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.
A few weeks back, some colleagues and I were invited to share some new thoughts and ideas on the theme of ‘ecomedia’, as a lovely and unconventional way to launch Simon R. Troon’s newest monograph, Cinematic Encounters with Disaster: Realisms for the Anthropocene. Here’s what I presented; a few scattered scribblings on environmental imaginaries as mediated through AI.
Grotesque Fascination:
Reflections from my weekender in the uncanny valley
In February 2024 OpenAI announced their video generation tool Sora. In the technical paper that accompanied this announcement, they referred to Sora as a ‘world simulator’. Not just Sora, but also DALL-E or Runway or Midjourney, all of these AI tools further blur and problematise the lines between the real and the virtual. Image and video generation tools re-purpose, re-contextualise, and re-gurgitate how humans perceive their environments and those around them. These tools offer a carnival mirror’s reflection on what we privilege, prioritise, and what we prejudice against in our collective imaginations. In particular today, I want to talk a little bit about how generative AI tools might offer up new ways to relate to nature, and how they might also call into question the ways that we’ve visualized our environment to date.
AI media generators work from datasets that comprise billions of images, as well as text captions, and sometimes video samples; the model maps all of this information using advanced mathematics in a hyper-dimensional space, sometimes called the latent space or a U-net. A random image of noise is then generated and fed through the model, along with a text prompt from the user. The model uses the text to gradually de-noise the image in a way that the model believes is appropriate to the given prompt.
In these datasets, there are images of people, of animals, of built and natural environments, of objects and everyday items. These models can generate scenes of the natural world very convincingly. These generations remind me of the open virtual worlds in video games like Skyrim or Horizon: Zero Dawn: there is a real, visceral sense of connection for these worlds as you move through them. In a similar way, when you’re playing with tools like Leonardo or MidJourney, there can often be visceral, embodied reactions to the images or media that they generate: Shane Denson has written about this in terms of “sublime awe” and “abject cringe”. Like video games, too, AI Media Generators allow us to observe worlds that we may never see in person. Indeed, some of the landscapes we generate may be completely alien or biologically impossible, at least on this planet, opening up our eyes to different ecological possibilities or environmental arrangements. Visualising or imagining how ecosystems might develop is one way of potentially increasing awareness of those that are remote, unexplored or endangered; we may also be able to imagine how the real natural world might be impacted by our actions in the distant future. These alien visions might also, I suppose, prepare us for encountering different ecosystems and modes of life and biology on other worlds.
But it’s worth considering, though, how this re-visualisation, virtualisation, re-constitution of environments, be they realistic or not, might change, evolve or hinder our collective mental image, or our capacity to imagine what constitutes ‘Nature’. This experience of generating ecosystems and environments may increase appreciation for our own very real, very tangible natural world and the impacts that we’re having on it, but like all imagined or technically-mediated processes there is always a risk of disconnecting people from that same very real, very tangible world around them. They may well prefer the illusion; they may prefer some kind of perfection, some kind of banal veneer that they can have no real engagement with or impact on. And it’s easy to ignore the staggering environmental impacts of the technology companies pushing these tools when you’re engrossed in an ecosystem of apps and not of animals.
In previous work, I proposed the concept of virtual environmental attunement, a kind of hyper-awareness of nature that might be enabled or accelerated by virtual worlds or digital experiences. I’m now tempted to revisit that theory in terms of asking how AI tools problematise that possibility. Can we use these tools to materialise or make perceptible something that is intangible, virtual, immaterial? What do we gain or lose when we conceive or imagine, rather than encounter and experience?
Machine vision puts into sharp relief the limitations of humanity’s perception of the world. But for me there remains a certain romance and beauty and intrigue — a grotesque fascination, if you like — to living in the uncanny valley at the moment, and it’s somewhere that I do want to stay a little bit longer. This is despite the omnipresent feeling of ickiness and uncertainty when playing with these tools, while the licensing of the datasets that they’re trained on remains unclear. For now, though, I’m trying to figure out how connecting with the machine-mind might give some shape or sensation to a broader feeling of dis-connection.
How my own ideas and my capacity to imagine might be extended or supplemented by these tools, changing the way I relate to myself and the world around me.
This semester I’m running a Media studio called ‘Augmenting Creativity’. The basic goal is to develop best practices for working with generative AI tools not just in creative workflows, but as part of university assignments, academic research, and in everyday routines. My motivation or philosophy for this studio is that so much attention is being focused on the outputs of tools like Midjourney and Leonardo.Ai (as well as outputs from textbots like ChatGPT); what I guess I’m interested in is exploring more precisely where in workflows, jobs, and daily life that these tools might actually be helpful.
