Hello hello

Please to meet you!

I yesterday I smelt the ground coffee! It is one of the best ones, don’t you agree?

Might bake some rhubarb pie if it’s still in me this smell

With vanilla sauce

And hey, did you see that after this rain, there was a warm sun.

The Apple trees looked as if they really were having a great summer, I picture these roots they’ve got like giant straw hands grabbing for the sustenance down below and sucking it up towards the sky! Relishing both the sun and the rain

I cooked yesterday, just lit the grill up and took whatever I found in the freezer

Some vegetarian food pre processed taste really like bark

I’m trying to be positive, it’s my mortar after all

Great great time for some more work

Hey do you use vim a lot for your daily work?

I see people do

:wq

To quit of course

Or even

:x

But I just go shift+ZZ

[FOTO]

Jose Vicente Grau Cardosa

Economista (UOC) especializado en Supply Chain.

Más de tres años en logística, combinando tráfico nacional, internacional y operaciones import/export.

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🔗 LinkedIn

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—

Formación: FP Superior en Transporte y Logística · Grado en Economía (3er año) · Erasmus+ en Bosnia · B2 First (Cambridge) · Formación aduanera UNED.

Experiencia: Grupo Arola · Transbenifayo · CSP Logitren · Valenciaport (FP Dual).

Intereses: logística, comercio internacional, datos aplicados a la economía y optimización de procesos.

📍 Benifaió (Valencia) · +64 635 95 89 26

Above: Not a fictional character, not from TV or film, but a real live person. Cédric Villani (actual last name), French mathematician and politician, spotted in Standart's Enki Bilal documentary. Love me an eccentric. Also of note: North American graphic novelists are rarely if ever seen conversing with mathematicians/politicians. This, I suppose, is part of what separates the French from Americans.

Below: The road back to Cairo from Suez. The construction goes on forever. Cairo, already an insane megalopolis, continues to balloon.

Finished the final touches on the design for the box that will collect the serialized editions of THE SOLAR GRID. My co-publishers at Radix Co-Op tell me it'll debut at the NY Art Book Fair in September. Cover reveal when I get the green light.

Gearing up for THE SOLAR GRID panel at Petrocultures 2026 in Dresden, which will be held on August 27 from 11:00am-1:00pm. I am told that it'll be held in a conference room with a capacity of up to 400 people.

Today: – Finishing a small illustration for a new Houston-based micro press. – Conference call for a potential podcast graphic. – Early prep work for a potential TSG-related exhibition. – Getting my brand new kitchen faucet replaced. Already. – Podcast episode review for edits.

#journal

No red flags and there are several green flags, and I’m a little bit scared because maybe this could be the one.

Old Smoky (Gouda)

Cheese from Jalisco.

Just a fraction of the other cheese selection.

The market.

Pickle Beer.

CORNBREAD ECLAIRS, chicken liver mousse, Luxardo cherries, chives.

MELON GAZPACHO, Le Zette sheep milk yogurt, crispy prosciutto, finger lime, mint.

MT. LASSEN TROUT, Khao Tod succotash, Sai Oua pork sausage, citrus velouté, peanuts.

The sun himself is weak when he first rises

Some days... I lose my mind.

I lost it last night. Hours went by and I could not remember if it was was real or fabrication. My compass, that guided me for so many years, when I check it now, it does not spin, but it bounces wildly from true north to other places on the map.

How does a boy navigate when his direction is inverted? I'm looking for my north star. I'm looking.

Maybe it isn't dark enough yet?

---

Today, just to day, let's not take life quite so seriously?

Deal?

Okay!

---

---

---

It's never a bad time for a cheese party!

---

Life in this country is shockingly luxurious. No one has everything they want. But...then I notice the peanut butter section at the grocery store and realize how privileged we all are.

Like nobles in Versailles.

Only with less head-loping.

Hopefully.

---

Client Work!

11:50a

Big posting to client's client tomorrow.

Funny how advertising is. I'm a guy in my bedroom, ahem, my STUDIO, making amazing art... well 'amazing' is probably a bit hyperbolic... making stuff, that's better. Anyway, I'm selling my services to a production studio. They sell that to an ad agency, they sell that product to the end client.

So, I'm the fourth guy down the chain on this. That's a LOT of approvals to get it out the door and green-checked to go into the world.

REGARDLESS! this three weeks of work ships final on Friday, meaning I'll be back to making sketchbooks, writing about Europe and staring into space. That's what romantic poet essayists, do, you know? Star into space. Though that's usually filled with boy scout stuff like helping little old ladies across the street and fetching groceries. :–)

I may not be a great man, but I'm trying to be a good one at least.

IF it all goes well, think I'll take a few days and go camping next week. My wife get's back from PSS (school) next week and she'll be ready for a break.

Okay! Better get this retouching done... oh, wait, no! It's LUNCHTIME!

:–)

---

12:30P

Shin-Raising a Glass

Have I ever told you about my buddy, Shin?

This guy.

He's absolutely amazeballs.

I love him to death.

He lives half a world away. We met on a volunteer project fifteen years ago, and if you'd asked me then which of those people I'd still be talking to years later—sharing my darkest fears, biggest failures, and the places where I still come up short—I never would have guessed it would be him.

But here we are.

It turns out we're wired in remarkably similar ways. We have many of the same weaknesses. Our wives have many of the same strengths and struggles. In a strange way, talking to Shin is a bit like talking to myself—but with the enormous advantage of hearing my own thinking from someone who isn't trapped inside my own head.

He's solved problems I'm still wrestling with and I've helped him through some that I've already fought.

