يمكن البعض منكم كيعرف نظام الدفع PIX، اللي تم انشائه من طرف البنك المركزي البرازيلي.

هاد النظام قلق ميريكان گاع! علاش؟ لحقاش مسح فضربة وحدة ارباح بالملايير ديال عمالقة الدفع : VISA و Mastercard

هاد النظام كيتيح تحويل الأموال مجانا بين الناس فالبرازيل 24/7، فقط العمليات التجارية اللي خاضعة للاقتطاع، اما بين الأفراد مجاني.

النظام ملك للدولة، و ارباحه كتبقى فالدولة، داكشي علاش غضبانين منو الوحوش الأمريكية.

و الأجمل : مفتوح المصدر، هاهي الrepo:

https://github.com/bacen/pix-api

المغرب محتاج و بشدة نظام مشابه، او حتى بناء نظام انطلاقا من PIX نيت، اللي يدفع بالبلاد لقدام و تولي عندنا سهولة اكبر فالدفع عوض الأنظمة التقليدية.

زعما زعما؟

Rebellion Against the Conspiracy Against the Human Race by Dr. Raymond Thoss is a peculiar book in a narrow niche of its own. I finished reading it this weekend. Its title references Thomas Ligotti’s treatise The Conspiracy Against the Human Race, the volume of essays in which the horror maestro expounds his profoundly pessimistic worldview. Ligotti maintains that consciousness is a unique burden borne by mankind. His argument, briefly summarized in the Wikipedia article about the book runs thus:

The more conscious one is of the meaningless and often horrifying nature of the world [...], the more one wishes not to be aware of this fact, and so overly conscious beings must constantly engage in exercises which limit their awareness of the negative aspects of existence, either intentionally or instinctively.

Dr. Raymond Thoss is a pseudonym drawn from a character in Ligotti’s fiction. It’s used here by “a clinical psychologist who works primarily with trauma patients”, a vocation he says he was drawn to having suffered major trauma of his own from abuse throughout his childhood. Thoss credits an encounter with Ligotti’s book The Nightmare Factory with saving his life when he read it as a deeply disturbed and suicidal youth. Internalising Ligotti’s nihilistic outlook proved paradoxically therapeutic for him, and has informed his own thought ever since, providing foundations on which he has built a decidedly idiosyncratic view of trauma and of therapy.

Thoss forcefully stresses the irony of treating abuse survivors as sick in a society where child abuse is distressingly commonplace yet still seldom openly discussed. To those cognizant of the sickness of society & the uncaring nature of the world, Thoss says “You are not insane. The world is. You are simply awake.” One hopes he can judge when such thinking will be useful for his patients and when it might be more appropriate to gloss things over a little.

The writing style is often hyperbolic and becomes all the more so in the final chapter when we spend more time in the writer’s troubled mind. This is not a comfortable place to be. Thoss declares himself insane, and his text gives the reader little with which to push back against this assessment. The phrase ‘physician, heal thyself’ comes to mind: but perhaps too much damage was done to him from too early an age for that to be a realistic prospect. One is impressed all the more with his ability to function at a high level — and moreover to provide comfort to others — in the light of the bewildering turmoil of his inner life.

Have you ever, as a fan of a artist or a creative work, been disconcerted to hear from a ‘superfan’ whose attachment to the object of your affection is that much deeper & more intense than your own? I’ve admired Ligotti’s work for decades, and some part of his pessimism has undoubtedly chimed with my own, further tinting my own outlook. Here though is someone for whom Ligotti’s thinking has been profoundly life-changing. It’s good, I’m thinking, but is it really that good: evidently the answer for Dr. Thoss, is yes; while for me, maybe not. That faintly discordant feeling was just one of several overlapping responses this book provoked in me. I’d never read anything quite like it. Fascinating though it often is, it’s a text I would hesitate to recommend. Prospective readers must decide for themselves whether they think it worth picking up.

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I was delighted when a recent visit to one of my customary record-buying haunts yielded a copy of Nancy Wilson/Cannonball Adderley, the 1962 album by the singer and the saxophonist (plus the other four members of the latter’s quintet). Wilson sings on six of the record’s eleven tracks, with the remainder instrumentals. I’ve owned a CD copy for some years, but this is one of those records better savoured on vinyl (or it will be once I’ve cleaned this one up). It’s a bright-toned record beautifully-performed by all concerned. The song-choice isn’t entirely to my taste — ‘Happy Talk’, for example, has never been a favourite of mine — but I can readily forgive that. A good example track: the opening number, ‘Save Your Love for Me’, which kicks things off in style. My copy is a later-’60s issue pressed for the World Record Club (who erroneously printed the title as The Swingin’s Mutual on its labels, this being the name of the similar record Wilson had made with the George Shearing Quintet).

Meanwhile, recent arrivals in the post have included a second copy of Dakota Staton’s ‘Round Midnight, as mentioned in the entry before last, this one in much better condition than the first; and, in a similar vein, an album by the singer Ethel Ennis called God Bless The Child, which is an early-’70s compilation bringing together four tracks from albums first issued in ‘64. It's a fantastic-sounding record, very well re-mastered. While a few of the tunes on it (such as the title-track) are familiar old standards, Ennis’s interpretations of them are well worth hearing.

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Cheese of the week: Carreg Las, yet another Welsh-made blue cheese. This one is made from ewesmilk by those experts at Caws Cenarth. It’s well-blued with a strong suite of flavours reminiscent of Roquefort: if anything perhaps a little bolder still. Its texture on the other hand is a little firmer and drier than the French classic. It has been an immediate hit with me & I hope this is a first taste of many.

Depuis quelques jours, je ponce les podcasts de David Perrell. Il y invite à chaque fois des écrivains de tous horizons, exceptionnels, tous.

À un moment, David révèle son mot préféré : la sérendipité.

Il a cette sensation que le mot en lui même, sa sonorité, porte déjà en quelque sorte la beauté de sa définition.

Ce n’est pas la première fois que j’entends ce mot. Et ce n’est pas la première fois que j’entends quelqu’un dire qu’il aime profondément ce mot.

