Category: Research

• AI is a dirty word

  July 22, 2026

  

  Last week on LinkedIn, I posted this:

  Right now is a difficult time to be doing anything AI-related. The conversation has somehow polarised even further — and the extreme ends are doubling down in their zealotry. Being in the humanities means that I’m often surrounded by (well-meaning!) folx who are reluctant, if not downright hostile, to the technology and/or the corporate interests peddling the frontier versions of that technology.
  
  Reading social posts saying “if you engage with genAI you’re dead to me/an awful person” is difficult to take, particularly when I know some of those folx absolutely still use the tech to some degree behind the scenes (or are unaware of the embeddedness of other AI/ML technologies). I myself have been privately negotiating the line between creative misuse and active complicity since I started experimenting with genAI 3-4 years ago.
  
  But I still believe that fun and play are valid methods for critically interrogating how these technologies work, what they’re made of, and what they’re useful for or not. I am not ignorant: Big Tech ideology, environmental impacts, and IP concerns are very real. But there is a lack of basic understanding and literacy about these tools: absolutely not society’s fault, particularly when the media are completely clueless, and it’s in Big Tech’s interests to obfuscate the mechanisms of the machine. All of this means that fear and uncertainty dominate the conversation.
  
  My smol and weird AI work over the last few years has been technically challenging, ethically confronting, occasionally disturbing… but it has also been surprising, educational, sometimes delightful, useful, deeply weird (positively), and so much fun. Importantly, this work suggests alternatives to [gestures broadly] whatever this is. Fun, play, and mess are not just valid methods — I would argue that they’re more necessary than ever at a time when things feel like they’re out of our control.

  It got a handful of likes in the first couple of days, but over the last 24-48 hours I’ve seen engagement well beyond my network: likes and reactions, and comments from a few folx I don’t know. The long tail of LinkedIn posts about topical issues is perhaps something for another time and place (this post has nearly 3000 impressions at time of writing… like WTF??).

  The comments bear out what I suggest in the post: that opinions remain polarised, that people are skeptical, concerned, or on the flip side, excited or inspired.

  I left a great many things out of that post. It went through many, many drafts. I tossed up whether or not to post it at all. And I’ve gone through the wringer of emotional/psychological states as I’ve watched the reactions pile up.

  But as a creative, as a researcher, as a teacher and writer, I feel like I have to put myself out there in this way. Being scared of what people might think is a completely normal feeling; but using that as an excuse to not engage with the conversation, with other people, feels dishonest. It also means that my blog posts, newsletters, academic writing, sits in a bubble where others might not find it, or where it may be interpreted as volleys over the parapets without owning them or being accountable for them.

  Less drastically, perhaps, I’m genuinely interested in what others have to say. I’m at a stage in my life and career where I’m open to other perspectives, to having my views challenged, for others to pick up on my errors or foibles; before now, I was scared because I was just trying to figure out what on earth my values and opinions were at all.

  Sharing my work publicly, as it happens, is something that I really only began trying in earnest in 2025, mainly as a way to document my work and experiments with genAI. I’m still not remotely comfortable doing so. But it’s something I feel is really valuable, for me and, hopefully, for others.

• From Literacy to Ecology

  May 15, 2026

  

  The third and final presentation of my research trip in France was delivered on Monday, April 27, at the colloquium “Créativités artificielles : approches critiques de l’IA” at the Université Côte d’Azur, Nice.

  My talk was titled “From Literacy to Ecology: Rethinking Critical-Creative AI After Automation”. This piece at once gestured backwards, to some of my earliest work in genAI, on ‘glitched companions’ and the smol and the weird, but also forwards, to where and how we might think about AI systems and outputs as part of a broader ecosystem and environment. I’m wanting to shift the conversation — and my research — from “How can I read this?” to “How can I live here?”

  I opened with the ‘literacy trap’ of technology, where outcomes- and skills-focused frameworks are instantiated across workplaces and education providers.

  These frameworks are normative — locking people in to particular modes of use and value systems. They position the user in a specific relationship to a tool. Furthermore, they assume that generative AI models are stable objects that can be learned and worked; that you can achieve a measurable standard of competency; that these are machines that can be mastered.

