WIRED Covers: How Do Artists Learn to Look at Artificial Intelligence? A Case Study in New York, NY During Google Spring
Random acts of art are not the only thing that an image generator spits out. They must be “prompted”—carefully guided by their human users. (The prompt is the real art form, Kevin Kelly argues in a recent essay.) We asked several of our favorite artists to re-create their original WIRED covers using these new tools. The results should be judged by yourself. The Art Department.
The artificial intelligence used by Dan Winters was entertaining and inspiring. This is a superior cover than the one that ran, and I am very happy with the result.
Margaret Swart said that she was trying to better articulate the differences between working with an illustrator and prompting DALL-E. I landed in this place because DALL-E works in a world of “things” and it gave me different versions of the information that I provided. I think that’s the most important aspect. Illustrators think differently than I do. They take the information I give them, then they expand on it. They do their own research, as well as other approaches and unexpected solutions. Some of the DALL-E results were unexpected but they appeared to be random data-crunching from my details. Because I wasn’t providing the unexpected ideas in the prompts, I didn’t get the innovative solutions. Artificial intelligence has a lot of data, but is not interested in looking at a concept from a different point of view. I do not see severing ties with my database anytime soon.
Late last year, I attended an event hosted by Google to celebrate its AI advances. The company’s domain in New York’s Chelsea neighborhood now extends literally onto the Hudson River, and about a hundred of us gathered in a pierside exhibition space to watch scripted presentations from executives and demos of the latest advances. Speaking remotely from the West Coast, the company’s high priest of computation, Jeff Dean, promised “a hopeful vision for the future.”
Something weird is happening in the world of AI. The field of artificial intelligence exploded in the beginning of this century due to innovation of deep learning led by three academics. Many of the applications within our company have become more useful because of this approach to the field of artificial intelligence. We’ve spent a dozen years in this AI springtime. There was a aftershock to that earthquake in the past year or so and many of the models appeared to be mind-bending.
The competitors don’t seem to have “slow” in their words. While the Test Kitchen app provides limited access, other companies have been offering all-you-can- eat options with their own image and chatbot generators. The most consequential release yet was Open AI’s new version of its powerful text generation technology that spits out coherent essays, poems, plays, songs and more. Taking advantage of the chatbot’s wide availability, millions of people have tinkered with it and shared its amazing responses, to the point where it’s become an international obsession, as well as a source of wonder and fear. Will ChatGPT kill the college essay? Destroy traditional internet search? Put millions of people out of work?
Answers to those questions aren’t clear right now. But one thing is. Granting open access to these models has kicked off a wet hot AI summer that’s energizing the tech sector, even as the current giants are laying off chunks of their workforces. Contrary to Mark Zuckerberg’s belief, the next big paradigm isn’t the metaverse—it’s this new wave of AI content engines, and it’s here now. In the 1980s, there was a rush on products moving tasks from paper to computer application. In the 1990s, you could make a quick fortune by shifting those desktop products to online. A decade later the movement was to be on the move. The big change in the 2020s will be toward building with generative automated machines. A large number of startups will have business plans that can be accessed by using the system’s APIs. The cost of churning out generic copy will go to zero. By the end of the decade, AI video-generation systems may well dominate TikTok and other apps. The humans may not be as inventive as the robots, but they will dominate.
Whether an AI model will one day create a masterpiece, achieve true indistinguishability, or become a literal deus ex machina is a moot point. At face value, both humans and machines create some form of art.
To expose the duplicative qualities of art, certain online communities are already using pattern- finding as a creative medium. The term comparatives means web weaving, a style of post that blends excerpts from other posts with images around a central theme. There are many different elements that come together, including Richard Siken verse, Renaissance paintings, street photography and film stills. A lot of the collections of digital curio are about the online moods of longing, alienation, and intimacy.