AI-generated artwork is the same as a gallery of rock faces. It is pareidolia, an illusion of art, and if culture falls for that illusion we will lose something irreplaceable. We will lose art as an act of communication, and with it, the special place of consciousness in the production of the beautiful.
…Just as how something being either an original Da Vinci or a forgery does matter, even if side-by-side you couldn’t tell them apart, so too with two paintings, one made by a human and the other by an AI. Even if no one could tell them apart, one lacks all intentionality. It is a forgery, not of a specific work of art, but of the meaning behind art.
Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language.
But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.”
As we’ve been researching what design teams need to do to create great user experiences, we’ve stumbled across an interesting finding. It’s the closest thing we’ve found to a silver bullet when it comes to reliably improving the designs teams produce.
The solution? Exposure hours. The number of hours each team member is exposed directly to real users interacting with the team’s designs or the team’s competitor’s designs. There is a direct correlation between this exposure and the improvements we see in the designs that team produces.