AI Art & Music Generators Project Information
In 2015, Google released their DeepDream visual generator, which relies on algorithms to find and enhance patterns in pictures, resulting in the creation of overprocessed images. Since then, generators using artificial neural networks have gained the capacity to create images from scratch based on textual natural language input. Sometimes these images are highly stylized and sometimes they are photorealistic. This technological development commonly known as AI image generation has become widely available in the United States to those with internet access and ability to pay around $10 per month, thereby increasing access to the means of making art for many who were previously unable or not likely to participate in art-making.
This project explores the ways that increased access to art-making via AI image generators has the capacity to change social meanings and values of “art,” with the possibility of both positive and negative social consequences. In some cases, AI image generators may diminish barriers to making art that individuals who have previously been excluded from formal and informal art communities may experience as exclusionary. This includes individuals who are unable to participate in traditional forms of visual art-making due to differences in physical ability. In other cases, it allows participation by individuals without the financial resources for supplies, dedicated space, or training that they may see as necessary to engage in traditional forms of visual art. Often these exclusions are more pronounced amongst individuals belonging to marginalized groups in terms of race, class, gender, disability, educational background, and immigration status. At the same time, the increased accessibility of art-making may have the potential to devalue the skills and products of trained artists who financially rely on visual art and see art as part of their identities. For example, this may affect contract artists who can no longer convince clients that hiring professional artists is cost effective. There has also been scrutiny of generators’ algorithms that are trained on images on the Internet without compensation for original creators. So while many agree that increased access to art is a public good, some artists also note that they are beginning to experience negative consequences of these technological advances. In asking how meanings and values of art may change as a result of increased accessibility, as a result of AI image generators, this project explores the ways that inequalities of access to “art worlds” (Becker 2008) may be diminished by the development of generators, and conversely, how such generators may create other forms of precarity. This exploration of technology’s power to reorient power relations (see Kelty 2008) incorporates longstanding anthropological attention to art across cultures related to individual and group identity (Bain 2005; Geertz 1976; Travis 2019), forms of local and global inequalities (Chen and Wellman 2004), the kinds of social distinction and power dynamics that are embedded in different art worlds (Bourdieu 1984; Marcus and Meyers 1995), and notions of authenticity related to artists and art works (Kirshenblatt-Gimblett 1988). The project poses questions related to the meanings that people attribute to various kinds of art, and the ways inequalities may be exacerbated, diminished, or both simultaneously through widening use of technologies. Taking into account both positive and negative repercussions of AI image generators, this project also considers how the increased accessibility of art through AI technologies changes the cultural meaning and value of “Art” for those who are emotionally and/or financially invested in it. In order to answer this question, it uses an ethnographic methodology, relying on participant observation and interviews with working visual artists, users of AI image generators, and those who understand AI generators from a technological and engineering standpoint. By seeking the opinions and experiences of individuals from these various relationships to visual art, it will contribute to further understanding the impacts of technology on what has been called “one of the defining characteristics of the human species” (Morriss-Kay 2010). This project begins from the standpoint that technological innovation is a constant feature of society. Anthropologists have observed that with each development, people are initially resistant and bemoan the certain technologies are “irreparably” changing the world. Yet, they often quickly adapt, integrating new technologies into their daily practices. Indeed, rather than seeing such technologies as reconfiguring what it means to be human (i.e., Haraway 1985), Miller and Sinanan (2014) see humanity as a consistently incomplete project. Their “theory of [human] attainment” posits that technologies facilitate humans’ ability to attain their aims, rather than disrupting or changing what it means to be human. However, simply focusing on the ability of technology to facilitate attaining aims does not quite describe the emotional, affective, and identity-laden relationship that many individuals have with art (Deleuze 1964; Van Alphen 2008), nor does it take into account constantly shifting media ideologies (Gershon 2010). This project brings together science and technology studies with studies of art worlds, disability studies, and research on shifting economies of labor to understand the wide-ranging impacts of AI image generators for differently-positioned individuals in the United States. In addition to general audiences’ interests in the impacts of technology, this project also speaks to important ongoing conversations in the humanities, particularly those related to futurity, technology and inequality, and the continued importance of art in the midst of resources increasingly being channeled toward STEM fields. In doing so, it represents an important intervention on the mutual impacts of art, science and technology, and social inequalities.