In class last week we held a Leonardo.Ai hackathon, inspired by one of the workshops that was run at the Re/Framing AI event I convened a month or so ago. Leonardo.Ai generously donated some credits for students to play around with the platform. Students were given a brief around what they should try to generate:
an AI Self-Portrait (using text only; no image guidance!)
three images to envision the studio as a whole (one conceptual, a poster, and a social media tile)
three square icons to represent one task in their daily workflow (home, work, or study-related)
For the Hackathon proper, students were only able to adjust the text prompt and the Preset Style; all other controls had to remain unchanged, including the Model (Phoenix), Generation Mode (Fast), Prompt Enhance (off), and all others.
Students were curious and excited, but also faced some challenges straight away with the underlying mechanics of image generators; they had to play around with word choice in prompts to get close to desired results. The biases and constraints of the Phoenix model quickly became apparent as the students tested its limitations. For some students this was more cosmetic, such as requesting that Leonardo.Ai generate a face with no jewelry or facial hair. This produced mixed results, in that sometimes explicitly negative prompts seemed to encourage the model to produce what wasn’t wanted. Other students encountered difficulties around race or gender presentation: the model struggles a lot with nuances in race, e.g. mixed-race or specific racial subsets, and also often depicts sexualised presentations of female-presenting people (male-presenting too, but much less frequently).
This session last week proved a solid test of Leonardo.Ai’s utility and capacity in generating assets and content (we sent some general feedback to Leonardo.Ai on platform useability and potential for improvement), but also was useful for figuring out how and where the students might use the tool in their forthcoming creative projects.
This week we’ve spent a little time on the status of AI imagery as art, some of the ethical considerations around generative AI, and where some of the supposed impacts of these tools may most keenly be felt. In class this morning, the students were challenged to deliver lightning talks on recent AI news, developing their presentation and media analysis skills. From here, we move a little more deeply into where creativity lies in the AI process, and how human/machine collaboration might produce innovative content. The best bit, as always, will be seeing where the students go with these ideas and concepts.
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. ↩︎
Obligatory artfully-cropped stock photo of a completely different Macbook model to the one discussed in this post. Photo by Math on Pexels.com.
Part 3: Give me my MacBook back, Mac.
2012 was a big year. The motherland had the Olympics and Liz’s Diamond Jubilee; elsewhere, the Costa Concordia ran aground; Curiosity also made landfall, but intentionally, on Mars; and online it was nothing but Konys, Gangnam Styles and Overly Attached Girlfriends as far as the eye could see.
For me, I was well into my PhD, around the halfway mark; I’d also scaled back full-time media production work for that reason, and was picking up the odd shift at Video Ezy again. It was also the year that I upgraded to a late 2011 MacBook Pro. I think I had had one Macbook before then, possibly purchased in 2007-8; prior to this a Windows machine that was nicked from my inner west apartment around 2009, along with a lovely Sony Alpha camera (vale).
I can’t believe this image persists on Flickr. Here’s the same machine, with its nice black suit on, in situ during the completion of said PhD!
The 2011 MacBook served me well until early 2015, when I was given the first work machine, which I’m fairly sure was a late 2014 MBP. I tried to revive the 2011 machine once before, when my partner needed a laptop for study; however, when in early 2020 it took approximately 5 minutes to load a two-page PDF, we thought maybe it was time to put it away. For some reason though, I just held onto it, and it sat idle in the cupboard, until a week or two ago, when I caught myself thinking: what if…?
So having more or less sorted the Raspberry Pi, I turned my attention to this absolute chunkster of a laptop. It’s amazing how the sizes and shapes of tech come in and out of vogue. The 2011 MBP is obviously heavier than the work laptop, but not by as much as you’d think (2.04kg vs. 1.6kg for my 2020 M1 machine), with roughly the same screen size. Obviously, though, the older model has much thicker housing (h2.4cm w32.5cm d22.7cm vs. h1.56 w30.41 d21.24cm). Anyway, some swift searching about (by myself but mainly by my best mate, who also has huge interest in older tech, both hardware and software) led to iFixIt, where a surprisingly small amount of money resulted in an all-in-one 500GB SSD upgrade kit arriving within a few days.
I aspire to the perfect techbro desktop-fu. How did I do?
I had some time to kill late last week, so I set about changing the hard drives. It was also the perfect opportunity to brush away many years of accumulated dust, and a can of compressed air took care of the trickier areas. With the help of tutorials and such, all of this took under half an hour. What filled the rest of the allotted time was sorting out boot disks for OS X. Internet Recovery was no-go at first, but with several failed attempts at downloading the appropriately agėd version, I tried once again. No good. Cue forum and Reddit diving for an hour or two, before finally obtaining what seemed to be the correct edition of High Sierra, without several probably-very-necessary security patches and so on.
