Artificial Intelligence in Art is Here to Stay.  What Do We Do Next?

Artificial Intelligence in Art is Here to Stay. What Do We Do Next?

Time after time, new innovations do not wait for human society to figure out how we’re going to integrate it. There’s a reason these things are called “disruptive” in business jargon. They shake the box.

For example, Photoshop has had AI powered tools in it for almost a decade now, and nobody’s making that a front-and-center issue. Grammerly has been around for a long time too, and nobody’s pointing at that in panic either.

But AI that can believably regenerate somebody’s voice, or study a few thousand images and make a new image that resembles them in style, and suddenly it’s important.

It’s not that the tools can do it. It’s a matter of degree. This shows us that the problem isn’t that the AI can do it – it’s that the sudden advances have taken us by surprise, and we realize that as a society we have been so busy trying to figure out how we CAN do it, that we haven’t stopped to think about whether we SHOULD.

Getty Sues Everybody

The lawsuit by Getty Images against the creators of Midjourney and Stable Diffusion claim that these tools store images and paste together parts to make new images like an electronic collage.

This is not even remotely how they work. Instead, a special kind of deep learning neural net is trained on the images, producing what is essentially a complex formula with hundreds of mllions of parameters that the AI generation tools use to create new images.

In my opinion these lawsuits will fail immediately on expert testimony because of this gross basic misunderstanding of the technology. Images are not being copied, are not being stored in the database. If they were, you would need thousands of terrabytes to store the data. As it is, Stable Diffusion can generate images on a dataset as small as 2.7 Gb. They don’t even make SD cards or flash drives that small anymore.

A further complication is that in Europe, as in the United States, datamining is legal, so after the question of copying is set aside (to reiterate, it’s not copying, it’s using the images to train a neural network), then it there’s a very good chance that the law suits will fail on the scanning without permission issue as well, because protecting from analysis is not a legal right any copyright holder anywhere in the world enjoys. If it were, simply observing an image displayed on the internet and having any kind of opinion about it would be a crime.

The images are being reduced to parameters in a very complex equation with hundreds of millions of parameters. Datamining isn’t illegal. Training neural networks on material you don’t own isn’t illegal either. Copyrights aren’t being directly violated, because you couldn’t bring up an exact copy of anything the neural nets are trained on if you tried (though you can get close). And, you can’t copyright a style, or a composition, or a color scheme. All that’s left is Right to Publicity, and the responsibility for that falls on the users of the tools, not the tools’ makers.

That doesn’t leave much meat left on the bone.

It’s Just Going Sideways

And sure enough, this is exactly how the law suits are shaking out. Sarah Silverman et al. tried to sue OpenAI for  reading their stuff and incorporating that knowledge into their ChaptGPT model.  The only problem was that they couldn’t make ChatGPT spit out exact copies of their manuscripts.  The New York Times tried the same thing, and had the same problem . Why does this matter?  Because in order for the courts to offer anything to the plaintiffs, first there must be a viable record of wrongdoing.  It’s impossible for the courts to proceed on the basis of being butt-hurt alone. There have to be provable damages.   The court runs on two things above all else:  monetary damages, and proof of injury.  The New York Times — and Sarah Silverman, and the handful of artists trying to sue Midjourney — haven’t established either one. Even to argue undue restraint of trade, the “right to publicity” argument, they have to show exactly how they’ve been hurt by the AI’s, and none of them can demonstrate this.  These cases have been largely thrown out because of these lacks, and all that’s left is the damages from restraint of trade, which none of them can clearly demonstrate.

In my opionion, the writers and artists suing are the victims of class action ambulence chaser lawyers. If they win, mostly the lawyers get the money.  And companies like Getty Images are only suing because they want to make their own generative AI service based on Getty Images licensed images and sell that as a service.  When you can download Stable Diffusion and SDXL for free, why would anybody care?

The Right to Publicity

What remains appears to be Right to Publicity violations – the recognizability of artist styles, or celebrity faces, which have traditionally been treated by the courts as the responsibility of the individuals using the tools, and not the makers of the tools themselves. As a user, it is my responsibility not to try to sell AI generated images that simulate the style of Salvadore Dali, Chris Claremont or Michael Whelan and sell them with the claim that they are by the original artist.

