The Mutual Empowerment of AI and Humanities

Generative artificial intelligence 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, while the demands of AI development 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 that AI can achieve.

Bridging Humanities Scholars to Multidisciplinary Approaches

As modern disciplines become increasingly specialized, the 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 difficult 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 can provide new solutions to this issue.

Large language models, constructed through deep learning on massive text datasets, represent a highly condensed form of human written knowledge. They are based on neural network architectures and algorithm-driven probabilistic predictions, achieving context-aware human-like reasoning guided by specific prompts. In this sense, AI can serve as a powerful assistant for humanities scholars, bridging them to multidisciplinary approaches and empowering the production of humanistic knowledge through information search, literature screening, semantic analysis, and cross-domain integration.

Currently influential “distant reading” methods utilize AI models to establish interdisciplinary literary criticism and research modes based on the overall framework of world literature. 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, plot structures, and linguistic features, providing a macro description of the overall development of human literature. This effectively addresses the technical challenges of processing massive texts and the cross-cultural, cross-disciplinary knowledge dilemmas 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 term “humanities” emerged in the twentieth century. During the Enlightenment in the West, humanities scholars sought to find their unique nature and methods outside of natural sciences. They viewed the humanities as a “new science” concerning human thoughts and behaviors, distinct from natural sciences, emphasizing the use of “individualized methods” linked to values, and attempting to construct epistemology and methodology for the humanities.

Overall, in this logic criticized by later generations as the “spirit-nature dichotomy,” the humanities emphasize “existential thought,” with research objects existing in symbolic forms such as language, text, images, and rituals, involving faith, conscience, emotion, aesthetics, values, and ideals that are difficult to quantify. This encompasses deep individual psychology and instincts, consciousness and unconsciousness, and carries historical cultural memory and collective unconsciousness, possessing intrinsic characteristics of value, culture, individuality, spirituality, emotionality, thought, and symbolism inseparable from humanity. Methodologically, the humanities focus on empathetic understanding, contemplative experience, and intuitive insight to reveal unique individual experiences, complex mental worlds, and deep cultural meanings that cannot be captured by replicable, quantifiable, and verifiable technical means of natural sciences.

As disciplines develop, this binary oppositional thinking model is continually being reflected upon. Marx once stated, “Natural sciences will eventually include the science of man, just as the science of man 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 continually 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, significantly expanding the breadth and depth 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 meanings through written language. This differs from natural sciences, which rely on formulaic deductions, data charts, and repeatable experimental validations, and from social sciences, which heavily utilize surveys and statistical models for empirical paths. Humanistic writing is not only an expression of thoughts and emotions but also a comprehensive cognitive movement that integrates creativity, criticality, and reflection—“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 sensitivity, intellectual penetration, and cultural insight merge. Scholars have pointed out that writing style itself carries the unique emotional tones, academic judgments, and value positions of the researcher to some extent. In this sense, humanistic writing is a core aspect of academic research; it is not only a mode of knowledge production in the humanities but also reflects its ways of thinking and disciplinary characteristics, serving as a fundamental vehicle for maintaining disciplinary existence and promoting academic exchange, as well as a vital source of disciplinary vitality. Whether expressing philosophical thoughts 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 and argumentation, and the deepening of thoughts and condensation of spiritual experiences all occur within the creative writing process.

Currently, AI models can transfer the language structures, argumentative patterns, and disciplinary terminology learned from vast corpora into specific fields of knowledge production in the humanities, promoting human-AI collaboration and achieving a holistic leap in humanistic writing. On one hand, in humanistic academic writing, researchers can fully leverage AI’s powerful data processing capabilities to efficiently gather, systematically organize, and deeply analyze literature before writing. On the other hand, during the writing process, through human-AI collaboration and dialogue, they can organically integrate dispersed knowledge, building new knowledge graphs and cognitive frameworks, helping researchers break through existing theoretical and cognitive limitations, uncovering deep thoughts and internal logical structures from complex texts, revealing developmental laws, refining 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 outcomes, opening new paths for academic research and knowledge innovation. Furthermore, AI can partially polish and optimize professional academic expressions, correcting and enhancing the knowledge, normative, logical, and systematic aspects of humanistic academic expressions, even forcing low-quality academic research out of relevant fields. Sometimes, certain academic disputes in the humanities significantly suffer from 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 continual deepening of thought and inspiration through human-AI interaction and back-and-forth dialogue. This process places high demands on researchers’ collaborative abilities with AI, especially in correctly inputting instructions, 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 depth in theoretical construction, critical reflection, value selection, and aesthetic judgment. Human intuition-based judgments uncover subtle connections among vast information, strategic choices based on value positions, and unique expressions arising from aesthetic tastes, all hold significant importance. If not verified, modified, and deepened by humans, the content generated by AI will carry a strong “machine flavor,” presenting as bland and homogenized expressions.

To ensure the academic independence of thought, unique insights, and distinct academic styles, the personal characteristics of humanities researchers—“talent, courage, insight, and ability”—should not be diminished by machine assistance, preventing dependency thinking and intellectual inertia; otherwise, their research outcomes will lose the dynamism inherent in humanistic research. Humanities 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, possessing both depth of thought and warmth of emotion.

The Development of AI Relies on Humanities Understanding of “Humanity”

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 becomes the fundamental basis for the future development and governance of AI technology. Marx pointed out, “Conscious life activity distinguishes man directly from animal life activity.” Thus, humanity’s strength lies in its possession of intellect, practical creativity, and continuous learning to acquire knowledge, master skills, and apply them toward achieving goals.

Currently, AI still belongs to the imitation of human intelligence, exhibiting human-like behavior; its development goal should 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 accidental but a product of human creativity and self-awareness reaching a certain stage. Although currently specialized vertical models have shown superior execution efficiency and precision in specific tasks and fields, they fundamentally remain tools of humanity. Thus 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. Essentially, 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. Humanity’s reflections on AI also represent 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.”

Both natural sciences and humanities and social sciences are in a cycle of “disenchantment” and “enchantment” regarding humanity, with the core of “enchantment” always being the mystery of humanity itself. Without a profound understanding of one’s own intellect, a “general model” cannot truly emerge. As Marx stated, “Anatomy of man is the key to the anatomy of the ape;” the signs of higher animals displayed in lower animals can only be understood after the higher animals themselves are recognized. Understanding humanity and comprehending what it means to be human is the fundamental nature and basic value goal of the humanities. Today, AI still possesses many “unexplainabilities,” largely due to humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, technology governance, and value alignment all require a premise of human understanding of its own 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 stacked and fused into 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 advancements in humanistic scholarship alter humanity’s understanding of the world, thereby having a significant impact on generative AI. At the same time, the effects of new technologies like AI on society and humanity also become focal points of humanistic scholarship, with related reflections becoming part of the human spiritual world. The humanities and AI are always in a dynamically intertwined state of coexistence and mutual promotion. It is essential to remember that AI is created by humanity, and humanity should possess the ability to truly understand and effectively harness its creations. In this sense, we are fully confident that humanistic thought can illuminate the future path of AI.