In recent years, art creation using artificial intelligence (AI) has started to become a mainstream phenomenon. One of the latest applications of AI is to generate visual artwork from natural language descriptions where anyone can interact with it to create thousands of artistic images with minimal effort, which provokes the questions: what is the essence of artistic creation, and who can create art in this era? Considering that, in this study, the theoretical communication framework was adopted to investigate the difference in the interaction with the text-to-image system between artists and nonartists. In this experiment, ten artists and ten nonartists were invited to co-create with Midjourney. Their actions and reflections were recorded, and two sets of generated images were collected for the visual question-answering task, with a painting created by the artist as a reference sample. A total of forty-two subjects with artistic backgrounds participated in the evaluated experiment. The results indicated differences between the two groups in their creation actions and their attitude toward AI, while the technology blurred the difference in the perception of the results caused by the creator’s artistic experience. In addition, attention should be paid to communication on the effectiveness level for a better perception of the artistic value.
Artificial Intelligence (AI) is becoming more popular in various fields, including the area of art creation. Advances in AI technology bring new opportunities and challenges in the creation, experience, and appreciation of art. The neural style transfer (NST) realizes the intelligent conversion of any artistic style using neural networks. However, the artistic style is the product of cognition that involving from visual to feel. The purpose of this paper is to study factors affecting audience cognitive difference and preference on artistic style transfer. Those factors are discussed to investigate the application of the AI generator model in art creation. Therefore, based on the artist’s encoding attributes (color, stroke, texture) and the audience’s decoding cognitive levels (technical, semantic, effectiveness), this study proposed a framework to evaluate artistic style transfer in the perspective of cognition. Thirty-one subjects with a background in art, aesthetics, and design were recruited to participate in the experiment. The experimental process consists of four style groups, including Fauvism, Expressionism, Cubism, and Renaissance. According to the finding in this study, participants can still recognize different artistic styles after transferred by neural networks. Besides, the features of texture and stroke are more impact on the perception of fitness than color. The audience may prefer the samples with high cognition in the semantic and effectiveness levels. The above indicates that through AI automated routine work, the cognition of the audience to artistic style still can be kept and transferred.
From entertainment to medicine and engineering, artificial intelligence (AI) is now being used in a wide range of fields, yet the extent to which AI can be effectively applied to the creative arts remains to be seen. In this research, a neural algorithm of artistic style was used to generate six AI paintings and these were compared with six paintings on the same theme by an amateur painter. Two sets of paintings were compared by 380 participants, 70 percent of whom had previous painting experience. Results indicate that color and line are the key elements of aesthetic appreciation. Additionally, the style transfer had a marked effect on the viewer when there was a close correspondence between the painting and the style transfer but not when there was little correspondence, indicating that AI is of limited effectiveness in modifying an existing style. Although the use of neural networks simulating human learning has come a long way in narrowing the gap between paintings produced by AI and those produced in the traditional fashion, there remains a fundamental difference in terms of aesthetic appreciation since paintings generated by AI are based on technology, while those produced by humans are based on emotion.
Intangible cultural heritage tourism has become a hot topic in academia and industry. As a vital tourism resource, intangible cultural heritage can activate the in-depth experience of tourists for local culture to enhance the attraction and competitive advantage of national or regional tourism. From the perspective of culture, design is used to realize a kind of life taste and form a lifestyle through cultural creativity and industry, with applications in different fields to create a human lifestyle through innovative design. This study proposed a framework exploring form and ritual and discusses the aesthetic economy from form (Hi-tech) to ritual (Hi-touch) through case studies. There were three cases that analyzed how to improve local tourism development through the interaction between form and ritual. The results show that this model can integrate sustainable development into intangible cultural heritage tourism and can be further verified in other countries and regions.
This study explores how audiences responded to perceiving and distinguishing the paintings created by AI or human artists. The stimuli were six paintings which were completed by AI and human artists. A total of 750 subjects participated to identify which ones were completed by human artists or by AI. Results revealed that most participants could correctly distinguish between paintings made by AI or human artists and that accuracy was higher for those who used “intuition” as the criterion for judgment. The participants preferred the paintings created by human artists. Furthermore, there were big differences in the perception of the denotation and connotation of paintings between audiences of different backgrounds. The reasons for this will be analyzed in subsequent research.
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