Finally, if I happen to produce output that resembles one of those artists, how much can the original artist claim they have been damaged by such a production when human artists imitate the style of other artists all the time? Cases where one artist considers themselves damaged by someone else emulating their style are virtually nonexistent, and I could find no examples.  Certainly apart from being grumpy about it, few can actually demonstrate in real numbers that their business is being negatively affected by it, if any.  Greg Rutowski comes to mind, and even he is circumspect about it.  He’s concerned, but he’s not losing his shit over it.

Sue the Tool User, Not the Tool Maker

Think about it for a moment: if they can stop Stable Diffusion and Midjourney for being able to replicate the style of other artists, then they should be able to stop all word processors for being able to output written pieces that emulate the style of other writers. Oops, I accidentally wrote a story in the style of Roger Zelazny, they’ll be coming for my copy of Windows Notepad now… Saxaphones should be outlawed because it is possible for another player to use one to replicate the style of Kenny G … Do you see the fallacy here? It’s not clear cut at all, and is in fact a matter of degree, which makes it a purely subjective call. In point of fact, those bringing these amorphous law suits not based on any established rule of law fail to inform the court as to why the existing protections against copyright infringement are insufficient and why the makers of tools are suddenly liable when they never were before now.

In any case, it’s too late to stuff the genie back in the bottle.  AI powered art tools are here. It’s what we do next, to find ways to understand and integrate the new tools, that will define the new landscape.

It Feels Wrong, But Why?

And yet, one way or the other,  we still have the same situation.  Stable Diffusion, underlying technology for all the successful AI image generation tools, is open source.  That makes it very hard to unmake, and even harder to undistribute. Additionally,  while it’s obvious that disruptive technology is generally created for the primary purpose of eventually making money,  it’s doing so here without breaking the law in any obvious way.

And THAT’S where the problem lies. The ability to replicate somebody’s artistic style to produce specific results is the part that’s disruptive. It makes it harder (and I know I’m preaching to the choir here) for artists to get paid for their work and to have the value of their work respected. Artists instinctively know this, but they don’t have much of defense for what’s happening to them, and this makes them feel like victims, and in a real way, they are.

Artists gotta eat. And pay rent. And visit the doctor. And initially, tools that do work they can do are going to break things.

But as with the invention of the camera, and the music synthesizer, artists will adapt their workflows to include the new tools, and those that do will have an incredible competitve edge.

And those that don’t — or can’t — will suffer for it, and as with any new technology, there isn’t a lot we can do to change that, except maybe help them avoid having their stuff analyzed for neural networks, or helping them learn how to use the new tools. The legal questions won’t be resolved soon enough to matter.

Nobody likes to be hit in the face with some new career-threatening problem that they didn’t see coming, and it’s hard to say that three years ago anybody saw this as an impending storm on the horizon. That’s why it feels wrong. It’s doing something with people’s artwork and photographs that nobody saw coming and for which the standard rules for intellectual property offer no protection whatever Whatever is going to happen as a result of this new technology is just going to happen, long before we figure out something practical to do about it, if we figure out anything at all..

Can Anything Be Done?

I can’t imagine how one would unexplode the hand grenade this represents, given that it takes ten to fifteen years to resolve landmark cases in court. By that time, the technology will have evolved well beyond its current state and likely built into practically everything.

The Getty lawsuit against Midjourney, Stable Diffusion et al. will likely fail on the merits because they don’t fully understand what they’re suing over, and they appear to be trying to claim rights they don’t actually have, but it’ll take years to even get that far. They can start their lawsuits over again  and file new cases, but that starts the clock over from scratch.

Nor can they simply use the DMCA and have the source libraries removed from the web (I can’t imagine on what grounds they would do this, because the DMCA only applies to finished works, not tools for making them). Using DMCA’s on this stuff is like a perpetual unwinnable game of whack-a-mole even if somehow you could make it work.

So, I’m going to estimate ten to fifteen years to see anything on this, assuming there isn’t some sort of settlement. Considering Getty is looking for a couple of trillion dollars in damages, and they know they’ll never get that, it seems to me that they’re trying to just scare the ever-loving crap out of the defendants in court, going after settlement money so as to look good to their shareholders. They don’t give a crap about setting a legal precedent. There will be nothing upon which to base new case law, no judgment to cite, and the end result will be money changes hands (if it even gets that far).  Once the lawsuits are over, the tools will just chug along as always, completely undeterred.

And the Getty lawsuits are the best shot at this there is.

