The Murky Ethics of AI-generated Images

The other day, I was playing with Stable Diffusion, one of the new generative AI products out there, and I found myself in an ethical quandary. Or maybe quandaries.

More specifically, I was playing with putting famous haiku poems into the “Generate Image” box and seeing what kinds of images the Stable Diffusion generator would concoct.

It was pretty uninspiring stuff until I started adding the names of specific illustrators in front of the haiku. Things got more interesting artistically but, from my perspective, murkier ethically.

The Old Pond Meets the New AIs

The first famous haiku I used was “The Old Pond” by Matsuo Bashō. Here’s how it goes in the translation I found:

An old silent pond

A frog jumps into the pond—

Splash! Silence again.

At first, I got a bunch of photo-like but highly weird and often grotesque images of frogs. You’ve got to play with Stable Diffusion a while to see what I mean, but here are a a few examples:

Okay, so far, so bad. A failed experiment. But that’s when I had the bright idea of adding certain illustrators’ names to the search so the generator would be able to focus on specific portions of the reticulum to find higher quality images. For reasons that will become apparent, I’m not going to mention their names. But here are some of the images I found interesting:

Better, right? I mean, each one appeals to different tastes, but they aren’t demented and inappropriate. There was considerable trial and error, and I was a bit proud of what I eventually kept as the better ones.

“Lighting One Candle” Meets the AI Prometheus

The next haiku I decided to use was “Lighting One Candle” by Yosa Buson. Here’s how that one goes:

The light of a candle

Is transferred to another candle—

Spring twilight

This time I got some fairly shmaltzy images that you might find in the more pious sections of the local greeting card aisle. That’s not a dig at religion, by the way, but that aesthetic has never appealed to me. It seems too trite and predictable for something as grand as God. Anyway, the two images of candles below are examples of what I mean:

I like the two trees, though. I think it’s an inspired interpretation of the poem, one that I didn’t expect. It raised my opinion of what’s currently possible for these AIs. It’d make for a fine greeting card in the right section of the store.

But, still not finding much worth preserving, I went back to putting illustrators’ names in with the haiku. I thought the following images were worth keeping.

In each of these cases, I used an illustrator’s name. Some of these illustrators are deceased but some are still creating art. And this is where the ethical concerns arise.

Where Are the New Legal Lines in Generative AI?

I don’t think the legalities relating to generative AI have been completely worked out yet. Still, it looks like does appear that artists are going to have a tough time battling the against huge tech firms with deep pockets, even in nations like Japan with strong copyright laws. Here’s one quote from the article “AI-generated Art Sparks Furious Backlash from Japan’s Anime Community”:

[W]ith art generated by AI, legal issues only arise if the output is exactly the same, or very close to, the images on which the model is trained. “If the images generated are identical … then publishing [those images] may infringe on copyright,” Taichi Kakinuma, an AI-focused partner at the law firm Storia and a member of the economy ministry’s committee on contract guidelines for AI and data, told Rest of World….But successful legal cases against AI firms are unlikely, said Kazuyasu Shiraishi, a partner at the Tokyo-headquartered law firm TMI Associates, to Rest of World. In 2018, the National Diet, Japan’s legislative body, amended the national copyright law to allow machine-learning models to scrape copyrighted data from the internet without permission, which offers up a liability shield for services like NovelAI.

How About Generative AI’s Ethical Lines?

Even if the AI generators have relatively solid legal lines defining how they can work, the ethical lines are harder to draw. With the images I generated, I didn’t pay too much attention to whether the illustrators were living or dead. I was, after all, just “playing around.”

But once I had the images, I came to think that asking the generative AI to ape someone’s artistic style is pretty sleazy if that artist is still alive and earning their livelihood through their art. That’s why I don’t want to mention any names in this post. It might encourage others to add the names of those artists into image generators. (Of course, if you’re truly knowledgeable about illustrators, you’ll figure it out anyway, but in that case, you don’t need any help from a knucklehead like me.)

It’s one thing to ask an AI to use a Picasso-esque style for an image. Picasso died back in 1973. His family may get annoyed, but I very much doubt that any of his works will become less valuable due to some (still) crummy imitations.