  The paper proposes a shift in metaphor from literacy, which implies a stable object to be learned, to ecology, which implies an environment to be inhabited. Reviving Guattari’s notion of ‘ecosophy’, I present an ecological approach to AI across critical, creative, and communicative registers.

  

  As an example activation of this idea, I presented by companions Wuwu and Fynik — little scripted agents that mess with folders on my computer. This work is being developed theoretically and philosophically, but also practically for a game/RPG artefact.

  The three-day event in Nice and Cannes brought together international scholars around critical, ethical, creative, scientific, and experimental interrogations of artificial intelligences generative and otherwise. My contribution will be submitted for consideration for a just-announced publication from the event.

• Against the totalising imaginary

  April 28, 2026

  

  My sabbatical in France has continued apace, with plenty of fruitful meetings and discussions, and not a little writing (deadlines sadly declined a similar holiday).

  On 24 April, I had the opportunity to present some of my research at Université Paris 8-Vincennes-Saint Denis — a university founded by figures including Jacques Derrida, Hélène Cixous, and Roland Barthes in the aftermath of May ’68.

  I presented a talk titled “Against the Totalising Imaginary: Weird AI and the Ecology of the Possible”, in which I discussed my glitch-based experiments and methodologies, which I refer to as ‘ritual-technics’. For the first time, I also proposed worldbuilding and storytelling as productive frameworks for engaging with technologies like generative AI.

  I began with the Slopocene. This has been bandied about as a pejorative term for our current overload of synthetic content and governance by algorithm, with the resulting crises of authenticity, ‘reality’, and authorship. As in other work, I’m working to reclaim the Slopocene as a productive and playful term, but also as a speculative near-future or alt-present, where recursive training collapse turns the web into a haunted archive of confused bots, discarded memes, and broken truths.

  How to navigate the Slopocene? I co-opted the work of my co-presenters for the seminar: Boris Eldagsen, Rosa Cinelli, and Philippe Boisnard, alongside Chris Chesher and Cesar Albarran-Torres, Eryk Salvaggio, and Ian Haig. These are diverse approaches, but they have a few common clusters: material/semiotic, i.e. we can read AI outputs diagnostically as results of training data; relationality/phemomenology, in terms of what kind of encounter or interaction we have with AI technology; and then an aesthetic/resistant thread, which finds value in the visual breakdown and visceral sensation of encountering AI media.

  These are methods, approaches, attitudes that resist zealous techno-utopia or simplistic and naive dystopic rejection, preferring instead to pay close attention to generative AI’s computational and cultural mechanisms. Essentially these are all ways to ‘stay with’ the machine.

  My own approach weaves a thread through the material/semiotic, the relational/phenomenological, and the aesthetic/resistant — an approach I refer to formally as critical-creative AI, or informally: gonzo AI. The approach is the practical/experimental arm of my broader media-materialist approach, where I position myself as a tinkerer-theorist, which translates beautifully in French to bricoleur-théoricien.

  I went through a few of my experiments with genAI, including semantic collapse, music generation, before introducing The Drift, my worldbuilding project where all my weird AI creations live. The Drift is “a space to think and to play and to build, and an alternative imaginary to the totalising mythology that Big Technology would love us to believe, where AI is everything and everything has to be AI”:

  “It’s a world where messiness is the point, where you can be a critical observer but also someone who lives in the space as an inhabitant. There are lovely tensions between delight and disturbance, being critical and being caught-up-in-it — living in these tensions is the only honest position you can have. Games and world-building and storytelling are forms where you can hold the contradiction, you can live with the tension. And it’s a feature of these media rather than a bug or an error.”

  

  This HERMES Seminaire, titled “Imaginaires artificiels : créativité et recherche à l’ère de l’image générative”, featured co-presenters Boris Eldagsen, Rosa Cinelli, and philippe boisnard, who shared their innovative approaches to exploring and deconstructing large language models and media generators.

  Université Paris 8 has been my host throughout this research trip, and it already feels like home. The institution embraces a diversity of experience among students and faculty, with interdisciplinary research and creative methods as the norm. Special thanks to Everardo Reyes of Laboratoire Paragraphe, who has been a generous friend and co-conspirator over the past couple of years.