A Note about Glaze and Nightshade

Both of these anti-AI image mangler apps attempt to “poison” AI by either adding small non-zero numbers to the latent image before passing it to the diffuser, or by adding “phantom” data to the image to fool the training step for the graphical models into thinking that a picture of a cat is, in fact, a dog. Neither of these really do what they claim to do. Both were developed in the “publish or perish” academic environment, by professors who only understand in general how their anti-AI tools work, and both were built on the efforts of unpaid graduate students who did the actual work. The effectiveness and quality of the results are, therefore, about what you’d expect.

Remember that the point of these tools is not to help artists protect their work.  The point of the tools is to advance the reputation and standing of the professors involved, and few have the technical prowess to demonstrate that they don’t, in fact, work, except in a cleanroom setting where the variables of the test can be strictly controlled.  They were both built to test against Stable Difussion 1.5, which is at this writing two full generations of technology behind that in most common use today. Moreover, the way Nightshade works focuses on token frequency in LAION and LAION tagging, which has been irrelevant for a while now.

Both rely on adding informational noise to the image to create the impression that the image is in a different style than it really is, or contains a different subject than it really does. Both, however, require that a model be trained on a heavy diet of the adulterated images before the trained model will exhibit the desired properties, i.e., to screw up the art styles or the content portrayal. Trust me when I say this: unless you are one of the most prolific artists in the world, and have the time to adulterate everything you’ve ever done over the years and re-upload adulterated versions of what you’ve made, you’re not going to have any affect at all on the training of new models.  Heaven knows, after being trained on literally billions of images, you’re not going to have any affect at all on Midjourney or any of the other similar generative AI systems.  That ship sailed literally years ago.

Most importantly, there is no evidence, apart from extremely narrowly defined tests in carefully controlled environments, that either Glaze or Nightshade work at all. I can’t stress this enough. You are far better off learning and growing as an artist and creating new art than you are hoping that magical fairy dust will protect your old work. The time to set all that up was before any of the major models were built, and anybody with a home computer can train a LoRa on your work and completely bypass whatever effects of either of these tools have.

For more, read this Reddit thread.

 

We Need a Better Plan Than This.

I’m sorry if this is disappointing, but if it’s going to be stopped by the global community, there must be a plan put into motion that works. Intellectual property rights laws and right to access as they stand now simply don’t cover it. The next step is a concensus on what to do, but good luck reaching one. Humans have always acted as individuals. Given a population of a sufficient size, and a given stimulus, they will not choose to do a certain specific thing in response to that stimulus. They will do all the things.

That, to me, is what makes the arguments against generative AI art so frustrating.  If AI art can’t be copyrighted, as many claim, then what rights are being taken from actual artists? There’s nothing to recover, because by that definition AI art has no intrinsic value. It’s all doublethink gobbledegook.

Anything that a human can imagine will eventually be made or built or invented, and sometimes by multiple people at the same time. I believe that AI art tools on this scale were inevitable. It’s how we use them and what we do next that matter.

These images, by the way, were all generated, by me, using a Stable Diffusion. I used Google to do image searches for each of them and I can confirm that they are not other people’s images. They’re unique as far as I can tell.  If you find any of these images and it’s older than the copy posted here, let me know and I’ll take down my copy and reexamine my life.

They’re meant as computer wallpaper. If you see one you like, click on the image to zoom in, then right-click and “Save As.”

 

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Free Modern Lab Backgrounds

Free Modern Lab Backgrounds

I’m playijng with Stable Diffusion now, and my father expressed an interest in good laboratory backgrounds for his videos that he wouldn’t have to worry about accidentally infringing on somebody’s copyright.

Gene to the rescue.  Here you go, Dad.

To everyone else, if you want to use any of these, go right ahead. They are specifically not copyrighted (currently there’s debate on whether images generated by AI can be copyrighted at all), or proprietary, and made for using as background plates in Zoom.   Go nuts.

To Use an Image

  • Click on an image you like, and it will zoom up.
  • Right click on the opened image, and select “Open in New Tab”.
  • In the new tab, right-click again and select “Save As” and you’ll be able to download the image to your hard disk.

Remember that these are all copyright free.  Use them in anything you like, and don’t bother with attribution.

Don’t believe I did these myself?

Well ….

AI Art is Here to Stay.  Better Get Used To It.

AI Art is Here to Stay. Better Get Used To It.

