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 of AI.

Bridging the Gap for Humanities Scholars

As modern disciplines become increasingly specialized, the humanities face barriers not only with natural sciences but also with 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” in contemporary humanities. The emergence of AI can provide new solutions to this issue.

Large language models, built 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, achieving context awareness through deep learning and performing human-like logical reasoning under specific prompts. In this sense, AI can serve as a powerful assistant for humanities scholars, bridging them to multidisciplinary research and empowering the production of humanistic knowledge through information search, literature screening, semantic analysis, and cross-domain integration.

Currently influential “distant reading” methods, based on the overall framework of world literature, utilize AI models to establish interdisciplinary literary criticism and research models. Unlike traditional literary studies that advocate close reading of a few classics, distant reading involves data mining and quantitative analysis of large-scale text collections, systematically revealing characteristics such as thematic distribution, emotional tendencies, plot structures, and linguistic rhetoric, thereby describing 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 analysis in traditional literary history and world literature research cannot resolve.

Updating Methods and Paradigms in the Humanities

China has a long and rich tradition of humanistic scholarship, but the term “humanities” emerged in the 20th century. During the Enlightenment in the West, humanists 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 to construct epistemology and methodology for the humanities.

Overall, this logic, criticized by later generations as the “spirit-nature dichotomy,” emphasizes “thoughts of existence,” with research objects existing in symbolic forms such as language, text, images, and rituals, involving faith, conscience, emotions, aesthetics, values, and ideals—elements that are difficult to quantify. This encompasses deep individual psychology, instincts, consciousness and unconsciousness, as well as historical and cultural memories, embodying intrinsic characteristics such as value, culture, individuality, spirituality, emotion, thought, and symbolism. Methodologically, the humanities focus on internalized ways of understanding through empathy, 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 continue to develop, this binary oppositional thinking model is being constantly reexamined. Marx 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 investigates 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 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.

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 the spiritual and cultural cores of human existence, values, and meanings through written language. This differs from natural sciences, which rely on formulaic deductions, data charts, and reproducible experimental validations, and from social sciences, which heavily use 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 reflexivity—“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 merge.

Scholars point out that writing styles themselves carry researchers’ unique emotional tones, academic judgments, and value positions 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 a reflection of its thinking methods and disciplinary characteristics. It serves as a fundamental carrier of academic exchange and the vitality of the discipline. 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, viewpoint argumentation, and the refinement of thoughts and spiritual experiences all occur within the creative writing process.

Currently, AI models can transfer the language structures, argumentative patterns, and disciplinary terminology learned from large-scale corpora into specific humanistic knowledge production, promoting human-AI collaboration and achieving a holistic leap in humanistic writing. On one hand, in humanities academic writing, researchers can fully utilize AI’s powerful data processing capabilities to efficiently collect, systematically organize, and deeply analyze vast amounts of literature before writing. Moreover, during the writing process, through human-AI collaboration and dialogue, they can organically integrate dispersed knowledge, building new knowledge maps and cognitive frameworks that help 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 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 perform localized polishing and overall optimization of professional academic expressions. This can correct, adjust, and enhance the quality of humanistic academic expressions in terms of informativeness, normativity, logicality, and systematization, potentially forcing low-quality academic research out of relevant fields. Sometimes, certain academic debates within the humanities suffer from insufficient materials, unclear concepts, and weak logic; AI assistance can significantly improve the quality of academic discussions and enhance their value.

The involvement of AI is not a simple process of machine-assisted writing but rather a continual deepening of thought, inspiration, and expression optimization through human-AI interaction and back-and-forth dialogue. This process demands a high level of AI literacy from researchers in terms of correctly inputting commands, providing high-level prompts, and deeply interpreting output results. These skills 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 in 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 intuitive judgments about subtle connections between things found in vast amounts of information, strategic choices made based on value positions, and unique expressions arising from aesthetic tastes are all of significant importance. Without human verification, modification, and deepening, AI-generated content can carry a strong “machine flavor,” presenting as bland and homogenized expressions.

To ensure the academic independence of thought, 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. It is crucial to prevent dependency thinking and intellectual inertia; otherwise, research outcomes may lose the dynamism inherent in humanistic inquiry. Humanistic 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, achieving both depth of thought and warmth of feeling.

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

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, “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.

Currently, AI still belongs to the imitation of human intelligence, exhibiting behavior like humans. Its developmental goal should be to 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 currently specialized vertical models have shown execution efficiency and precision surpassing humans in specific tasks and fields, they are fundamentally still tools of humanity. 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 when common sense reasoning is required. 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 contemplation of AI is also a re-examination and reflection 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 and repetition of “demystification” 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, 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 displayed on lower animals can only be understood after recognizing the higher animals themselves. Understanding humans and comprehending humanity is the fundamental nature and basic value goal of the humanities. Today, AI still possesses many “explainability issues,” largely because humanity’s understanding of its own intellect is still insufficient. Breakthroughs in AI creation, technological governance, and value alignment require a premise of humanity’s understanding of its own 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, 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 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 humanity’s understanding of the world, which in turn has a significant impact on generative AI. Simultaneously, the effects of new technologies like AI on society and humanity also constitute 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 essential to remember that AI is created by humanity, and humans should possess the ability to truly understand and effectively harness their creations. In this sense, we can be fully confident that humanistic thought can illuminate the future path of AI.