There's this beautiful exchange of ideas, encouragement, correction, and goodness that I've only experienced with a few people in my lifetime.

The Bible speaks of friends who are “born for times of distress.”

It's a verse that I have long loved. I think Shin and I have become that for one another.

Ninety minutes on the phone with him leaves me feeling... human again.

Not perfect.

Not finished.

Just... capable.

Capable of being kinder than I was yesterday.

More patient, more thoughtful, more willing to put away selfishness and choose the path of building others up instead of making mself feel comfortabel.

Lately I've been thinking a lot about self-control.

Growing up in a house of violence, anger wasn't something you mastered. It was something people flexed. Tempers weren't controlled; they were wielded.

It took decades to break that horse.

Or at least to get it mostly broken.

I thought that was the battle.

Then I discovered there's another horse entirely.

A quieter one... and WAY more powerful, more intense.

Inward storms that flood worlds not by exploding outward but causing us to turn on our better judgment and chase the unattainable.

Apparently becoming an adult isn't about taming one beast and getting the trophy. It's discovering there's always another challenge hiding behind a tree.

Being human is astonishing.

We have this incredible capacity for love, generosity, courage, sacrifice, forgiveness, friendship. Entire libraries have been written trying to explain what makes people choose goodness over selfishness.

And somehow, one of the greatest gifts in that journey is another person who simply refuses to let you settle.

Someone who reminds you—sometimes without even trying—that you can be better than you were yesterday.

That's what Shin has become for me.

A reminder.

An encouragement.

A friend.

Who makes me want to become the kind of man others can trust. The kind who brings peace instead of turmoil. Hope instead of cynicism. Contentment instead of complaint.

None of us become that person alone.

So tonight, I'm raising my glass to fifteen years of friendship.

To honest conversations.

To brothers who tell the truth.

And to you, Shin.

Thank you, my friend.

---

5:30pm

Better is the end

Heavy news: two longtime friends of mine who are full time volunteers and spent the last 5 years fighting cancer are on the back end of a 3rd surgery. They THINK they finally got it all. They took all the parts that can grow the cancer... so let's HOPE!

Pray.

The heavy news is that they just found out their volunteer assignment is changing. This is a tough transition, one that I made in my own way and one that I've had 2 dozen friends make. It is never easy, and they're VERY scared. This is a big adjustment. They are in their late 40's and spent the last 20 years doing nothing but taking care of other people. Now there will be jobs to find, homes to rent, a life to rebuild.

It's not immediate. The team they're attached to is keeping them on until she's fully recovered and back on her feet. Which is probably 3 months, I'm guessing.

When you love someone, you only want the best. But what's best isn't always what's easiest. And this won't be an easy change for them. But they are both so kind and so generous, I have absolutely no doubt they will succeed.

There's a Proverb that says 'Better is the end of a matter than its beginning.' And in my experience, this always true. I'm looking for the end of a matter right now, and I'm confident it will work out for the best in the long run for everyone. Wiser, funner and more of good things than not. But sheesh, getting there is the low road to hell.

I know A and M will do fine.

Maybe time to make that guest room ready to guest. Think I'll go say a prayer.

---

645P

It's been A LOOOOOOONG day. I started at 9 after staying up until 5am because I'm stupid. I fell down a well, what can I say.

Everything took longer than it should have, but without distractions, it was still very productive. I got 4 of my 6 images done. At 30x30 inches, that's an achievement. Then I got changes on them all!

haha! So I'll be up late again finishing image #5 and revising 1-4. Then tomorrow morning, up early and KOing #6 for an EOD showing to the client.

My guys are super calm, so that means everything is supergroovy!

Tonight's screening while I work: Galaxy Quest – Feel-good cooperative to overcome a common obstacle. Scratches my SciFi Itch and my dream of being a space faring adventurer. One day. Just as long as I don't have to learn aeronautics.

I may yet slip these surly bonds.

And surely they are. Surly.

Desert, dessert.

I feel a little fragile, I think that's lack of sleep.

Funny story: well, not that funny: we have a cat. Well my wife has a cat. I tolerate it, it tolerates me. Our deal is: I pet her, my wife feeds and everything else's her. Including food.

That dumb cat pesters my wife all day long to be fed.

Since she left, my wife left out a bowl of food. That was gone first thing this morning.

Cat hasn't asked me ONCE for food. I'd say I trained it pretty well.

---

FOOD!!

I always forget to eat when my wife's away. It's the nature of 'creative' work. Your brain get's dialed in and you forget. When I was drinking a lot, it was way worse. I'd have a whiskey or two and it would be 2 o'clock in the morning before I realized I wanted food.

Tonight: BBQ chicken and potato salad. The dinner of champions.

---

8:55pm

### Tearfest

Just got off the phone with my friends who are getting a new assignment. They are in the throes of the grieving process. Learning that they're going to be starting a new chapter in life at 50 is a hard thing.

They know they'll be fine, but they're also going to say goodbye to 30 years of rhythm.

And so we all cried together... I couldn't say enough good things about them and they were equally kind to my wife and I. I feel so unworthy. But I appreciate their kindness.

I hope hope hope and pray they move here. At least for a little while. They're probably six months out... so time will tell. We agreed to make a road trip up to see them in October (they live in NY). So it will be a good transition.

Some days feel so empty and... faded sort of. Grey. And others just overflow with love and joy and kindness. Today may have started a little rocky, but it's shaped up to be an absolute boon.

I wish I could package this feeling and post it hear for you to download into your heart and mind!

Okay! I'd better get serious about work!

