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 comprehensive implementation of the “Artificial Intelligence +” initiative, emphasizing the need to strengthen the integration of AI with cultural development. In this technology-driven era, culture is not merely an “application scenario” or a “subject of transformation” for AI; rather, it is an indispensable “enabler” in this technological revolution. While AI addresses efficiency and precision in fields like healthcare, industry, and logistics, it encounters meaning, emotion, and humanity in the cultural domain. This uniqueness determines that culture provides 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 to identify defects and optimize paths, with clear and quantifiable goals. However, in cultural creation, AI faces the production and transmission of meaning. When AI enters this realm, it must learn to handle the ambiguity of meaning, the diversity of interpretations, and the relativity of values. The nuances of a painting’s blank spaces, the essence of a poem, and the emotional tension of a film are all elements that cannot be easily quantified, yet they are essential for training AI to reach higher levels of intelligence. We refer to this as cultivating “meaning sensitivity”—enabling algorithms to not only understand “what it resembles” but also to attempt to grasp “what it signifies.” Furthermore, culture injects an indispensable emotional dimension into AI. Although AI cannot possess emotions, when it engages in cultural creation, it must learn to recognize emotional expressions, understand emotional logic, and generate emotional symbols. This process, while not a true emotional experience, 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 is rising, and 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 that culture provides to AI, then China’s vast cultural consumption market offers a “horizontal” testing ground for AI. From creation to dissemination, from education to cultural tourism, the cultural sector has built an extensive 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 the content production process, enabling ordinary creators to generate high-quality cultural products at a very low cost, 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” at the Palace Museum and the immersive digital exhibitions at 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. More importantly, the participatory nature 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 the field of cultural construction, such as structural imbalances at the industrial level, the “Matthew effect” in 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 has never been a one-way “technological determinism” but rather a complex bidirectional construction process. To truly enable culture to empower AI development, we need to work collaboratively across multiple dimensions, including institutional innovation, platform construction, human-machine relationships, cross-border integration, and talent cultivation. This is both a necessary response to real challenges and a strategic choice to seize 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 is essentially a misalignment between the copyright system of the industrial era and the creative methods of the digital age. To resolve this dilemma, we need to quickly establish copyright regulations that adapt to the characteristics of AI—clarifying copyright ownership of AI-generated content, standardizing 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 advancement 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 should respect the dignity of creation, and every institutional design should protect 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 bottlenecks that restrict cultural creation in the AI era. Starting from top-level design, we should establish a national-level cultural digital resource platform, break down departmental barriers, and reduce the search costs for creators, allowing dormant cultural resources to be transformed into actionable wisdom. Building a database of cultural genes that captures the patterns, traditional skills, and intangible cultural heritage of various ethnic groups will provide rich and standardized material support for artistic creation in the AI era and allow outstanding traditional Chinese culture to gain new forms of life in the digital age.

Redefining Human-Machine Relationships

Third, we need to redefine the relationship between humans and machines in the AI era. AI can provide options, but the power of choice always lies with humans; AI can generate content, but value judgments must be made by people. The ideal human-machine relationship should be a collaborative one: humans lead in creativity, value judgment, and emotional expression, while AI is responsible for technical realization, efficiency enhancement, and solution generation. We should embrace technology while firmly maintaining human subjectivity—this is both a principle of artistic creation and a wisdom for 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 infusing the logic of technology with the spirit of humanity.

Expanding Cultural Value through Cross-Border Integration

Fourth, we should expand the value of culture through cross-border integration. The vitality of culture lies in its flow and fusion. We should further deepen the integration of new popular arts with cultural tourism, cultural creativity, technology, and other fields, innovatively creating development models such as “micro-short dramas + cultural tourism,” “online literature + IP derivatives,” and “online games + traditional culture,” and cultivate new cultural economy formats such as digital cultural heritage, immersive performances, smart cultural tourism, and virtual cultural communities. By promoting the deep integration of culture, tourism, sports, and commerce, we can release cultural value in broader scenarios and make the synergy of “sports as a platform, culture as the performance, tourism as the draw, and consumption upgrade” a reality. This is not only necessary for the development of the cultural industry itself but also a rightful mission for culture to empower economic and social development.

Building a Foundation for Innovative Development through Talent Cultivation

Fifth, we must build a solid foundation for innovative development through talent cultivation. Cultural creation in the AI era calls for interdisciplinary talents—those who understand artistic creation and technical logic, who appreciate traditional culture and grasp 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 techniques, copyright protection, and overseas dissemination, with a focus on supporting young, grassroots, and amateur creators. Additionally, we should improve talent evaluation and incentive mechanisms, breaking down barriers related to identity and education, and enhancing pathways for talent growth to create a favorable industry ecosystem where “everyone can create, and everyone can produce excellent works.” This is the true essence of integrating AI with cultural development.