Je t’avoue que je ne savais plus ce qu’il voulait dire.

Mais si tu veux tout savoir : c’est cette capacité à saisir de la valeur dans une situation inattendue. Autrement dit, c’est réussir à voir le beau lorsque celui-ci ne fait pas de bruit, qu’il passe presque inaperçu.

Pourquoi ce mot fascine ?

Parce que je crois qu’il arrive à capturer une vérité profondément abstraite que l’on cherche tous à embrasser ou ne serait-ce qu’à toucher du doigt.

Faire preuve de sérendipité, c’est donner à la vie sa vraie valeur.

Alors ouvrons les yeux, soyons attentifs.

Governor is the only office Massachusetts republicans have shown that they can win, though only if they run someone who is tall, handsome, and not a politician. Their current candidate for governor, Mike Minogue, is tall (I assume, as he’s a former CEO, and C-suite jobs are pretty inaccessible to short men) and not a politician, but he’s currently running over 20 points behind incumbent Democrat Maura Healey in the polls.

He’s going to get crushed in the election. This is a foregone conclusion. And he sunk 17 million of his own dollars into this vanity campaign. Which presumably isn’t real money to him, but think of what else he could have done with it!

So imagine my surprise when I got a mailer sort of supporting his campaign yesterday!

It’s…well, see for yourself.

(alt text: Maura Healey is a liberal. But Andrea James is a SUPER liberal. Some pictures of James supporters holding signs that say “Free Palestine” and “Free Child Care” and a list of James’ policy priorities, each with an X next to it: End all State Cooperation with ICE/Implement Rent Control and Tax the Rich/Provide free child care and health care/Mandate electric buildings and vehicles/Ban Israeli companies from Massachusetts/Stop construction of new state prisons.

(alt text: Stop sign with an arrow pointing at Andrea James. Below, “Stop the Massachusetts Mamdani. We can’t afford socialist Andrea James!”)

Now, why would Mike Minogue be advertising against Andrea James, who is polling at between 8 and 17%? She’s not a threat to him!

Well, first of all, this isn’t from the Minogue campaign—it’s from the Massachusetts First Independent Expenditure Political Action Committee, which is primarily funded, to the tune of a million bucks, by Robert Neuner, a Connecticut resident and CEO of a company that sells “recreational oxygen.” I am not making this up. (It’s also got funding from local sneaker fascists Jim Davis and Paul Fireman!).

And second of all, this isn’t really an anti-Andrea James flyer. Because even the rich idiots running this super PAC in support of a doomed vanity candidacy can use a voter registration list and know that nobody in my house is voting for Mike Minogue. They’re sending this flyer to registered Democrats not to warn us against Andrea James, but to point out that she better represents our priorities than Maura Healey does.

They have to know that we’re out here waiting in vain for the “Massachusetts Mamdani”, and that the bulleted list of priorities mostly reads like a wish list for Democrats. Free child care and health care? Horrors! She must be stopped!

So clearly the desperate play here is to try to divert enough Democratic voters from Healey to James to allow Minogue to win the election.

It’s not going to happen, but here’s what makes me sad about the whole thing: fascists know exactly what Democratic voters want, and they can spell it out in clear language.

Democrats, on the other hand, continue to run away from what Democratic voters actually want. Maura Healey’s campaign website is basically “she’s queer! She played basketball!” No, that’s not actually all—if you dig around you can find some accomplishments she touts, some of which are good, some of which are less good (millions of dollars in grants to state and local law enforcement for programs that have netted 500 arrests. So let’s say it’s 2 million, which is the smallest amount you can call “millions.” That’s $4k per arrest. Not sure that’s the best use of taxpayer money, but whatever.). And she doesn’t fundamentally address the climate crisis or the affordability crisis or the healthc care crisis or…well, you get the idea.

Don’t get me wrong—I’m going to vote for Healey, because I certainly don’t want Minogue and I have some concerns about Andrea James’ past legal difficulties. But I wish there were a Democrat running on the mostly common-sense priorities that Massachusetts fascists correctly identify as appealing to voters.

Spurs vs Thunder, Tonight.

Though it'll certainly push past my preferred bedtime, tonight's NBA game between my San Antonio Spurs and the Oklahoma City Thunder with its scheduled start time of 8:30 PM CT will be my game of choice tonight. With my bedside Bose radio tuned to 1200 WOAI, flagship station for the Spurs, I'll find it easy to listen to the game then turn down the volume and drift off to sleep when the brain fogs over and lets me know it's time.

And the adventure continues.

by Tijana Cvetković

In May, the Shared Visions consortium and friends gathered in Nikšić, Montenegro, for the Founding Assembly of our cooperative. As part of the program, we picked a name: O.U.R. COOP. Curious how and why we settled on this name? Read Tijana’s report below!

When unable to decide, suspended between possibilities, a shift is needed. Change the scenery, change the rhythm, change the rules, and the answer could appear by itself.

For months we've been trying to name the cooperative. The task was simple. A name is only a name – until it isn't. A name becomes a story, a declaration of intent, an invitation, and occasionally a burden. It carries expectations, creates associations, determines what people imagine before they know anything else about us.

The cooperative is founded by artists and cultural workers from different countries, backgrounds, languages, and experiences. We all had some name ideas. As the months passed, suggestions accumulated, some were poetic, some practical:

The list was long enough to suggest either a diversity of imagination or a complete inability to make a decision. Eventually, the moment arrived when the cooperative needed to be named. We had reached the point where either we would decide on a new name or remain indefinitely attached to the working title inherited from the Shared Visions project, an administrative placeholder. The problem was that the program of the Founding Assembly and 5-day in-person meeting of coop founders held in Montenegro was already full. Since no time slot was left for naming the cooperative, the decision was relocated to a place where decisions are rarely made – to a bus! A bus travelling through Montenegro on the third day of the meeting.

