Opinions expressed are solely those of the author and do not reflect the views of Rolling Stone editors or publishers.
I so perfectly recall the magical day I bought my first computer. I was about 13 years old and had scrimped and saved from my teenage moneymaking schemes to assemble a grand total of $115. At the local big box store, that would get me a Timex Sinclair 1000.
Now understand that I am a digital fossil, but if you’ll just imagine all of this through the early Eighties lens of a Stranger Things episode, it will start to come into focus. These were days when there wasn’t any dominant computer platform. Steve Jobs and Steve Wozniak were just coming out of the garage with the Apple 1. IBM earnestly presented its plain vanilla IBM 5150 (which we can only assume it didn’t realize was also the police Welfare and Institution Code). At the fringes were all kinds of nascent and primitive magical bits of kit from companies like Atari, Commodore and Sinclair. They were cheap, a bit brutalist and required a nerdy dedication to make work.
From the very first, I wanted one thing from my computer: I wanted a friend. I desperately wanted to teach that computer to talk to me. In an adolescence marked by movies like Wargames and episodes of Star Trek, I had developed a mind that wanted to see these dreams of a technological future come to life.
I wrote a conversation bot. I typed “Hello”and it responded, “Hi there, how are you?” Then, magic happened. It would look for words like “happy” or “sad” selections based on my 13-year-old responses and it would respond with “that’s great!” or “sorry to hear that!
The next summer I attended a weekend camp at MIT for kids and computers. Most of the kids wanted to create space games. But I was still chasing my talking computer friend — and I had ambitions beyond that. I wanted to teach my friend how to paint with pixels. If I could ever describe a scene from a movie to a computer, could it make the movie? The camp counselors at MIT, beleaguered undergrads making some financial aid money, weren’t going to get me there. Space warfare it was.
Last January, I got a message from a friend. He had found a pulsing little community of code freaks who were using machine learning apps to make pictures based on a description or prompt. He sent me a few pictures. My mind was blown. They were amazing. Some were painterly, delicate brushstrokes and surprising compositions that seemed to be the undiscovered work of masters. Others were photographic, high-resolution images of strange characters or steampunk jewelry, with a deep and luscious depth of field.
Then began a month of sleep deprivation and family abandonment. I could do nothing beyond experimenting with this incredible new image creating “friend.” I tried feeding it fragments of poetry and song, which led to the creation of images I could never imagine but which were spot-on visual representations of narrative. I probed further — what happened if I wanted to create 25 variations of a logo or sample renderings of architectural space by Zaha Hadid? The results kept amazing me. Unexpected results would often bubble up, ranging from hilarious misunderstandings to strange interpretations — or just wrong guesses. But sometimes they were creative leaps that I hadn’t ever thought of.
How did all of this work? One thing to understand is that it’s not creative intelligence. This is pattern matching, or maybe more appropriately pattern finding. These code engines have been exposed to massive datasets: famous art, artists, design movements, contemporary culture, architectural styles, historical events, and consumer information. The more the code can be exposed to and cataloged, the more raw materials it has. In most cases, it starts with visual noise: foggy static that the code chips away at like a sculptor, creating composition, shape and points of view. Then within it, based on the user input, the specifics of the image and style are revealed.
Similar tools abound: copywriting apps that could create blog posts, listicles and long-form writing; teaching apps that take a script and provide a virtual actor speaking and explaining it with convincing sincerity; musical scoring tools that translate a few twists of whimsical emotion and vibe knobs into complete pieces of a song.
So, for real, if you’re a graphic artist, a copywriter or a musician, is this robot coming for your job?
That’s a complicated question. The tech needs more development. Getting specific outcomes out of it isn’t always straightforward. But the quality of the output is impressive. The rate of advancement is a bit blinding. The big purveyors of creative toolsets are already moving fast to deploy this functionality. From word processors to photo retouching to film and game development software, I believe we are about to see an ability to promote the computer from tool to collaborator.
At that point, it does seem inevitable that what humans work on and what computers do will change. Concept art, project treatments, outlines, drafts, social media copy, thumbnail graphic creation, mood boards and elements of game-level design — these are already starting to be tasks that are being taken on by AI.
Humans still need to do the describing. While I think the computers will get there too, in their own way, I am still a believer in something ineffable in the human soul. Maybe because we are a crazy soup of evolution and weird world views, there is poetry, song, beats and ideas that silicon can’t quite get because being messed up in that tragically human kind of way is actually maybe the secret sauce.
In the meantime, I am joyfully playing with my creative robot “friends.” Maybe later on, when they are in charge, they will still come around and make time to play with me.