• New research published: A media-materialist method for interpreting generative AI images

  April 17, 2026

  

  After plenty of play and experimentation with AI imagery, I found myself reacting viscerally to commentary and early scholarship that was pejorative about — or outright dismissive of — these outputs. The prevailing discourse treated AI images as a kind of slop monolith, when I found a lot of my generations to be fascinating, disturbing, amusing, and even beautiful. In response, I wrote this article, which presents a four-layer method for a structured, formal analysis of AI-generated images. The four layers are data, model, interface, and prompt, reflecting the mechanisms of generative AI technology. Each layer offers various considerations and questions to ask about actual outputs, encouraging researchers, students, educators, and commentators to move beyond dismissing these images as mere slop, and to begin considering them as cultural artefacts.

  This piece is the foundation of all my work on genAI over the past two years (I hinted at its publication last year), and also the first where I’ve attempted to create a new method rather than just apply one. It’s also the first to really put forward my own take on media materialism, a philosophy and methodology that has guided my work for nearly ten years.

  I am a big believer in close analysis, be it of texts, imagery, video, films: all the objects of culture. But I struggled for a long time to bridge that method with a context that made sense to me. In figuring out that the mechanisms of making were another foundational aspect of my work, it took me a few pieces to be able to make this connection, i.e. what I’ve nearly always tried to do is to consider how the means of an object’s production leave their mark on the object itself. It’s a simple conclusion, but it’s taken several attempts for me to articulate it in a way that felt satisfactory. This article feels like the first to actually explain it appropriately; the next step is to deploy the approach across other kinds of synthetic media and generative systems more broadly, but also to possibly return with this approach to cinema and TV.

• Like No One Is Watching

  April 8, 2026

  

  I’ve kicked off a month’s research sabbatical in France, hitting the ground running…

  My first invited presentation was today at Université Paris I: Panthéon-Sorbonne, as part of the journée d’étude “L’intelligence et l’éthique de la télévision à l’ère des algorithms”. Today’s talks looked at de-ageing as a quest for immortality and fracturing of the present, televisuality and intelligence, and teaching LLMs about humans by making them watch a lot of TV; the seminar concludes tomorrow.

  My own piece, “Like No One Is Watching: The Form of Television in the Algorithmic Moment”, examined how episodic storytelling navigates the constraints of the platform and attention economies. I looked at the chaotic inconsistency of The Bear and the aggressive tedium of The Pitt as shows pushing formal boundaries to reassert a direct relationship with their audience.

  The talk had three key moves.

  Firstly, I re-establish television as the ‘miscreant medium’, drawing from John Fiske and John Hartley’s seminal work. On the one hand, television has always served as a scapegoat or delivery channel for whatever moral panic is current at the time; alongside this, it is a medium perennially torn between the strictures of institutions and technology, and the creativity of its artists.

  Secondly, I argue that platform logic holds two contradictory assumptions about audiences. On one hand, there is an assumption that audiences are passive and distracted. This assumption leads to baked-in redundancies, including explicit exposition and constant re-explanation (a phenomenon that Will Tavlin explores in his piece ‘Casual Viewing’). On the other hand, platform capitalism is contingent on metrics of retention; active, engaged viewing, then, is assumed.

  In the third section, I spoke to sample clips from The Bear and The Pitt, both shows that embody and embrace this presumptive schizophrenia. From The Bear I played part of the seventh episode of the first season, which includes a 17-minute unbroken take. I also shared a couple of mundane conversation scenes from the premiere episode of The Pitt. I used formal analysis here as a diagnostic tool, to observe how creatives push against (or acquiesce to) the algorithmic frame of their distribution. In the case of both shows, I offered that formal experimentation — whether at a dialogue, scene, episode, or series level — demonstrates friction as an exercise in meaning-making: a conversation and negotiation between creator and audience quite apart from questions of data, platform, capital.

  What close formal analysis reveals is that television is not a medium in decline, but one still jovially misbehaving; always exceeding what the discourse says it’s capable of, and still worth watching.

  This talk was a return to formal analysis for me, and it felt great to be home. I’ve been very lucky to be taught by or to work with a bunch of academics who really value close textual analysis, and I think it’s such an incisive and enjoyable means of understanding texts and their contexts.

  It’s highly likely an edited collection will result from this gathering, so fingers crossed that this work will be in print soon!

  

  I now have a little breathing room before my second presentation, so I’ll be using this time to actually get out and wander around Paris a little, but also to feed and tend to a few items moving through the publication pipeline.