With the advent of modernism, trends in art have shifted toward a greater autonomy in the definition, and practice of art. Art is no longer bounded by the constraints of traditional conceptions of beauty, and more importantly, of its primary function of representation. The result of such trends is, unfortunately, the widening distance between the culture of the art connoisseurs, and that of the larger public. Especially in today's highly modernized, and capitalist society, where fast gratification is widely available with the advanced technologies, art is often perceived as something esoteric, or something irrelevant to one's daily life. At this confusing time in the history of art, there seems to be no right answer to how art or the experience of art should be defined.
One may suggest that aesthetic experience in response to works of art should be defined as an experience qualitatively different from everyday experience. It is apparent that works of art can allow people the feelings of admiration, fascination, and awe, which are certainly distinguishable from everyday emotions; however, the value of art would truly manifest only when it is enjoyed as a part of our daily lives. Among its countless functions, one of the irremovable functions of art is to be consumed, and to be enjoyed, as if it is nearly impossible to ponder the meaning of art without considering the presence of its audience or appreciator.
But still there remain some big questions, such as about what to appreciate, or what to qualify as a work of art. Despite the social notion on the judgment of taste, which has been reinforced by the gap between the two cultures, of the art experts and of the public at large, there is no innate hierarchical measure in judgments of taste, or of art itself. The efforts, however, have been made in determining the value of works of art, either for matters of convenience or sometimes for one's benefit. With the rise of the art market, the works of art are typically being evaluated according to the two separate terms: an aesthetic, and a commercial value. Although setting the price for artwork, the product of human gift, might be considered as an attempt to degrade human creativity, the commercial value is now an inseparable part of the artwork as a whole, indirectly representing people's demand in art.
Nowadays, the works of art that are preferred by the larger public appear to be the works that can offer unquestionable beauty without invoking any complex philosophical questions. Such artworks are produced with clear objectives to fulfill human desire for beauty, functioning as an instrument to offer visual satisfaction. Among those works, some observable similarities can be found as listed below.
- There are (preferably) no discernible figures or shapes;
- The mood or atmosphere of an artwork provides positive (or at least neural) connotations;
- Any negative reactions (e.g. fear, contempt, disgust, and etc.) should not be evoked to the viewers
If what has been presented exceeds the underlying aesthetic or philosophical intention in terms of significance, the mere appearance of an artwork then becomes the primary reason for its existence. In the production of such kind of works, the presence of the creators or artists loses its importance. And the potential of artificial intelligence as an art-maker begins to reveal at this very point.
THE PROJECT
The project had been proceeded with the aims to shed light on the true value of art, and to challenge the traditional conceptions of art. The code used in the project are heavily borrowed from ArtGAN (https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN). ArtGAN proposes a novel framework to synthetically generate more challenging and complex images, which is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The model suggests innovative approaches for conditional image synthesis, allowing backpropagation of the loss function with respect to the labels to the generator from the discriminator. As a result, ArtGAN exhibits the phase of training that is dramatically less susceptible to mode collapse compared to other traditional models.
The major change to ArtGAN is the use of customized data loader function to facilitate a more of general use. The new label Abstract Art has been added to the original Wikiart dataset. Abstract Art contains 4,000 images (1,000 collected from web sources, 3,000 data augmented) that qualify the above-listed characteristics.
Sample of the real artwork
Sample of the generated artwork
Although it should be acknowledged that there still are numerous limitations of an intelligent agent in the creative field of art, the results have shown that the images generated by artificial agents can elegantly fulfill one of the pivotal functions of art, offering an unconditional visual satisfaction to the viewers. The generative model is also capable of generating a massive number of images. Thus, despite the absence of the traditional artists, the images generated by ArtGAN, and by other generative models, have revealed their future potentials to satisfy the larger demographics of people in terms of appearance and a method of production.
With the advent of modernism, trends in art have shifted toward a greater autonomy in the definition, and practice of art. Art is no longer bounded by the constraints of traditional conceptions of beauty, and more importantly, of its primary function of representation. The result of such trends is, unfortunately, the widening distance between the culture of the art connoisseurs, and that of the larger public. Especially in today's highly modernized, and capitalist society, where fast gratification is widely available with the advanced technologies, art is often perceived as something esoteric, or something irrelevant to one's daily life. At this confusing time in the history of art, there seems to be no right answer to how art or the experience of art should be defined.
One may suggest that aesthetic experience in response to works of art should be defined as an experience qualitatively different from everyday experience. It is apparent that works of art can allow people the feelings of admiration, fascination, and awe, which are certainly distinguishable from everyday emotions; however, the value of art would truly manifest only when it is enjoyed as a part of our daily lives. Among its countless functions, one of the irremovable functions of art is to be consumed, and to be enjoyed, as if it is nearly impossible to ponder the meaning of art without considering the presence of its audience or appreciator.
