Introduction

During this year’s National Two Sessions, “Artificial Intelligence + Culture” became a hot topic among representatives. The 14th Five-Year Plan clearly states the need to fully implement the “AI +” initiative, emphasizing the integration of AI with cultural development. In this technology-driven era, culture is not merely an application scenario or an object of transformation for AI; rather, it is an indispensable enabler in this technological revolution. While AI addresses hard issues of efficiency and precision in fields like healthcare, industry, and logistics, in the cultural domain, it grapples with meaning, emotion, and humanity. This uniqueness determines that culture can provide the most distinctive and irreplaceable value support for AI development.

Culture as a Training Ground for AI

Culture provides a training ground for AI in terms of meaning and emotion. The evolution of AI is essentially a process of moving from “computation” to “cognition” and then to “understanding.” In industrial contexts, AI’s tasks are clear and quantifiable, such as defect detection and path optimization. However, in cultural creation, AI must deal with the production and transmission of meaning. When AI enters this realm, it must learn to handle the ambiguity of meaning, the diversity of interpretation, and the relativity of value. Elements like the blank space in a painting, the ambiance of a poem, and the emotional tension of a film are difficult to quantify and are essential lessons for training AI towards higher intelligence forms. We refer to this as cultivating “meaning sensitivity”—enabling algorithms to understand not just “what it looks like” but also “what it means.” At the same time, culture injects an indispensable emotional dimension into AI. While AI cannot possess emotions, it must learn to recognize emotional expressions, understand emotional logic, and generate emotional symbols when participating in cultural creation. Although this process does not equate to genuine emotional experience, it allows AI to better serve human emotional needs. Particularly in the context of an aging society, the demand for emotional companionship and spiritual comfort among the elderly continues to rise. AI with emotional understanding will play an irreplaceable role in the silver economy.

Culture as a Laboratory for Public Participation

If the dimensions of meaning and emotion are the “vertical” nourishment of culture for AI, then China’s vast cultural consumption market provides a “horizontal” testing ground for AI. From creation to dissemination, education to cultural tourism, the cultural sector constructs a long value chain—creative conception, material generation, production, distribution, derivative development, and audience interaction—each link can embed AI capabilities and generate new demands for AI technology. On the creation side, AI is significantly changing content production processes, enabling ordinary creators to generate high-quality cultural products at very low costs, further expanding the boundaries of public creation. On the dissemination side, AI-driven precise recommendations allow cultural content to efficiently reach target audiences. In the cultural tourism sector, immersive experiences and digital twin technologies make cultural heritage perceivable and interactive. The dynamic presentation of the “Along the River During the Qingming Festival” by the Palace Museum and immersive digital exhibitions in various museums provide new possibilities for exploring traditional culture. This virtuous cycle of “demand driving supply and supply creating demand” vividly illustrates how culture empowers AI. Importantly, the public participation aspect of cultural scenarios allows AI technology to be tested, feedbacked, and iterated among the broadest population.

Challenges in Cultural Empowerment of AI

However, the process of culture empowering AI development is not without challenges. Some contradictions and issues in cultural construction, such as structural imbalances at the industry level, the “Matthew effect” of resource allocation, copyright dilemmas, and challenges to subjectivity, prompt us to re-examine the direction and governance logic of AI development. History also tells us that the relationship between culture and technology is never a one-way “technological determinism” but rather a complex bidirectional construction process. To truly empower AI development with culture, we need to collaborate across multiple dimensions, including institutional innovation, platform construction, human-machine relationships, cross-border integration, and talent cultivation. This is not only a necessary response to current dilemmas but also a strategic choice to seize the opportunities of the times.

Institutional Innovation to Protect Originality

First, we must safeguard the dignity of originality through institutional innovation. The copyright dilemma in the AI era essentially stems from the misalignment between the copyright system of the industrial era and the creative methods of the digital age. To resolve this dilemma, we need to establish copyright norms that adapt to the characteristics of AI as soon as possible—clarifying copyright ownership of AI-generated content, regulating the authorized use of training data, and establishing a labeling mechanism for AI-created works. More fundamentally, we must establish a basic principle at the institutional level: technological progress should not come at the expense of creators’ legitimate rights and interests, and the “learning” of algorithms should not devolve into the uncompensated appropriation of originality. Every technological breakthrough must respect the dignity of creation, and every institutional design must safeguard the value of originality—this is the institutional cornerstone for cultural prosperity in the AI era.

Activating Cultural Data Value through Platform Construction

Second, we should activate the value of cultural data through platform construction. The decentralization, departmentalization, and isolation of cultural data are among the bottlenecks restricting cultural creation in the AI era. Starting from top-level design, we need to establish a national-level cultural digital resource platform to break down departmental barriers, reduce creators’ search costs, and truly transform dormant cultural resources into actionable wisdom. Building a database of distinctive cultural genes and creating digital archives for ethnic patterns, traditional crafts, and intangible cultural heritage will provide rich and standardized material support for artistic creation in the AI era, allowing excellent traditional Chinese culture to gain new life forms in the digital age.

Redefining Human-Machine Relationships

Third, we must redefine the relationship between humans and machines. In the AI era, the relationship between humans and tools needs redefinition. AI can provide options, but the choice always lies with humans; AI can generate content, but value judgment must be completed by humans. The ideal human-machine relationship should be a collaborative one: humans are responsible for creative leadership, value judgment, and emotional expression, while AI handles technical realization, efficiency enhancement, and solution generation. We should embrace technology while also maintaining the subjectivity of humanity—this is both a principle of artistic creation and the wisdom of human-technology interaction in the AI era. On a deeper level, we have a responsibility to explore the ethical boundaries of human-machine collaboration, challenging the aesthetic homogenization that algorithms may bring, and injecting the spirit of humanity into the logic of technology.

Expanding Cultural Value through Cross-Border Integration

Fourth, we should expand cultural value through cross-border integration. The vitality of culture lies in its flow and fusion. We should further deepen the integration of new mass art with cultural tourism, cultural creation, technology, and other fields, innovating development models such as “micro-short dramas + cultural tourism,” “online literature + IP derivatives,” and “online games + traditional culture.” This will cultivate new cultural economy formats like digital cultural heritage, immersive performances, smart cultural tourism, and virtual cultural communities. Promoting the deep integration of culture, tourism, sports, and commerce will allow culture to release value in broader scenarios, making the combination of “sports as a platform, culture as the performance, tourism as the draw, and consumption upgrading” a reality. This is not only necessary for the development of the cultural industry itself but also an essential aspect of culture empowering economic and social development.

Talent Cultivation as the Foundation for Innovative Development

Fifth, we must build a solid foundation for innovative development through talent cultivation. Cultural creation in the AI era calls for versatile talents—those who understand artistic creation and technical logic, traditional culture and the aesthetics of the digital age. We should establish diversified and specialized talent cultivation platforms, linking universities, industry associations, and leading institutions to conduct specialized training in creative skills, copyright protection, and overseas dissemination, with a focus on supporting young, grassroots, and amateur creators. At the same time, we need to improve talent evaluation and incentive mechanisms, breaking down identity and educational barriers, and creating a growth pathway for talents, fostering a positive industry ecology where “everyone can create, and everyone can produce excellence.” This is the true essence of the integration of AI and cultural construction.