We had one hour available in total: 30 minutes from Nikšić to Grahovo, where we were having group lunch, and 30 minutes on the way back. Around 30 participants were enclosed together in a moving vehicle. A perfect environment for a social experiment. A laboratory in motion. The rules were simple. On the way to the restaurant, a sheet containing all proposed names circulated through the bus. Each participant could distribute three votes, assigning first, second, and third preference points. On the way back, a second round took place. This time we could vote only among the names that had received at least one point in the first round. By then, one proposal had already begun to separate itself from the rest by the majority of votes – OUR COOP.

The second vote merely confirmed what had already become visible during the first. The decision was made. The cooperative will be called O.U.R. COOP – or, in its original form, NAŠA ZADRUGA, but with a twist hidden inside the name. The proposal originally emerged in BHS as NAŠA ZADRUGA, literally meaning Our Cooperative. When translated into English (the common language of our international cooperative) it naturally became OUR COOP. What happens if, instead of reading “OUR” as an English word, we read it as an acronym in BHS? Then it has additional meaning O.U.R. – Organizacija Udruženog Rada, translated into English: Organisation of Associated Labour. The acronym unexpectedly connects the cooperative to the Yugoslav legacy of self-management socialism. An O.U.R. was a basic organisational unit in which workers in all areas, including culture, collectively managed production, governance, and the distribution of resources. Rather than operating through a conventional top-down corporate structure, these organisations were intended to be governed by their workers.

Whether by coincidence or not, the name carries several layers: shared ownership among its members, a reminder of the self-management legacy, and a bridge between local histories and international collaboration.

What remains is not simply a name but a question of how a collective comes into being. Not through a single act of foundation, but through a succession of encounters, decisions, reflections, and shared efforts. The bus eventually stopped. The Montenegro meeting ended. The cooperative got the name. Yet none of these marked a final form. Any living collective or organisation continues to exist only in motion between what it has inherited and what it will become.

What matters is not the point of departure or arrival, but the capacity to keep working together!

Join us on 27 October at 17h CET for an O.U.R. COOP Reading the Scene session with the CEO of a large cooperative bank!

oran Jeras is the CEO and Chairman of the European Ethical Bank (ZEF), based in Zagreb. A former mainstream banking consultant with years of experience in the Netherlands, he became an ethical finance visionary and founded ZEF, Croatia's largest cooperative. ZEF believes in a future society whose economic system is democratic, transparent, solidary, inclusive, rooted in cooperative principles, serving the real needs of communities and caring for the planet. It aims to build tools that enable a sustainable and just transformation of financial infrastructure; to develop members' capacities for active contribution to a good economy, and to change the institutional framework toward greater recognition of the cooperative model.

During our session, Goran will explain ZEF’s banking models and how they support cooperative development.

Yesterday, at lunch I met with an old friend,

He was getting old, feeling that he was losing his beauty, feeling spent, seeing no escape, just the endless grind, and for every day, the feeling that everything he so painstakingly built now is slowly slipping through his fingers, even though he’s holding onto it for dear life

And still, retirement is so very far away

And he asked me, do I notice too now people in general seem to be struggling these days

And I said, that truly I do, truly

But, I said, maybe it’s always been like this, only now we see ourselves reflected in these other people

They just didn’t use to be us, is all.

منين كتشوف الهول ديال الباسووردات و المعلومات الحساسة ديال مختلف الادارات و المؤسسات ديال بلادنا كتتسائل شنو السبب؟

كاين جوج اسباب، اللول ما تقدرش تتحكم فيه و الثاني ممكن يتقاد.

اللول هو بشري، بنادم كيأنسطالي برامج ولا كيحل ملفات Malware مصيفطين فالايميل فيهم

واخا تعيا ما توعي و تقرّي فبنادم راه غيدير الغلط و هادشي كيوقع فگاع دول العالم.

السبب الثاني هو ويندوز، هاد النظام المشؤوم الخاري على دينمو هو سبب أغلب الكوارث الأمنية.

لهذا الحل كيف ما دارو بزاف ديال الدول فالسنين الأخيرة Linux هو اعتماد

اما شي اصدار واجد او كتكلف ادارة معينة تصمم و تعمل التحديثات لشي اصدار محلي خاص

من بين الدول اللي دارت هاد الخطوة :

Pardus تركيا : صممات لينكس خاص بيها سميتو

فرنسا : الدرك الفرنسي كيستعمل واحد الاصدار خاص GendBuntu بيه سميتو

اوروبا : كاين برنامج ممول من الاتحاد الاوروبي لنظام EU OS شامل سميتو

الصين : سنين هادي باش الدولة كتحارب استعمال ويندوز OpenKylin و كتدعم اصدارات محلية فحال

Astra Linux روسيا : الدولة كتشجع على استعمال نظام

Maya OS الهند : وزارة الدفاع تبنّات نظام

هادشي غادي يهنينا من بزاف ديال المشاكل الامنية و يخلي الناس تنفتح على أنظمة اخرى عوض ما يبقاو فالحبس ديال مايكروسوفت.

ملحوظة : خوتي الصغار هادي اكثر من عشر سنين باش علمتهم يستعملو لينكس، و اذا عندكم خوت او وليدات Elementary OS عطيوهم يبداو فشي اصدار ساهل فحال

Irreverent is this moment. —sorting stacks and boxes —aligning aches with pains —dissolving the debts of diverging indifference. —deafening self to the despondent dredges of discontent.

I whittle away paid this-n-thats into an error of conformity. I plague the flatlined observance to devour purpose for practical unseaming. I...I...I...drift to stay— floating in a brailed cistern that sinks all hope of sustaining sought's balanced buoyancy.

If error contorts in tipping wonder, could not the deviation of dwelling direct a derailed blunder into devolving coined debasement to sail? I cannot detail for failure's wake. Rather that I widen my broach into a culture of coached calamity.

May chaos rue its play, for I continue to sway recumbent.

© 2026 AnOublietteofThought. All rights reserved.