But it’s a different story with living artists. If a publisher wants the style of a certain artist for a book cover, for example, then the publisher should damn well hire the artist, not ask a free AI to crank out a cheap and inferior imitation. Even if the copyright system ultimately can’t protect those artists legally, we can at least apply social pressure to the AI generator companies as customers.

I think AI generator firms should have policies that allow artists to opt out of having their works used to “train” the algorithms. That is, they can request to be put on the equivalent of a “don’t imitate” list. I don’t even know if that’s doable in the long run, but it might be one step in a more ethical direction.

The Soft Colonialism of Probability and Prediction?

In the article “AI Art Is Soft Propaganda for the Global North,” Marco Donnarumma takes aim at the ethics of generative AI on two primary fronts.

First is the exploitation of cultural capital. These models exploit enormous datasets of images scraped from the web without authors’ consent, and many of those images are original artworks by both dead and living artists….The second concern is the propagation of the idea that creativity can be isolated from embodiment, relations, and socio-cultural contexts so as to be statistically modeled. In fact, far from being “creative,” AI-generated images are probabilistic approximations of features of existing artworks….AI art is, in my view, soft propaganda for the ideology of prediction.

To an extent, his first concern about cultural capital is related to my previous discussion about artists’ legal and moral rights, a topic that will remain salient as these technologies evolve.

His second concern is more abstract and, I think, debatable. Probabilistic and predictive algorithms may have begun in the “Global North,” but probability is leveraged in software wherever it is developed these days. It’s like calling semiconductors part of the “West” even as a nation like Taiwan innovates the tech and dominates the space.

Some of his argument rests on the idea that generative AI is not “creative,” but that term depends entirely on how we define it. Wikipedia, for example, states, “Creativity is a phenomenon whereby something new and valuable is formed.”

Are the images created by these technologies new and valuable? Well, let’s start by asking whether they represent something new. By one definition, they absolutely do, which is why they are not infringing on copyright. On the other hand, for now they are unlikely to create truly new artistic expressions in the larger sense, as the Impressionists did in the 19th century.

As for “valuable,” well, take a look at the millions if not billions of dollars investors are throwing their way. (But, sure, there are other ways to define value as well.)

My Own Rules for Now

As I use and write about these technologies, I’ll continue to leverage the names deceased artists. But for now I’ll refrain from using images based on the styles of those stilling living. Maybe that’s too simplistic and binary. Or maybe it’s just stupid of me not to take advantage of current artistic styles and innovations. After all, artists borrow approaches from one another all the time. That’s how art advances.

I don’t know how it’s all going to work out, but it’s certainly going to require more thought from all of us. There will never be a single viewpoint, but in time let’s hope we form some semblance of consensus about what are principled and unprincipled usages of these technologies.

Featured image is from Stable Diffusion. I think I used a phrase like "medieval saint looking at a cellphone." Presto.    

The Rising Seas of AI-Generated Media

We are about to be awash in AI-generated media, and our society may have a tough time surviving it.

Generated by Stable Diffusion. The prompt was “Dali tsunami”

Our feet are already wet, of course. The bots inhabit Twitter like so many virtual lice. And chatbots are helpfully annoying visitors on corporate websites the world over. Meanwhile, algorithms have been honing their scribbler skills on the virtual Grub Street of the Internet for a while now.

But soon, and by soon I mean within months, we will be hip deep in AI-generated content and wondering how high the tide is going to get.

My guess is high, baby. Very high indeed.

What Are We Really Talking Here?

Techopedia defines generative AI as a “broad label that’s used to describe any type of artificial intelligence that uses unsupervised learning algorithms to create new digital images, video, audio, text or code.”

Generated by Stable Diffusion. Prompt was “network”

I think that label will ultimately prove too restrictive, but let’s start there. So far, most of the hype is indeed around media, especially image creation and automated writing, with music and video not being far behind.

But we’ll get to that.

For now it’s enough to say that generative AI works by learning from, and being “inspired by,” the dynamic global reticulum that is the Internet.

But generative AI also applies to things like computer code. And, by and by, it’ll start generating atoms in addition to bits and bytes. For example, why couldn’t generative AI be applied to 3D printing? Why not car and clothing design? Why not, even, the creation of new biological systems?

The Money Generator

First, let’s follow the money. So how much dough is going into generative AI these days?

