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.

An excerpt:

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.