Today's musical inspiration. https://youtube.com/watch?v=aKyX-bWK5xU&is=zccgGfPJlCK5n9xN

JOURNAL 20 octobre 2026

Est ce que c’est moi ? Est-ce que je suis une fouteuse de merde partout ? J'ai demandé à To sensei si il voulait bien accueillir deux kendoka français je serai pas là, mais hayame est ok, comme cest lui le chef de cette partie je pensais qu’il n’y aurait aucun problème. Il me dit non tout sec. Ça se fait pas en japonais. Et voilà qu’il se lance dans un grand procès, il trouve il y a trop d'étrangers au Japon, ils détruisent notre culture, il est furieux que j'aie accepté un Américain, il désapprouve ce qu’il appelle la féminisation du dôjô, meme hayame a eu droit. Il reconnaît sa compétence mais il aurait préféré un mec, et voilà qu’il me tombe dessus personnellement avec le procès de ma sexualité perverse et dévoyée etc. J'étais stupéfaite. En même temps je comprends pourquoi il ne veut pas manger avec nous et sortir le soir. C’est un sale vieux con de japonais. Je le lui ai dit. Le ton est monté. On est fâchés. Du coup hayame démissionne. Et moi puisque c’est comme ça j'ai téléphoné à mon frère pour lui dire que je ne reviendrai pas après l'Ukraine. Il est furieux, tout le monde est furieux, yôko veut partir aussi, c’est un désastre ! Ces vieux japonais sont insupportables, on en sortira jamais, on en a toutes marre. Hayame a une offre de formation pour les juniors c’est moins bien payé mais tant pis elle part. Yôko ne sait pas où aller mais elle veut pas rester seule ici. Elle est très compétente, elle retrouvera quelque chose, elle est désolée elle adorait son travail ici. Voilà. Et c’est moi qui ai foutu la merde encore. Je laisse le dernier groupe aux garçons, eux sont biens, ils sont désolés aussi et je rentre avec T chan. On a encore deux jours ensemble, sa tante vient jeudi pour nous rencontrer et repartir avec T, elle lui a trouvé un collège elle pourra finir son année. C’est un peu trop agité ma vie en ce moment, je suis fatiguée.

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J’ai pris mon bain puis j’ai regardé mon téléphone. Il y avait des sms et appels manqués de mon frère puis : (je transpose en français, en japonais c’est un peu plus grossier mais c’est le même sens) — est ce que tu vas décrocher ton putain de téléphone merde j´ai a te parler tête de mule ! J'ai attendu, il a rappelé, j’ai décroché. On s'est insultés comme des chiens pendant deux minutes j’ai fini par le traiter de connard de macho de merde il m'a dit que j’avais un caractère à chier je lui ai fait remarquer qu’on avait les mêmes ancêtres de merde, on a raccroché ensemble et il a rappelé après dix minutes. — est ce qu'on peut parler et un peu m'écouter cinq minutes sans gueuler comme une tomoe en furie que tu es ? Je lui dis oui si toi-même tu cesses de me prendre de haut comme un daimio que tu te crois être. On a repris nos respirations. Il me dit : — écoute, je sais que tu passes par des moments difficiles, tu es fatiguée et je l'admets. J'admets que ce qui s’est passé est inacceptable. D'autre part je refuse votre démission collective, vous êtes chacune les meilleures qui aient travaillé dans ce dôjô depuis qu'il existe. Si quelqu’un doit partir c’est To sensei. Je vais le lui demander, seulement tu pars un mois — COMMENT TU SAIS ÇA ? — Je le sais. Tu pars donc un mois j’ai besoin de quelqu'un pour assurer la gérance. Il faut aussi te remplacer tu comprends, ça se fait pas comme ça. Je te propose de prendre des vacances avant ton départ. Tu en as besoin ne le nie pas. Les garçons vont assurer des entraînements jusqu'à ce que je t’aie trouvé un ou une remplaçante pour la durée. Hayame va continuer son job avec ses élèves et To sama les siens ça ne sera pas facile pour elle mais elle est solide elle est ok. Je trouve quelqu'un pour remplacer le vieux dès que possible. Hayame sensei m’aidera à décider. Ça te va comme ça, espèce de chat enragé ? J'ai regardé A qui écoutait elle me fait signe… c’est bon — Tu vois si tu me laisses en placer une on arrive à quelque chose. Le vieux va écraser il y a des témoins et notamment des élèves adultes qui ont tout entendu. Si l'affaire sort du dôjô officiellement il est cuit dans le milieu, une pareille perte de contrôle c’est totalement inadmissible. Inutile de te dire que ça m'a beaucoup étonné mais pour des raisons que je ne comprends pas il a pété les plombs. Je me suis laissé dire récemment qu’il s'était mis à boire et maltraiter sa fille… on fait la paix, petite sœur enragée ? — d'accord, grand couillon de frère aîné.

Voilà où on en est ce soir. Il est 9:30 l'heure du bain des petites fesses, toute heureuse que de son point de vue j'aie gagné. Et finalement elle a pas tort je crois. J’ai eu un gros câlin de ma souveraine qui m'a chuchoté à l'oreille : « je suis fière de toi ma tomoe »

#dojo #Tchan

I have been fairly busy and a little bit, overwhelmed with messages recently, and I’ve noticed that Hinge falls very low on my list of priorities, where it takes me about three days or so to respond to a message now and I don’t really want to respond to messages, and I guess it just feels like a weird difference between where I know I’ve been in the past.

Moving Day

There is a strange moment when a house becomes a home.

It isn't when the papers are signed.

It isn't when the keys are handed over.

It may not even be when the first box crosses the threshold.

It happens quietly.

A chair finds its corner.

Books find a shelf.

Clothes enter a closet.

Something familiar is placed in an unfamiliar room, and suddenly the room begins to recognize you.

Moving is usually described as taking our belongings from one place to another.

But sometimes we are moving more than furniture.

We are moving from one season of life into another.

And that requires deciding what comes with us.

Some things should.

The people who loved us.

The lessons that cost us something to learn.

The memories that still make us smile.

The gratitude we owe to places and people who carried us farther than they were meant to go.

But other things have served their purpose.

Old resentment.

Old arguments.

The need to explain every wound.

The belief that because something ended, it must have been a mistake.

