2024-01-19 01:32:00
original title:
Artificial Intelligence: Dilemmas and Challenges to Art
The German conceptual artist Joseph Beuys said that “everyone is an artist”, which means that the thinking activities of ordinary people also include creative thinking similar to that of artists or designers. However, there are technical thresholds for turning such creative thinking into art. However, with the emergence of artificial intelligence (AI) painting tools, the technical gap between creative thinking and artistic presentation is increasingly being bridged – on AI painting tools, as long as we input the prompt words we set, the corresponding text will be generated. image. “Everyone is an artist” seems to be becoming a reality.
The high productivity of AI painting tools has had a great impact on artistic creation, and can even be said to have brought a dilemma to art.
In the history of Eastern and Western art, there are some creative concepts similar to “retrofitting as innovation”. For example, in the European art tradition, the Renaissance, Baroque and Neoclassicism, which emphasize learning from the classical art of Greece and Rome, all base their art on learning and borrowing from classical paradigms. In China, since the Song and Yuan Dynasties, the trend of “worshipping the ancients” and “respecting the ancients” has become increasingly popular in the art world. In the Yuan Dynasty, Zhao Mengfu advocated “following the ancient” when discussing calligraphy and opposed copying the methods of modern people. When discussing painting, he said that “painting should have ancient meanings.” His calligraphy and painting practice can also be traced back to the Jin and Tang Dynasties, borrowing from the past to create the present. There is also a kind of appropriation art (Appropriation Art), which borrows existing styles or patterns and structurally grafts them together to splice history and the present to create new images and images.
This type of artistic creation that emphasizes learning from the ancients or using historical styles as a resource library has seen unprecedented improvements in its creation efficiency after the emergence of AI painting tools. As long as you have an idea and are guided by appropriate prompt words, whether realistic or abstract, AI painting tools can enable instant mass production of various styles. Therefore, for artistic creation, the birth of AI painting tools is like opening a Pandora’s Box of creativity – the creator himself no longer has to master a certain artistic technique in order to obtain a certain style.
Based on this, I believe that with the continuous development of AI painting tools, the identity of artists and art education will face tremendous changes and challenges.
From the perspective of art history, although the definition of art has been changing, it generally still revolves around two basic levels: at the spiritual level, art is an intellectual creation and the externalization of human reason and emotion. , which is Hegel’s so-called “beauty is the perceptual manifestation of ideas”; on the material level, art is the product of human labor, involving the use of media, materials, craftsmanship and other aspects. For thousands of years, the imagination and creation of art at the spiritual level have been completed by the human brain, while at the material level it mainly relies on the coordination of hands and brain. After the advent of the era of mechanized mass production, machines have completed a large number of processes that cannot be completed by human hands, making up for the lack of human capabilities. Later, with the development of computer technology, computer-aided design (CAD) and computer-aided manufacturing (CAM) greatly changed the way artists and designers work. The widespread use of drawing software also influenced the image language of appropriation art and postmodernity. It played a great boosting role. However, these technological advances are at best a revolution in the instrumental sense, an innovation on the material level.
Let’s look at two more representative theories of art creation mechanisms. British art historian Ernst Gombrich used the “making and matching” theory to explain the mechanism of art creation. He believes that artists must first master the patterns left by their predecessors before creating, and then observe nature, try various color traces or line combinations on the canvas, and slowly correct the patterns through trial and error, in order to achieve a pattern that matches nature. To a certain extent, this process is called “schematization and revision.” American architectural theorist Christopher Alexander created the pattern language system. In his famous book “Architectural Pattern Language”, he described a total of 253 patterns such as towns, neighbourhoods, houses, gardens and rooms. In his view, the process of using pattern languages to produce architecture is not a simple addition of parts, but a process of continuous differentiation, deduction and aggregation. New designs and plans can continue to come up with new designs based on these pattern languages. . In fact, the emergence of AI painting tools is equivalent to reducing the theory of artistic creation based on existing schemas, styles and pattern languages into an evolution problem of technical models.
In the traditional training and creation system, in order to achieve a given artistic effect, artists must devote themselves to the training and perfection of skills. However, AI has made it possible to achieve many artistic effects without skill training. “Artistic creation” based on acquired experience, for artificial intelligence, is a problem of data, calculation and generation. In this case, artistic creation has returned to a certain extent to the classic proposition of the Italian esthetician Croce, “Art is intuition, intuition is expression,” and the bridge between intuition and expression is artificial intelligence. After AI becomes a creative tool, creative activities no longer require a lot of brain power, physical strength and time, and artistic creation becomes simple and feasible. After “everyone is an artist”, who was the artist in the past? What should the artist’s art be?
Today, with the development of generative artificial intelligence, computers have truly begun to extend to human imagination, aesthetics, and emotion, and can play a role in a wide range of artistic creation fields such as music, art, design, and movies. In the past, it could only be exerted by humans. role. Generative artificial intelligence is not only a technological advancement in a tool sense, but its large language model is constantly penetrating into the center of artistic imagination and creativity. If we recognize the subjective value of artists for artistic creation, then in the era of artificial intelligence, The subject of art creation will change from “human” to “a combination of human and highly intelligent personification”. So who is the artist who creates art?
This “submerging dissolution” brought about by artificial intelligence may be the biggest crisis facing art today.
At the level of art education, in the face of artificial intelligence, what and how to teach art schools will also face huge challenges.
Artificial intelligence has become a powerful tool for artistic creation. However, this bundling of the human brain and artificial intelligence can easily cause the human brain to “hitchhike”, leading to the degradation of brain creativity. How to set up the teaching of art so that the iron triangle of human creativity – eyes, hands and brain can be more coordinated rather than degraded will be a practical problem that art education must face.
Compared with universities, art vocational education encounters more obvious challenges in this regard. In the past, art vocational education paid more attention to the cultivation of technical abilities. With the development of artificial intelligence, vocational skills such as illustration, modeling, and design software operation taught in art vocational education can be completed more using artificial intelligence. The methods, methods and future of future vocational education must be rethought. In the past, vocational education that emphasized application abilities may have met the requirements of mechanized mass production, but it may not have met the requirements of the intelligent era. When people can use artificial intelligence tools to teach certain repetitive skills and techniques, it may have Far behind.
Currently, we are in an era of rapid development of artificial intelligence, and it is difficult to predict the future social development trend. Faced with the difficulties and challenges that artificial intelligence brings to artistic creation, I think three points may be the solution:
Regarding how to recognize art, I believe that artistic creation is a process from quantitative change to qualitative change. Artificial intelligence can greatly improve the efficiency of quantitative change, and the problem that humans have to solve is qualitative change, which is truly creative labor.
In terms of how to create art, I feel it’s important to build a bridge between words and images. Artists must be able to skillfully grasp the relationship between language and the style and taste of artistic works, and be able to train artificial intelligence and select good and suitable works.
For art education, the advantage of generative artificial intelligence in art is to “reveal what others have already developed” rather than “reveal what others have not developed”. Most of our previous education models were guided by famous masters and artistic models in history. Many of the proud artistic creations produced under this model are actually combinations and variations of many models. The development of artificial intelligence technology is making this academic creation mode increasingly common and cheap. In the future, art education must not be a simple inheritance of craftsmanship, nor a one-dimensional professional training, but the cultivation of talents with the ability to connect multiple knowledge, resources and possibilities.
Artificial intelligence does make me a little worried. Is it so smart that it can surpass humans? Will it replace humans in artistic creation? Can humans control artificial intelligence? These are the challenges and dilemmas that artificial intelligence brings to us.
(Author: Zhou Bo, professor at the Central Academy of Fine Arts)
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