The Symbiotic Relationship Between AI and the Humanities

Generative AI is profoundly changing various fields such as education, employment, entertainment, healthcare, transportation, and elder care, becoming a hot topic of discussion. The relationship between the humanities and generative AI is complex and symbiotic. AI is reshaping the forms and future development paths of the humanities. Meanwhile, the needs of AI development highlight the value and functions of the humanities, suggesting that the evolution of the humanities will fundamentally influence the cognitive heights and social acceptance of AI.

Bridging Humanities Scholars to Multidisciplinary Approaches

As modern disciplines become increasingly specialized, barriers between the humanities and natural sciences, as well as between the humanities and social sciences, are widening, potentially leading to a “knowledge dilemma.” It is challenging to find scholars within the humanities who can bridge literature, art, philosophy, history, and language, resulting in a limitation of “partial profundity” in contemporary humanities. The emergence of AI provides a new solution to this issue.

Large language models are built through deep learning on vast amounts of text, creating a distributed representation system of language and knowledge, highly condensing human written knowledge. They utilize neural network architectures and algorithm-driven probabilistic predictions, achieving contextual awareness through deep learning. Guided by specific prompts, they engage in human-like logical reasoning to output knowledge. In this sense, AI can serve as a powerful assistant for humanities scholars, providing a bridge to multidisciplinary connections and empowering the production of humanistic knowledge through information search, literature screening, semantic analysis, and cross-domain integration.

Currently influential methods like “distant reading” leverage AI models to establish interdisciplinary literary criticism and research models based on a global literary framework. Unlike traditional literary studies that advocate close reading of a few classics, distant reading involves data mining and quantitative analysis of large text collections to systematically reveal themes, emotional tendencies, narrative structures, and linguistic features, thereby macro-describing the overall development of human literature. This effectively addresses the technical challenges of processing vast amounts of text and cross-cultural, interdisciplinary knowledge that qualitative analyses in traditional literary history and world literature research cannot solve.

Updating Methods and Paradigms in the Humanities

China has a long and rich tradition of humanities scholarship, but the formal establishment of the “humanities” as a discipline occurred in the twentieth century. During the Enlightenment in the West, humanities scholars sought to identify their unique nature and methods beyond the natural sciences. They viewed the humanities as a “new science” concerning human thoughts and behaviors, distinct from the natural sciences, emphasizing the use of “individualized methods” linked to values to construct the epistemology and methodology of the humanities.

Overall, this logic, criticized by later generations as the “spirit-nature dichotomy,” emphasizes “thought of existence,” with research objects existing in symbolic forms such as language, text, images, and rituals, involving beliefs, conscience, emotions, aesthetics, values, and ideals—elements that are difficult to quantify. This encompasses deep individual psychology and instincts, consciousness and the unconscious, while also carrying historical cultural memory and collective unconsciousness, embodying intrinsic qualities of value, culture, individuality, spirituality, emotionality, thought, and symbolism inseparable from humanity. Methodologically, the humanities focus on empathetic understanding, reflective experience, and intuitive insight, aiming to reveal unique individual experiences, complex mental worlds, and deep cultural meanings that cannot be captured by replicable, quantifiable, and verifiable techniques of the natural sciences.

As disciplines evolve, this binary thinking model is continuously being reexamined. Marx noted, “Natural sciences will eventually include the science of humans, just as the science of humans includes natural sciences: this will be a science.” Emerging digital humanities research not only examines the humanistic concerns and governance challenges brought about by digital technology but also actively explores new research methods and paradigms derived from digital technology, reshaping the landscape of humanistic research. Various literary laboratories and quantitative humanities research initiatives are continuously emerging. AI is evolving from a mere auxiliary tool to a key force driving paradigm innovation, providing humanities scholars with new interdisciplinary research perspectives and theoretical innovation support, significantly broadening the depth and breadth of humanistic research experiences.

Enhancing Critical Thinking and Writing Skills through Human-AI Collaboration

A unique aspect of the humanities is that its knowledge forms often manifest as narrative or speculative texts, expressing researchers’ unique insights and profound reflections on human existence, values, and meaning through written language. This contrasts with the natural sciences, which employ formulaic deductions, data charts, and reproducible experimental validations, and differs from the empirical paths of social sciences that heavily rely on surveys and statistical models. Humanistic writing is not only an expression of thoughts and emotions but also a comprehensive intellectual exercise that integrates creativity, criticality, and reflexivity. “Writing is thinking,” representing a process of generating and deepening thoughts and emotions. Writing can stimulate creative vitality, enhance self-reflection, and expand expressive boundaries, merging linguistic acuity, intellectual penetration, and cultural insight.

Scholars point out that writing style itself carries the unique emotional hues, academic judgments, and value positions of researchers to some extent. In this sense, humanistic academic writing is a core component of academic research; it is not only a method of knowledge production in the humanities but also a reflection of its modes of thought and disciplinary characteristics. It serves as a fundamental vehicle for maintaining the existence of the discipline and promoting academic exchange, representing a vital source of the discipline’s vitality. Whether expressing philosophical thoughts and probing ultimate meanings, describing historical contexts and narrating events, or constructing values and poetic insights in literary criticism and research, the organization and structural integration of materials, logical reasoning and argumentation, as well as the deepening of thoughts and the distillation of spiritual experiences, all occur within the creative writing process.

