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. There exists a complex and profound interrelationship between the humanities and generative AI. AI is reshaping the forms and future development paths of the humanities, while the development needs of AI highlight the value and functionality of the humanities. In this sense, the development of the humanities will fundamentally influence the cognitive heights and social acceptance of AI.

Building Bridges for Humanities Scholars

As modern disciplines become increasingly specialized, the humanities face barriers not only with the natural sciences but also with the social sciences, leading to a potential “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 offers new solutions to this problem.

Large language models are constructed through deep learning on vast amounts of text, representing a highly condensed form of human written knowledge. They utilize neural network architectures and algorithm-driven probabilistic predictions, achieving context awareness through deep learning, and perform human-like logical reasoning under specific prompts. In this sense, AI can serve as a powerful assistant for humanities scholars, building bridges to interdisciplinary fields and empowering the production of humanistic knowledge in areas such as information retrieval, literature screening, semantic analysis, and cross-domain integration.

Currently influential “distant reading” methods leverage AI models to establish interdisciplinary literary criticism and research models based on the overall 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 characteristics such as thematic distribution, emotional tendencies, plot structures, and linguistic rhetoric, 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, interdisciplinary knowledge challenges that qualitative analysis 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 term “humanities” was coined in the twentieth century. During the Enlightenment in the West, humanities scholars sought to find their unique nature and methods outside 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” connected to values to construct the epistemology and methodology of the humanities.

Overall, within this logic, often criticized as the “spirit-nature dichotomy,” the humanities emphasize “thought of existence,” with research objects existing in symbolic forms such as language, text, images, and rituals, involving difficult-to-quantify spiritual cultural content such as beliefs, conscience, emotions, aesthetics, values, and ideals. This includes deep individual psychology, instincts, consciousness, and the unconscious, carrying intrinsic characteristics of value, culture, individuality, spirituality, emotionality, thought, and symbolism that are inseparable from humanity. Methodologically, the humanities focus on internalized approaches such as empathetic understanding, reflective experience, and intuitive insight, aiming to reveal unique individual experiences, complex spiritual worlds, and deep cultural meanings that cannot be captured through replicable, quantifiable, or verifiable techniques of the natural sciences.

As disciplines continue to develop, this binary opposition in thinking has been increasingly reflected upon. Marx once stated, “Natural science will eventually include the science of man, just as the science of man includes natural science: this will be a 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 and framework of humanistic research. Various literary laboratories and quantitative humanities research initiatives 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.

Enhancing Critical Thinking and Writing Skills through Human-Machine 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 meanings through written language. This contrasts with the natural sciences, which utilize formulaic deductions, data charts, and reproducible experimental demonstrations, and differs from the empirical paths of social sciences that heavily rely on surveys and statistical models. Humanistic writing is not merely an expression of thoughts and emotions; it is a comprehensive cognitive movement that integrates creativity, criticality, and reflexivity. “Writing is thinking”—it is a process where thoughts and emotions are generated and continually deepened. Writing can stimulate creative vitality, enhance self-reflection, and expand expressive boundaries, merging linguistic acuity, intellectual penetration, and cultural insight. Scholars have pointed out that writing style itself carries researchers’ unique emotional tones, academic judgments, and value positions. In this sense, humanistic writing is central to academic research; it is not only a mode of knowledge production in the humanities but also a reflection of its thinking style and disciplinary characteristics, serving as a fundamental carrier of academic exchange and a vital source of disciplinary vitality. Whether expressing philosophical ideas and ultimate meanings, describing historical contexts and narrative events, or constructing values and poetic insights in literary criticism and research, the organization and structural integration of materials, logical reasoning, viewpoint argumentation, and the distillation of thoughts and spiritual experiences are all accomplished through the creative writing process.

