The Symbiotic Relationship Between AI and the Humanities

Generative AI is profoundly changing various fields such as education, employment, entertainment, healthcare, transportation, and elderly care, becoming a hot topic. The relationship between the humanities and generative AI is complex and symbiotic. AI is reshaping the forms and future development paths of the humanities, while the demands of AI development highlight the value of the humanities. In this sense, the development of the humanities will fundamentally influence the cognitive heights and societal acceptance of AI.

Bridging Humanities Scholars to Multidisciplinary Approaches

As modern disciplines become increasingly specialized, barriers exist not only between the humanities and natural sciences but also between the humanities and social sciences, 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” within contemporary humanities. The advent of AI offers new solutions to this issue.

Large language models are distributed representation systems of language and knowledge constructed through deep learning on vast amounts of text. They condense human written knowledge and utilize neural network architectures and algorithm-driven probabilistic predictions to achieve context-aware, human-like logical reasoning under specific prompts. In this sense, AI can serve as a powerful assistant for humanities scholars, providing a bridge to multidisciplinary approaches and empowering the production of humanistic knowledge through information search, literature screening, semantic analysis, and cross-disciplinary integration.

Currently influential methods like “distant reading” utilize AI models to establish interdisciplinary literary criticism and research models based on the framework of world literature. Unlike traditional literary studies that advocate close reading of a few classics, distant reading employs data mining and quantitative analysis of large text collections to systematically reveal themes, emotional tendencies, plot structures, and linguistic features, providing a macro description of the overall development of human literature. This effectively addresses the technical challenges of processing vast amounts of text and the cross-cultural and interdisciplinary knowledge dilemmas that qualitative analyses of 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 term “humanities” emerged in the twentieth century. During the Western Enlightenment, humanities scholars sought to identify their unique nature and methods outside of natural sciences. They regarded the humanities as a “new science” about human thoughts and behaviors, distinct from natural sciences, emphasizing the use of “individualized methods” linked to values, attempting 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 of spiritual culture that are difficult to quantify. This encompasses deep individual psychology, instincts, consciousness, and the unconscious, carrying inherent characteristics of value, culture, individuality, spirituality, emotion, thought, and symbolism inseparable from humanity. Methodologically, the humanities focus on empathetic understanding, contemplative 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 natural sciences.

As disciplines evolve, this binary thinking model is continually being reconsidered. Marx stated, “Natural sciences will eventually include the science of humans, just as the science of humans includes natural sciences: this will be one science.” Emerging digital humanities research not only deeply examines the humanistic concerns and governance challenges brought by digital technology but also actively explores new research methods and paradigms from digital technology, reshaping the landscape of humanistic research. Various literary laboratories and beneficial attempts at quantitative humanities research are continuously emerging. AI has evolved from an auxiliary tool to a key force driving paradigm innovation, providing humanities scholars with new interdisciplinary research perspectives and theoretical innovation support, greatly expanding the breadth and depth of humanistic research experiences.

Human-Machine Collaboration Enhances Critical Thinking and Writing Skills

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 meanings through written language. This differs from the use of formulaic derivations, data charts, and reproducible experiments in natural sciences, as well as 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 mental exercise that integrates creativity, criticality, and reflexivity—“writing is thinking,” a process of generating and deepening thoughts and feelings. Writing can stimulate creative vitality, enhance self-reflection, and expand expressive boundaries, where linguistic acuity, intellectual penetration, and cultural insight are intertwined. Scholars have pointed out that writing style itself carries the unique emotional color, academic judgment, and value stance of the researcher. In this sense, humanistic writing is a core aspect of academic research, serving not only as a means of knowledge production but also as a reflection of thinking styles and disciplinary characteristics, acting as a fundamental carrier of academic exchange and a vital source of disciplinary vitality. Whether expressing philosophical thoughts and probing ultimate meanings, narrating historical contexts and events, or constructing values and poetic insights in literary criticism and research, the organization and structuring of materials, logical reasoning, and viewpoint argumentation, as well as the deepening of thoughts and the condensation of spiritual experiences, all occur within the process of creative writing.