Answer: how much you got, angels and VCs?

Generated by Stable Diffusion. Prompt “printing press printing money”

For example, a start-up called Stability AI, which created the increasingly popular Stable Diffusion image-generating algorithm, was recently injected with a whopping $101 million round of investment capital. The company is now valued at a billion bucks.

Meanwhile other image generators such as DALL-E 2 and Midjourney have already acquired millions of users.

But investors are not just hot for image generators. Jasper, a generative writing company that’s just a year old (and one that plagues me with ads on Facebook) recently raised $125 million in venture capital and has a $1.5 billion valuation.

Investing in these technologies is so hot that a Gen AI Market Map from Sequoia recently went viral. The wealth wave rises and everyone wants to catch it.

Running the Gamut

Although image and prose (usually with an eye toward marketing) are the hot tickets in generative AI for now, they are just the proverbial tip of the iceberg. Indeed, it appears that Stability AI, for one, has much grander plans beyond images.

Generated by Stable Diffusion. Prompt was “color gamut”

The New York Times reports that the company’s soon-to-be massive investments in AI hardware will “allow the company to expand beyond A.I.-generated images into video, audio and other formats, as well as make it easy for users around the world to operate their own, localized versions of its algorithms.”

Think about that a second. Video. So people will be able to ask generative AI to quickly create a video of anything they can imagine.

Fake Film Flim-Flams

Who knows where this leads? I suppose soon we’ll be seeing “secret” tapes of the Kennedy assassination, purported “spy video” of the Trump/Putin bromance, and conspiracy-supporting flicks “starring” a computer-generated Joe Biden.

Generated by Stable Diffusion. Prompt was “human shakes hands with extraterrestrial”

We can only imagine the kind of crap that will turn up on YouTube and social media. Seems likely that one of the things that generative AI will generate is a whole new slew of conspiracists who come to the party armed with the latest videos of Biden handing over Hunter’s laptop to the pedophiliac aliens who wiped Hilary’s emails to ensure that Obama’s birth place couldn’t be traced back to the socialist Venusians who are behind the great global warming scam.

Even leaving political insanity aside, however, what happens to the film and television industries? How long until supercomputers are cranking out new Netflix series at the rate of one per minute?

Maybe movies get personalized. For example, you tell some generative AI to create a brand new Die Hard movie in which a virtual you plays the Bruce Willis role and, presto, out pops your afternoon’s entertainment. Yippee ki yay, motherfucker!

Play that Fakey Music

Then there are the sound tracks to go with those AI-gen movies. The Recording Industry Association of America (RIAA) is already gearing up for these battles. Here’s a snippet of what it submitted to the Office of the U.S. Trade Representative.

Generated by Stable Diffusion. Prompt was “music”

There are online services that, purportedly using artificial intelligence (AI), extract, or rather, copy, the vocals, instrumentals, or some portion of the instrumentals (a music stem) from a sound recording, and/or generate, master or remix a recording to be very similar to or almost as good as reference tracks by selected, well known sound recording artists.

To the extent these services, or their partners, are training their AI models using our members’ music, that use is unauthorized and infringes our members’ rights by making unauthorized copies of our members’ works. In any event, the files these services disseminate are either unauthorized copies or unauthorized derivative works of our members’ music.

That’s an interesting argument that will probably be tried by all creative industries. That is, just training your AI based on Internet copies of musical works violates copyright even if you have no intention of directly using that work in a commercial project. I imagine the same argument could be applied to any copyrighted work.

Of course, there are plenty of uncopyrighted works AI can be trained on, but keeping copyrighted stuff from being used for machine learning programs could put a sizeable dent in the quality of generative AI products.

So, it won’t only be media that’s generated. Imagine the blizzard of lawsuits until it’s all worked out.

Stay tuned.

Revenge of the Code

AI can code these days. Often impressively so. I suppose it’d be ironic if a lot of software developers were put out of work by intelligent software, but that’s the direction we seem headed.

Consider the performance of DeepMind’s AlphaCode, an AI designed to solve challenging coding problems. The team that designed it had it compete with human coders to solve 10 challenges on Codeforces, a platform hosting coding contests.

