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This study outlines the rationale behind the new undergraduate curriculum in translation and interpreting introduced by the author's department. Those involved in the department considered recent changes in the field and the broader context of university restructuring in South Korea. The article outlines the main components of the new curriculum and describes students' responses to a survey. Overall, students expressed high levels of satisfaction with the new curriculum, emphasizing that it reflects current trends such as AI-assisted translation and the increasing popularity of K-content. 84.5% emphasized their desire to further strengthen their English skills before applying them in broader contexts. However, the new curriculum should constantly be upgraded so that K-content courses foster students' creativity and AI T&I courses help students acquire strategic competence, as well as collaborative and communication skills. At the same time, it is important to identify majors or disciplines that can generate synergy with translation and interpreting.

This paper proposes a new paradigm for translation (studies) education grounded in Aristotle’s five intellectual virtues -- nous, epistēmē, sophia, technē, and phronēsis -- to cultivate complex, creative expertise for the AI era. Critiquing the field’s traditional emphasis on epistēmē that reduces translators to linguistic technicians, it advances an integrated model that redefines nous as cultural-contextual insight, sophia as the basis for deep textual understanding and ethical judgment, and technē as practical competence in leveraging AI tools, ultimately synthesized through phronēsis to form socially responsible intellectuals.

Artificial intelligence (AI), particularly neural machine translation (NMT) and large language models (LLMs), is transforming the translation and interpreting profession. While AI offers efficiency and scalability, it also raises concerns over professional identity and job security. This study employs scenario planning to examine future prospects for translators. Two key uncertainties—AI translation reliability and the level of institutional support—were used to construct a 2×2 matrix, producing four scenarios: Golden Partnership, Collapse and Replacement, Dual Structuring, and Governance Reinforcement. Each scenario was assessed using a SWOT framework to highlight opportunities and threats. The analysis indicates that the profession’s future will depend less on technological progress itself than on how stakeholders respond through education, industry adaptation, and policy frameworks. Translators can remain vital by evolving into cultural interpreters, global communication consultants, and AI-human collaboration mediators, ensuring professional sustainability in the AI era.

This study examines how the rapid diffusion of AI interpreting will affect interpreting research and training, and proposes future directions. On the research side, there is an urgent need to build an evidence base through systematic collection of real-world AI interpreting outputs, robust quality-assessment frameworks, user experience analyses, and large-scale market surveys. In anticipation of human-in-the-loop service models, new roles must be defined for interpreters such as that of a multilingual communication manager. In interpreter training, program goals should be recalibrated around two pillars: (i) cultivating professional knowledge on AI interpreting technology, and (ii) deepening core human interpreting competences. Flexible academic governance and diversified faculty profiles, supported by collaboration with industry and tech-sector partners, will be essential. Overall, AI is poised to reconfigure and expand the interpreting service landscape, with evidence-based research and curricular redesign enabling a broader, evolving role for human interpreters.

This study examines how instructor roles in translator and interpreter education are being reframed in the era of generative AI. Grounded in the AI-TPACK framework and Mollick and Mollick’s model of AI-enabled instructional roles, the study conceptualizes AI use as a matter of instructional design rather than tool adoption. Four instructional enactments—Role Play, Goal Play, Teach the AI, and Co-Create—are analyzed to illustrate how instructors configure AI’s role and structure learner–AI interactions in translation and interpreting training contexts. The analysis shows that these enactments correspond to distinct instructor roles, including simulation designer, metacognitive facilitator, cognitive designer, and professional and ethical mediator. Across cases, generative AI functions as a mediated resource whose educational value depends on instructors’ design judgments. It contributes a conceptual foundation for understanding instructor expertise as design-oriented in AI-enhanced translator and interpreter education.

This paper aims to classify video games from the perspective of localization and to propose localization strategies for each category. Drawing on Lee et al. (2014), classification criteria for games were identified by analyzing the significance of their core components in the context of localization. The analysis found that video games can be classified according to three key dimensions: reception, expected audiences, and objects of localization work. Then, examples of games and their localized versions were compared to propose localization strategies for each classified game category. With regard to reception, games can be classified into ‘control-focused’ and ‘non-control-focused’ types based on player engagement and interaction with modifying media (e.g. using dubbed audio) and preservation respectively suggested. For expected audiences related to the age rating system, modifying content for broader appeal or maintaining original elements for current fans are proposed. According to objects of localization, games are categorized as ‘real-world based’ and ‘fictional world based’. For the former, culturally immersive localization is recommended while more creative approaches is encouraged for the latter.

This essay explores various aspects of creativity in AI-assisted translation, focusing on how generative AI systems are reshaping long-held assumptions about creative agency and expertise. The discussion is structured around six interrelated themes: (1) whether AI can be regarded as creative in comparison with human beings; (2) whether translation creativity and productivity can coexist under conditions of automation and efficiency-driven workflows; (3) the concepts of “satisficing creativity” and “creative post-editing” as both practical and theoretical responses to AI-mediated translation; (4) two case studies of poetry translation that illustrate the emergence of “co-creativity” through AI-human interaction; (5) the “multi-cycle evolutionary process” through which human translators and AI tools collaborate in accomplishing tasks that require creative solutions; and (6) pedagogical suggestions for addressing creativity and AI literacy in translation courses. These discussions clarify changing modes of creative practice in the AI era and broaden the conceptual scope of creative translation in translation studies.