2026北外英语语言文学考研811外语翻译写作（英语）真题参考答案

绿水青山就是金山银山，这不仅是一个重要理念，更是沉甸甸的时代责任。

Lucid waters and lush mountains are invaluable assets. This is not only an important philosophy, but also a weighty responsibility of our times.

树林阴翳，鸣声上下，这样诗意的画卷不应该只出现在古籍和诗词里。

Imagine a place with woodlands shaded by dense foliage and birds chirping in the trees: such a poetic picture should not be confined to ancient books and poems.

失去了绿色的底色，就缺少了可持续性和诗意。

Without the green backdrop, we will lose the foundation for sustainability and poetic charm.

千百年来，中华民族对大自然保持着敬意和热爱，现在这一份责任落到了我们青年一代的肩膀上。

For thousands of years, the Chinese nation has always held nature in reverence and affection. Now, this responsibility has fallen on the shoulders of the younger generation.

守护每一片绿色土地，参加每一次环保活动，都是在"美丽中国"的画卷上添上我们青春的一笔。

To safeguard every patch of green land and participate in every environmental protection activity is to pay a youthful piece of contribution to the grand picture of a "Beautiful China".

This research report investigates the transformation of humanities research from Digital Humanities to AI Humanities, arguing that the advent of generative artificial intelligence marks a qualitative shift in humanistic knowledge production rather than a linear technological upgrade. Tracing the genealogy of Digital Humanities from early humanities computing, the report highlights emblematic milestones such as Roberto Busa’s collaboration with IBM and Franco Moretti’s concept of “distant reading” and the Stanford Literary Lab. These cases reveal both the ambition and the limitations of traditional digital humanities: high technical thresholds, labor-intensive data cleaning and annotation, and strong dependence on human programming expertise.

The report then analyzes how generative AI fundamentally reconfigures this paradigm. Whereas Digital Humanities focuses on digitization, data analysis, and visualization, AI Humanities integrates large-scale pre-trained models (e.g., BERT and domain-specific models such as SikuBERT trained on Siku Quanshu) to automate and intelligentize the entire research pipeline. Generative AI significantly lowers barriers to entry through natural-language interaction, allowing researchers to conduct complex tasks -- text segmentation, semantic modeling, and hypothesis generation -- via prompt-based communication rather than code-heavy workflows. Examples including ChatGPT, Wenxin Yiyan, and multimodal models such as Sora illustrate how AI expands humanities research from text analysis to image restoration, video generation, and cultural simulation.

A core theoretical contribution of this report is the concept of the “vectorization of human experience.” By encoding large-scale cultural memory -- texts, images, sounds, and historical records -- into mathematical vectors, generative AI enables deep pattern recognition, information recombination, and predictive inference. Drawing on cases such as topic modeling in Quan Tang Poetry and AI-assisted restoration of ancient manuscripts (e.g., the Vesuvius Challenge), the report argues that AI systems now possess preliminary knowledge-production capacities rather than functioning merely as auxiliary tools.

However, the report maintains a critical stance. It emphasizes that generative AI lacks epistemic justification, moral reasoning, tacit knowledge, and genuine critical reflexivity. Problems such as algorithmic opacity, bias, and hallucination underscore the necessity of human oversight. Accordingly, the report proposes the framework of “AI that needs humans” and “humanities that possess AI,” affirming human subjectivity, ethical judgment, and interpretive creativity as irreplaceable.

In conclusion, this report positions AI Humanities as a transformative yet human-centered paradigm, one that redefines -- rather than replaces -- the role of the humanities in the age of intelligent machines.

请以“大学生活里重要的一课”为题，书写感悟与思考，400词左右。