The large-scale intervention of generative artificial intelligence in the field of literary criticism has sparked sustained academic debates on the essential differences between artificial intelligence (AI) criticism and human criticism. Existing studies have mostly been carried out from the perspectives of technical principles and theoretical speculation, lacking systematic empirical comparison between the two types of critical texts, and failing to anchor discussions on their essential differences at the level of textual details and cognitive mechanisms. To this end, this paper takes five classic Tang poems as analytical samples, conducts a multi-dimensional empirical comparison between the commentary texts generated by the DeepSeek large language model (LLM) and those by renowned human critics across dynasties, systematically sorts out their systematic differences in analytical focus, judgment mode, linguistic style and theoretical depth, and explores the deep-seated roots of the differences from four dimensions: intentionality, embodied experience, value rationality and linguistic expression. The study finds that AI criticism and human criticism are cognitive activities with fundamentally different natures: human criticism is contemplative interpretation and value judgment rooted in intentional aesthetic experience, while AI criticism is computational analysis and descriptive data output based on algorithmic processing. This research not only debunks the myth of technological optimism, but also transcends the simplistic negation of humanistic conservatism, deepens the understanding of the humanistic essence of literary criticism, and provides a theoretical reference for the practice of human-machine collaborative literary criticism in the digital age.
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Share and Cite
Shen, M. (2026) The Essential Boundaries of Generative AI Literary Criticism: An Investigation Centered on Classic Tang Poems. Global Education Bulletin, 3(1), 25-40. https://doi.org/10.71052/grb2025/MRUF2713