---

You have done everything right. You read the job description twice, tailored the application, rehearsed the difficult questions in the shower, ironed the shirt that only the top half of the camera will ever see. You log in two minutes early, because being early is a habit you cannot break, and you wait. A box appears. A voice, smooth and untroubled, begins to speak. It thanks you for your time. It asks you to describe a moment when you overcame a significant challenge. And somewhere in the second sentence of your carefully prepared answer, a quiet realisation settles over you like cold water: there is no one there. The voice is not listening in any sense you would recognise. The chair on the other side of the conversation is empty. You are performing sincerity, vulnerability, ambition, for a system that will compress all of it into a vector and a score.

This is no longer a fringe experience or a Silicon Valley curiosity. It has become, with startling speed, one of the most common ways that people in the United States, the United Kingdom and Australia now encounter the labour market. And it is producing a strange new emotion that does not yet have a settled name: the feeling of having prepared, in good faith, to be seen by someone who was never going to be there.

The Scale of the Empty Chair

In May 2026, the hiring software company Greenhouse published the results of a survey of 2,950 active job seekers across the United States, the United Kingdom, Germany, Ireland and Australia. The headline figure was the kind of number that makes you read it twice. Sixty-three per cent of candidates reported that they had already been interviewed by an AI. Six months earlier, the same measure had stood thirteen percentage points lower. Whatever the future of work is, it is not arriving gradually. It is arriving in quarters.

What gives the Greenhouse data its particular sting is not the adoption rate, impressive though it is, but the asymmetry that surrounds it. Seventy per cent of candidates said they were never clearly told, ahead of time, that an AI would be the thing evaluating them. For roughly one in five, the discovery came only once the interview had already begun: the box opened, the voice started, and the human they had braced themselves for simply failed to materialise. Thirty-eight per cent of those surveyed had already withdrawn from a hiring process specifically because it involved an AI interview with no human present, and a further twelve per cent said they would do the same if asked. Only eighteen per cent believed their prospective employers had any clear policy governing how AI was used to judge them.

The numbers compound into something close to a paradox. A practice that half of all candidates find serious enough to walk away from is being deployed, at scale, without disclosure, without policy, and without consent. Daniel Chait, the chief executive of Greenhouse, put the diagnosis bluntly when the survey landed: most AI in hiring today, he said, is making a bad system worse, generating more applications, less signal and less transparency. His chief people officer, Sharawn Tipton, was sharper still. Seventy per cent of job seekers, she noted, were not told AI was involved at all. AI, in her phrasing, is not fixing bias; it is scaling it.

The downstream experience is no kinder. Of the candidates who completed an AI interview, the Greenhouse figures suggest only around twenty-eight per cent were moved forward, thirteen per cent were formally rejected, and a remarkable fifty-one per cent received no feedback whatsoever. They were neither advanced nor turned away. They were simply left in the silence that follows a conversation with no one in it.

A New Name for an Old Injury

In January 2026, a paper appeared on the preprint server arXiv that gave this whole landscape a piece of vocabulary it had been missing. Written by Ibrahim Denis Fofanah of the Seidenberg School of Computer Science and Information Systems at Pace University, and titled “The Algorithmic Barrier: A Framework for Artificial Frictional Unemployment and Information Asymmetry in Automated Recruitment Systems”, it proposed that a meaningful share of contemporary joblessness is, in a precise and unsentimental sense, manufactured. Not by recession, not by automation eating the jobs themselves, but by the machinery that is supposed to connect people to the work that already exists.

To understand why “artificial frictional unemployment” is such a loaded phrase, it helps to know where the unloaded version comes from. Frictional unemployment is one of the oldest and most respectable ideas in labour economics. It describes the joblessness that exists simply because matching workers to firms takes time: a vacancy cannot be filled instantly, and a person cannot sift through every posting at once. The economists Peter Diamond, Dale Mortensen and Christopher Pissarides built an entire formal apparatus, the search-and-matching framework, around exactly this problem, work that earned them the 2010 Nobel Memorial Prize in Economic Sciences. In their account, friction is natural, even healthy. It is the cost of a dynamic economy in which people change jobs, firms open and close, and information is never perfect. Full employment, in this tradition, has never meant zero unemployment; it has always included a residue of people in motion between roles.

What Fofanah's paper argues is that we have begun, quietly and at scale, to add friction that has nothing to do with any of that. The new friction is not the natural cost of search. It is an artefact of design. Applicant tracking systems and automated screening tools, the paper contends, have reframed hiring as a high-precision classification problem, one tuned above all to avoid the embarrassment of a bad hire. In statistical terms, the systems are optimised to minimise false positives, the unsuitable candidate who slips through. The predictable consequence is a surge in false negatives: qualified people quietly discarded because the language in which they describe themselves does not align with the language the machine has been told to look for. A nurse who has used clinical software for a decade is filtered out for lacking “computer experience”. A designer is rejected for not listing a degree in programming. The skill is real. The signal is lost in translation.

This is the heart of the concept. Artificial frictional unemployment is the joblessness of people who are not, in any genuine sense, unsuitable. They are simply illegible to the system reading them. The paper's proposed remedy is technical, a candidate-side architecture called JobOS that would standardise, verify and semantically translate a person's competencies into a form the machines can parse. The accompanying simulation is careful about what it claims: a controlled proof of concept built to demonstrate the mechanism rather than measure its scale, showing that variation in wording alone is enough to manufacture false negatives, and that semantic competency mapping recovers applicants a keyword system wrongly discards. What it does not establish, as Fofanah says plainly, is how much real-world friction is artificial, a question he leaves to future field studies. That restraint deserves respect. The deeper contribution is conceptual. It hands a name to an experience millions of people have had and could not quite describe: the sense of being rejected not for who you are, but for how badly you compressed.