AI Art, or generated art, is a problem, yes, but not for the reasons people think. It’s a problem because nobody was prepared for how rapidly it would impact our world of creatives. Nobody was ready for how hard it would shake the box.

The Argument

The No to AI Generated Images logo, designed by Alexander Nanitchkov
People claim that it steals artwork from the original artists (it doesn’t, only making generalizations made from the observance of the artwork of humans, just as a human artist would do) or that it takes jobs away from humans (TOR Books is in some hot water over a book cover they commissioned that used stock library art that turned out later to have been AI generated). If I paint in the style of Van Gogh (warm saturated earthy colors, impasto, impressionistic, with emphasis on the arcs and swirls that flow between in the negative spaces), am I stealing from his work? No reasonable person would claim this. Now, what If I use an AI Art generator like Midjourney to do the same thing? It’s a shortcut, yes, but stealing, or cheating somehow? To me, it just appears to be a really sophisticated tool, and one in its rocky infancy. It is, however, a new process whose potential as an art tool is understood by very few, and whose operation is understood by even fewer. It is my observation that the alarum being raised is similar to that raised about the rise in popularity of synthesizers as early as the mid-1950’s. Everyone was sure that the synthesizer would put a lot of professional musicians out of work. Of course, that did not happen. It’s true that synthesizers were used in place of an ensemble of real musicians, but in a lot of those situations there just wouldn’t have been money to pay humans.  Instead, music became possible where the alternative would have been silence, canned music taken from something else, or somebody trying to make do with a single guitar or a piano and a set of bongo drums. Synthesizers simply became one more tool in the toolbox.  AI Art is just one more step past CGI, and nobody these days is claiming that isn’t art. A healthy debate is already in full swing. Already facing some backlash from artists, Artstation is allowing artists to opt out of having the artwork they submit to the Artstation web site used to feed AI art generators, and there is an on-going protest there among artists who think Artstation shouldn’t be allowing people to sell AI-generated images there. The site was awash with anti-AI posts protesting the original policy, with the illustrator Alexander Nanitchkov, creator of the No AI logo, proclaiming AI generated work to be “soulless stealing”. The counter-argument to this is, of course, if a human looks at a body of work and says, “Yeah, I think I can paint in that style”, and then does it, is that stealing? Few would argue that studying and replicating somebody else’s art style is theft, because original artwork isn’t being simply copied. Yet, when a machine does it instead of a human, somehow it’s supposed to be different.

How It Works in Very Basic Terms

Superfrog, in the comicbook style of Van Gogh. Midjourney had never seen a Van Gogh comicbook, so it took its cues from Van Gogh paintings and comicbook art it had analyzed. Even so, the elements look just sort of mashed together, and don’t form a cohesive artistic whole. Of course Van Gogh never did comics; the point here is to show that the AI is mashing up concepts, not just copying things.

AI-generated art doesn’t just copy bits and paste them together. Instead, the artificial intelligence is taught about art by looking at a huge number of images, adding noise to each one until it becomes unrecognizeable for what it was, and then taking notes on exactly what made that image recognizable as being a certain thing. The process is repeated on a very large number of similar subjects so that the AI can tell, in general, what makes that subject look like what it is. This may include photographs, or the work of human artists, but always in great quantity, usually tens of thousands or more. To generate a new image, the process is reversed. It begins with a noise field, and then everything that doesn’t look like the requested subject is slowly repaired. It’s further skewed by another instruction layer that adds other elements to the scene as described, to create a new and unique image. The resulting image may contain varying percentages of a given individual’s artwork, but it’s never a straight up copy.

It Needs What It’ll Never Have On Its Own: A Little Heart

Synthesized art suffers the same problem that synthesized music does: it lacks heart. A performance in either medium created solely by algorithm lacks the human touch, the emotional connection that makes that creative product worth consuming. Without it, it’s just an attractive but ultimately soulless effort. It can save time producing creative content, but without the guidance of an actual artist it will produce only the facade of meaning without ever actually touching it. As a result, AI created art is actually pretty easy to spot when you see it. I predict that there will be a great deal of arguing back and forth about AI art, but in the end, people will pause long enough to realize that AI art can’t reasonably compare to the creativity of a skilled human artist, and we’ll all get on with our lives. There is precedent; this is pretty much how the arguments against synthesizers went.  After a while people realized that the synthesizer was just another tool, and in the wrong hands it could produce flavorless pap just like any other tool in any other medium—or in the other direction, allow the art form to be taken to new places previously inaccessible. AI-generated art is like a chainsaw: it can do a lot of damage very fast, and it seems dangerous to be around. Without its human guiding what it does, though, it’s just another tool to be tamed. And, after a while, we’ll get used to the idea that there are such things as chainsaws in the world that do useful things.
Superfrog, in the style of Jack Kirby, third iteration of the prompt, created in MidJourney.