Not everything from the old house belongs in the new one.

That doesn't mean we throw away our history.

It means we stop asking history to become our address.

There is grace in being able to look backward without needing to go backward.

To say:

That mattered.

That hurt.

That changed me.

That was good.

That is over.

And all of those things can be true at once.

Maybe that's what moving day really is.

Not a rejection of where we have been, but an acceptance that we no longer live there.

There will always be another box to unpack.

Something that hasn't found its place.

A room that isn't finished.

Life rarely gives us a clean transition.

Sometimes the best we can do is carry what is worth keeping across the threshold and trust that we will figure out where everything belongs in time.

Then eventually the work stops.

The door closes.

The noise settles.

And for the first time, we stand inside the life that has been waiting for us to inhabit it.

No announcement.

No ceremony.

Just the quiet recognition:

I live here—-

Explore more writing from Silent Sentinel →

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© SilentSentinel, 2026. All rights reserved. Excerpts may be shared with attribution.

• 🌳 I have been spending more time offline this month...
• ...And part of that was a trip to Parc Montagne du Diable in Quebec. This park has all sorts of different options for camping, and me and partner rented a tiny house to spend a long weekend. It was very nice, we just needed to bring drinkable water, food and blanket. The house was equipped with fridge, an induction cooktop, microwave, towels, pillows and all basic kitchen utensils. It is very nice! I loved the minimalist vibe. There was no Wi-Fi, and the cellphone signal was hit and miss, so not very reliable, which was great for an offline weekend.
• ⛰️ The main goal was to go hiking, which we did! It was 18km hike around the Windigo Lake, mostly. We actually wanted to get to the top of the mountain, but that was probably another 10+ km, so we decided it was not feasible. Later we learned that it's better to start the hike to the mountain from the other side of the park. Well, maybe next time.
• 🍁 We also hiked to the Windigo waterfall, which was very close to where we stayed. It was beautiful, the weather was nice, and fall colours were amazing. But, to be honest, it was a challenging hike, and my legs were sore for a couple of days after. It think it was the hardest hike I've ever done! But it was totally worth it.
• 🎃 Went to a Pumpkin Farm, drank cider and got lost in hedge mazes and puzzle mazes.
• 🏺 I finally played 7 Wonders Duel! I still have to try out the Pantheon expansion, tho.
• 🎭 I have still been feeling tired on some days and I never know exactly why. I think it's hormonal changes.
• 🚗 Switched my car to winter tires. Ready for colder days!
• 👓 I did an eye exam and now I need to update my prescription glasses. I really like my current frame, but I haven't decided yet if I get new frames or just replace the lenses on my current one.
• 📖 I've been reading more slowly, it seems. Or it feels harder to read, I guess. It could be related to the low energy situation. Or glasses.
• 📔 I'm still staying away from screens as much as possible. After 8 hours working on a computer, I've been less inclined to look at more screens when I get home. I am on page 168 of my personal Bullet Journal, and I'm still using it everyday.

#weeknotes

A red car rolls towards a junction. A pedestrian steps into the road. The car turns, hits the pedestrian, who goes down, gets up and walks over to the driver. The whole thing lasts 25 seconds, is rendered in the engine of Grand Theft Auto V, and is about as simple as evidence gets. One thing happens in it, and that thing is a collision.

When researchers asked two consumer AI systems to write factual, neutral summaries of that clip and a near-identical twin, 19 of the 20 summaries they got back failed to mention that the car hit the pedestrian.

That finding comes from a paper posted to arXiv on 23 September 2026, “AI-Enabled Human Memory Manipulation: Misleading AI-Generated Summaries Distort Human Memory”, by Mattea Sim of Georgetown University, Yael Eiger of the University of Washington and Tadayoshi Kohno of Georgetown. It was picked up over the following days by The Independent, Neuroscience News and a string of science outlets, and it is due to be presented at the AAAI/ACM Conference on AI, Ethics and Society in October. The headline numbers travelled fast. The machines were bad at summarising. And when people read a summary that got a detail wrong, their memory of what they had seen with their own eyes bent to fit the text.

That second finding is the one worth sitting with. Copilot writes up the meeting you sat through. Your phone condenses the news alerts you swiped past. Police officers in several American states file reports drafted by software from body camera audio. Each tool is sold as a memory aid. The study suggests that when the aid is wrong, it does not merely fail to help. It can overwrite.

So what happens to a person's own memory when the machine's recap of their experience is wrong? And when a summary quietly edits the past someone believes they lived, who is supposed to catch it: the reader, the company that sold the recap, or, as things currently stand, more or less nobody?

Twenty Summaries and One Missing Collision

The researchers used two short animated clips that already had a history in memory research. Both show a red saloon approaching an intersection and striking a pedestrian. The only meaningful difference is the road sign at the junction: in one video it is a stop sign, in the other a yield sign (the American equivalent of a give way sign). The team fed each clip to two models, OpenAI's ChatGPT-5.5 and Google's Gemini 2.5 Flash-Lite, five times per model per video, using a single standardised prompt. The instruction asked for a factual and neutral summary of at least 300 words, with no speculation and no invented facts. That gave them 20 summaries to analyse.

Every one of the 20 contained mistakes, somewhere between seven and 21 per summary. All of them left things out. According to the paper, 65 per cent contained what the authors classed as critical inaccuracies, 90 per cent contained non-critical inaccuracies, and 60 per cent added material that simply was not there. The summaries hallucinated extra pedestrians and extra vehicles and described erratic driving the video did not show. One stated that the pedestrian slightly repositioned but did not enter the roadway, when the pedestrian plainly walks into the road.

Averaged across all prompts and both models, the summaries omitted 51.6 per cent of the central details of the event. And in 95 per cent of cases, the summary did not mention the central detail at all: the car colliding with the pedestrian.

Summaries are supposed to be lossy, but their entire job is to keep what matters and drop what does not. These models did the reverse, producing long, fluent paragraphs about a scene in which the one thing that happened did not happen.

“I was struck by how bad the summaries were, even at this stage in AI development,” Eiger said in the coverage published by Neuroscience News.