The Hidden Worker Was Already Here

If this all sounds suspiciously like a problem invented by the latest wave of generative AI, it is worth remembering that the mechanism predates the chatbots by years. In 2021, researchers at Harvard Business School, working with Accenture, published a study that has aged into something close to prophecy. They coined the term “hidden workers” to describe people who are perfectly capable of doing a job but rendered invisible to employers by the very systems designed to find them. Their estimate of the scale was extraordinary: more than twenty-seven million such workers in the United States alone, locked out not by a deficit of skill but by a deficit of recognition.

The detail that haunts the report is not the headline number but the admission buried inside it. Eighty-eight per cent of the employers surveyed conceded that their own screening tools were filtering out qualified candidates. They knew. Nearly nine in ten companies were aware that their automated gatekeepers were rejecting people who could do the work, and the overwhelming majority had no plan to do anything about it. With algorithmic screening now embedded in virtually every large employer, the gap between what these systems filter and what the job actually requires has become one of the quietest structural failures in the modern economy.

What the 2026 wave of AI interviewing adds to this older story is a cruel new intimacy. The applicant tracking system rejected you in private, before you had invested much of yourself. You sent a CV into a void and heard nothing, and while that is dispiriting, it is at least impersonal in a way that protects you. The AI interview asks for more. It asks you to show up, to be present, to be vulnerable on camera, to talk about the time you failed and what you learned, and then it processes that performance with the same indifference the CV-screener applied to your keywords. The friction has been moved closer to the bone. You are no longer filtered before you speak. You are invited to speak, at length, to no one.

Disclosure, Consent, and the Asymmetry at the Centre

Strip away the technology for a moment and you are left with a question that is really about manners, and beneath manners, about power. When seventy per cent of candidates are not told that a machine will judge them, and only eighteen per cent of employers have any clear policy on the matter, what has actually broken is not an algorithm. It is the most basic norm of reciprocity that has always underpinned the act of applying for work.

An interview, historically, has been a two-way evaluation dressed up as a one-way one. Yes, the employer is assessing the candidate. But the candidate is also reading the room: gauging the warmth or coldness of the interviewer, noticing whether questions are thoughtful or rote, deciding whether these are people they could stand to work alongside. The exchange is asymmetric in power, certainly, but it is mutual in information. Both sides learn something. Both sides are, however briefly, exposed to each other.

The undisclosed AI interview collapses that mutuality entirely. The candidate is fully exposed, on camera, performing sincerity in real time, while the other side of the table offers nothing back: no face to read, no warmth to gauge, no reciprocal vulnerability, often not even the courtesy of having been told that this is what was going to happen. The Greenhouse data captures how acutely people feel this imbalance. Fifty-seven per cent of candidates said they believed disclosure of AI use ought to be a legal requirement. When more than half of the people subjected to a practice think it should be illegal to do it to them without warning, you are not looking at a user-experience problem. You are looking at a legitimacy problem.

It would be one thing if candidates were rejecting AI outright, retreating into nostalgia for the all-human interview with all its own well-documented biases and inconsistencies. They are not. The same survey found that most people want roughly the same amount of AI, or even more, but with guardrails: forty-four per cent want it disclosed upfront, thirty-nine per cent want a clear explanation of what the AI is actually measuring, forty-six per cent want the option to request a human interview instead, and thirty-eight per cent want a human being to review the AI's verdict before it becomes final. These are not the demands of Luddites. They are the demands of people asking to be told the rules of a game they have already been forced to play.

The Psychology of Being Unseen

There is a particular kind of injury that the empty chair inflicts, and it is worth taking seriously rather than dismissing as squeamishness about new tools. To be seen, properly seen, by another person is one of the deepest social needs human beings have. The job interview, for all its artifice and stress, is one of the few remaining institutional moments in adult life where you present your whole working self to a stranger and ask, in effect, to be recognised as worthy. When that stranger turns out to be a script with a synthesised voice, something in the transaction curdles.

Candidates reaching for language to describe the experience keep landing on the same words. They say it feels awkward, humiliating, dystopian. They describe a one-way interaction with a system that cannot see nuance, cannot answer a clarifying question, cannot register the context that a human interviewer would absorb without thinking. They talk about being reduced to keyword matches and algorithmic calculations, about being processed rather than considered. That last distinction, processed versus considered, is the whole thing in miniature. To be considered is to have someone weigh you, attend to you, hold your particulars in mind. To be processed is to be run through a pipe. Tipton, at Greenhouse, named exactly this when she observed that candidates feel processed rather than considered, and that the bad experiences travel: people share them, and an employer's reputation erodes one humiliating interview at a time.

The dignity at stake here is not a soft concept. Researchers studying AI in recruitment have begun to argue that automated assessment has, specifically, a dignity problem, distinct from its accuracy problem, because it treats people without regard at precisely the moments when they are most exposed and most human. When a rejection arrives through a process that feels opaque, robotic and indifferent, the harm is not only practical, the lost income, the prolonged search. The harm is to your sense of being a person whose effort registered somewhere. You prepared for a conversation. You got a transaction. And then, more than half the time, you got nothing at all, not even the closure of a no.

