Daniel Binns is a media theorist and filmmaker tinkering with the weird edges of technology, storytelling, and screen culture. He is the author of Material Media-Making in the Digital Age and currently writes about posthuman poetics, glitchy machines, and speculative media worlds.
Made by me in, of course, Procreate (27 Aug 2024).
The team behind the powerful and popular iPad app Procreate have been across tech news in recent weeks, spruiking their anti-AI position. “AI is not our future” spans the screen of a special AI page on their website, followed by: “Creativity is made, not generated.”
It’s a bold position. Adobe has been slowly rolling out AI-driven systems in their suite of apps, to mixed reactions. Tablet maker Wacom was slammed earlier this year for using AI-generated assets in their marketing. And after pocketing AU $47 million in investor funding in December 2023, Aussie AI generation platform Leonardo.Ai was snapped up by fellow local giant Canva in July for just over AU $120 million.
Artist and user reactions to Procreate’s position have been near-universal praise. Procreate has grown steadily over the last decade, emerging as a cornerstone iPad native art app, and only recently evolving towards desktop offerings. Their one-time purchase fee, in direct response to ongoing subscriptions from competitors like Adobe, makes it a tempting choice for creatives.
Tech commentators might say that this is an example of companies choosing sides in the AI ‘war’. But this is, of course, a reductive view of both technology and industries. For mid-size companies like Procreate, it’s not necessarily a case of ‘get on board or get left behind’. They know their audience, as evidenced by the response to their position on AI: “Now this is integrity,” wrote developer and creative Sebastiaan de With.
Consumers are smarter than anyone cares to consider. If they want to try shiny new toys, they will; if they don’t, they won’t. And in today’s creative environment, where there are so many tools, workflows, and options to choose from, maybe they don’t have to pick one approach over another.
Huge tech companies control the conversation around education, culture, and the future of society. That’s a massive problem, because leave your Metas, Alphabets, and OpenAIs to the side, and you find creative, subversive, independent, anarchic, inspiring innovation happening all over the place. Some of these folx are using AI, and some aren’t: the work itself is interesting, rather than the exact tools or apps being used.
Companies ignore technological advancement at their peril. But deliberately opting out? Maybe that’s just good business.
Up until this year, AI-generated video was something of a white whale for tech developers. Early experiments resulted in janky-looking acid dream GIFs; vaguely recognisable frames and figures, but nothing in terms of consistent, logical motion. Then things started to get a little, or rather a lot, better. Through constant experimentation and development, the nerds (and I use this term in a nice way) managed to get the machines (and I use this term in a knowingly reductive way) to produce little videos that could have been clips from a film or a human-made animation. To reduce thousands of hours of math and programming into a pithy quotable, the key was this: they encoded time.
RunwayML and Leonardo.Ai are probably the current forerunners in the space, allowing text-to-image-to-(short)video as a seamless user-driven process. RunwayML also offers text-to-audio generation, which you can then use to generate an animated avatar speaking those words; this avatar can be yourself, another real human, a generated image, or something else entirely. There’s also Pika, Genmo and many others offering variations on this theme.
Earlier this year, OpenAI announced Sora, their video generation tool. One assumes this will be built into ChatGPT, the chatbot which is serving as the interface for other OpenAI products like DALL-E and custom GPTs. The published results of Sora are pretty staggering, though it’s an open secret that these samples were chosen from many not-so-great results. Critics have also noted that even the supposed exemplars have their flaws. Similar things were said about image generators only a few years ago, though, so one assumes that the current state of things is the worst it will ever be.
Creators are now experimenting with AI films. The aforementioned RunwayML is currently running their second AI Film Festival in New York. Many AI films are little better than abstract pieces that lack the dynamism and consideration to be called even avant-garde. However, there are a handful that manage to transcend their technical origins. But how this is not true of all media, all art, manages to elude critics and commentators, and worst of all, my fellow scholars.
It is currently possible, of course, to use AI tools to generate most components, and even to compile found footage into a complete video. But this is an unreliable method that offers little of the creative control that filmmakers might wish for. Creators employ an infinite variety of different tools, workflows, and methods. The simplest might prompt ChatGPT with an idea, ask for a fleshed-out treatment, and then use other tools to generate or source audiovisual material that the user then edits in software like Resolve, Final Cut or Premiere. Others build on this post-production workflow by generating music with Suno or Udio; or they might compose music themselves and have it played by an AI band or orchestra.