Anyway, I managed to boot up High Sierra off an ancient USB, got it installed on the SSD, and then very quickly realised that while the SSD certainly afforded greater speed than before, High Sierra was virtually unusable apart from the already installed apps and a browser. I knew I could probably try to upgrade to Mojave or maybe even Big Sur, but even with the SSD, I wasn’t sure how well it would run; and it was still tough to find usable images for those versions of macOS. But somewhere in my Reddit and forum explorations I’d seen that some had succeeded in installing Linux on their older machines, and that it had run as well and/or even better than whatever the latest macOS was that they could use.
Two laptops, both alike in backlit keyboard, on fair floor where we lay our scene.
Thanks to the Pi, I had a little familiarity with very basic Linux OS’s (aka DISTROS, yeah children I can use the LINGO I am heaps 1337); it was down to whether the MBP could run Ubuntu, or whether Mint or Elementary would be more efficient. In the end, I went with Mint, and so far so good? It’s a little laggy, particularly if multiple apps are open; I’m drafting this in Obsidian and the response isn’t great. I would also note that the systems’s fan is on, and loud, most of the time, even with mbpfan running. The resolution on my 4K monitor is worse than the Pi, of course, but this is due to the lack of direct HDMI output from the MBP; I’m using a Thunderbolt to HDMI adapter. That said, maybe I just have to tweak some settings.
A glimpse behind the curtain.
In the meantime, it’s been fun to play in a new OS; Mint feels very Windows-esque, though with some features that felt very intuitive to a longer-term Mac user. Being restricted to maybe a maximum of five apps running simultaneously means I have to be conscious of what I’m doing: this actually helps me plan my workspace and my worktime more carefully. I’m using this as a personal machine, so mostly for creative writing and blogging; in general, it affords more than enough power to do a little research, take notes, draft work. If there’s anything more complex, I’ll probably have to shift to the work machine, though I did clock ShotCut and GIMP being available for basic video/image work, and obviously there’s Audacity and similar for audio.
Physically, the MBP sits flat on my desktop in front of the monitor. Eventually I will probably get a monitor arm, so it can slide back a little further. Swapping it out for my work machine isn’t too difficult; I just have to plug the HDMI into a USB-C dongle that permanently has a primary external drive, webcam and mic hooked up to it. Now that I think of it, my monitor probably has more than one HDMI input, so potentially I could just add a second HDMI cable to that arrangement and save a step. Something to try once this is posted! I’m still in a bit of cable hell, as well, due to just wanting the simplicity of plugging in a USB keyboard and mouse to the old Macbook; over the next week or two I’ll try to configure the Bluetooth accessories for bit more desktop breathing room.
Behold the crisp image quality of the iPhone 8 (an old-tech story for another time…).
Apart from these little tweaks, the only ‘major’ thing I want to tweak short-term is the Linux distro; it just feels like Mint Cinnamon may be pushing the system a little too hard. Mint does offer two lighter variants, MATE and Xfce, though I also did download Elementary and Ubuntu MATE. Mint MATE for the MBP, I reckon, and then maybe even Ubuntu MATE on the Pi. To be fair, though, most of the time the machine is struggling, I have Chrome open, so I could also just try a lighter browser, like one of your Chromiums or your Midoris.
Looking back over this drafted post, it reads like I know way more about this than I actually do. Like I’m just flashing drives and rebooting systems and slinging OS’s and SSD’s like it’s nobody’s business. To be clear: I absolutely don’t. Most of the time it was either my aforementioned best mate who knew much more about all of this stuff than I ever did, or other tech-savvy friends or colleagues; my machines have always been repaired, maintained, serviced by Mac folx, or I would just restart and hope for the best. I have a working knowledge of basic computer operation, but that barely extends to the command line, which I think I’ve used more in the last week than across my entire life. As discussed here, I don’t really code either. Most of this, for me, is just trial and error; I guess my only ‘rules’ are reading up as much as I can on what’s worked/not for other people, and trying not to take too many unnecessary risks in terms of system security or hardware tinkering. The risk in this instance is also lessened by the passing of time: warranties are well out of date and thus won’t be voided by yanking out components.
As a media/materialism scholar, I know conceptually/theoretically that sleek modern devices and the notion of ‘the cloud’ belies the awful truth about extractive practices, exploited workforces, and non-renewable materials. Reading and writing about it is one thing; to see the results of all of that very plainly laid out on your desk is quite another. One cannot ignore the reality of the tech industry and how damaging it has been and continues to be. In the same vein, though, I’m glad that these particular materials and components won’t be heading to landfills (or more hopefully, some kind of recycling centre) for a little while longer.
Her language contains elements from Aeolic vernacular and poetic tradition, with traces of epic vocabulary familiar to readers of Homer. She has the ability to judge critically her own ecstasies and grief, and her emotions lose nothing of their force by being recollected in tranquillity.