It is worth being honest that the picture is not uniformly grim, and the better operators in this space know it. Sapia.ai's “Humanising Hiring” research, published in September 2025, drew on more than a million AI chat interviews and eleven million words of candidate feedback across more than thirty countries, reporting average candidate satisfaction of 9.05 out of ten. Many candidates, it found, preferred a well-designed AI conversation to a rushed or distracted human one, saying the AI felt more patient, more consistent, less prone to snap judgement. Kathi Enderes, SVP Research and Global Industry Analyst at The Josh Bersin Company, called it one of the most comprehensive examinations of candidate experience to date. The caveat belongs in the open: this is a vendor reporting on the reception of its own product, measured with its own instrument, and satisfaction data gathered by the party under evaluation tends to flatter. It should be weighed carefully rather than waved away; the sample is enormous and the finding is not implausible. A bored recruiter glancing at the clock is not a gold standard worth defending. The problem the 2026 data exposes is not that AI is inherently more dehumanising than a human. It is that AI deployed without disclosure, without explanation, without a human fallback and without any feedback at the end is dehumanising, and that this careless version is the one most people are actually meeting.

What It Does to Trust

Trust, in the employment relationship, has always run on a kind of advance credit. You apply to a company believing, provisionally, that it will treat your candidacy in good faith: that a real person will at least glance at your effort, that the process is what it claims to be, that the firm is the kind of place that behaves decently toward people it has not yet hired. The undisclosed AI interview spends that credit recklessly. The first substantive thing the company tells you about how it operates is that it was willing to let you talk to a machine without mentioning it. Whatever else you learn later, you have already learned that.

The damage runs in both directions, which is the part employers tend to miss. Tipton has pointed out that recruiters themselves are inundated and anxious, worried about being automated out of their own jobs, and that there is a trust gap on both sides of the table. The AI interview did not appear because hiring teams are villains. It appeared because application volumes, inflated in no small part by candidates using AI to fire off hundreds of tailored applications, have become genuinely unmanageable. One set of machines is answering another. The human beings at both ends are increasingly bystanders to a conversation between systems, each side suspecting, correctly, that the other is not really there.

This is the trap that the labour market is sleepwalking into: an arms race in which candidates automate their applications because employers automate their screening, employers automate their screening because candidates automate their applications, and the signal that the whole edifice exists to transmit, can this person actually do this job and would we want them here, gets drowned in the noise that both sides are generating to cope with the noise. Trust is the first casualty, and trust is expensive to rebuild. An employer that treats applicants as inputs to be processed should not be surprised when the best of them, the ones with options, the ones confident enough to walk, do exactly that. The thirty-eight per cent who have already withdrawn are not a random sample. They disproportionately include the people any sane organisation would most want to hire.

The Economics of Discarded Signal

Zoom out from the individual humiliation and a macroeconomic shape comes into view, and it is not flattering to anyone. The polite economic story about frictional unemployment has always been that the friction is, on balance, productive: it represents people taking the time to find the right match, which is good for them and good for the firms that eventually land them. Artificial frictional unemployment inverts that logic. The friction it introduces produces no better matches. It simply destroys signal, leaving good matches unmade on both sides.

Consider what the systems are actually doing to the information economy of hiring. A qualified candidate generates a signal, a body of experience, a way of describing it, a manner, a set of competencies, and submits it. A well-functioning labour market transmits that signal to an employer who needs precisely it. The keyword screener and the carelessly tuned AI interviewer act as lossy compression: they throw away most of the signal and keep a thin, distorted residue. The nurse who cannot get past “computer experience” is not a market clearing efficiently. She is a match that should have happened and did not, a vacancy left open and a worker left idle, the two of them separated by nothing more substantial than a semantic gap.

Multiply that across the twenty-seven million hidden workers the Harvard study identified, across an economy in which vacancies and unemployment have at times risen together in a way the old models struggle to explain, and the cost stops looking like an individual misfortune and starts looking like a drag on aggregate productivity. Firms complain they cannot find talent while their own tools reject it. Workers conclude the market is rigged and reduce their search effort, or drop out of the official labour force altogether, which is precisely the behavioural response the search-and-matching tradition would predict from people who have learned that effort does not pay. The friction is artificial, but the unemployment it produces is entirely real, and so is the output that never gets made.

There is a distributional edge to this as well, and it cuts the wrong way. The candidates best placed to game an AI interview are those who have been coached on how the systems work, who know to seed their answers with the right vocabulary, who can afford the tools and the tutoring that decode the black box. The Greenhouse analysis flags exactly this risk: that those coached on AI tools gain an advantage over those without access, and that AI hiring deployed carelessly will accelerate existing inequities rather than dissolve them. A system sold on the promise of objectivity ends up rewarding fluency in its own quirks, which is just a new name for privilege.

There is a slower, more corrosive cost too, one that does not show up in any quarterly figure. Labour markets run partly on belief, on the shared expectation that effort and ability will, eventually, be rewarded with a fair look. That belief is a public good, and like all public goods it is easy to deplete and hard to replenish. Every candidate who walks away from an empty chair, every applicant left in the fifty-one per cent silence with no decision and no feedback, learns a small lesson about how much their effort is worth to the institutions they are trying to join. They tell their friends. They tell the internet. The Greenhouse figures already show the cynicism hardening: only twenty-one per cent of candidates believe employers are using AI responsibly, and more than a third reported perceiving age bias from the process. When a generation of workers concludes that applying for a job is an exercise in performing for an indifferent machine, the resulting withdrawal of faith is not a soft cost. It is a structural one, and it will be paid by the very employers who imagined they were saving money.

What Fairer Machinery Might Look Like

None of this is a counsel of despair, and it is emphatically not an argument for pretending the pre-AI world was a meritocratic idyll. It was not. Human interviewers are biased, inconsistent, swayed by the firmness of a handshake and the school on a CV. The interesting question is not whether to use machines but how to use them in a way that adds signal rather than destroying it, and that treats the people on the other side as people. The outlines of an answer are already visible, partly in regulation and partly in what candidates themselves are asking for.

