The Symbiotic Relationship Between AI and Humanities

Generative AI 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 deeply interwoven. AI is reshaping 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 of AI.

Bridging Disciplines for Humanities Scholars

As modern disciplines become more specialized, the humanities face barriers not only with the natural sciences but also with the 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, leading to a limitation of “one-sided depth” in contemporary humanities. The emergence of AI can provide new solutions to this issue.

Large language models are built through deep learning on vast amounts of text, creating a distributed representation system of language and knowledge, highly concentrated with human written knowledge. They utilize neural network architectures and algorithm-driven probabilistic predictions, achieving context awareness through deep learning. Guided by specific prompts, they perform human-like logical reasoning and knowledge output. In this sense, AI can serve as a powerful ally for humanities scholars, bridging them to multiple disciplines and empowering the production of humanistic knowledge through information search, literature screening, semantic analysis, and interdisciplinary integration.

Currently, influential “distant reading” methods utilize AI models to establish interdisciplinary literary criticism and research models based on the overall framework of world literature. Unlike traditional literary research advocating close reading of a few classics, this approach employs data mining and quantitative analysis of large-scale text collections to systematically reveal themes, emotional tendencies, plot structures, and rhetorical features, 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 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 humanistic scholarship, but the formal establishment of the “humanities” occurred 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 in an attempt to construct an epistemology and methodology for the humanities.

Overall, this logic, criticized by later generations as a “spirit-nature 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 that are difficult to quantify. It encompasses deep individual psychology, instincts, consciousness, and the unconscious, carrying historical cultural memories and collective unconscious, embodying intrinsic qualities of value, culture, individuality, spirituality, emotion, thought, and symbolism. Methodologically, the humanities focus on internalized approaches such as empathetic understanding, reflective experience, and intuitive insight, aiming to reveal unique individual experiences, complex mental worlds, and deep cultural significance structures that cannot be replicated, quantified, or verified by natural sciences.

As disciplines evolve, this binary oppositional thinking pattern is continuously reflected upon. Marx stated, “Natural sciences will include the sciences of man, just as the sciences of man will include natural sciences: 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 beneficial attempts at quantitative humanities research 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, 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 form often manifests as narrative or speculative texts, expressing researchers’ unique insights and profound thoughts on human existence, values, and meanings through language and writing. This differs from natural sciences, which utilize formulaic deductions, data charts, and repeatable experimental validations, and from social sciences, which largely employ 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”—it is 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 have pointed out that writing style itself carries the researcher’s unique emotional tone, academic judgment, and value stance. In this sense, humanistic writing is a core aspect of academic research; it is not only a mode of knowledge production but also a reflection of thinking patterns and disciplinary characteristics, serving as a fundamental medium for maintaining the existence of the discipline and promoting academic exchange, and is a vital source of the discipline’s vitality. Whether in expressing philosophical thoughts and probing ultimate meanings, describing historical contexts and narrating events, or constructing values and poetic insights in literary criticism and research, the organization and structural integration of materials, logical reasoning, and argumentation, as well as the deepening of thoughts and the condensation of spiritual experiences, all occur within the creative writing process.

Currently, AI models can transfer the language structures, argumentative patterns, and disciplinary terminologies learned from vast corpora to specific fields of humanistic knowledge production, promoting human-AI collaboration and achieving an overall 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 literature prior to writing. Furthermore, 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, uncovering deep thoughts and internal logical structures from complex texts, thereby revealing developmental laws of phenomena, refining core concepts, and ultimately nurturing new knowledge outcomes. This process is not merely an 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 enhance and optimize professional academic expressions, correcting, adjusting, and improving the knowledge-based, normative, logical, and systematic aspects of humanistic academic expressions, even forcing subpar 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, enhancing its value.

The involvement of AI is not a simple process of machine-assisted writing; rather, it is a process of deepening thought, inspiring creativity, and optimizing expression through human-AI interaction and iterative dialogue. This process places high 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. Moreover, as some studies have pointed out, AI excels in 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 intuitive judgments about subtle connections found within vast information, strategic choices made based on value stances, and unique expressions arising from aesthetic tastes are all of significant importance. Without human validation, modification, and deepening, the content generated by AI will carry a strong “machine flavor,” presenting as uniform and homogenized expressions.

To ensure the independent thinking character, unique insights, and distinctive academic style of scholarly research, the personal characteristics of human 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 will lose the dynamism inherent in humanistic research. Humanistic research must always be able to see 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 feel the emotional investment and value care of researchers, achieving both depth of thought and warmth of emotion.

Understanding Humanity Through AI Development

As a mirror of human intelligence, AI 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 distinguish 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, master skills, and apply them to achieve goals.

Currently, AI still belongs to the realm of imitating human intelligence, performing like humans, with its developmental goal being to 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 coincidental; it is a product of human creativity and self-awareness reaching a certain stage. Although current vertical models focused on specific tasks have demonstrated superior execution efficiency and accuracy in certain tasks and fields, they remain fundamentally 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 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 understanding agent. 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-evaluation and reflection on itself as a complex intelligent entity, making a groundbreaking effort to explore the deep essence of humanity and understand “what makes us human” by comparing with non-human intelligent agents.

Whether in natural sciences or humanities and social sciences, there exists an alternating and repetitive process of “disenchantment” and “enchantment” regarding humanity, with the core of “enchantment” being the mystery of humanity itself. Without a profound understanding of human intellect, a “general model” cannot genuinely emerge. As Marx stated, “The dissection of the human body is a key to the dissection of the monkey body.” The signs of higher animals revealed 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, AI still possesses many “explainability issues,” largely due to humanity’s insufficient understanding of its own intellect. Breakthroughs in AI creation, technology 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, 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. Instead, they 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 humanity and its understanding of the world, thereby exerting a significant influence on generative AI. At the same time, the impact of new technologies like AI on society and humanity itself also constitutes 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 can be confident that humanistic thought can illuminate the future path of AI.