As with everything, though, the tools don’t matter. If the finished product doesn’t have a coherent narrative, theme, or idea, it remains a muddle of modes and outputs that offers nothing to the viewer. ChatGPT may generate some poetic ideas on a theme for you, but you still have to do the cognitive work of fleshing that out, sourcing your media, arranging that media (or guiding a tool to do it for you). Depending on what you cede to the machine, you may or may not be happy with the result — cue more refining, revisiting, more processing, more thinking.
AI can probably replace us humans for low-stakes media-making, sure. Copywriting, social media ads and posts, the nebulous corporate guff that comprises most of the dead internet. For AI video, the missing component of the formula was time. But for AI film, time-based AI media of any meaning or consequence, encoding time was just the beginning.
AI media won’t last as a genre or format. Call that wild speculation if you like, but I’m pretty confident in stating it. AI media isn’t a fad, though, I think, in the same ways that blockchain and NFTs were. AI media is showing itself to be a capable content creator and creative collaborator; events like the AI Film Festival are how these tools test and prove themselves in this regard. To choose a handy analogue, the original ‘film’ — celluloid exposed to light to capture an image — still exists. But that format is distinct from film as a form. It’s distinct from film as a cultural idea. From film as a meme or filter. Film, somehow, remains a complex cultural assemblage of technical, social, material and cultural phenomena. Following that historical logic, I don’t think AI media will last in its current technical or cultural form. That’s not to say we shouldn’t be on it right now: quite the opposite, in fact. But to do that, don’t look to the past, or to textbooks, or even to people like me, to be honest. Look to the true creators: the tinkerers, the experimenters, what Apple might once have called the crazy ones.
Creators and artists have always pushed the boundaries, have always guessed at what matters and what doesn’t, have always shared those guesses with the rest of us. Invariably, those guesses miss some of the mark, but taken collectively they give a good sense of a probable direction. That instinct to take wild stabs is something that LLMs, even a General Artificial Intelligence, will never be truly capable of. Similarly, the complexity of something like, for instance, a novel, or a feature film, eludes these technologies. The ways the tools become embedded, the ways the tools are treated or rejected, the ways they become social or cultural; that’s not for AI tools to do. That’s on us. Anyway, right now AI media is obsessed with its own nature and role in the world; it’s little better than a sequel to 2001: A Space Odyssey or Her. But like those films and countless other media objects, it does itself show us some of the ways we might either lean in to the change, or purposefully resist it. Any thoughts here on your own uses are very welcome!
The creative and scientific methods blend in a fascinating way with AI media. Developers build tools that do a handful of things; users then learn to daisy-chain those tools together in personal workflows that suit their ideas and processes. To be truly innovative, creators will develop bold and strong original ideas (themes, stories, experiences), and then leverage their workflows to produce those ideas. It’s not just AI media. It’s AI media folded into everything else we already do, use, produce. That’s where the rubber meets the road, so to speak; where a tool or technique becomes the culture. That’s how it worked with printing and publishing, cinema and TV, computers, the internet, and that’s how it will work with AI. That’s where we’re headed. It’s not the singularity. It’s not the end of the world. it’s far more boring and fascinating than either of those could ever hope to be.
I threw around a quick response to this article on the socials this morning and, in particular, some of the reactions I was seeing. Here’s the money quote from photographer Annie Leibovitz, when asked about the effects of AI tools, generative AI technology, etc, on photography:
“That doesn’t worry me at all,” she told AFP. “With each technological progress, there are hesitations and concerns. You just have to take the plunge and learn how to use it.”1
The paraphrased quotes continue on the following lines:
She says AI-generated images are no less authentic than photography.
“Photography itself is not really real… I like to use PhotoShop. I use all the tools available.”
Even deciding how to frame a shot implies “editing and control on some level,” she added.2
A great many folx were posting responses akin to ‘Annie doesn’t count because she’s in the 1%’ or ‘she doesn’t count because she’s successful’, ‘she doesn’t have to worry anymore’ etc etc.
On the one hand it’s typical reactionary stuff with which the socials are often ablaze. On the other hand, it’s fair to fear the impact of a given innovation on your livelihood or your passion.
As I hint in my own posts3, though, I think the temptation to leap on this as privilege is premature, and a little symptomatic of whatever The Culture and/or The Discourse is at the moment, and has been for the duration of the platformed web, if not much longer.