Generated by Stable Diffusion. The prompt was “Vinge singularity”

Prof. John Naughton writing in The Guardian describes the contest and summarizes, “The impressive thing about the design of the Codeforces competitions is that it’s not possible to solve problems through shortcuts, such as duplicating solutions seen before or trying out every potentially related algorithm. To do well, you have to be creative.”

On its first try, AlpaCode did pretty well. The folks at DeepMind write, “Overall, AlphaCode placed at approximately the level of the median competitor. Although far from winning competitions, this result represents a substantial leap in AI problem-solving capabilities and we hope that our results will inspire the competitive programming community.”

To me, a very amateurish duffer in Python, this is both impressive and alarming. An AI that can reason out natural language instructions and then code creatively to solve problems? It’s kind of like a Turing test for programming, one that AlphaCode might well be on target to dominate in future iterations.

Naughton tries to reassure his readers, writing that “engineering is about building systems, not just about solving discrete puzzles,” but color me stunned.

With this, we seem to be one step closer to Vernor Vinge’s notion of the technological singularity, in case you needed another thing to keep you up at night.

Up and Atoms

Movies? Music? Code?

What’s next for generative AI once it finds its virtual footing?

Generated by Stable Diffusion. Prompt was “atoms”

Well, atoms are the natural next step.

Ask yourself: if generative AI can easily produce virtual images, why not sculptures via 3D printers? Indeed, why not innovative practical designs?

This is not a new idea. There is already something called generative design. Sculpteo.com describes, “Instead of starting to work on a design from scratch, with a generative design process, you tell the program what you need to accomplish, you set your design goals and mention all the parameters you can. No geometry is needed to start a project. The software will then deliver you hundreds or thousands of design options, the AI can also make an in-depth analysis of the design and establish which one is the most efficient one! This method is perfect to explore design possibilities to get an optimal part.”

Yup, perfect.

How About Bio?

Generated by Stable Diffusion. Prompt was “bioprinter”

Not long ago, I wrote a tongue-in-cheekish post about the singularity. An acquaintance of mine expressed alarm about the idea. When I asked what scared her most, she said, “If AI can alter DNA, I’d say the planet is doomed.”

That particular scenario had never occurred to me, but it’s easy enough to see her point. DNA is biological code. Why not create a generative AI that can design new life forms almost as easily as new images?

Generated by Stable Diffusion. Prompt was “live cells”

In fact, why stop at design? Why not 3D print the new critters? Again, this is a concept that already exists. As the article “3D Bioprinting with Live Cells” describes it, “Live cell printing, or 3D bioprinting, is an emerging technology that poses a revolutionary development for tissue engineering and regeneration. This bioprinting method involves the creation of a spatial arrangement of living cells and biologics into a functionalized tissue.”

The good news? Probably some fascinating new science, designer replacement organs on demand, and all the strange new machine-generated meat you can eat!

The bad news? Shudder. Let’s not go there today.

Mickey Mouse and the Age of Innovative AI

Although we’re calling this generative AI, the better term might be innovative AI. We are essentially contracting AI writers, artists and coders to do our bidding. Sure, they’re imitating, mixing and matching human-made media, but they are nonetheless “the talent” and will only get better at their jobs. We, on the other hand, are promoted to the positions of supercilious art directors, movie producers and, inevitably (yuck) critics.

Generated by Stable Diffusion. Prompt was “Tim Burton 3 people caught in whirlpool”

If the singularity ever actually happens, this emerging age of innovative AI will be seen as a critical milestone. It feels like a still rough draft of magic, and it may yet all turn out wonderfully.

But I find it hard not to foresee a Sorcerer’s Apprentice scenario. Remember in Fantasia, when Mickey Mouse harnesses the power of generative sorcery and winds up all wet and sucked down a whirlpool?

Unlike Mickey, we’ll have no sorcerer to save our sorry asses if we screw up the wizardry. This means that, on sum, we need to use these powerful technologies wisely. I hope we’re up to it. Forgive me if, given our recent experiences with everything from social media madness to games of nuclear chicken, I remain a bit skeptical on that front.

Feature image generated by Stable Diffusion. The prompt terms used were "Hokusai tsunami beach people," with Hokusai arguably being the greatest artist of tsunamis in human history. In other words, the AI imitated Hokusai's style and came up with this original piece.