The Reading Room: Chapter 8

Conversations on systems, selves, and the future we’re already inside

One of my favourite writers is Kafka.

I love how reading his work feels like being inside a dream where everything is procedurally correct and quietly wrong at the same time.

And how you just keep nodding along, and then you look up and realise where he’s brought you.

So much of the AI conversation lives in that same territory. Conversations about systems, power, alienation, identity, performance, and communication breakdowns. People trying to hold onto themselves inside structures that feel bigger than them.

This week’s Reading Room circled it all: AI, judgement, communication, transformation, performance, and the strange tension between technology helping people while also reshaping the way we think, work, communicate, and relate to each other.

Which, on reflection, sounds very heavy, but I promise there was also poetry, butterflies, gingerbread, and gardening prompts involved, too.

In no particular order, here are my week’s highlights:

1. What is AI doing to humans? Why aren’t we measuring it?

[ Center for Humane Technology ] has long been concerned with the human consequences of technology, and this piece from Imran Khan applies that lens to AI in a way I found useful.

It asks why we’re so focused on measuring what AI systems can do, while still not properly measuring what they are doing to us. Not just productivity or performance, but the impact it can have on humans — dependency, trust, emotional reliance, critical thinking, sycophancy. The small ways people start adapting themselves around systems over time.

What I appreciated most was the refusal to make the conversation simple. AI can support learning, help people, and offer genuinely useful interventions. It can also create risks we still do not have good enough ways to understand.

That middle space feels important to me, because so much of AI safety is still discussed as if the main question is what the tool does. But the more interesting question, at least for the work I keep circling, is what kinds of habits, dependencies, shortcuts, and risks start forming around it once people bring it into ordinary life.

A lot of the most important effects will not arrive dramatically. They will arrive gradually, relationally, and through repetition.

2. How the Mind Became a Computer

This was the first piece I’d read from Ellen Burns, PhD , and honestly, it made me want to read more.

Ellen writes about AI consciousness and philosophy of mind, which already sits close to a lot of the questions I find myself drawn to. Here, she traces the birth of cognitive science through Turing, behaviourism, early AI, linguistics, psychology, and philosophy of mind, then asks what assumptions became embedded along the way.

Especially the idea that minds can be understood like computers.

What I held on to most was not just the history, but the way the piece slows down concepts we often inherit too quickly — intelligence, computation, information processing, mind, machine.

So much of the AI conversation starts after the metaphor has already settled. This piece asks what happens if we pause before that point and look again at the ideas underneath the ideas.

As someone who studied philosophy years ago, I always enjoy writing that reopens questions people have started treating as resolved.

3. Quiet Residue ✍🏾 Winged Arithmetic

Randolph Sydnor’s piece is a poem inspired by butterflies, transformation, and the photographs of Paula Mitchell. A little different to my usual reads, but it was a breath of fresh air among the heavier topics.

This piece felt like being told to unclench your jaw.

I guess I’d call it a meditation on becoming, one that never tips into self-help language or dramatic reinvention narratives. It doesn’t frame transformation as escape, betrayal, or spectacle. It frames it as fulfilment.

‘The caterpillar did not betray itself. / It fulfilled itself.’ - lines like this will captivate you throughout.

The gentleness of the piece is what I loved the most. The trust it places in quieter forms of becoming. No performance. No grand announcement. No need to explain itself. Just slow transformation unfolding at its own pace.

There’s something deeply calming about writing that trusts quietness this much.

A highly recommended read if you just need a moment to breathe.

4. The Performance Trap

Lisa Kostova writes about performance, identity, and the systems that teach people to measure their worth through achievement. This piece moves between personal experience, tech workplace culture, forced rankings, PIPs, and the emotional damage caused when structural decisions are dressed up as personal failure.

Honestly, this was a powerful read. The essay itself feels physical. The stomach drop. The self-doubt. The way a comment can lodge itself somewhere in the body even when your logical mind knows the wider system is at play.

I kept thinking about that gap between knowing something was not really about you, and still feeling it for years afterwards.

The piece also names something I think a lot of people will recognise: the way performance language can build a person and then be used to break them. The same vocabulary that calls someone a top performer, a high achiever, driven, ambitious, turns around to say they’re not working out, they need improvement. Different labels, same machinery.

Lisa’s point that the Rockstar award and the PIP verdict are part of the same tool is clarifying. One says ‘we need you’ and dresses it up as exceptionalism. The other says ‘you are too expensive’ and dresses it up as failure.

Definitely one to add to your saved stacks.

And a special shout out to Code Like A Girl who consistently champions incredible voices.

5. How to bulletproof your taste in the age of AI

Mia Kiraki 🎭 writes about using AI without losing your own judgement, and this piece does that in the most Mia way possible: Hansel and Gretel, gingerbread, writing taste, practical prompts, and a warning to stay Gretel.

It was funny, useful, and did make me want to bake gingerbread, which I imagine was only half the intended outcome.

Mia frames AI output as the gingerbread house: tempting, comforting, and appearing exactly when you are tired and looking for an easier way through.

The metaphor is brilliant, but what I really loved was the argument underneath it.

Taste is not just what you like. Taste is what you reject.

The sentence you cut. The phrase you refuse. The transition that technically works but has not earned itself. The rough edge you keep because smoothing everything down too perfectly starts making the work feel less alive, less chosen, less yours.

I’ve been thinking about this a lot in my own writing lately. Especially the parts I leave a little imperfect on purpose because nine times out of ten that’s exactly where my voice lives.

The piece is also practical in the best way. It doesn’t just say ‘protect your taste’ and leave you there looking dramatic in the forest. It gives you things to do: feed your judgement better work, practise explaining what feels wrong, and publish the pieces that make you slightly nervous.

Or, as Mia puts it: stay Gretel.

6. AI Beats Doctors. Musk Confesses. US Cuts Thousands More Jobs

MrComputerScience’s AI roundups are always a rollercoaster, and this one was no exception.

AI spotting cancer years early. AI outperforming doctors in triage. Musk and OpenAI in courtroom drama. China drawing a legal line around AI layoffs. US companies cutting thousands of jobs anyway. And then, somehow, a perennial fruit food forest prompt at the end.

A very normal sequence of events.

What stood out to me most was the contradiction running through the whole piece. The same technology can genuinely improve people’s lives, while also becoming a language for efficiency, displacement, and power consolidation, depending on who is holding it and why.

That’s the AI conversation that reruns in my mind. Not whether it’s good or bad in the abstract, but who benefits, who gets protected, who gets automated around, and who is left carrying the consequences.

Read it to understand why ‘your safety net is from 1935’.

I love reading Mike’s roundup, as much as I love sharing his prompts, which always feels like an unexpectedly wholesome side plot in the AI news cycle.

And that’s it for this week.

A room full of writers holding onto taste, attention, language, the body, the slow shape of becoming.

Which, on reflection, is what I most wanted from this week’s reading. Less time inside the dream. More time noticing when I’m in it.

Thank you for being here.

Jade