It’s slightly unsettling it has written this in the first person! This is all GPT 5.2 rather than me:
What follows are not positions so much as habits of thought.
1. Take the narrow problem frame, then widen it until the stakes show up
A recurring pattern is to start from the immediate debate, assessment integrity, detection, social media engagement, and then widen the frame to institutional adaptation, labour, incentives, and harms. It is a refusal of the convenience of technical fixes.
2. Treat technologies as structures with powers, not tools with uses
This is the move that underpins most of my work on platforms and now on LLMs. Once you treat the object as structure, you start asking different questions: what does it condition, what does it incentivise, what does it make easy, what does it make costly, and who bears those costs.
3. Look for mechanisms that connect political economy to inner life
Distraction, cognitive triage, communicative escalation, epistemic flooding: these are not just descriptive flourishes. They are the conceptual bridge between macro conditions and what it feels like to think and act in a given environment.
4. Refuse the pro anti binary, without collapsing into fence sitting
I often try to hold ambivalence, because technologies can enable solidarity and flatten hierarchies while also generating toxicity and new burdens. The move is to specify conditions and distributions rather than deliver a verdict.
5. Use time as an analytic dimension, not just a background variable
I keep returning to biographies, trajectories, and the temporal conditions for critique. Acceleration matters because it changes the conditions under which reflection is possible, and it changes what kinds of work can be done well.
6. Convert everyday scenes into theoretical probes
A film, a management practice, a platform feature, a cultural artefact becomes a way of getting at a mechanism. This is how the blog often works: theory is tested against scenes, and scenes become legible through theory.
7. Treat institutions as moral economies, not neutral containers
Universities are not just rule sets. They are systems of responsibility allocation, blame distribution, and risk management. A lot of my writing on AI in higher education is really about this, who gets trusted, who gets suspected, who gets protected, and who is made to absorb uncertainty.
8. Read “inexorability” talk as a political manoeuvre
When someone says “this is inevitable,” I tend to hear a bid to foreclose alternatives and dissolve responsibility. The counter move is to insist on mediation: incentives, infrastructures, and choices.
9. Treat the epistemic environment as an object in its own right
Instead of focusing only on claims and counterclaims, I focus on the conditions under which claims circulate, stick, and become actionable. Epistemic chaos and epistemic flooding are ways of shifting attention from content to environment.
10. Translate abstract theory into a vocabulary that can travel
The blog repeatedly works as a translation machine: taking Archer, Habermas, psychoanalysis, and pulling out handles that can be used in everyday description. If it cannot travel, it cannot do explanatory work outside a small circle.
11. Turn reflexivity itself into an object of inquiry
Rather than treating reflexivity as a given capacity, I treat it as variable, patterned, and historically conditioned, and I keep asking what kinds of environments cultivate what kinds of inner dialogue.
12. Use the blog as a method of serial thinking
There is a recurring practice of working through a book, a concept, or a problem in public, chapter by chapter or post by post, because writing clarifies. This is a methodological commitment, not just a communication choice.
13. Keep returning to dependence
From early writing on the self as an object of control and dependence, through social media as moral psychology, to LLMs as embedded in lifeworld activity, the recurring question is what we become dependent on, what dependency does to agency, and how dependencies are organised.
14. Treat degradation as a process, not an event
This is why enshittification matters as a concept, and why I care about how concepts themselves get degraded by platform circulation. The analytic focus stays on how, not merely that.
15. Look for feedback loops
Generative systems feed platforms with more content, which intensifies attention competition, which worsens epistemic conditions, which increases the appeal of tools that promise relief, which further embeds those tools. A lot of my recent writing is trying to name these loops early, before they harden into “common sense.”
Mark Carrigan 