The Mutual Empowerment of Artificial Intelligence 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 functions 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 Fields

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.” Within the humanities, it is difficult to find scholars 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 vast amounts of text, represent a distributed system of language and knowledge, highly condensing human written knowledge. They utilize neural network architectures and algorithm-driven probabilistic predictions, achieving context awareness through deep learning and performing human-like logical reasoning under specific prompts to produce knowledge outputs. In this sense, AI can become a powerful assistant for humanities scholars, building a bridge to multidisciplinary fields and empowering the production of humanistic knowledge in areas such as information search, 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 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 vast texts and the cross-cultural, cross-disciplinary knowledge dilemmas that traditional literary history and world literature studies 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 identify 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 an individualized approach linked to values, aiming to construct epistemology and methodology for the humanities.

Overall, this logic, criticized by later generations as a “spiritual-natural dichotomy,” emphasizes “thought of existence” in the humanities, with research objects existing in symbolic forms such as language, text, images, and rituals, involving faith, conscience, emotion, aesthetics, values, and ideals—elements of spiritual culture that are difficult to quantify. This encompasses deep individual psychology, instincts, consciousness, and the unconscious, carrying intrinsic characteristics of value, culture, individuality, spirituality, emotion, thought, and symbolism that are inseparable from humanity. Methodologically, the humanities focus on internalized approaches such as empathetic understanding, contemplative experience, and intuitive insight, aiming to reveal unique individual experiences, complex spiritual worlds, and deep cultural meanings that cannot be captured by the replicable, quantifiable, and verifiable technical means of natural sciences.

As disciplines develop, this binary thinking model is continually being reexamined. Marx stated, “Natural science will 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 of humanities research. Various literary laboratories and quantitative humanities research initiatives are continuously emerging. AI is evolving 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 contrasts with the natural sciences, which utilize formulaic deductions, data charts, and repeatable experimental validations, and with social sciences that heavily rely on survey data and statistical models. Humanistic writing is not only an expression of thoughts and emotions but also a comprehensive cognitive process that integrates creativity, criticality, and reflection—“writing is thinking,” a process of generating and deepening thoughts and emotions. Writing can stimulate creative vitality, enhance self-reflection, and expand expressive boundaries, where linguistic sensitivity, intellectual penetration, and cultural insight converge. Scholars have noted that writing styles can also carry unique emotional colors, academic judgments, and value positions of the researchers. In this sense, humanistic academic writing is a core aspect of academic research; writing is not only a mode of knowledge production in the humanities but also a reflection of its thinking modes and disciplinary characteristics, serving as a fundamental medium for maintaining the discipline’s existence and promoting academic exchange, as well as a vital source of the discipline’s 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 integration of materials, logical reasoning and argumentation, and the deepening of thoughts and condensation of spiritual experiences are all accomplished through the creative writing process.

Current AI models can transfer the language structures, argumentative 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 academic writing, researchers can leverage AI’s powerful data processing capabilities to efficiently gather, systematically organize, and deeply analyze literature before writing. 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, unearth deep thoughts and internal logical structures from complex texts, reveal developmental laws, distill 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 the knowledge, normative, logical, and systematic aspects of humanistic academic expressions, even compelling low-quality academic research to exit relevant fields. Sometimes, certain academic debates in the humanities suffer from insufficient materials, unclear concepts, and logical inconsistencies; 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 continuous deepening of thought, inspiration, and expression optimization through human-machine interaction and back-and-forth dialogue. This process places high demands on researchers’ AI literacy regarding human-machine collaboration, particularly in correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These capabilities determine the effectiveness of AI tool usage. 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, unable to replace human depth in theoretical construction, critical reflection, value selection, and aesthetic judgment. The subtle connections discovered by humans based on intuitive judgments among vast amounts of information, strategic choices made based on value positions, and unique expressions arising from aesthetic tastes all hold significant importance. Without human verification, modification, and deepening, the content generated by AI will carry a strong “machine flavor,” presenting as bland and homogenized expressions.

To ensure the independent thinking character, unique insights, and distinct academic style of scholarly work, humanities researchers’ personal characteristics—“talent, courage, insight, and ability”—should not be diminished by machine assistance, preventing dependency thinking and intellectual inertia; otherwise, their research outcomes may lose the dynamism inherent in humanistic inquiry. 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 be able to sense the emotional investment and value care of researchers, with both depth of thought and warmth of emotion.

The Development of AI Depends on Humanities’ Understanding of “Human”

As a mirror of human intelligence, artificial 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 activities directly distinguish humans from animal life activities.” 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 imitation of human intelligence, exhibiting human-like behavior. Its developmental 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; it is a product of human creativity and self-awareness reaching a certain stage. Although current specialized vertical models demonstrate execution efficiency and precision that surpass humans in specific tasks and fields, they remain tools created by humans. To date, “general models” that autonomously adapt to different environments and needs often perform worse than human infants when faced with new situations, counterfactual problems, or tasks requiring 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 imitator to understander. Questions about the generative mechanisms and operational modes of human intellect are particularly significant in this context. Humanity’s contemplation of AI is also a re-examination and reflection on itself as a complex intelligent entity, making a groundbreaking effort to uncover the deep essence of humanity and understand “what it means to be human” by comparing it with non-human intelligent agents.

Whether in natural sciences or humanities and social sciences, there exists an alternating cycle of “disenchantment” and “enchantment” regarding humans, with the core of “enchantment” always being the mystery of humanity itself. Without a profound understanding of their own intellect, a true “general model” cannot emerge, as Marx stated, “anatomy of the human body is the key to the anatomy of the ape.” The signs of higher animals displayed in lower animals can only be understood after higher animals themselves have been recognized. Understanding humans and comprehending humanity is the fundamental nature and basic value goal of the humanities. Today, the many “unexplainabilities” of AI are largely due to humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, technological governance, and value alignment require a prerequisite understanding of humanity’s essence, and 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 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 stacked and merged 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 the progress of humanistic scholarship alters both humanity and its understanding of the world, thereby significantly impacting generative AI. Simultaneously, the influence 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 dynamically intertwined state of coexistence and mutual promotion. It is essential to remember that AI is created by humans, and humanity must 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.