Leibovitz is and has always been a jobbing artist. Sure, in later years she has been able to pick and choose a little more, but by all accounts she is a busy and determined professional, treating every job with just as much time, effort, dedication as she always has. The work, for Leibovitz, has value, just as much — if not more — than the product or the paycheck.
I don’t mean to suddenly act my age, or appear much older and grumpier than I am, but I do wonder about how much time aspiring or current photographers spend online discussing and/or worrying and/or reacting to the latest update or the current fad-of-the-moment. I 100% understand the need for today’s artists and creators to engage in some way with the social web, if only to put their names out there to try and secure work. But if you’re living in the comments, whipping yourselves and others into a frenzy about AI or whatever it is, is that really the best use of your time?
The irony of me asking such questions on a blog where I do nothing but post and react is not lost on me, but this blog for me is a scratchpad, a testing ground, a commonplace book; it’s a core part of my ‘process’, whatever that is, and whatever it’s for. This is practice for other writing, for future writing, for my identity, career, creative endeavours as a writer. It’s a safe space; I’m not getting angry (necessarily), or seeking out things to be angry about.
But I digress. Leibovitz is not scared of AI. And as someone currently working in this space, I can’t disagree. Having even a rudimentary understanding of what these tools are actually doing will dispel some of the fear.
Further, photography, like the cinema that it birthed, has already died a thousand deaths, and will die a thousand more.
Brilliant4 photography lecturer and scholar Alison Bennett speaks to the legacy and persistence of photographic practice here:
“Recent examples [of pivotal moments of change in photography] include the transition from analogue film to digital media in the late 20th century, then the introduction of the internet-connected smart phone from 2007,” they said.
“These changes fundamentally redefined what was possible and how photography was used.
“The AI tipping point is just another example of how photography is constantly being redefined.”5
As ever, the tools are not the problem. The real enemies are the companies and people that are driving the tools into the mainstream at scale. The companies that train their models on unlicensed datasets, drawn from copyrighted material. The people that buy into their own bullshit about AI and AGI being some kind of evolutionary and/or quasi-biblical moment.
For every post shitting on Annie Leibovitz, you must have at least twenty posts actively shitting on OpenAI and their ilk, pushing for ethically-sourced and maintained datasets, pushing for systemic change to the resource management of AI systems, including sustainable data centers.
The larger conceptual questions are around authenticity and around hard work. If you use AI tools, are you still an authentic artist? Aren’t AI tools just a shortcut? Of course, the answers are ‘not necessarily’. If you’ve still done the hard yards to learn about your craft, to learn about how you work, to discover what kinds of stories and experiences you want to create, to find your voice, in whatever form it takes, then generative AI is a paintbrush. A weird-looking paintbrush, but a paintbrush nevertheless (or plasticine, or canvas, or glitter, or an app, etc. etc. ad infinitum).
Do the work, and you too can be either as ambivalent as Leibovitz, or as surprised and delighted as you want to be. Either way, you’re still in control.
See here, and with tiny edits for platform affordances here and here. What’s the opposite of POSSE? PEPOS? ↩︎
I am somewhat biased as, at the time of writing, Dr. Bennett and I currently share a place of work. To look through their expanded (heh) works, go here. ↩︎
So much of what I’m being fed at the moment concerns the recent wave of AI. While we are seeing something of a plateauing of the hype cycle, I think (/hope), it’s still very present as an issue, a question, an opportunity, a hope, a fear, a concept. I’ll resist my usual impulse to historicise this last year or two of innovation within the contexts of AI research, which for decades was popularly mocked and institutionally underfunded; I’ll also resist the even stronger impulse to look at AI within the even broader milieu of technology, history, media, and society, which is, apparently, my actual day job.
What I’ll do instead is drop the phrase algorithmic moment, which is what I’ve been trying to explore, define, and work through over the last 18 months. I’m heading back to work next week after an extended period of leave, so this seems as good a way of any as getting my head back into some of the research I left to one side for a while.
The algorithmic moment is what we’re in at the moment. It’s the current AI bubble, hype cycle, growth spurt, whatever you define this wave as (some have dubbed it the AI spring or boom, to distinguish it from various AI winters over the last century1). In trying to bracket it off with concrete times, I’ve settled more or less on the emergence of the GPT-3 Beta in 2020. Of course OpenAI and other AI innovations predated this, but it was GPT-3 and its children ChatGPT and DALL-E 2 that really propelled discussions of AI and its possibilities and challenges into the mainstream.