The regulatory scaffolding is being built, unevenly, in real time. New York City's Local Law 144, in force since 2023, requires that automated employment decision tools undergo an independent bias audit each year, that a summary of the results be posted publicly, and that candidates be notified that such a tool will be used and told of their right to request an alternative. It is, in principle, exactly the disclosure-and-consent regime the Greenhouse respondents are crying out for. In practice, a December 2025 audit by the New York State Comptroller's office, covering July 2023 to June 2025, found the law's enforcement to be ineffective, hobbled by weak complaint handling and inaccurate compliance reviews. Seventy-five per cent of test calls to the city's 311 hotline about these tools never reached the Department of Consumer and Worker Protection, the agency charged with enforcing it; and when that department reviewed thirty-two companies it flagged one violation, while the Comptroller's auditors found seventeen potential ones in the same set. The framework is sound; the teeth are missing.

The European Union has the larger hammer, and has just postponed the moment it falls. Under the EU AI Act, systems used to filter applications and evaluate candidates remain classified as high-risk under Annex III, and the obligations are substantial: risk assessments, technical documentation, bias testing, meaningful human oversight, transparency disclosures and continuous monitoring, with a specific duty to inform the people subject to them, and a scope reaching beyond conventional employees to freelancers and platform workers. What has changed is when it starts to bite. Under the Digital Omnibus on AI, agreed provisionally on 6 May 2026, confirmed by Member State representatives on 13 May and granted final approval by the European Parliament on 16 June, the Annex III obligations were pushed back from 2 August 2026 to 2 December 2027: a sixteen-month deferral, fixed and unconditional, replacing an earlier proposal that would have tied the start date to the readiness of technical standards. Annex I systems embedded in regulated products slipped in parallel, from August 2027 to August 2028. The stated reason was that the regulatory infrastructure needed to make the obligations operable had not materialised on schedule: a candid admission, and for anyone waiting on protection a cold one.

The shape of that delay reproduces this essay's problem exactly. Article 50's transparency obligations were not postponed; they remain live from 2 August 2026. So the layer that tells you a machine is involved arrives on time, while the machinery that would make it answerable, the bias testing, the documented risk assessment, the human oversight meant to stand between an algorithmic verdict and your livelihood, slips by sixteen months. Candidates get the disclosure and wait until December 2027 for the substance behind it: told what is happening to them, given no means to contest it. Whether enforcement matches ambition remains the open question, the same one New York is currently failing. The direction of travel is still clear, disclosure and human oversight migrating from courtesy to legal requirement, but the timetable has slipped.

The American picture follows the same rhythm of ambition and deferral. Colorado passed the country's first comprehensive state AI statute, SB 24-205, and never brought it into force: a federal court halted enforcement on 27 April 2026, and it was repealed and replaced by SB 26-189, a narrower automated-decision-making-technology regime signed by Governor Jared Polis on 14 May 2026 and effective from 1 January 2027. What survives the narrowing is instructive. Deployers must give consumers clear and conspicuous notice before the technology is used in a decision affecting them; must furnish, within thirty days of an adverse decision, a plain-language description of it and of the automated system's role; and must offer meaningful human review and reconsideration on request. Disclosure upfront, an explanation, a human in the loop: very nearly the list the Greenhouse respondents gave. The law is converging on the candidates' own asks. It also does not begin until 2027, and Colorado's first attempt died before it bound a single employer.

Beyond compliance, the design principles are not mysterious, because candidates have spelled them out. Tell people, before they invest themselves, that AI will be involved. Explain what it is measuring, so the exercise is a test and not a trap. Offer a human alternative to those who want one, which is most of them. Put a human being in the loop to review the machine's verdicts before they become destinies. Close the loop with feedback, so that the fifty-one per cent currently left in silence at least receive the dignity of a decision. And audit the systems for the bias they are so good at scaling. Fofanah's JobOS proposal points at the same goal from the other direction: give people a way to make their signal legible to the machines, rather than leaving them to be discarded for failing to speak fluent algorithm. The technology to do all of this exists. What is mostly missing is the will to slow down enough to use it.

The Chair Is a Choice

Return, at the end, to the person logging in two minutes early, because that person is the whole argument. They did not ask for the labour market to become a conversation between systems. They simply wanted a job, and believed, reasonably, that wanting it and being able to do it might be enough to earn them a fair hearing from another human being. The empty chair tells them otherwise. It tells them that their preparation, their nerves, their carefully chosen story about the time they failed and recovered, all of it was poured into a vessel that was never going to hold it.

What is happening to their relationship with work is a slow withdrawal of faith. Not a dramatic refusal, just a quiet recalibration: apply to fewer places, expect less, invest less of yourself, assume the no before it arrives. What is happening to their relationship with employers is the conversion of provisional trust into settled suspicion. And what is happening to their sense of being seen is the discovery that an institution they had imagined was, at some level, about people, has decided that people are the expensive part.

The deepest point is that there is nothing inevitable about any of this. The empty chair is not a law of physics. It is a procurement decision, a default setting, a box left unticked on a configuration screen by someone who never had to sit on the other side of it. Every one of the harms in the Greenhouse data, the non-disclosure, the missing policies, the silence where feedback should be, is a choice an organisation made and could unmake tomorrow. The machines are not the problem. The problem is that we have allowed the machines to inherit, and amplify, our willingness to treat the people who want to work for us as a queue to be cleared rather than a set of human beings to be met. The interview was always a small ritual of recognition, an hour in which a stranger's life mattered enough to attend to. We are deciding, application by undisclosed application, whether that ritual is worth keeping. The candidate is still showing up, early, prepared, hopeful. The only question is whether anyone will be there.

