Generative AI & The Digital Production Divide
Three years before the term digital divide was coined, and 30 years ago this month, I saw a seed of an idea I had planted sprout and take root in South Jamaica Queens, NY. During my four years as an undergraduate computer graphics student I worked as a teaching artist for the Jamaica Arts Center. I was sent to teach all over New York City and I noticed that none of the community centers where I taught visual art had computers. It bothered me, so I mentioned it to my JAC supervisor. Eventually, I moved to Chicago for graduate school.
The reason it bothered me was because I had been introduced to computer graphics/art in high school and that led to my creation of a portfolio that earned a full scholarship to Pratt Institute. At duPont Manual Magnet High School in Louisville, KY I majored in Visual Art but it was the work I did in the computer graphics lab that gave me the best chance to attend my top school. I imagined that younger children would have an even better chance to do the same if they had access to what I had in high school.
We installed 5 Macintosh Performa LC IIIs with 5 1/4 inch floppy drives and Apple Displays. The lab also had a color inkjet printer. I ran workshops for kids through December. However, a series of unfortunate occurrences left me disheartened but the spirit of the project stayed with me. When I returned in the new year the computers and printer were gone… stolen. The sewer flooded the basement and managed not to get to the computers but it took weeks to drain, dry, and clean the space. Eventually, I moved on.
For 30 years I’ve built several labs and created projects that engage underserved, underrepresented, or underestimated children and youth in creative, computational activities. As a PhD student I worked with researchers on a suite of culturally situated design tools or CSDTs to teach students how to generate Afrofuturistic designs (see above). A few years later I taught AP Computer Science Principles in a STEAM Lab and discovered generative artificial intelligence, or AI that is capable of generating text, images, or other media, using generative (training) models. After the course was over I kept exploring “GenAI.”
Most digital inequality research focuses on digital consumption or participation, but some researchers have used a production lens to look at who is creating digital content and who isn’t. Today, with the advent and proliferation of social media sites such as Instagram and TikTok, young people around the world have become digital content creators. Their content provides data used by generative AI training models, as well as other artists’ works.
Even among people who are already online, a digital production gap challenges theories that the Internet creates an egalitarian public sphere. Instead, digital production inequality suggests that elite voices still dominate in the new digital commons. — Jen Schradie in 2011
Since 2019 I’ve purposefully created and posted generative AI images on my social media accounts every single day. On Instagram alone my follower count went from 1,200 to 94.5k in less than three years. In 2021, staff at Mission Bit asked students Alyssa Wu and Natalie Huang to lead a coding workshop. They chose to teach their peers about the “ways in which coding can be used to make art, which can in turn be used to make a positive change.” When asked why, Alyssa said,
“We were inspired after learning about the concept of creative coding and seeing some of the artwork created by Nettrice Gaskins. We wanted to be able to combine the technical and creative aspects of coding.”
The Mission Bit students were referring to my practice of using Processing programming language to generate images that I then used as style reference images in Deep Dream Generator. Before prompt-based AI tools, I was exploring ‘Deep Style’ or image style transfer to apply styles to existing images, including my own. You can see the students’ results here.
In some ways, the Mission Bit student work brings me full circle to my first computer lab where children came to learn how to make digital art. Today, access to computers and digital art applications are much more ubiquitous and I no longer need to build spaces for young people to work. They simply find me and my work on social media or online, then follow the visual breadcrumbs to articles such as this one.