Current AI models can transfer the language structures, argumentation patterns, and disciplinary terminology learned from large-scale corpora into specific fields of humanistic knowledge production, promoting human-machine 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 collect, systematically organize, and deeply analyze literature before writing. During the writing process, through human-machine collaboration and dialogue, researchers can organically integrate dispersed knowledge, building new knowledge graphs and cognitive frameworks, helping them break through existing theoretical and cognitive limitations, extract deep thoughts and internal logical structures from complex texts, reveal developmental laws, refine core concepts, and ultimately give birth to 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 paths for academic research and knowledge innovation. On the other hand, AI can refine and optimize professional academic expressions, correcting and enhancing aspects of knowledge, normativity, logic, and systematization, even prompting low-quality academic research to exit relevant fields. Sometimes, some academic debates in the humanities suffer from insufficient materials, unclear concepts, and weak logic, and AI assistance can significantly improve the quality of academic discourse and enhance its value.

The involvement of AI is not a simple process of machine-assisted writing but a continual deepening of thought and inspiration optimization through human-machine interaction and back-and-forth dialogue. This process demands a high level of AI literacy from researchers regarding their collaboration abilities, especially in correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These abilities determine the effectiveness of using AI tools. In this context, the ability to pose genuine, good, and new questions becomes extremely important, returning to the essence of academic research. At the same time, 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. The subtle connections discovered by humans through intuitive judgments amidst vast information, strategic choices based on value stances, and unique expressions arising from aesthetic tastes hold significant importance. Without human verification, modification, and deepening, the content generated by AI tends to carry a strong “machine flavor,” presenting as uniform and homogenized expressions.

To ensure independent academic thinking, unique insights, and distinct academic styles, the personal characteristics of humanities researchers—such as talent, courage, insight, and capability—should not be diminished by machine assistance, and dependency thinking and intellectual inertia should be avoided. Otherwise, their research outcomes will lose the dynamism inherent in humanistic research. Humanistic research must always reflect the “human” aspect, integrating 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 be able to feel the emotional investment and value care of researchers, achieving both depth of thought and warmth of emotion.

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

AI, as a mirror of human intelligence, can help humanity understand the essence of being human more profoundly. Simultaneously, humanity’s understanding of itself becomes the fundamental basis for the future development and governance of AI technology. Marx once pointed out that “conscious life activities directly distinguish humans from animal life activities.” Thus, humanity’s strength lies in its possession of intellect and practical creativity, continually acquiring knowledge and skills through learning and applying them to achieve goals.

At this stage, AI still imitates human intelligence, aiming to behave like a human, and its development 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 but a product of human creativity and self-awareness reaching a certain stage. Although currently focused vertical models have demonstrated execution efficiency and precision surpassing humans in specific tasks and fields, they remain tools of humanity. So far, the “general models” that autonomously adapt to different environments and needs often perform worse than human infants when faced with new situations, counterfactual problems, or common-sense reasoning. Fundamentally, 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 an imitator to an understander. In this context, questioning the generative mechanisms and operational modes of human intellect becomes particularly important. Humanity’s reflection on AI is also a re-evaluation of itself as a complex intelligent entity, further using non-human intelligent agents as mirrors to explore the deep essence of humanity and understand “what it means to be human.”

Whether in natural sciences or in the humanities and social sciences, there is an ongoing alternation between “demystifying” and “enchanting” the human experience, with the core of “enchantment” being the mystery of humanity itself. Without a profound understanding of human intellect, a “general model” cannot genuinely emerge. As Marx stated, “anatomy of the human body is the key to the anatomy of the monkey body;” the signs of higher animals revealed in lower animals can only be understood after recognizing higher animals themselves. 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, technology 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 evolution of “general models.”

From the perspective of the relationship between the humanities and social life, the humanities cannot be replaced by AI because they possess reflexivity. Every emergence and change in humanistic cognition and understanding intervenes in the development of social life and the construction of public sentiment, embodying the quality of “establishing a heart for heaven and earth, establishing a destiny for the people.” In this sense, the development of the humanities is not a linear progression; various humanistic thoughts cannot simply be added together to form a single 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 humans and their understanding of the world, thereby exerting a significant influence on generative AI. Simultaneously, the impact of new technologies like AI on society and humanity itself also constitutes a focus of humanistic scholarship, and related reflections become part of the human spiritual world. The humanities and AI are always in a dynamic interplay of coexistence and mutual promotion. It is essential 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 are fully confident that humanistic thought can illuminate the future path of AI.