Some caution is due. This was a small corpus: two short animated clips, two models, one prompt, 20 outputs. The authors say so plainly in their limitations section, acknowledging that one standardised prompt and a modest number of summaries limit how far the results generalise. Models change month to month, so nobody should read these figures as a stable error rate for all AI video summarisation. What they do show is that two widely available consumer systems, given a clear and simple task, were confidently and substantially wrong about the most important fact in front of them.

Fifty Years of Stop Signs and Yield Signs

The second half of the study is where the story turns from software quality to human cognition, and where it plugs directly into one of the most studied findings in psychology.

In 1974, Elizabeth Loftus, then at the University of Washington, and her colleague John Palmer showed people films of car accidents and asked them how fast the cars were going. The trick was in the verb. Asked how fast the cars were going when they “smashed” into each other, participants gave higher estimates of speed than those asked about cars that “collided”, “bumped”, “hit” or “contacted”. A week later, people who had heard “smashed” were more likely to say yes when asked whether they had seen broken glass. There was no broken glass in the film. The paper became one of the founding texts of what is now called the misinformation effect.

Four years later, Loftus, David Miller and Helen Burns published a series of experiments in the Journal of Experimental Psychology that will look very familiar to anyone who has just read the Georgetown and Washington paper. Across five experiments and a pilot, 1,242 participants watched a sequence of slides showing an accident between a car and a pedestrian at a junction. Afterwards some were fed information consistent with what they had seen, and some were fed misleading information: a stop sign became a yield sign, or the other way round. Misleading information made people less accurate on later recognition tests, and it had a larger effect when introduced just before the test than immediately after the event. The authors concluded that information a witness encounters after an event, consistent or misleading, gets integrated into the witness's memory of it.

The new study is, in effect, that experiment rerun for the age of the chatbot, split into two sessions between 24 and 48 hours apart. In the first, people watched one of the two animated clips. In the second, they read a summary of what they had seen, then answered a 12-item recognition test in which each question offered two choices. The critical question asked whether the car had approached a stop sign or a yield sign.

Here is a crucial design detail that some coverage skated past. The misleading summaries were not raw machine errors. The researchers took AI-generated summaries and edited them, removing sentences describing the details that differed between the two clips and splicing in AI-generated text from other outputs, so that participants who had seen a stop sign read about a yield sign and vice versa. In other words, the memory experiment tested what happens when an AI-style summary contains a specific, plausible error. It did not test whether the particular errors the models spontaneously made would distort memory in the same way.

That caveat matters, but it cuts less deeply than it seems. The first half of the study showed that errors of exactly this kind are routine. The second half showed what they do once they land. Of the 331 participants who completed both sessions (328 after attention checks), those who read a summary consistent with the video answered the critical sign question correctly 83.6 per cent of the time. Those who read a misleading summary got it right 44.8 per cent of the time. On a two-choice question, that is worse than a coin toss. The statistics were not subtle: the probability of a gap that size arising by chance was below one in a thousand.

Meanwhile participants remembered other details well. On a non-critical question about whether the scene took place in daytime or at night, accuracy was 96.6 per cent. People had not forgotten the video. They had swapped one piece of it for the version they had been told.

“AI is a new method of delivering misinformation, and it has the potential to create these false memories for people who are reading that information,” Sim said in the Georgetown announcement.

Why Knowing It Was a Machine Did Not Help

Participants were randomly told that the summary they read had been written either by an AI or by a human. In reality all of the summaries were AI-generated. If a machine label worked as a kind of cognitive inoculation, you would expect people who knew they were reading AI output to discount its claims and lean more on their own memory.

They did not. Among those who read a misleading summary labelled as AI-generated, 46.3 per cent answered the critical question correctly. Among those who read the same kind of summary labelled as human-written, 43.4 per cent did. The difference was not statistically significant. The researchers also measured participants' trust in AI and how much they used it, and neither made a meaningful difference to how susceptible they were.

This is consistent with what the misinformation literature has long suggested about warnings. In a 2005 review in Learning and Memory, looking back on three decades of this research, Loftus wrote that warnings about the potential for misinformation sometimes work to inhibit its damaging effects, but only under limited circumstances. The Georgetown and Washington authors reach a similar conclusion. They suggest that noticing discrepancies between the original event and later information can reduce the impact of misinformation, and float warning people about potential discrepancies before they read an AI summary. But they also note that simply knowing the source was AI provided no protection in their data.

Related evidence points the same way. In 2024 a team at the MIT Media Lab, with Loftus among the co-authors, had 200 participants watch a crime video and then answer questions, five of them misleading, via a survey, a scripted chatbot or a generative chatbot built on a large language model. The generative chatbot induced more than three times as many immediate false memories as the control condition, and a week later those false memories persisted, held with higher confidence than in the control group.

A fluent system can introduce errors into your memory. Telling you it is a fluent system does not reliably stop that. And the errors can outlast the conversation that planted them.

The Meeting You Attended, as Told by Copilot

Move from a laboratory junction to an office, and the stakes change shape without shrinking.

Automated meeting recaps are now a standard feature across the major collaboration platforms. Microsoft's intelligent recap in Teams, available with Teams Premium or a Copilot licence, generates AI summaries and follow-up tasks, marks when your name was mentioned, organises the discussion into chapters, and tells you who said what. Microsoft's own support documentation is candid about the risk: “AI-generated content is based on the event transcript and is powered by GPT and other AI models. The AI-generated content may occasionally be inaccurate, incomplete, or inappropriate.”

That is a reasonable disclosure. But if an AI label did not protect participants from absorbing a planted error about a road sign, there is little reason to think small print will protect an employee from absorbing an error about who agreed to what in a budget meeting.

The people most likely to rely on a recap are those who were least attentive: double-booked, multitasking, half-listening while answering email. They are witnesses with weak original traces, exactly where post-event information has most room to take hold. And if a recap is reread just before someone needs to remember, the 1978 finding suggests that is exactly when misleading information bites hardest. A recap consulted before a Friday dispute is not merely a record of Monday's meeting. By Friday, it may be the meeting.

