Ryan Aasen (SMACT ’20) recently wrote an essay, New Media, Old Problems: Racial Stereotypes in AI Image Generation, which he published on Medium. In it, he explores the power of AI generators and the images they can create.
Like many people, I’ve spent the last few months playing with the new wave of consumer-oriented (what I call “over-the-counter”) AI tools like ChatGPT. As an artist, I’ve been especially fascinated by AI image generators such as Dall-E, Midjourney, and Stable Diffusion, which have gone from fantasy to photorealism in just a year.
Because these models are trained on existing images, they offer a kind of meta-narrative on the way we create, consume, and analyze images as a society — highlighting patterns, perceptions, and biases in interesting ways.
For example, I was generating images of members of Congress in Midjourney— not specific members, but what AI thought a member of Congress would look like. I did this partly as a reflection on my frustration with the age of Congress and their disconnect from the impacts of new technologies, but in a lot of ways these images are a perfect dataset to work with: there are many of them and they are nearly identical in style — both in composition and subject. This means the results can be fairly predictable.
Initially it was purely humorous — the subtle change of making them hold an object such as a cat or rock quickly makes these utilitarian portraits absurd (unfortunately “holding a gun” does not look so absurd).
Read the full essay here.