The hype around Artificial Intelligence is real and AI is slowly penetrating every sphere around us. Especially with the growing popularity and ease of access of powerful tools like DALL•E, an AI that generates images from descriptions fed to it by its users. DALL•E’s images can be surprisingly realistic, or entirely nonsensical. When the user’s imagination runs wild, the comedic potential of the output is undeniable, making it easy to spend hours testing the system’s capabilities. We even took DALL•E for a spin with our Cloudberry 2022 Holiday Card Experience.
But is AI truly all fun and games? In this article, we’ll explore how AI tools can be harmful, where they have been helpful, and consider how they may lend a hand in UX workflows.
When AI hurts
If you entered a marathon, only to drive a car to the finish line, not only would it turn heads, it would be considered cheating. Marathons are something people spend months– years even– training their bodies and minds for. The same can be said about artists, who continuously create to hone their craft. So why was it that when Jason Allen submitted his “Théâtre D’opéra Spatial” to the Colorado State Fair’s fine arts competition, he won first place and a cash prize despite using AI to do the heavy lifting?
His win sparked a backlash from artists and generated heated discourse around AI “art.” However, controversy over emerging artistic technologies is nothing new. When the invention of the camera rolled around many painters recoiled, and the rising popularity of tools like Clip Studio Paint and Procreate among digital artists irked many who preferred more traditional mediums. That didn’t stop their adoption. And this certainly won’t be the last time an AI-generated piece will go head-to-head with the creation of a human artist. One solution could be to create a new category that separates AI images from artworks made by real people. Then again who’s to say we would be able to tell which is which.
The battle between AI and artists doesn’t stop there though. Recently, there has been an uptick in people stealing art from creators who post their work online, feeding those images to AI systems, and changing the original image just enough to be passed off as their own. One technique being explored to counteract theft is running images through a snippet of code called Stable Diffusion, which generates a watermark that is undetectable to the human eye but can disrupt the AI’s processing of the watermarked image. AI learns fast, and this approach could be rendered useless if the algorithm finds a way around Stable Diffusion.
Where AI helps
Some AI tools leave more room for debate regarding the ethics of their use, like systems that streamline some of the most tedious steps in creative processes, saving designers time that they can instead use to work on the more creatively challenging aspects of their work.
One example of this is Adobe’s AI-powered Masking Tool that launched back in October 2022 for Lightroom. This new feature allows users to select people, objects, and backgrounds to mask with a singular click; a step that typically eats up a significant portion of image editing processes. Gone are the days of selecting pixels with the lasso tool.
Anyone who comes across old family photographs that have not held up against the test of time probably wishes they had the means to restore the photographs to its former glory. GFP-GAN is an AI image restoration tool that does just that, restoring damaged and faded photos with surprising accuracy. It can heal stains, cracks, and wrinkled photo paper, breathing new life into damaged photographs. It’s in instances like these where the power of AI shines.
AI and UX
Image manipulation is only one of AI’s vast use cases. So where does it fit into the picture with UX workflows? Does automation pose a threat to some of UX’s more specialized titles? In UX, empathy is at the core of what we do. It’s what allows us to understand others and design solutions that meet their needs. It’s hard to imagine how designers could be replaced by tech incapable of empathetic emotion. The field has many subdivisions, one of which AI could potentially have a massive impact on; UX Writing.
It seems that the rise of AI-assisted writing programs has writers both excited and leery, wondering if their jobs are at risk but curious about AI’s capabilities at the same time. Software like Writer is like having a copy editor right at your fingertips, helping catch spelling mistakes, cut down on wordiness, and correct any deviations from the user’s chosen format. It’s not a tool that aims to replace editors and copywriters altogether, rather it’s there to help minimize the number of smaller mistakes we as humans make often.
In addition to assisted writing tools, UXers are also exploring different collaboration models. Asking themselves how AI can work with them and creating Figma plugins to help optimize day-to-day workflows. Tools like Magician are helping designers quickly generate unique icons and images from descriptive text, taking their visual designs to the next level with minimal time spent. As our industry figures out the most robust use cases for emerging AI technologies, the best thing we can do is keep an open mind.