Superfrog in the style of Jack Kirby. Has Jack Kirby ever drawn a superhero frog? Not that I know of. The heavy bombastic ink and color style reminiscent of Kirby is here in these images, but nobody would mistake one of these for a Kirby original.
These are a good jumping off point (pardon the pun), and may be most useful as a tool for ideation, but repeatability is still very dodgy. 
The frog with the spitcurl is just a goofy take on Superman. Artificial intelligence alone will only carry you so far. The rest requires an actual artist to make some creative decisions and use the elements to create actual art.
Oh, and don’t look too closely at the hands. That’s some real nightmare fuel.

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Reprinted from [SCIFI.radio]  
Finally, I’m a Director

Finally, I’m a Director

This is not how I thought this was going to go.

My first director’s credit was supposed to happen 30 years ago. That’s how I saw it all happening in my head, anyway. But I quickly found out that unless you’re born into the system at the right level of connectivity, that’s just not going to happen. If you have responsibilities to anyone but yourself, it’s just not in the cards, because you can’t risk letting them down.

And so it went, until I was 61, and I was finally in a position in my life to try something, because at this point I had to try something to move forward because nothing else was working anyway. And what I did was this.

Aphrodite and Ben from ‘Mighty Aphrodite!’

I created an animated web series almost on a whim, using a machinema engine that ran on my phone. We made a Kickstarter, it succeeded, and by the time we’re done we’ll have four animated episodes, about 3 minutes long each.

Gone with the Wind it is not. But it’s real, and it’s mine, and it’s my first producer’s credit, my first writer’s credit, my first director’s credit. As small a project as this thing is, I brought this into being by sheer force of will, and with the help of my wife Susan (without whose support it wouldn’t have been possible, and without whose participation it would have suffered from a character arc standpoint), and my actor and voice actor friends, we made a thing. It’s up on IMDB now, and it gives proper credits to everyone who worked on it.

The thing is, in my 20’s I thought I was going to be a director by the age of 30. I went to film school, graduated from UCLA, concentrated on screenwriting because it was cheaper than paying for all that film lab work, and I had a bunch of friends at the time who were all going into terrible debt paying for their student films. So I got my degree and out into the world I went.

And part of it was because UCLA at the time was not all that great a film school, and part of it was because I lacked the industry connections to make any impression on anybody, but my career foundered after that, and I went into computer programming and game development instead, and it was only after years of that that I finally came back full circle. Computers were now being used to make movies with, and I sort of slipped in the back door while nobody was looking and ended up with some 30 odd film credits. Unfortunately since I was working for an often neglected department in a very large studio, I almost never got screen credit for the work I did.

No matter. I still did the work, I still learned what a world class organization looked like from the inside, I still learned what world class artists and animators did every day and if not in every detail how they did it, at least what they did and where to look things up.

And now my lifelong dream of becoming a director and writer has come to pass, but it’s on the smallest project one could imagine. But it’s a commercial project, for a company – my own company, which I founded – and there’s an IMDB listing.

What more may come of Mighty Aphrodite! The Web Series? I have no idea, but I bet we can make some waves with it once I get the fourth episode done – and then we can release them all as a single piece, a ‘fifth episode’, if you will, which will be a good solid fifteen minutes of animated narrative.

I’m certainly humbled by the entire process. I imagined myself at the helm of much greater projects than this, but starting with literally nothing but an idea, I and my friends made something happen. We moved the needle.

I’ve always wanted a home at the Magic Store. I didn’t anticipate either that I’ve have to build the Magic Store myself, nor that the roof might be made of cardboard.

This year I’m hoping to put some shingles on that roof.

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Mighty Aphrodite: Animating is @#$#@ Hard Work.

Mighty Aphrodite: Animating is @#$#@ Hard Work.

This is probably obvious to everyone reading this, professionals and fans alike, but animation is hard work. I’m learning this the hard way. I’m in the middle of production of my first animated web series Mighty Aphrodite!, and I’m quickly finding out that there are a lot of hidden tasks involved in producing something like this that actually haven’t anything to do with animation at all.

