The Impact of Generative AI on Artistic Creation

As artificial intelligence deeply integrates into various aspects of society and industry, it brings about a new wave of transformation. The involvement of generative AI in artistic creation not only injects vitality into the field but also raises a series of questions: Can it replace artists? Will it shake the value concepts of art? Or is it rewriting the entire logic of subjectivity established for art? We must confront and actively examine these issues within the contexts of art history, technology history, and the construction of subjectivity, rather than simplifying them to mere efficiency gains from technological advancements or reducing them to an optimistic notion that “everyone is an artist.”

Human-machine collaboration primarily challenges the originality of art. With the rapid development of large language models and multimodal models, natural language interaction has gradually become the basic method for human-machine collaborative creation. Throughout this process, the production of text, music, images, and videos has been significantly affected, though the impact is not uniform. In fact, generative AI plays different roles across various art forms, with varying degrees of involvement. Notably, art forms that utilize digital media are undergoing systematic reshaping. For instance, in the field of video creation, independent creators can leverage generative AI to directly complete scripts, storyboards, visuals, soundtracks, and post-production styles through prompts, greatly compressing or even eliminating the previously collaborative and hands-on aspects of creation.

In the visual arts, if we still understand it as a form of modeling art associated with a specific medium and manual creation, the involvement of generative AI will change the creative process. In traditional artistic creation, artists use tools like brushes and chisels, relying on their mastery of modeling techniques to transform their creative ideas into tangible works. However, with generative AI’s involvement in visual art creation, it first intervenes in the front-end processes of visual imagination and plan generation, rather than directly eliminating drawing, sculpting, and production. Creators still need to possess material, technique, and formal control abilities to filter, edit, and deepen the image resources provided by the machine, thus transforming them into artworks. This tangible participation by the creator highlights their ideological intent, which reflects the originality of the work. If the creator reduces or omits specific hands-on operations, the creation is no longer considered part of visual art.

Thus, the impact of generative AI on visual art creation is not simply about replacing artists; it reorganizes the weight of various stages within the creative process. Certain preliminary cognitive activities, once viewed as key creative stages, are partially outsourced to algorithmic systems; meanwhile, skills that merely test execution, selection, and reproduction are becoming important again in many specific creative practices. This means that understanding the relationship between AI and visual art should start from this structural change, rather than superficial judgments about whether it replaces artists.

Redefining the position of the subject is a value reference brought by generative AI. Similar to the emergence of photography, generative AI also presents creators with a new visual generation mechanism and forces a reconsideration of which abilities can be taken over by technology and which need to be redefined and maintained by creators themselves. Generative AI touches upon compositional, combinatorial, style simulation, and even artistic concept activities that are closer to human “cognitive activities.” These activities, originally seen as manifestations of creative subjectivity, are now shared or even replaced by technology. Generative AI is transitioning from a mere auxiliary tool to a “quasi-subject” participating in cultural production, which is particularly sensitive in the current context of artistic creation. Once it becomes difficult to determine how much of a creative idea, composition, or concept comes from the author, the stability of originality as the core of artistic value begins to waver. The question then shifts from whether generative AI can create art to what criteria should define art in the context of substantial generative AI involvement.

Returning to the discussion of new popular literature and art, the involvement of generative AI in visual art creation also serves as a breakthrough for dismantling professional monopolies, redistributing cultural power, and integrating creative structures. Utilizing generative AI for creation can directly bypass certain traditional training paths while also imposing new skill requirements on creators, such as prompt organization, model understanding, image selection, style judgment, and cross-media integration. This indicates that generative AI does not dissolve professionalism but reshapes its content and form.

The involvement of generative AI directly impacts the monopolistic structures in visual art creation: first, it weakens the traditional technical monopoly over creative entry, allowing those without formal artistic training to enter visual production; second, as the boundaries of originality expand, visual art creation is no longer an internal affair of a few professional groups but becomes a cultural practice that broader social subjects can participate in. In this process, the relationships between creation, dissemination, and evaluation are also changing: the public is not only viewers and consumers but also creators, disseminators, and evaluators. However, the control over platforms, algorithms, and models remains in the hands of a few technical entities, who reshape creators’ tastes and choices through model preferences and data training, causing new popular practices to fall back under the discipline of technical power. In this context, while creative rights may partially descend, the descent of evaluative rights remains unresolved. Only with the reorganization of creative rights, dissemination rights, and evaluative rights can the new wave of popular visual art brought by generative AI drive a more structurally significant cultural shift.

Essentially, generative AI is a highly complex, stylized reorganization and interpretation based on existing data. Its underlying logic is “learning” and “optimization,” rather than “subversion” and “revolution.” Currently, generative AI lacks the fundamental creative source of artists—the embodied individual emotional experience. Artistic creation, especially great works, is deeply rooted in the unique life insights and profound spiritual realms of the artist. Therefore, in the face of generative AI, it should be seen as a co-creation tool that stimulates creativity, expands imagination, and enriches expression, rather than allowing it to completely take over the creation process.

In conclusion, in the era of artificial intelligence, the nature of art is undergoing unprecedented renewal and reconstruction. The deep driving force behind this transformation is a dual impetus of technological revolution and cultural consciousness, inspiring us to engage in multifaceted reflections. A correct understanding of the relationship between AI and visual art, and clarifying the intrinsic value of art, will help achieve better human-machine co-creation and unlock more new artistic possibilities.