But still there remain some big questions, such as about what to appreciate, or what to qualify as a work of art. Despite the social notion on the judgment of taste, which has been reinforced by the gap between the two cultures, of the art experts and of the public at large, there is no innate hierarchical measure in judgments of taste, or of art itself. The efforts, however, have been made in determining the value of works of art, either for matters of convenience or sometimes for one's benefit. With the rise of the art market, the works of art are typically being evaluated according to the two separate terms: an aesthetic, and a commercial value. Although setting the price for artwork, the product of human gift, might be considered as an attempt to degrade human creativity, the commercial value is now an inseparable part of the artwork as a whole, indirectly representing people's demand in art.
Nowadays, the works of art that are preferred by the larger public appear to be the works that can offer unquestionable beauty without invoking any complex philosophical questions. Such artworks are produced with clear objectives to fulfill human desire for beauty, functioning as an instrument to offer visual satisfaction. Among those works, some observable similarities can be found as listed below.
- There are (preferably) no discernible figures or shapes;
- The mood or atmosphere of an artwork provides positive (or at least neural) connotations;
- Any negative reactions (e.g. fear, contempt, disgust, and etc.) should not be evoked to the viewers
If what has been presented exceeds the underlying aesthetic or philosophical intention in terms of significance, the mere appearance of an artwork then becomes the primary reason for its existence. In the production of such kind of works, the presence of the creators or artists loses its importance. And the potential of artificial intelligence as an art-maker begins to reveal at this very point.
THE PROJECT
The project had been proceeded with the aims to shed light on the true value of art, and to challenge the traditional conceptions of art. The code used in the project are heavily borrowed from ArtGAN (https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN). ArtGAN proposes a novel framework to synthetically generate more challenging and complex images, which is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The model suggests innovative approaches for conditional image synthesis, allowing backpropagation of the loss function with respect to the labels to the generator from the discriminator. As a result, ArtGAN exhibits the phase of training that is dramatically less susceptible to mode collapse compared to other traditional models.
The major change to ArtGAN is the use of customized data loader function to facilitate a more of general use. The new label Abstract Art has been added to the original Wikiart dataset. Abstract Art contains 4,000 images (1,000 collected from web sources, 3,000 data augmented) that qualify the above-listed characteristics.
Sample of the real artwork
Sample of the generated artwork
Although it should be acknowledged that there still are numerous limitations of an intelligent agent in the creative field of art, the results have shown that the images generated by artificial agents can elegantly fulfill one of the pivotal functions of art, offering an unconditional visual satisfaction to the viewers. The generative model is also capable of generating a massive number of images. Thus, despite the absence of the traditional artists, the images generated by ArtGAN, and by other generative models, have revealed their future potentials to satisfy the larger demographics of people in terms of appearance and a method of production.
PROJECT DANSAEKHWA
RESTORE THE PURITY IN ART THROUGH ARTIFICIAL INTELLIGENCE
Dansaekhwa refers to a group of monochrome paintings that represented Korean abstract painting of the 1970s and have emerged again after 40 years. Credited as one of the proper nouns in the global art scene, dansaekhwa has successfully strengthened its position. Drawing worldwide attention in a short period of time, dansaekhwa is laden with Korea’s intrinsic emotion and history remarkably distinguishable from those aroused by Western minimalism as well as considered to be contemporary Korean art’s freestanding brand. Therefore, we have to first of all understand the social phenomena of the 1970s when dansaekhwa first emerged in order to grasp this painting genre properly.
Any cardinal art tendency tends to come into being inextricably bound up not only with art history and aesthetics but also political, economic, and social aspects. The monochrome of the 1970s often referred to as “the white monochrome” and white was a color suggestive of Korean people’s emotion and racial characteristics. Yusuke Nakahara denoted the unique hallmarks of Korean dansaekhwa in the catalog essay for Five Korean Artists, Five Kinds of White, a group show featuring Korean dansaekhwa held at Tokyo Gallery in 1975. Art critic Lee Yil discovered the possibility that Korean dansaekhwa could be defined collectively with the single term “Korean monochrome,” thereby striving to spread it to the entire art scene. In the 1970s, however, artists called monochrome painters did not use this term actively and only a few of artists in the Korean art community gave prominence to this painting genre.
In the 2010s, dansaekhwa was revived amid a globalized economic recession and a depressed art market. This was a sort of the movement to revive Korean art in a continuing economic recession. Unlike monochrome paintings of the 1970s, dansaekhwa in this period discarded the symbolism of white but works by painters commonly called “dansaekhwa artists” had something in common: paintings done in this period were made up of colors that looked visually similar and in sync with one another. Each artist has their own distinctive methodological traits and idioms. As its appellation implies, however, there are elemental limits. As mentioned above, dansaekhwa cannot depart from the conceptual limits of monochrome paintings or those with very limited colors and tones.