A change Microsoft has scheduled for this autumn sharpens the point. In a Microsoft 365 message centre notice first published in April 2026, the company announced a “recap without saving transcript” option, which lets Copilot users generate an AI meeting summary from live meeting context without retaining a recording or transcript. The notice says the feature addresses scenarios where organisations want AI-generated recaps “but have policies that limit or prohibit the retention of transcripts or recordings”, and it advises administrators to review their AI governance policies to decide whether it fits their compliance posture. Rollout is scheduled for October 2026.

There are sound privacy reasons for not keeping transcripts. But if the summary is the only artefact that survives the meeting, there is nothing to check it against except the attendees' memories, and the study is precisely about what happens to those memories after people read a summary that is wrong.

Even the transcript layer is not safe ground. In October 2024 an Associated Press investigation reported that OpenAI's Whisper speech recognition model was prone to inventing chunks of text, and that more than 30,000 clinicians and 40 health systems were using a Whisper-based tool from Nabla to transcribe and summarise patient visits, despite OpenAI's warnings against use in high-risk domains. The layer that turns a live event into text can introduce words nobody said.

News You Only Half Read

For most people, the summary that shapes memory is not a meeting recap but a news digest glimpsed on a lock screen.

In December 2024 and January 2025, Apple Intelligence's notification summaries produced a run of false headlines attributed to news organisations. One summary of BBC News alerts suggested that Luigi Mangione, the man charged over the killing of the UnitedHealthcare executive Brian Thompson, had shot himself. He had not. Other summaries wrongly claimed, under the BBC's name, that the darts player Luke Littler had won the PDC World Championship before the final had been played, and that Rafael Nadal had come out as gay. A summary of New York Times alerts said Israel's prime minister, Benjamin Netanyahu, had been arrested. The BBC complained. In January 2025 Apple paused notification summaries for news and entertainment apps in a software update, and said summaries would be shown in italics to distinguish them from ordinary notifications. In July 2025 the iOS 26 beta brought news summaries back, this time with a warning beneath the setting: “Summarization may change the meaning of the original headlines. Verify information.” Given the Georgetown and Washington finding that knowing a summary came from AI did not protect memory, a label is a thin defence.

Those were spectacular, checkable errors. The quieter problem is the everyday rate. In February 2025 the BBC published research in which its journalists put 100 news questions to ChatGPT, Microsoft Copilot, Google Gemini and Perplexity, asking them to use BBC sources. It found that 51 per cent of answers had significant issues, 19 per cent of answers citing BBC content introduced factual errors such as wrong dates and figures, and 13 per cent of quotations attributed to BBC articles had been altered or did not exist in the cited article. In October 2025 a far larger follow-up, coordinated by the European Broadcasting Union and led by the BBC, assessed around 3,000 responses across 14 languages and found that 45 per cent of AI answers about news had at least one significant issue, with sourcing the most common problem.

Now put those error rates next to the audience. The Reuters Institute's Digital News Report 2026, published in June, found that weekly use of AI chatbots for news had risen to 10 per cent of people across the markets it surveys, and to 17 per cent among 18 to 24 year olds. Getting summaries was among the most common uses, cited by about a third of those using chatbots for news, and only a small fraction of users regularly clicked through to the original source.

That last number is the hinge. The traditional corrective for a bad summary is the source it summarised, but the whole value proposition of a summary is that you will not open the source. A reader who half-reads an AI digest of a court case and never opens the report carries a version of events that, on this evidence, will not simply sit alongside the truth. For memory's purposes, it becomes what they recall.

Google's AI Overviews were mocked in May 2024 for suggesting glue on pizza and eating rocks, and Liz Reid, Google's head of Search, acknowledged that some answers had drawn on satirical or joke content. Those errors were funny because they were absurd. The errors that reshape memory are not absurd. They are a yield sign where there was a stop sign.

Police Reports and the Officer in the Loop

The authors' main concern is policing, where the question of who checks the machine is most concrete. Axon, the largest supplier of police body cameras in the United States, sells a product called Draft One that uses generative AI to draft police report narratives from body-worn camera audio. The officer is expected to review and edit the draft before submitting it. In July 2025, the Electronic Frontier Foundation published an investigation arguing that the product was designed in a way that frustrated auditing. According to the EFF, Draft One does not save the draft it generates or subsequent edited versions, so once an officer exports the final report there is no record of which parts were written by the AI and which by the officer.

Put that alongside the new study. The standard defence of tools like this is the human in the loop: the officer was there, knows what happened, and will correct the machine. The paper's authors address exactly that defence. “Though 'humans-in-the-loop' are often expected to correct for AI's mistakes,” they write, “our work suggests human memory can instead be distorted by these mistakes.”

The logic is brutal. The officer is the check on the draft, but reading the draft is precisely the kind of post-event exposure that alters memory. If it says the pedestrian stepped off the kerb against the signal, the reviewing officer may come to remember it that way. The check has been contaminated by the thing it was meant to check, and if the draft is deleted, nobody can reconstruct which version came first.

In the Georgetown announcement, Eiger said it worried her that police departments may be using video summarisation tools without rigorous testing, and without an awareness of how wrong AI-generated summaries could be.

Legislators in two American states have begun to respond. Utah's SB 180, which took effect in May 2025, requires police reports produced wholly or partly with generative AI to carry a disclaimer and requires the author to certify that the report was checked for accuracy. California went further. SB 524, signed by Governor Gavin Newsom in October 2025 and in force since 1 January 2026, requires disclosure of AI use on reports, requires agencies to retain the first draft for as long as the final report is kept, and bars vendors from selling or sharing information police provide to the AI. As the EFF put it, the draft retention requirement means judges, defence lawyers or auditors can see which portions of the final report were written by the officer and which by the computer.

Notice what these rules assume. Utah makes the officer answerable for accuracy, yet the officer's memory is one of the things the draft may have altered. California's retention rule is more robust because it does not rely on memory at all: it preserves an artefact that can be compared against the footage. That is a useful template elsewhere.