References

1. Greenhouse, “63% of Job Seekers Have Faced an AI Interview. Most Haven't Had a Good One Yet”, Greenhouse Newsroom, 1 May 2026. https://www.greenhouse.com/newsroom/63-of-job-seekers-have-faced-an-ai-interview-most-havent-had-a-good-one-yet
2. Greenhouse, “AI interviews in hiring: What candidates actually want, and how to get it right” (2026 Candidate AI Interview Report), Greenhouse Blog, 2026. https://www.greenhouse.com/blog/2026-candidate-ai-interview-report
3. Ibrahim Denis Fofanah, “The Algorithmic Barrier: A Framework for Artificial Frictional Unemployment and Information Asymmetry in Automated Recruitment Systems”, arXiv preprint 2601.14534, submitted 20 January 2026, revised (v2) 2 July 2026. https://arxiv.org/abs/2601.14534
4. Fortune, “Nearly 4 in 10 job candidates have bailed on a hiring round because it required an AI interview”, 4 May 2026. https://fortune.com/2026/05/04/4-in-10-job-candidates-bailed-hiring-rounds-required-ai-interview/
5. HR Dive, “Job candidates say they're quitting the hiring process over AI interviews”, 2026. https://www.hrdive.com/news/job-seekers-walk-away-from-AI-interviews/819443/
6. The Harvard Gazette, “New study says 'hidden workers' are being excluded”, Harvard University, September 2021. https://news.harvard.edu/gazette/story/2021/09/new-study-says-hidden-workers-are-being-excluded/
7. New York City Department of Consumer and Worker Protection, “Automated Employment Decision Tools (AEDT)”, New York City. https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page
8. Office of the New York State Comptroller, “Enforcement of Local Law 144, Automated Employment Decision Tools”, 2 December 2025. https://www.osc.ny.gov/state-agencies/audits/2025/12/02/enforcement-local-law-144-automated-employment-decision-tools
9. European Commission, “AI Act, Shaping Europe's digital future”, European Commission. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
10. EU Artificial Intelligence Act, “Annex III: High-Risk AI Systems Referred to in Article 6(2)“. https://artificialintelligenceact.eu/annex/3/
11. Gibson Dunn, “EU AI Act Omnibus Agreement: Postponed High-Risk Deadlines and Other Key Changes”, 2026. https://www.gibsondunn.com/eu-ai-act-omnibus-agreement-postponed-high-risk-deadlines-and-other-key-changes/
12. Morgan Lewis, “EU Approves Delays and Other Amendments to Certain EU AI Act Obligations: What Businesses Should Know”, June 2026. https://www.morganlewis.com/pubs/2026/06/eu-approves-delays-and-other-amendments-to-certain-eu-ai-act-obligations-what-businesses-should-know
13. AI Compliance Atlas, “Colorado AI Act (SB 24-205, repealed and replaced by SB 26-189)”, 2026. https://aicomplianceatlas.com/law/colorado-ai-act
14. Sapia.ai, “Humanising hiring: the largest study of AI candidate experience ever”, 18 September 2025. https://sapia.ai/resources/blog/humanising-hiring-the-largest-study-of-ai-candidate-experience-ever/
15. RM Compare, “AI Assessment has a dignity problem, here's how to fix it”, RM Compare Blog. https://compare.rm.com/blog/ai-assessment-has-a-dignity-problem-heres-how-to-fix-it/
16. The Nobel Prize, “Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2010” (Diamond, Mortensen, Pissarides). https://www.nobelprize.org/prizes/economic-sciences/2010/popular-information/

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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I've had a Claude Pro subscription for a few months now. I've used it to build a few apps that my kids and I use at home. Most recently, I rebuilt my personal homepage with the help of Claude Code.

Choosing a tech stack

Part of my discussion with Claude was what tech stack to build the new site on. I considered React, ASP.NET, or even a popular static site generator like Eleventy. But at the end of the day, those all felt like overkill for a static site with at most 2-3 pages. I decided to just have Claude build it with plain HTML and CSS. Any future updates I can handle myself by editing those files directly, and with continuous deployment from GitHub to Netlify, shipping a new build is quick and easy.

That continuous deployment pipeline turned out to be one of the real benefits of using Claude to help build websites. It knows GitHub, and it knows Netlify. I had no idea how to set up a pipeline that deploys automatically from GitHub to Netlify, and researching it myself probably would've taken a few hours. With Claude, I had step-by-step instructions and a working pipeline in under 10 minutes.

Getting the design right

The first design Claude came up with was kind of bland. I told it the design was “meh,” and it responded by putting together three more options for me to choose from. One of the designs seems to have taken inspiration from this very own site, it mimicked the blinking cursor, but gave it its own spin, pulling in some design cues from terminals and code. I chose that one. I toned it down a bit from the original concept, but I think it turned out pretty well.

This was the other big benefit of rebuilding the site with Claude. I can build websites, but I'm not much of a designer. Giving Claude some direction and getting back multiple design options to choose from, made that part of the process a lot less painful.

Sunsetting apps.dinobansigan.com

In other news, I took down the Blazor Web App at apps.dinobansigan.com. The site itself is still up, but it's now been replaced by a maintenance page (also built by Claude Code). That also means the Write.as Archive Page Generator app that used to live there is now gone.

