
The emergence of AI-generated art has sparked intense debate, often polarizing individuals into pro- and anti-AI factions based on varying perceptions of AI’s impact on creativity. However, the dynamics of AI’s relationship with artistic expression are more nuanced than a binary perspective allows.
AI serves as a significant ally in enhancing the creative process by enabling rapid visualization and increasing the range of possible iterations an artist can churn out during their workflow. Generative AI not only fosters quick creativity but also expands an artist’s skill set, crucial in a world where contemporary art practices are increasingly interdisciplinary.
Specifically, AI-generated art produced from textual prompts exemplifies the intersection of AI and artistic production. Some artists celebrate the depth involved in prompt engineering, while others criticize it as lacking the depth of traditional artistic skills, which raises questions about the true metrics of creativity. Historically, recognized art movements, such as Duchamp’s readymade art, demonstrate that perceived effort and technical ability may not be the most relevant measures of creativity.
Generative AI’s influence is becoming ubiquitous in creative processes involving digital tools. Software giants like Adobe are promoting these technologies, often making it challenging for artists to avoid using AI. For instance, Photoshop has incorporated features that prioritize AI-based functions.
It is essential to recognize that assistive intelligent tools have existed long before the rise of generative AI. Technologies such as face detection in photography and selection tools in design software have long aided artistic endeavors. Understanding this history is crucial for students and emerging artists, empowering them to discern when to leverage technology versus executing tasks manually.
Despite the advantages offered by AI, many artists raise ethical concerns regarding its usage. Issues range from the environmental toll of AI technologies to ethical dilemmas surrounding AI’s deployment in military contexts and the potential for generating disinformation. The fear of job displacement is also prominent; employers might favor AI for its lower cost, leading to a perception of diminished value in artistic work.
Furthermore, a pointed critique exists among artists regarding the utilization of their own creations within the datasets that train generative AI. Artists have established mechanisms to track the use of their work without permission, with some tools emerging to let them know if their art has been included in datasets by AI development companies.
AI-generated art is not merely a substitute for human creativity but also contributes to shaping a novel aesthetic. Artists encounter a new realm where generative AI dictates stylistic consistency. Users often obtain similar artistic outputs when employing the same generative models, which leads to a homogenization in visual language that is readily identifiable.
The rapid evolution in image and video generation capabilities poses a challenge to authenticity, as various AI outputs can be compellingly realistic, while a growing segment of AI-produced content may lack credibility. This juxtaposition could give rise to what some might affectionately call ‘AI slop’—an aesthetic born from AI’s peculiarities. Such anomalies could open avenues for artistic exploration, compelling creators to engage with the uncanny qualities that emerge from AI-generated art.
As the field progresses, artists may wrestle with decisions on whether to embrace the imperfections of human craftsmanship or the idiosyncrasies of AI-produced work.
Tyler Calkin, MFA, is an associate professor of art and head of digital media at the University of Nevada, Reno, where he focuses on integrating AI and machine learning into artistic practices, linking social experience with innovative forms of digital expression.