Generative AI is all the rage now. I suppose there might be some applications for it, but you will not see any of it in my work. What I show is entirely created by me, and I have no plans of ever changing that.
It’s all around
The news is full of hype about ChatGPT and Bard and, for images, DALL-E 2. Tech companies are inventing hundreds of billions (yes, “billions”) in it, so it must be about to take over everything, right?
It is hard to read anything without seeing references to the coming revolution. It is the “next big thing” in tech. MIcrosoft, for instance, has invested huge in ChatGPT and says it will embed it in its browser and all of its applications. With so much press and money and interest, it must be true, right? Maybe.
But do you understand what it is?
What is AI?
I have said before that I am a reforming Engineer. Well, I must admit that at one time I was involved in AI applications. I even believed in it at the time. That is just to say I have some technical background in the subject, so I am not just quoting press releases.
“Artificial Intelligence” is a weird term. It is definitely artificial. Whether or not it represents intelligence is debatable. To me, there is no real “intelligence” involved. It is just a fancy computer algorithm with a lot of data embedded in it.
The AI that is hyped today is called neural networks. It is based on a fairly simple structure that tries to mimic the way the human brain is organized by simulating neurons and synapses. Then they train the network with huge sets of data. The connections and values of the neurons and synapses are adjusted to give a desired output for a given input.
To over-simplify it, imagine a patient teacher trying to train a neural net to recognize an egg. They “show” it a picture of an egg and say “this is an egg” and let the network adjust its values to give a positive output. Then they show it a picture of something else and say “this is not an egg” and again let the network adjust its values to give a negative output. Repeat it over and over thousands, maybe millions of times with different pictures. Eventually the neural net would get pretty good at identifying an egg, if the training data was good enough and extensive enough.
But so what? The AI does not at that point know what an egg is. It just classifies shapes as being one or not.
What is the good of it?
We are discussing generative AI, so I will try to focus on that. Generative AI takes a request to make a picture or song or some such work, maybe based on the style of another artist. You could say “make a picture of a tree in the style of van Gogh”. It would make one. It would probably look like something Vincent might have done.
If you were generating the image for an advertisement, you might be able to simulate a certain style without the encumbrances of creative fees or intellectual property laws. For you, the user of the image, you get to bypass paying the artist. Or maybe, charitably, you get something you wish the artist had created, but they did not.
Many companies are very eager to have AI trained to be able to produce minimally acceptable results faster and cheaper than a human. Be aware of those companies that want to get rid of their people and replace them with minimal acceptable results. Have you used an AI-based chat agent to try to get support from a company? My results have been way below minimum acceptable. Maybe search engines is the best application for these bots. Most of the search results already can’t be trusted.
So for someone wanting something cheap for a practical use, it can be a good thing.
Is it art? I have my opinion, but let’s get to that in a minute.
What are the limitations?
Neural network-based AI only “knows” what it is trained to do. Its abilities are limited strictly by the data it is fed. And I used “know” in quotes because, one of the great limitations of this system is that it doesn’t know what it knows. It doesn’t even know what knowing is.
AI cannot explain it’s actions. The data compressed into its network has been stripped away from its source. This is going to become one of the major limitations that will cripple it or stop it’s use. So, for instance, when an AI system turns you down for a loan, you cannot force it to explain why. All it can say is that you just didn’t meet the pattern. Lawsuits will come of this.
And it may produce wonderful seeming results, but it is a cheap trick. AI products are a regression to the average, at best. That is, a large set of training data defines the average of whatever domain is being learned. This is all it knows. It does not understand the difference between unacceptable and acceptable and exceptional results. It does not understand the concepts behind what it is doing at all.
So when you ask it to make a picture of a tree in the style of van Gogh, its data bank has many images of trees. It has encodings of parameters describing patterns of van Gogh’s style. It can mix them and make something. But it can’t step back and say “Wow, that is great. I’m proud of that! That is good art.” There is no more feeling than a tax form.
Where does the training data come from?
This is a little off topic of the quality of the results, but have you considered where this huge volume of training data comes from? Google, Meta, Amazon, Microsoft and many, many others, including your Government, collect and use all the information they can find . This includes public data like Wikipedia or the Library of Congress, but also everything they can scrape up about you. So every network search you have ever done, every web page you have ever visited, all of your email, all of your pictures, your contacts, your contacts contacts, every post you have ever made, your facial images, your job, your salary, your spending habits, all of your telephone calls, everything is just free data to them.
This is all used without your permission or control. So for an artist, for example, all of their online works can be used to train the AI to do better to try to replace them. And with no compensation or attribution.
There is currently no accountability for AI or the companies profiting from it. It has been proven that much of the training data used was biased or incorrect, producing bogus responses from ChatGPT. And Google’s Bard got a black eye the day it was announced when it gave false information to a query about the Hubble telescope. No accountability, no ability to explain.
A passing fad?
One part of me thinks AI is just another passing fad. It has come and gone before. AI was going to revolutionize the world about 20 years ago or so. It died. Now the pundits are enamored with it again. Most of them are too young to realize it died of natural causes already. But venture capitalists and tech gurus are very quick to throw billions of dollars at “the next big thing”, even if it has been unable to generate any money.
But no, I’m afraid we will have to live with this for a while. Too many billions have been invested for it to die soon. And it can show some limited tricks. Either you believe AI is a higher and more perfect form of life that will make the world better or you don’t. I don’t.
Not on my watch
Lots of rambling, but back to the adoption of generative AI. As far as I can see, I will never use this in my art. This is not like the introduction of digital imaging, where film purists wailed about the passing of a wonderful era. This is not a technology shift, it is a tool that plans to eliminate artists.
I will use useful tools, like sky selection in LIghtroom or Photoshop, but that is just a force multiplier to get my job done quicker. I could do the same thing myself and I can often get better results. It is like a woodworker using a planer to smooth a tabletop quickly rather than spending hours sanding it. You don’t say the tool created the piece of furniture.
When you see images from me, they were created personally by me. I don’t and do not plan to use AI to create my art. I don’t think art created by AI is really art, but that gets into the argument of what art is. What I call art is only created by humans.
Call me a Luddite, but I believe only humans can actually create.