This project explores the ways that increased access to art-making via AI image generators has the capacity to change social meanings and values of “art,” with the possibility of both positive and negative social consequences. In some cases, AI image generators may diminish barriers to making art that individuals who have previously been excluded from formal and informal art communities may experience as exclusionary. This includes individuals who are unable to participate in traditional forms of visual art-making due to differences in physical ability. In other cases, it allows participation by individuals without the financial resources for supplies, dedicated space, or training that they may see as necessary to engage in traditional forms of visual art. Often these exclusions are more pronounced amongst individuals belonging to marginalized groups in terms of race, class, gender, disability, educational background, and immigration status. At the same time, the increased accessibility of art-making may have the potential to devalue the skills and products of trained artists who financially rely on visual art and see art as part of their identities. For example, this may affect contract artists who can no longer convince clients that hiring professional artists is cost effective. There has also been scrutiny of generators’ algorithms that are trained on images on the Internet without compensation for original creators. So while many agree that increased access to art is a public good, some artists also note that they are beginning to experience negative consequences of these technological advances. In asking how meanings and values of art may change as a result of increased accessibility, as a result of AI image generators, this project explores the ways that inequalities of access to “art worlds” (Becker 2008) may be diminished by the development of generators, and conversely, how such generators may create other forms of precarity. This exploration of technology’s power to reorient power relations (see Kelty 2008) incorporates longstanding anthropological attention to art across cultures related to individual and group identity (Bain 2005; Geertz 1976; Travis 2019), forms of local and global inequalities (Chen and Wellman 2004), the kinds of social distinction and power dynamics that are embedded in different art worlds (Bourdieu 1984; Marcus and Meyers 1995), and notions of authenticity related to artists and art works (Kirshenblatt-Gimblett 1988). The project poses questions related to the meanings that people attribute to various kinds of art, and the ways inequalities may be exacerbated, diminished, or both simultaneously through widening use of technologies. Taking into account both positive and negative repercussions of AI image generators, this project also considers how the increased accessibility of art through AI technologies changes the cultural meaning and value of “Art” for those who are emotionally and/or financially invested in it. In order to answer this question, it uses an ethnographic methodology, relying on participant observation and interviews with working visual artists, users of AI image generators, and those who understand AI generators from a technological and engineering standpoint. By seeking the opinions and experiences of individuals from these various relationships to visual art, it will contribute to further understanding the impacts of technology on what has been called “one of the defining characteristics of the human species” (Morriss-Kay 2010). This project begins from the standpoint that technological innovation is a constant feature of society. Anthropologists have observed that with each development, people are initially resistant and bemoan the certain technologies are “irreparably” changing the world. Yet, they often quickly adapt, integrating new technologies into their daily practices. Indeed, rather than seeing such technologies as reconfiguring what it means to be human (i.e., Haraway 1985), Miller and Sinanan (2014) see humanity as a consistently incomplete project. Their “theory of [human] attainment” posits that technologies facilitate humans’ ability to attain their aims, rather than disrupting or changing what it means to be human. However, simply focusing on the ability of technology to facilitate attaining aims does not quite describe the emotional, affective, and identity-laden relationship that many individuals have with art (Deleuze 1964; Van Alphen 2008), nor does it take into account constantly shifting media ideologies (Gershon 2010). This project brings together science and technology studies with studies of art worlds, disability studies, and research on shifting economies of labor to understand the wide-ranging impacts of AI image generators for differently-positioned individuals in the United States. In addition to general audiences’ interests in the impacts of technology, this project also speaks to important ongoing conversations in the humanities, particularly those related to futurity, technology and inequality, and the continued importance of art in the midst of resources increasingly being channeled toward STEM fields. In doing so, it represents an important intervention on the mutual impacts of art, science and technology, and social inequalities.
Collaborators
Dr. Nell Haynes is an associate professor of anthropology at Saint Mary's College. She is a media anthropologist focusing on the ways pop culture impacts and is impacted by social inequalities such as race, gender, class, (dis)ability, and citizenship status.
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Dr. Mark Cartwright is an assistant professor in informatics at New Jersey Institute of Technology where he leads the Sound Interaction and Computing (SInC) Lab. His research lies at the intersection of human-computer interaction and machine learning applied to audio.
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Forthcoming Publications
Nell Haynes. 2026. AI Image Generators, (Dis)ability, and the Politics of Normativity. Social Analysis special issue on “AI and the Shifting Terrain of Mediation,” edited by Philipp Budka, Martin Slama, and Suzana Jovicic.
Acknowledgements
This project has been generously funded by the National Endowment for the Humanities (2024) and a fellowship at University of Wisconsin's Center for Humanistic Inquiry into AI and Uncertainty
