Often new products come with disclaimers, but in April artificial intelligence company OpenAI issued an unusual warning when it announced a new service called DALL-E 2. The system can create vivid and realistic photos, paintings and illustrations in response to a line of text or an uploaded image. Part of OpenAI’s release notes warned that “the model may increase efficiency in performing some tasks such as photo editing or stock photography production, which could crowd out the jobs of designers, photographers, models, editors, and artists.”
So far this has not happened. People who were previously granted access to DALL-E have found that rather than making it obsolete, it enhances human creativity. Benjamin von Wong, an artist who creates installations and sculptures, says it has actually increased his productivity. “DALL-E is a wonderful tool for someone like me who can’t draw,” says Von Wong, who uses the tool to explore ideas that could later be incorporated into physical artworks. “Rather than having to sketch out concepts, I can just generate them through different imperative sentences.”
DALL-E is one of many new AI image generation tools. Aza Raskin, an artist and designer, used open-source software to create a music video for musician Zia Cora, which was shown at April’s TED conference. The project helped convince him that image-generating AI will lead to an explosion of creativity that will permanently change humanity’s visual environment. “Anything that can have an image will have one,” he says, potentially turning people’s intuition on its head with how much time or effort has gone into a project. “Suddenly we have this tool that makes things that are difficult to imagine and visualize easy to achieve.”
It’s too early to know how such transformative technology will ultimately affect illustrators, photographers, and other creatives. But at this point, the notion that artistic AI tools will displace workers from creative jobs — the way people sometimes describe robots replacing factory workers — seems like an oversimplification. Even for industrial robots performing relatively simple, repetitive tasks, the evidence is mixed. Some economic studies suggest that corporate adoption of robots leads to lower overall employment and lower wages, but there is also evidence that robots increase job opportunities in certain settings.
“There’s far too much doom and gloom in the art community,” where some people are too quick to assume machines can replace human creative labor, says Noah Bradley, a digital artist who posts YouTube tutorials on using AI tools. Bradley believes the impact of software like DALL-E will be similar to how smartphones impact photography – making visual creativity more accessible without replacing professionals. Creating high-performing, usable images still requires a lot of careful tweaking after something’s been generated for the first time, he says. “It is very complex to create art that machines are not yet ready for.”
Announced in January 2021, the first version of DALL-E was a milestone for computer-generated art. Machine learning algorithms were shown to feed many thousands of images, as training data could reproduce and recombine features from these existing images in novel, coherent, and aesthetically pleasing ways.
A year later, DALL-E 2 significantly improved the quality of the images that could be generated. It can also reliably adopt different artistic styles and produce images that are more photorealistic. Want a studio quality photo of a Shiba Inu dog wearing a beret and black turtleneck? Just type that in and wait. A steampunk illustration of a castle in the clouds? no problem. Or a 19th-century style painting depicting a group of women signing the Declaration of Independence? Great idea!
Many who experiment with DALL-E and similar AI tools describe them less as a surrogate and more as a new breed of artistic assistant or muse. “It’s like talking to an extraterrestrial being,” says David R. Munson, a photographer, author and English teacher in Japan who has been using DALL-E for the past two weeks. “It’s trying to understand text input and tell us what it’s seeing, and it just squirms in this amazing way and produces things you really don’t expect.”