It’s fundraising, yes, but after that it’s writing, and scheduling, and recording voice artists, and editing.

And then it’s design and animation (in my case nearly all the design work was done by somebody else, an artist at the company who makes Plotagon), and then you have to render it all out. It was supposed to be a short little thing, just a few quick inserts to cover things Plotagon couldn’t do.

Ben is holding a box. You can’t do this in Plotagon either.

And then reality hit. Plotagon, as neat as it is, really isn’t suited for dramatic storytelling. Not really. Your actors can stand or sit in interesting settings and talk to each other. And that’s it. No walking through the scene, no getting up or sitting down as a motion, no carrying anything, no hand props (unless you count a cell phone welded to their hand), no running, no falling down, no dancing (unless you count dancing in place doing a weird sort of Austin Powers dance move). Even something as simple as a character handing a bag of coins to another character requires special animation.

So, you do your best, and you light everything, and render it out, and then you discover that you haven’t checked your scene well enough before sending it to the render queue, and you’ve just wasted $100 of render farm resources, and you didn’t have it to spare. Vowing not to waste any more money, you render it on the one machine you have, and 216 frames takes 3.5 days. So you’re now trading dollars for time.

Aphrodite standing up from a seated position. You absolutely positively cannot do this in Plotagon.

Some people use a game engine to produce their animation. Some animate straight up in Blender, or Maya. I’m doing a hybridized approach, animating using something similar to a game engine, and then padding out its capabilities when I hit something in the script that I need to do that it can’t do. The next result is that, at most, I have to hand animate perhaps 500 frames out of the some 8000 frames that comprise the episode, which is an enormous savings of time and effort. I only have to animate about 6% of the completed episode, and while that sounds great, and it means my production costs are $300 to $400 per episode instead of $25,000, it’s still a daunting, soul sucking amount of work. The production literally owns you until it’s done.

So far my damned project is about four months behind schedule. Thank God my backers are all behind me and being patient. But boy, lesson learned. An errant line in a script can mean weeks of extra expense and production effort. I’m so looking forward to finishing this episode, so I can get to work on the next two. This is a story that needs to be told, and we need significantly more money than I got on the first Kickstarter to make it not painful to produce the next batch of episodes.

The payoff, though, should be pretty huge. I’m using Plotagon to save me 95% of my production costs and time, at least, but it’s something that isn’t likely to be spawning a hoard of imitators. My show is going to set some records, and hopefully be greater than the sum of its parts.

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The Patreon Quandry

The Patreon Quandry

Obi-Shawn’s t-shirt design for his morning show on Krypton Radio, “Good Morning, Tatooine!”

This was written in 2017. We changed the name of the station to SCIFI.radio on January 25, 2021.
We use Patreon to keep our sci-fi radio station, Krypton Radio, fueled up and on the air, and it’s been working for years. However, it’s also a struggle, and we’re not doing anywhere near as well as we should be given the size of the market. Getting the word out is an enormous problem when what you do is a service, not putting 100% of your energy into a single one-shot incendiary mortar shell of a geeky project.
Here’s what I’ve learned so far.

Patreon is Hard

The main issue with Patreon is that you have to live there to make it work. You can’t run your stuff out of your web site and visit only occasionally, you pretty much have to move into Patreon and run your entire operation from there.
For most creators, that’s a real problem, because they’ve spent years developing a following on the web and in social media, and it’s very hard to get your fans to follow you over to Patreon, and it’s hard to keep their attention once you do. Patreon is not social media, and it lacks all the things that make people hang around for extended periods. Once your patron is done reading your page, there’s nothing else to keep them there.
Very very recently Patreon has released a plugin for WordPress that makes it possible to post Patrons-only content on your own web site, so that lets you bring the Patreon to the fans instead of having to do it the other way around, and we’re about to start experimenting with members-only content that way. We have no idea how much or how little that will help yet, it’s totally uncharted territory for us.
One important factor with Patreon is that you have to be very very active in it or people will think you’re out of business. A post a week isn’t bad. Two a week is probably optimal.
Another important factor is that you’re going to have to plan your productivity to include creating assets specifically for Patreon that aren’t directly part of whatever creative thing it is that you do. You’ll need videos, graphics, short articles, sound bytes, all sorts of things specifically shaped to the needs of running a continuous crowdfunding campaign. It’s like running a Kickstarter, but you never get a break and it never stops.

