannot be understood as a universal technological solution because its social consequences vary across linguistic, cultural, institutional, and regulatory contexts. In multilingual societies, AI translation may support cross-cultural communication, yet it may also reproduce linguistic bias, weaken cultural nuance, and marginalize low-resource languages. Similarly, AI-generated literary and cultural content challenges conventional ideas of originality, creativity, human imagination, and cultural ownership. Drawing on media studies, education, translation studies, cultural studies, and AI ethics, the chapter proposes a critical framework for responsible AI use in contemporary society. It emphasizes culturally sensitive AI literacy, transparent governance, inclusive design, and human-centered pedagogy. The chapter concludes that socially responsible AI futures must balance innovation with accountability, linguistic justice, cultural plurality, and human meaning.