This also means that much of this moment is swept up with the COVID pandemic. While online life had bled into the real world in interesting ways pre-2020, it was really that year, during urban lockdowns, family zooms, working from home, and a deeply felt global trauma, that online and off felt one and the same. AI innovators capitalised on the moment, seizing capital (financial and cultural) in order to promise a remote revolution built on AI and its now-shunned sibling in discourse, web3 and NFTs.
How AI plugs into the web as a system is a further consideration — prior to this current boom, AI datasets in research were often closed. But OpenAI and its contemporaries used the internet itself as their dataset. All of humanity’s knowledge, writing, ideas, artistic output, fears, hopes, dreams, scraped and plugged into an algorithm, to then be analysed, searched, filtered, reworked at will by anyone.
The downfall of FTX and the trial of Sam Bankman-Fried more or less marked the death knell of NFTs as the Next Big Thing, if not web3 as a broader notion to be deployed across open-source, federated applications. And as NFTs slowly left the tech conversation, as that hype cycle started falling, the AI boom filled the void, such that one can hardly log on to a tech news site or half of the most popular Subs-stack without seeing a diatribe or puff piece (not unlike this very blog post) about the latest development.
ChatGPT has become a hit productivity tool, as well as a boon to students, authors, copy writers and content creators the world over. AI is a headache for many teachers and academics, many of whom fail not only to grasp its actual power and operations, but also how to usefully and constructively implement the technology in class activities and assessment. DALL-E, Midjourney and the like remain controversial phenomena in art and creative communities, where some hail them as invaluable aids, and others debate their ethics and value.
As with all previous revolutions, the dust will settle on that of AI. The research and innovation will continue as it always has, but out of the limelight and away from the headlines. It feels currently like we cannot keep up, that it’s all happening too fast, that if only we slowed down and thought about things, we could try and understand how we’ll be impacted, how everything might change. At the risk of historicising, exactly like I said I wouldn’t, people thought the same of the printing press, the aeroplane, and the computer. In 2002, Andrew Murphie and John Potts were trying to capture the flux and flow and tension and release of culture and technology. They were grappling in particular with the widespread adoption of the internet, and how to bring that into line with other systems and theories of community and communication. Jean-Francois Lyotard had said that new communications networks functioned largely on “language games” between machines and humans. Building on this idea, Murphie and Potts suggested that the information economy “needs us to make unexpected ‘moves’ in these games or it will wind down through a kind of natural attrition. [The information economy] feeds on new patterns and in the process sets up a kind of freedom of movement within it in order to gain access to the new.”2
The information economy has given way, now, to the platform economy. It might be easy, then, to think that the internet is dead and decaying or, at least, kind of withering or atrophying. Similarly, it can be even easier to think that in this locked-down, walled-off, platform- and app-based existence where online and offline are more or less congruent, we are without control. I’ve beendroppingbreadcrumbs over these last few posts as to how we might resist in some small way, if not to the detriment of the system, then at least to the benefit of our own mental states; and I hope to keep doing this in future posts (and over on Mastodon).
For me, the above thoughts have been gestating for a long time, but they remain immature, unpolished; unfiltered which, in its own way, is a form of resistance to the popular image of the opaque black box of algorithmic systems. I am still trying to figure out what to do with them; whether to develop them further into a series of academic articles or a monograph, to just keep posting random bits and bobs here on this site, or to seed them into a creative piece, be it a film, book, or something else entirely. Maybe a little of everything, but I’m in no rush.
As a postscript, I’m also publishing this here to resist another system, that of academic publishing, which is monolithic, glacial, frustrating, and usually hidden behind a paywall for a privileged few. Anyway, I’m not expecting anyone to read this, much less use or cite it in their work, but better it be here if someone needs it than reserved for a privileged few.
As a bookend for the AI-generated image that opened the post, I asked Bard for “a cool sign-off for my blog posts about technology, history, and culture” and it offered the following, so here you go…
Signing off before the robots take over. (Just kidding… maybe.)
Notes
For an excellent history of AI up to around 1990, I can’t recommend enough AI: The Tumultuous History of the Search for Artificial Intelligence by Daniel Crevier. Crevier has made the book available for download via ResearchGate. ↩︎