Dansaekhwa has been marketed and promoted through an emphasis on “Koreanness” or “Korean identity.” Most works of dansaekhwa are obviously marked by their collective trait, considering only this type of painting itself without involving any other factors. However, no academic issues and questions, such as how this mode of painting represents Korean identity and what invariable Korean identity is despite a time difference of 40 years, have not been fully discussed. Some fears that dansaekhwa has been established based on a feeble theoretical foundation and may have encouraged lopsided preferences in that abstract paintings by senior artists have monopolized the market. Although dansaekhwa became a sensation in the global art scene of the 2010s, its boom was enjoyed at only a few galleries and by very few artists as its artists and works were extremely limited. The majority of artists and the public were not involved in this fever. Therefore, there is a critical evaluation that dansaekhwa was exploited as the means to bring about an abnormal concentration of wealth to a small minority of artists, excluding the majority of people who represent Korean identity.
THE PROJECT
The project is intended to explore the relationship between artwork, creator, and observer as well as the true essence of art. Dansaekhwa is selected as a subject of the project particularly for its relevancy to the current Korean art scene, and global acclamation. The major aims for the project are:
1. to devise a method to generate the images that are similar to the original artworks with minimal human intervention.
2. to evaluate the meaning of the synthesized images, generated with the absence of the traditional artists.
3. to re-examine the role/significance of human creators in the art-making process
The code used in the project are heavily borrowed from ArtGAN (https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN). ArtGAN proposes a novel framework to synthetically generate more challenging and complex images, which is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The model suggests innovative approaches for conditional image synthesis, allowing backpropagation of the loss function with respect to the labels to the generator from the discriminator. As a result, ArtGAN exhibits the phase of training that is dramatically less susceptible to mode collapse compared to other traditional models.
The four series of Dansaekhwa are chosen for their formal appropriacy and the amount of data available. The selected four are "From Line선으로부터" by Ufan Lee, "Ecriture묘법" by Seobo Park, "Correspondence조응" By Ufan Lee, and "Untitled무제" by Yun Hyong-keun. Based on over 12,000 image files achieved through web crawling, and data augmentation, the four separate datasets were created respectively.
Examples of the selected images. From top to bottom: From Line, Ecriture, Correspondence, and Untitled
The major changes to the vanilla ArtGAN are the use of customized data loader function to facilitate a more general use, and the enlarged output size. After applying parameter tuning and network reconfiguration, the revised model stably generate the images with a size of 256 X 256 pixels, compared to the existing model, which generates 128 X 128-pixel images.
Examples of the synthesized images. From top to bottom: From Line, Ecriture, Correspondence, and Untitled
After applying parameter tuning and network reconfiguration, the revised model stably generate the images with a size of 256 X 256 pixels, compared to the existing model, which generates 128 X 128-pixel images. As the above samples indicate, the synthesized images exhibit formal features (e.g. shapes, colors, textures, brushstrokes, and etc.) that are similar to the original images.
The last one-third of training. The model exhibits an unconventional way of learning
CONCLUSION
This project started with the premise that any art or trends in art cannot be separated from the current social conditions. As reviewed above, however, dansaekhwa fever was developed divorced from the political and social realities the general public faced.
Dansaekhwa has not only promoted prejudiced taste but also used as a means to increase the wealth of the few prosperous investors. Under the influence of capitalism, it is not unreasonable to regard a work of art as goods, real properties, or investments. Unfortunately, as we have been observing with this very case of dansaekhwa, there are many problems arise when artworks are thought merely as commercial goods.
Art forgeries, ghostwriter artists, aggressive marketing, and lack of supporting academic, and scholastic research are all issues surrounding dansaekhwa and most of which are due to its abnormally high market demand. With this current tendency in mind, by eliminating the presence of human artists, which have fallen as a mere brand name, in the creation of dansaekhwa paintings, the project aims to contemplate on the true essence of art, which should not be discolored even in capitalistic society. The project acknowledges the involvement of unconventional artist in the artmaking process. By minimizing human intervention, the project suggests that the future potentials of artificial intelligence as a tool to restore purity in art and to challenge the traditional definition of creative practice.
References
Tan, W. R., Chan, C. S., Aguirre, H. E., & Tanaka, K. (2017). ArtGAN: Artwork synthesis with conditional categorical GANs. 2017 IEEE International Conference on Image Processing (ICIP). doi:10.1109/icip.2017.8296985