But Does It Work?

Well – I can honestly say that we wouldn’t have a radio station if it didn’t work.
Advertising certainly doesn’t work. Nobody clicks on anything, and web browsers are built to filter them out by default. Kickstarters are a pain, and very stressful and make you crazy. Subscriberships are the only way to go if you want to be paid every month for what you do.

What About the Perks?

That’s one of the things we’re struggling with.
We produce audio, so there’s no finite physical product that we can send people. We have to come up with content specifically geared to being output in little parcels that our fans would want, so we’re exploring publishing fiction exclusively for our subscribers.
We’re also developing a sci-fi radio drama, and when that comes out we’ll have props and costumes, and challenge coins, and patches, but it’s a massive push to get it done, and it’s taking years longer than we planned to do this.
We also feature a line of sci-fi / geek t-shirts that we’ve designed ourselves that nobody else carries, and you’d think that would be an attractant, but to be completely honest, apparently nobody gives a @#$#@ about t-shirts. Like, at all. We’ve given away maybe two of them as perks in the last two years when people ask for them, despite the fact that half our patrons are eligible for them.

White Elephant? Why, Yes. Yes We Are.

Part of our problem stems from what we are. We’re a full time sci-fi fandom format radio station, and that makes us unique on the planet (one or two other stations lay claim to this, but they also do things like fill up 60% of their air time with metal or hiphop).  We don’t fit categories. In anything.
Most radio station listing services don’t even have a listing category for us, so we get stuck in “Other”, or “Eclectic”. Nobody searches for “other” when they’re looking for a radio station, and people don’t think to search for sci-fi radio because all they get is podcasts when they try it – so we’re hard to categorize, hard to find, and searched for much less than we’d like because people don’t even realize that full time sci-fi radio (as contrasted to a podcast) is a thing.
Our response for that is to hit as many distribution platforms as we can. We get another dozen patrons, and we will be able to get listed on iHeartRadio. Suddenly we’ll be exposed to 70 million iHeartRadio subscribers, and available in people’s cars, which is where most people listen to the radio in the first place. We’re hoping our fortunes will improve after that.

What’s Next?

Our biggest problem is that since nobody knows we’re here, relatively speaking, we have to maximize our exposure. We have to position ourselves so that the maximum number of people have a chance to find us by serendipitous search.  I can’t tip my hand just yet, but there’s another distribution network we’re looking at in addition to iHeartRadio, and between the two of them we’ll have exposure to a new potential audience of 190 million people that we didn’t have access to before. We’ve never made a jump this big before, and surprisingly, the two services we’re going after will make us big fish in a small pond despite the huge subscriber numbers for each service.
The reason is, once again, that Krypton Radio is unique. Literally nobody else in the world does what we do the way we do it. It’s not like regular radio stations. How many hip-hop stations are there across the country? About 250. Rock? About 360. Oldies? Oh my god, 500 plus of those. Metal?   You get the idea.
But full time sci-fi geek culture genre format stations?  There’s one. When people look for that, they find us, and that’s it. I’m hoping to improve our odds by expanding our “broadcast range” so to speak.
Nine tenths of success is not giving up. We’re already heard in 135 countries and we reach between 65,000 and 100,000 listeners a month depending on the season.
So far, so good.

Fast Forward to 2021

And now our Patreon campaign is moved to the new URL, https://patreon.com/scifiradio.  And I’ve learned a few things.

Don’t Be Stingy

Expect to send out about 30% of what you get as perks. People pay money to get stuff, as much as to help you. Show your true appreciation, even if it hurts a little. You’ll be much better off. Of course, you do have to make your goals, so you’re walking a fine line when you’re just starting up. It helped a lot that Patreon started doing fulfillments as a service, so that we can spend our time actually doing the thing instead of churning around trying to do fulfillments, which we were very bad at.

Name Yourself Something that Makes Sense

When we changed our name from Krypton Radio to SCIFI.radio on January 25, 2021, suddenly our findability and listener traffic jumped 30% – and it stayed there. It was a permanent boost, and the boost we needed. Now we’re reaching 300,000 listener connections a month, over about 110,000 uniques. This, in turn, has translated to a big boost in Patreon receipts, a bigger jump since the January name change than we’ve ever seen in the history of the station.