The Mutual Empowerment of AI and Humanities

Generative AI is profoundly changing various fields such as education, employment, entertainment, healthcare, transportation, and elder care, becoming a hot topic. The relationship between the humanities and generative AI is complex and symbiotic. AI reshapes 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 social acceptance achievable by AI.

Bridging Humanities Scholars to Multidisciplinary Fields

As modern disciplines become increasingly specialized, the humanities face barriers not only with natural sciences but also with 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 issue.

Large language models, constructed through deep learning on vast amounts of text, represent a highly condensed form of human written knowledge. They utilize neural network architectures and algorithm-driven probabilistic predictions to achieve context awareness and perform human-like logical reasoning under specific prompts. In this context, AI can serve as a powerful assistant for humanities scholars, providing a bridge to multidisciplinary fields 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 readings of a few classics, distant reading employs data mining and quantitative analysis on large text collections to reveal themes, emotional tendencies, plot structures, and linguistic features, thereby macro-describing the development of human literature. This effectively addresses the technical challenges of processing vast amounts of text and cross-cultural knowledge that traditional literary history and world literature research cannot resolve.

Updating Methods and Paradigms in 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 individualized methods linked to values and attempting to construct epistemology and methodology for the humanities.

In general, within this logic, criticized later as the “spirit-nature dualism,” the humanities emphasize “thought of existence,” studying objects that exist in symbolic forms such as language, text, images, and rituals, involving faith, conscience, emotion, aesthetics, values, and ideals—elements that are difficult to quantify. This includes deep individual psychology, instincts, consciousness, and the collective unconscious, embodying intrinsic characteristics such as value, culture, individuality, spirituality, emotion, thought, and symbolism. Methodologically, the humanities focus on empathetic understanding, reflective experience, and intuitive insight, aiming to reveal unique individual experiences, complex spiritual worlds, and deep cultural meanings that cannot be captured by replicable, quantifiable, and verifiable techniques of natural sciences.

As disciplines develop, this binary oppositional thinking model is continuously reflected upon. Marx once 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 humanities research. Various literary labs and quantitative humanities research initiatives are continuously emerging. AI has evolved 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 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 thoughts on human existence, values, and meanings through written language. This differs from natural sciences, which use formulaic deductions, data charts, and repeatable experiments for validation, and from social sciences, which heavily rely on surveys and statistical models. Humanistic writing not only expresses thoughts and emotions but also integrates creativity, criticality, and reflexivity into a comprehensive cognitive movement. “Writing is thinking”—it is a process of generating and deepening thoughts and feelings. Writing can stimulate creative vitality, enhance self-reflection, and expand expressive boundaries, where linguistic sensitivity, cognitive penetration, and cultural insight are intertwined. Scholars have pointed out that writing style itself carries researchers’ unique emotional tones, academic judgments, and value positions. In this sense, humanistic writing is a core aspect of academic research; it is not only a means of knowledge production in the humanities but also reflects its modes of thinking and disciplinary characteristics, serving as a fundamental medium for maintaining academic existence and promoting scholarly exchange, as well as a vital source of disciplinary vitality. Whether expressing philosophical thoughts and ultimate meanings, describing historical contexts and events, or constructing values and poetic insights in literary criticism and research, the processes of material organization, structural integration, logical reasoning, and argumentation, as well as deepening thoughts and refining spiritual experiences, are all accomplished through creative writing.

Current AI models can transfer the language structures, argumentation patterns, and disciplinary terminologies learned from vast corpora into specific humanistic fields of knowledge production, 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, efficiently collecting, systematically organizing, and deeply analyzing large amounts of literature before writing. During the writing process, through human-AI collaboration and dialogue, they can organically integrate dispersed knowledge, building new knowledge graphs and cognitive frameworks that help researchers break through existing theoretical and cognitive limitations, uncover 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 an accumulation of knowledge but an innovative mechanism capable of generating specific theoretical results, opening up new pathways for academic research and knowledge innovation. On the other hand, AI can provide local refinement and overall optimization of professional academic expressions. This can correct, adjust, and enhance the quality of humanistic academic expressions in terms of knowledge, normativity, logic, and systematics, even forcing low-quality academic research to exit relevant fields. Sometimes, certain 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; rather, it is a process of deepening thought, stimulating inspiration, and optimizing expression through human-AI interaction and dialogue. This process places high demands on researchers’ AI literacy, particularly in terms of correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These capabilities 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 at 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 in discovering subtle connections among vast information, strategic choices based on value positions, and unique expressions arising from aesthetic tastes are all of significant importance. Without human verification, modification, and deepening, content generated by AI will carry a strong “machine flavor,” presenting as uniform and homogenized expressions.

To ensure the academic independence of thought, unique insights, and distinctive academic style, the personal characteristics of humanities researchers—such as talent, courage, insight, and ability—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. Humanities research must always reflect “the human” and integrate personal life experiences into academic exploration, responding to the challenges of the times 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, encompassing both depth of thought and warmth of emotion.

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

As a mirror of human intelligence, AI can help humans understand the essence of “what it means to be human” more profoundly. At the same time, human understanding of itself becomes the fundamental basis for the future development and governance of AI technology. Marx pointed out, “Conscious life activity distinguishes humans from animal life activities directly.” Thus, human strength lies in its possession of intellect, practical creativity, and the ability to continuously acquire knowledge and skills through learning to achieve goals.

Currently, AI still belongs to the imitation of human intelligence, performing like humans. Its development goal should gradually align with the internal cognitive 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 have demonstrated superior execution efficiency and accuracy in specific tasks and fields, they essentially remain tools for 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 questions, 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. Questions regarding the generative mechanisms and operational modes of human intellect become particularly important in this context. Human reflection on AI is also a re-examination of the complex intelligent entity that is humanity itself, further 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 entities.

Whether in natural sciences or humanities and social sciences, there is an ongoing alternation and repetition between the “demystification” and “enchantment” of humans, 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, just as Marx stated, “The dissection of the human body is a key to the dissection of the monkey body.” The signs of higher animals manifested in lower animals can only be understood after the 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 “explainability issues” of AI largely stem from humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, technology governance, and value alignment require a prior 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, as they possess reflexivity. Every emergence and change of humanistic cognition and understanding intervenes in the development of social life and the construction of human hearts, embodying the quality of “establishing heart for heaven and earth, and establishing destiny 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 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 humanities scholarship alters humans and their understanding of the world, thereby exerting a significant influence on generative AI. At the same time, the impacts of new technologies like AI on society and humanity also constitute a focus of humanistic scholarship, with related reflections becoming 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 truly understand and effectively control its creations. In this sense, we are fully confident that humanistic thought can illuminate the future path of AI.