Current AI models can transfer the language structures, argumentation patterns, and disciplinary terminology learned from large-scale corpora into specific domains of knowledge production in the humanities, 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 a vast amount of literature before writing, and during the writing process, through human-machine collaboration and dialogue, they can organically integrate dispersed knowledge, build new knowledge graphs and cognitive frameworks, helping researchers break through existing theoretical and cognitive limitations, excavate deep thoughts and internal logical structures from complex texts, reveal the laws of development, distill core concepts, and ultimately give birth to new knowledge outcomes. This process is not a simple accumulation of knowledge but an innovative mechanism capable of generating specific theoretical results, opening up new paths for academic research and knowledge innovation. On the other hand, AI can partially polish and optimize professional academic expressions, correcting, adjusting, and enhancing the quality of humanistic academic expressions in terms of knowledge, norms, logic, and systematization, even compelling low-quality academic research to exit relevant fields. Sometimes, certain academic disputes in the humanities are significantly hindered by insufficient materials, unclear concepts, and weak logic; AI assistance can greatly improve the quality of academic debates and enhance their value.

The involvement of AI is not a simple process of machine-assisted writing but a continuous deepening of thought, inspiration, and expression optimization through human-machine interaction and back-and-forth dialogue. This process places higher demands on researchers’ AI literacy, particularly in correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These abilities 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. At the same time, as some studies have pointed out, AI excels at knowledge inheritance but falls short in creative thinking, making it difficult to replace human deep involvement in theoretical construction, critical reflection, value selection, and aesthetic judgment. Human intuition-based judgments, subtle connections discovered amidst vast information, strategic choices made based on value positions, and unique expressions arising from aesthetic tastes are all of great significance. If not verified, modified, and deepened by humans, AI-generated content tends to carry a strong “machine flavor,” presenting as uniform and homogenized expressions.

To ensure independent academic thinking, unique insights, and distinctive 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 may lose the dynamism inherent in humanistic research. Humanistic research must always reveal the “human” aspect, integrating personal life experiences into academic exploration, responding to contemporary issues with keen perception, unique creativity, and a critical spirit in the pursuit of truth. People should be able to feel the emotional investment and value care of the researcher, achieving both depth of thought and warmth of emotion.

Understanding Humanity is Essential for AI Development

AI, as a mirror of human intelligence, can help humanity understand the essence of “what it means to be human” more profoundly. At the same time, humanity’s understanding of itself becomes the fundamental basis for the future development and governance of AI technology. Marx pointed out that “conscious life activity distinguishes humans from animal life activities directly.” 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 belongs to the realm of mimicking human intelligence, exhibiting behaviors akin to humans. Its developmental goal should gradually align with the internal cognitive structures and creative mechanisms of humans, rather than merely replicating external behaviors. The birth of generative AI is not accidental; it is a product of human creativity and self-awareness reaching a certain stage. Although currently, specialized vertical models have demonstrated execution efficiency and precision surpassing humans in specific tasks and fields, they essentially remain tools of humanity. To date, 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 remains unopened; it cannot evolve from a mere imitator to an understanding entity. In this context, inquiries into the generative mechanisms and operational modes of human cognition become particularly important. Humanity’s reflections on AI also represent a re-examination of itself as a complex intelligent being, further utilizing 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 the humanities and social sciences, there exists an alternation and repetition between the “demystification” and “enchantment” of humanity, with the core of “enchantment” always being the secret of humanity itself. Without a profound understanding of its own intellect, the emergence of a “general model” is impossible. As Marx stated, “anatomy of the human body is the key to the anatomy of the ape;” the signs of higher animals expressed in lower animals can only be understood after the higher animals themselves have been recognized. Understanding humanity and comprehending human nature are fundamental properties and basic value goals of the humanities. Today, the many “unexplainable” aspects of AI are largely due to humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, technological governance, and value alignment all require a foundational understanding of humanity’s 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 because they possess reflexivity. Every emergence and change in humanistic cognition and understanding intervenes in the development of social life and the construction of societal sentiments, embodying the qualities of “establishing the heart for heaven and earth, and establishing 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 singular ultimate truth but coexist in a pluralistic manner, collectively shaping the rich spiritual world of society and individuals. It can be said that advancements in humanistic scholarship change humanity and its understanding of the world, thereby exerting a tremendous influence on generative AI. At the same time, the impact of new technologies like AI on society and humanity also becomes a focal point 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 crucial to remember that AI is a creation of humanity, and humans must possess the ability to genuinely understand and effectively harness their creations. In this sense, we are fully confident that humanistic thought can illuminate the future path of AI.