Truth is, that app has needed a fix every few months since I built it. The root cause is different each time, but there's always something going on with it. At this point I don't have the bandwidth to keep chasing it, especially for something only a handful of people ever used. So I'm letting it go.

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That's it for this update. Between the new homepage and letting go of of the archive page generator app, it feels like I freed up space in my brain to focus on new stuff. Thanks for reading, and I'll catch you in the next DevLog.

Tags: #DevLog #ClaudeCode #WebDevelopment #WriteAs

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In Summary: * It's nearly time for the opening pitch of my Monday's MLB Game. I'll be listening to the call of the game provided by the Nationals' broadcast team.

And I'll be listening with hearing only at half-strength. I'm using ear wax removal drops to give me what little hearing I now have. Right ear is about half there, left ear is pretty much shut down. This happens to me yearly about this time of year and is not nearly as annoying as when I had season tickets to the Symphony Orchestras of Indianapolis and of San Antonio. It comes, I treat it, and it goes.

Anyway, after tonight's ball game and the night's prayers I'll be looking for an early bedtime.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night.

Health Metrics: * bw= 229.83 lbs. * bp= 137/79 (65)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups, BP breathing exercises, pilates

Diet: * 04:05 – 1 banana * 04:40 – 1 ham and cheese sandwich * 10:15 – pizza * 12:20 – mashed potatoes * 15:00 – 1 bean and cheese taco, 1 bacon and egg taco

Activities, Chores, etc.: * 03:10 – listen to local news talk radio * 03:55 – bank accounts activity monitored. * 04:10 – read, write, pray, follow news reports from various sources, surf the socials, nap * 09:00 – start my weekly laundry * 12:20 to 13:20 – watch old game shows and eat lunch at home with Sylvia * 13:30 – listening to relaxing music while folding laundry * 16:30 – listening to 106.7 The Fan, flagship station for the Washington Nationals, ahead of tonight's game between the Nationals and the Phillies.

Chess: * 09:47 – moved in all pending CC games

My Monday's MLB Game is less than an hour away. The Washington Nationals and Philadelphia Phillies are scheduled to start playing at 5:40 PM CDT. As I usually do, I'll follow the game's score and stats in real time via MLB's Gameday Service where we can also find links to the radio-call of the game provided by announcers of either team we choose.

And the adventure continues.

Fortitude lapses on the furnace of my chill like ripples cascading across an abandoned minefield. All it takes is one surprise snap, and suddenly it's Splash Mountain —arms all akimbo— in feat retracting clamber.

Void of spotlight shenanigans, I sink into the murky peace, and allow the temptation of hesitation to be clobbered by its own path of mutual resistance. Another step of tape-strung prep saving the splay.

It'll be okay. Speed is not for today.

Repetition quotes a diver-tranced “Again!” Pain is my friend. Ascend to the mend. Red lines may welt across this forwarded moment... Uhhhhmmm. ...but I'm fraught with survival, and an excess of laughing matter.

Written August 3, 2026. © 2026 AnOublietteofThought.

I managed ¾ of a mile this morning. It frustrates me to no end, but I'm reminding myself that all movement forward is still movement. I think learning compassion for myself has been one of the most challenging life lessons. It remains ongoing, and likely will continue to do so.

I was once involved with an organization whose motto is “adapt and overcome.” Who knew it'd become a very important mindset in my life. Of course, the definition of “overcome” has gone through its own metamorphosis. Kind of like me.

Chin up, Buttercup! Life may break your body, but your wit and spirit are unconquerable!

Fantastic documentary on Enki Bilal from Standart.

Finally got around to reading Ahmed Khaled Tawfik's 2008 novel UTOPIA (in its original Arabic), which is just brilliant and in 2026 eerily close to reality.

Started watching SILO which I am enjoying enough, though I can't stand Rebecca Ferguson.

#radar

Most mornings when I'm walking to work I listen to music. The playlists I choose are generally like the music version of comfort food, or a favorite pair of comfortable shoes. It is something I enjoy for that twenty minutes or so on my way to work where generally there isn't any enjoyment. Or maybe I shouldn't say there isn't any enjoyment. I think from time to time my coworkers and I intoxicate and entertain each other with sarcasm about how stupid our f'n job is. Is fabricating joy by hurling insults toward a corporate employer behind their back better than no joy at all? I don't know. Probably.

Most days when I listen to music on the way there I usually end up with one of the songs stuck in my head. One morning I had a rather strange and unexpected thing happen. When I got to the edge of the parking lot at work I decided to sit for a moment on the picnic table and finish the song that was playing, which happened to be Empty by Metric.

I removed my phone from my pocket before sitting down. Right after I sat down I unlocked it with my fingertip so I could check and see how much of the song was remaining. Just as the screen illuminated a lyric in the song played, “ask the line on your face what the line on your hand meant”. Not only did I hear it as it was playing, but the lyrics were also showing up below the little picture of the album cover. I also read the words while hearing them.

I had heard the song likely a hundred or more times over the years but I hadn't heard it in awhile. All day at work I could not stop thinking about that one lyric. It was not something that ever stood out to me on previous listens, and I found myself wondering if it even would have stood out this time if I hadn't sat down just then and read the words on my phone while they were being sung.

The lyric seemed to have an implication that maybe (most likely) it would not have had to me earlier in life. Sort of like regret, or like I had missed something fundamental along the way. At the same time though I felt a kind of freedom in knowing there is fuck all I can do about any of it now. The past can haunt me all it wants, but I can't change it. I can only live with the consequences of my bad decisions and enjoy the rewards of the good ones. Try to learn from all of it, and hopefully use what I have learned to make better decisions in the present.