New products often comes 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 generate 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 can increase the efficiency of performing some tasks such as photo editing or stock photography production, which can displace jobs for designers, photographers, models, editors and artists.”
So far this has not happened. People who have gained early access to DALL-E have found that it lifts human creativity rather than making it obsolete. 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,” he says Von Wong, who uses the tool to explore ideas that could later be built into physical works of art. “Instead of having to sketch concepts, I can simply generate them through various prompt sentences.”
DALL-E is one of a number of new AI tools for generating images. Aza Raskinan artist and designer, used open source software to generate a music video for musician Zia Cora, who appeared at the TED conference in April. The project helped convince him that image-generating AI will lead to an explosion of creativity that permanently changes humanity’s visual environment. “Anything that can have a visual will have one,” he says, potentially raising people’s intuition to assess how much time or effort was spent on a project. “Suddenly we have this tool that makes what was hard to imagine and visualize easy to make exist.”
It is too early to know how such a transformative technology will ultimately affect illustrators, photographers and other creatives. But at this point, the idea that artistic AI tools will displace workers from creative jobs – the way people sometimes describe robots that replace factory workers – seems to be an oversimplification. Even for industrial robots, which perform relatively simple, repetitive tasks, the evidence is mixed. Some economic studies suggests that corporate adoption of robots results in lower employment and lower wages in general, but there is also evidence that in some contexts robots increase job opportunities.
“There is far too much doom and gloom in the art community,” where some people too easily assume that machines can replace human creative work, says Noah Bradley, a digital artist who posts YouTube tutorials on using AI tools. Bradley believes that the impact of software like DALL-E will be similar to the impact of smartphones on photography – making visual creativity more accessible without replacing professionals. Creating powerful, usable images still requires a lot of careful adjustment after something is first generated, he says. “There’s a lot of complexity in creating art that machines are not ready for yet.”
The first version of DALL-E, announced in January 2021, was a landmark of computer-generated art. It showed that machine learning algorithms fed thousands of images as training data could reproduce and recombine functions from the existing images in new, coherent and aesthetically pleasing ways.
One year later, the DALL-E 2 significantly improved the quality of images that could be produced. It can also reliably adopt different artistic styles and can produce images that are more photorealistic. Want a studio-quality photograph of a Shiba Inu dog wearing a beret and black turtleneck? Just type it in and wait. A steampunk illustration of a castle in the clouds? No problem. Or a 19th-century-style painting of a group of women signing the Declaration of Independence? Really good idea!
Many people who experiment with DALL-E and similar AI tools describe them less as a replacement than as a new kind of artistic assistant or muse. “It’s like talking to a foreign entity,” he says David R Munson, a photographer, author and English teacher in Japan who has been using DALL-E for the past two weeks. “It tries to understand a text prompt and communicate back to us what it sees, and it just twists in this amazing way and produces things that you really don’t expect.”