AI-generated summary
With the popularization of generative artificial intelligence technology, the literary and art world is facing profound changes in creative methods, copyright ownership and evaluation systems.
China News Service, Beijing, November 10 (Reporter Gao Kai) Focusing on literature and art in the era of artificial intelligence, the theoretical seminar "Literature and Art in the Dual-Based Era—A Discussion of Literature and Art in the Age of Artificial Intelligence" was recently held at Beijing October Academy of Literature.
More than 20 experts, scholars and creators from different fields such as literature, art, publishing and artificial intelligence gathered together to participate in this discussion on technological change and literary and artistic development.
Yang Xiaomin, a professor at Beijing Foreign Studies University, analyzed the impact of artificial intelligence on literary production methods based on the concept of "double-based era". He believes that artificial intelligence has lowered the threshold for writing, allowing more people who originally lacked professional writing skills to gain expression opportunities, and may also change the existing literary production structure. But at the same time, as the generation of general texts becomes easier and easier, the scarcity and evaluation standards of literary works will also face changes. In his view, human writing, artificial intelligence writing and human-machine collaborative writing may coexist, and over-reliance on artificial intelligence may also lead to the degradation of the writer's own abilities.
Liu Hao, executive director of the Institute of Contemporary Art and Social Thought at the School of Intermedia Art at the China Academy of Art, led the discussion to art and education. He believes that the powerful image generation capabilities of artificial intelligence prompt people to rethink the meaning of art. When the methods of knowledge acquisition and production change, spiritual production, the creation of a good life, and the establishment of individual meaning become more important. When talking about the relationship between people and artificial intelligence, he proposed that we can think from two directions: "on top of AI" and "outside AI": we should not only focus on how people continue to create new data and knowledge, but also retain the possibility of not being limited by existing options and technical paths.
Qin Lanjun, a researcher at the China Academy of Arts, used two models: "Living Cat Telephone" and "Prosthetic Dancer" to discuss subjectivity and fairness and justice in human-machine collaboration. She uses these two images to distinguish two relationships: one is that people are incorporated into machine systems and become a link in the information processing chain; the other is that technology serves as an extension of people and helps people expand their abilities. Combining interviews with human-machine collaboration and art design cases, she pointed out that the key is not just whether technology can adapt to individuals, but also how people use technology and whether they can maintain their subjectivity during the collaboration process.
Yang Qingxiang, professor of the School of Liberal Arts of Renmin University of China, took the topic of "AI and Origin Issues" and led the discussion to the existence and meaning of human beings. Combining the experience of live music, he talked about the irreplaceable life experience carried by the body, voice, hometown and intimate relationships. He believed that the more rapidly technology develops, the more people need to re-examine the source of meaning. He also took the way in which poems and seals were jointly created in traditional Chinese paintings as an example, pointing out that the open and diverse creative concepts in Chinese culture may provide new ideas for understanding authorship and originality in the AI era.
Ji Yaya, chief editor of "October" and "Beijing Literary Review", combined with the "October" AI collaborative writing essay competition, sorted out the changes that are taking place after AI entered the literary creation scene. She introduced that generative AI-assisted writing has already appeared on online literature platforms, and has led to a hundreds or thousands of times increase in the number of submissions. "October" will hold an AI collaborative writing essay contest on the WeChat public account platform in March 2025. The original intention is to promote "egalitarianism" in literature and allow ordinary people with more expression desires to participate in creation; the second is to observe whether the creativity of AI can bring about literary innovation; the third is to manage AI-participated works in separate tracks when the copyright ownership is in doubt, and display the source on the new media platform. Through the observation of 555 works and creative memos, the more important issues are: the existing standards of literariness are facing re-examination, and AI's outstanding ability in complex metaphors, writing "good sentences" and "literary accents" is prompting changes in the evaluation dimensions of traditional "good literature"; and related to this, what is even more dangerous is the resulting self-censorship of writing - authors avoid complex sentence patterns and poetic expressions to avoid suspicion, which may be more harmful to literature than AI itself. At the same time, the copyright ownership of human-machine collaborative writing is suspended. The current AI platform’s “distillation” of content, especially content that is still being created and has not yet been published, is itself an infringement. She also pointed out that from the perspective of reading, AI writing has become ubiquitous; this is a new "death of the author", and the focus of literary discussions may also change in the future, and the reading side may replace the author side as the core topic of literature.
This event was co-sponsored by "October" magazine and the editorial department of "Beijing Literary Review" and was conducted in a combination of online and offline methods.

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