Art sits at the intersection of technology, representation, and influence. This includes literature, film, music, media, visual and graphic arts and are all crucial in storytelling and bearing narratives. Once technologies are related to artificial intelligence (AI), they have a strong impact in the creative field of art (Cetinic, 2022, p. 1). Artificial Intelligence (AI) is becoming ubiquitous as it makes inroads into the arts. While art is widely considered to be a uniquely human phenomenon, the proliferation of advanced AI models capable of mimicking human artworks raises issues of concern. AI creations may soon be able to replace the unique work of human creativity if not investigated properly and thoroughly. In this essay, the role of AI and art will be critiqued and analyzed by understanding the differences between humans and technology and what is meant to become of AI-art versus human-made art.
In recent years, there has been a surge of interest in exploring the creative potential of AI technologies amongst artists and researchers (Cetinic, 2021, p. 1). The advances in technology have allowed for humans to utilize AI techniques within everyday applications including the infamous ChatGPT and DALL-E-2. When a user has an idea in mind and types within the text box, ChatGPT will automatically generate tailored, detailed prompts for DALL-E-2 that will bring those ideas to life (OpenAI, 2023). DALL-E-2 is an AI tool that focuses on the creation of images and can be easily accessed from OpenAI as it generates images from text descriptions using a dataset of text-image pairs (OpenAI, 2021). An issue of concern with DALL-E creating images brings into question the legitimacy of true art and where credibility lies in AI generated art. On OpenAI (2023) itself, it is stated that the images created within DALL-E are free for the individual to use and permission is not needed to reprint, sell, or merchandise them. This AI-art interaction seems to suggest that, not only is AI art being similarly created to human-created art but that people will be failing to discern the true creator of the piece. DALL-E being programmed to “fill in the blanks” and generate images easily destroys the human utility of “creativity” through these advanced thinking machines. It is possible that the accessibility of creating AI art could hinder humans creative abilities and perhaps lose in comparison to technology when competing with artistic abilities.
The use of AI in the process of creating visual art has significantly increased due to the number of engaging AI technologies present. On the other side, the increasing online availability of digitized art presents new opportunities for technologies to analyze historic art and adapt through image data (Cetinic, 2021, p. 2). Creating new images has accelerated in the recent years that has led to the current AI art production but has raised ethical concerns. Rather than being sidelined in the debates about ethics in artificial intelligence and data practices more broadly, human artists should be centered alongside AI technicians and AI-coded technology (Elam, 2022, p. 204). One barrier to a shared understanding of the ethical issues raised by digital art practices is a lack of education regarding the technologies themselves. Until art critics engage more deeply with the technical frameworks of data art by understanding their ability to analyze and assess, the quality of human arts may be lacking compared to AI-art. Thus, if both artists and technicians do not work towards trying to understand how each art is processed and created, there will always be faults specifically in AI-art when it lacks the information and coding to include a variety of non-biased data.
Having those in data science, computer science, and engineering educating themselves about the aesthetics and art practices would be beneficial as they would be able to learn and implement a feminist, intersectionality, disability, and race studies approach towards AI. Without the balancing in place for both sides to understand each other, the subtle gatekeeping of information makes all the difference, especially the differential status of the arts in relation to each other. Nowadays, it is noted that artists are being taken for granted for their art but it is not solely on the artists to learn and adapt to new AI – the industry might as well shift in conversation and receive technological training and education. This is to reduce the negative impact of technologies by acquiring a mindset that AI and artists can be equal partners. Artist-technologist Amelia Bearskin-Winger, makes a case that any innovation should honour its debt to prior generations before paying it forward (Elam, 2022, p. 204).
The recent attention of paid art created by AI within galleries, museums, and social media has sparked a heated debate around the future of human art versus AI-generated art. There is reason to believe that the development of AI technologies capable of automating creativity (GAN/DALL-E) will not significantly impact the perceptions of human made art and their creativity (Bajohr, 2022, p, 206). It is the creativity that makes humans what they are, as long as there is no loss of creativity, a machine cannot perform as great of a fabricated quality piece of work that humans can create. AI art will not devalue human creativity when it is the artist getting paid for their visions, their brand, their use of colour and emotion within art pieces (Cetinic, 2022, p. 11). Subjective matters such as these make it hard to believe that AI art will completely take over artists’ jobs but it does make a standing impression of the impact of generative AI within the world. AI technologies are starting to have an ever important role in all aspects of curation, exhibition, and a rapid shift towards digitalized art scenes.
This is only the beginning in understanding the impact of AI technologies on the value of human creativity as AI-labelled art can still be greatly appreciated as much as human-labelled art. Individuals may appreciate human made art by different creators and how the difference in aesthetics play a role in deciding which art individuals like better when it comes to AI versus humans. To be noted, simply believing that certain pieces of art were created by AI negatively impacts appraisal as there was no skill, no vision, and no emotion present. It can be suggested that AI art already possess its own style and while it can be seen as more creative than human artwork at times, the human value of their creativity on original works suggest that art will not die. In conclusion, people often perceive art as a human-creative and specific experience, but when creative art pieces may be created by technology, our practical understandings of art may be challenged. The creation of AI-art has the ability to bring suggestions for a heightened appreciation for human creativity and human mad works while shedding light on human creativity to be valued.
References
Bajohr, H. (2022). Algorithmic Empathy: Toward a Critique of Aesthetic AI. Configurations (Baltimore, Md.), 30(2), 203–231. https://doi.org/10.1353/con.2022.0011
Cetinic, E., & She, J. (2022). Understanding and Creating Art with AI: Review and Outlook. ACM Transactions on Multimedia Computing Communications and Applications, 18(2), 1–22. https://doi.org/10.1145/3475799
Elam, M. (2022). Signs Taken for Wonders. Daedalus (Cambridge, Mass.), 151(2), 198–217. https://doi.org/10.1162/daed_a_01910
OpenAI. (2023). Research DALL-E-3. OpenAi. https://openai.com/dall-e-3
OpenAI. (2021). DALL-E: Creating Images from Text. OpenAI. https://openai.com/research/dall-eOpenAI. (2023). Research DALL-E-3. OpenAi. https://openai.com/dall-e-3