当前生成式人工智能正深度介入翻译实践,推动翻译活动由相对封闭的双语转换转向人､模型､ 语料､工具与情境协同参与的复杂实践,并由此重塑翻译教育的能力目标､教学过程､评价依据和伦理边界｡ 当前翻译教育面临学习者主体性弱化､教师角色转型压力增大､终稿评价效度下降､学术诚信风险加剧和译者责任边界模糊等问题,翻译教育应围绕能力目标､课程内容､教学模式､评价体系和伦理规范进行重构,建构以人机协同能力､译文诊断能力､过程管理和责任伦理为核心的翻译能力培养体系,培养适应智能化语言服务生态的新型翻译人才｡

Current generative artificial intelligence is deeply intervening in translation practice, driving translation activities from a relatively closed process of bilingual transfer to a complex practice involving the collaborative participation of humans, models, corpora, tools, and contexts, and thereby reshaping the competence objectives, teaching processes, assessment criteria, and ethical boundaries of translation education. At present, translation education faces challenges such as the weakening of learners’ agency, increasing pressure on teachers to transform their roles, declining validity of final product evaluation, rising risks of academic integrity, and blurred boundaries of translator responsibility. Translation education should be restructured around competence objectives, curricular content, teaching models, assessment systems, and ethical norms, and should build a translation competence cultivation framework centered on human machine collaboration competence, translation diagnostic competence, process management, and responsible ethics, so as to develop a new generation of translation professionals equipped to adapt to the intelligent language service ecosystem.