Current AI models can transfer the language structures, argumentative patterns, and disciplinary terminologies learned from large-scale corpora into specific domains of humanistic knowledge production, promoting human-AI collaboration and achieving a holistic leap in humanistic writing. On one hand, in humanistic academic writing, researchers can fully utilize AI’s powerful data processing capabilities to efficiently gather, systematically organize, and deeply analyze literature before writing. During the writing process, through human-AI collaboration and dialogue, they can organically integrate dispersed knowledge, constructing new knowledge graphs and cognitive frameworks that help researchers break through existing theoretical and cognitive limitations, unearthing deep thoughts and internal logical structures from complex texts, thereby revealing developmental laws, distilling core concepts, and ultimately nurturing new knowledge outcomes. This process is not merely a simple accumulation of knowledge but an innovative mechanism capable of generating specific theoretical results, opening new pathways for academic research and knowledge innovation. On the other hand, AI can refine and optimize academic expressions, correcting and enhancing the quality of humanistic academic writing in terms of knowledge, norms, logic, and systematics, potentially forcing low-quality academic research out of relevant fields. Sometimes, certain academic disputes in the humanities suffer from insufficient materials, unclear concepts, and loose logic; AI assistance can significantly improve the quality of academic debates and enhance their value.

The involvement of AI is not a simple process of machine-assisted writing; it is a process of deepening thought, inspiring creativity, and optimizing expression through human-AI interaction and iterative dialogue. This process demands a high level of AI literacy from researchers, particularly in correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These skills determine the effectiveness of using AI tools. Here, the ability to pose genuine, good, and new questions becomes extremely important, returning to the essence of academic research. Moreover, as some studies have pointed out, AI excels in knowledge inheritance but falls short in creative thinking, making it difficult to replace human involvement in theoretical construction, critical reflection, value selection, and aesthetic judgment. Human intuition-based judgments that discover subtle connections among vast information, strategic choices based on value positions, and unique expressions arising from aesthetic tastes are all of great significance. Without human verification, modification, and deepening, AI-generated content risks bearing a strong “machine flavor,” presenting as bland and homogenized expressions.

To ensure academic independence of thought, unique insights, and distinctive academic styles, the personal characteristics of human researchers—such as talent, courage, insight, and capability—should not be diminished by machine assistance. There is a risk of developing dependency on machine thinking and intellectual inertia; otherwise, research outcomes may lose the dynamism inherent in humanistic inquiry. Humanistic research must always reflect “the human” and integrate personal life experiences into academic exploration, responding to contemporary issues with keen perception, unique creativity, and a critical spirit in pursuit of truth. People should feel the emotional investment and value concerns of researchers, embodying both depth of thought and warmth of feeling.

The Development of AI Relies on the Humanities’ Understanding of “Human”

As a mirror of human intelligence, AI can help humanity understand the essence of “what it means to be human” more profoundly. Simultaneously, humanity’s understanding of itself serves as the fundamental basis for the future development and governance of AI technology. Marx pointed out that “conscious life activities distinguish humans from the life activities of animals.” Thus, humanity’s strength lies in its possession of intellect, practical creativity, and the ability to continuously acquire knowledge and skills through learning to achieve goals.

At this stage, AI still imitates human intelligence, exhibiting human-like behavior, and its developmental goal should be to gradually align with the internal mental structures and creative mechanisms of humans, rather than merely replicating external behaviors. The emergence of generative AI is not coincidental; it is a product of human creativity and self-awareness reaching a certain stage. Although currently specialized vertical models demonstrate execution efficiency and precision that surpass human capabilities in specific tasks and domains, they fundamentally remain tools for humans. To date, general models capable of autonomously adapting to different environments and needs often perform worse than human infants when faced with new situations, counterfactual problems, or tasks requiring common sense reasoning. At its core, current AI knows what to do but may not understand the underlying principles and logic; the AI black box has yet to be opened, and it cannot evolve from imitator to understander. In this context, questioning the generative mechanisms and operational modes of human intellect becomes particularly important. Human reflections on AI are also a re-examination of humanity itself as a complex intelligent agent, further utilizing non-human intelligent agents as mirrors to uncover the deep essence of humanity and understand “what it means to be human.”

Both natural sciences and humanities and social sciences oscillate between the processes of “disenchantment” and “enchantment” regarding humans, with the core of “enchantment” always being the secrets of humanity itself. Without a profound understanding of their own intellect, humans cannot genuinely realize the existence of “general models.” As Marx stated, “anatomy of the human body is the key to the anatomy of the monkey body.” The signs of higher animals displayed in lower animals can only be understood after higher animals themselves are recognized. Understanding humans and comprehending humanity is the fundamental nature and basic value goal of the humanities. Today, the many “unexplainabilities” of AI largely stem from humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, governance, and value alignment require a foundation of human understanding of its essence; the level of development in the humanities determines the future possibilities for the development of “general models.”

From the perspective of the relationship between the humanities and social life, the humanities cannot be replaced by AI, as they possess reflexivity. Every emergence and change of humanistic cognition and understanding intervenes in the development of social life and the construction of public sentiment, embodying the characteristic of “establishing a heart for heaven and earth, and a mission for the people.” In this sense, the development of the humanities is not a linear process of progress; various humanistic thoughts cannot simply be added together to form a singular ultimate truth but coexist in a pluralistic manner, collectively shaping the rich spiritual world of society and individuals. It can be said that the advancement of humanistic scholarship alters humanity’s understanding of the world, thereby exerting a significant influence on generative AI. Simultaneously, the impacts of new technologies like AI on society and humanity also constitute a focal point of humanistic scholarship, and related reflections become part of the human spiritual world. The humanities and AI remain in a dynamic interplay of coexistence and mutual promotion. It is crucial to remember that AI is created by humans, and humanity must possess the ability to genuinely understand and effectively harness its creations. In this sense, we can be fully confident that humanistic thought can illuminate the future path of AI.