Records That Outlive the Room

Outside policing, the law has not caught up with the idea that a summary can shape the memories of the people it describes. In the UK, meeting summaries that name or describe identifiable people are personal data, and Article 16 of the UK GDPR gives individuals the right to have inaccurate personal data about them rectified, and incomplete data completed, including by way of a supplementary statement. The Information Commissioner's Office guidance says organisations should take reasonable steps to satisfy themselves that data is accurate when a rectification request is made, taking into account the individual's arguments and evidence. An employee who finds that a Copilot recap attributes to them a commitment they never made has, in principle, a route to have it corrected.

In practice that route depends on the employee noticing the error and having something to prove it with. If the transcript was never kept, the evidence is two sets of memories, one of which may have been rewritten by the summary itself. The right was designed for a world in which records and memories were separate things that could be compared.

Grievances and disciplinary hearings routinely rely on contemporaneous notes. An AI recap looks contemporaneous, with a timestamp and a corporate logo, but it carries no indication of which sentences reflect what was said and which are the model's reconstruction.

What the Law Currently Asks of Whom

The European Union has come closest to allocating responsibility, though not for this specific harm.

Article 50 of the EU AI Act, whose core transparency obligations began applying on 2 August 2026, requires providers of AI systems that generate synthetic text, audio, images or video to ensure outputs are marked in a machine-readable format and detectable as artificially generated. It also requires deployers of AI systems that generate or manipulate text “published with the purpose of informing the public on matters of public interest” to disclose that the text was artificially generated. The Digital Omnibus, which pushed back the Act's high-risk obligations, left that date alone, although providers of generative systems already on the market before 2 August 2026 have until 2 December 2026 to meet the machine-readable marking requirement. The disclosure obligation falls away where the content “has undergone a process of human review or editorial control and where a natural or legal person holds editorial responsibility for the publication”.

That exception is revealing. It makes editorial responsibility, a named person or organisation standing behind the text, the alternative to disclosure. It does not make disclosure alone sufficient to discharge responsibility, and the new study suggests it should not. A label did not protect participants. A person accountable for checking the text before it reached them is a different kind of safeguard.

Liability is shifting too. The EU's revised Product Liability Directive, which member states must transpose by 9 December 2026, explicitly treats software, including AI systems, as a product for the purposes of no-fault liability, and eases the burden of proof for claimants dealing with technically complex systems. Its idea of damage centres on death, personal injury including medically recognised psychological harm, damage to property, and the destruction or corruption of data. A distorted memory of a meeting is unlikely to count. But the principle, that suppliers of software are answerable for defects in what they put on the market regardless of whether they were negligent, is a shift in the default assumption about who carries the risk.

In the United States, the picture is patchier. Beyond the Utah and California police laws, much of the current legal pressure on meeting assistants concerns consent rather than accuracy. In August 2025 a proposed class action, Brewer v. Otter.ai, was filed in federal court in California alleging that Otter's notetaker recorded conversations of people who had not consented, including non-users, and used the data to train its models. In October 2025 it was consolidated with similar suits as In re Otter.AI Privacy Litigation, and on 13 August 2026 Judge Eumi K. Lee refused to dismiss the core claims, allowing wiretap claims under federal and California law to proceed on the basis that Otter, by using recordings to develop its own models, could be treated as a third-party eavesdropper. The case illustrates where the legal system's attention currently sits: on whether the machine should have been listening, not on whether what it wrote afterwards was true.

Why the Reader Cannot Carry This Alone

The easy answer to who should check the summary is the person reading it. That is what the disclaimers say, and what “human in the loop” means in most enterprise AI policies.

The study makes that answer hard to defend, for three reasons.

The first is that the checking mechanism is compromised by the thing being checked. Memory is the natural reference for testing a summary of an event you attended, but reading the summary changes the memory. Not every time, and not for everyone, but often enough that “check it against what you remember” is not a reliable safeguard.

The second is that the people most exposed to summaries are the people least equipped to check them. Summaries are used by people who did not attend, did not pay attention or did not read the original. That is the point of them. Asking those users to verify the summary against a source they were trying to avoid is asking them to do the work the product was meant to save.

The third is that confidence in the tool reduces checking. In a survey of 319 knowledge workers presented at the CHI conference in 2025, researchers at Microsoft Research and Carnegie Mellon University found that higher confidence in generative AI was associated with less critical thinking, while higher self-confidence was associated with more. The more reliable a tool seems, the less people scrutinise it, and a tool that is right most of the time trains exactly the complacency that lets its occasional errors through.

None of this means readers bear no responsibility. Attendees can take their own notes, readers can click through, officers can write their own account first. But a design that depends on users consistently doing the things the product was designed to spare them is not a design with a human safeguard. It is a design with a human scapegoat.

What Suppliers Could Actually Owe

If the burden cannot sit only with readers, the obvious alternative is the organisations that build and deploy the summarisers. What would taking that burden seriously look like?

It would start with measurement. The authors call for more technical audits of summarisation tools and for examining real-world uses such as body camera footage. Vendors selling summarisation for high-stakes settings could publish error rates on representative material, broken down by type: omissions of central events, substitutions, additions. A summariser that routinely omits the central event of a clip is not ready to summarise evidence.

It would continue with provenance. California's approach to police reports offers a model: keep the draft, keep the source, make it possible to see which words came from the machine. For meeting recaps, that could mean retaining source audio or transcripts for a defined period when a summary is created, or linking each sentence of a summary to the moment in the recording it draws on. Microsoft's recap already offers timeline markers and speaker navigation. Anchoring every claim to its evidence would make checking something a reader can do in seconds rather than a reconstruction from memory.

It would include friction in the right places. The study's authors suggest that noticing discrepancies helps, and that warnings delivered before reading might help. That points towards designs that ask users to recall something before showing them the summary, or that flag which parts of a recap are high-stakes (decisions, attributions, commitments) and invite confirmation from the people named. It points away from designs that deliver a finished, authoritative paragraph and a disclaimer.

And it would include restraint. The authors raise a question most product roadmaps do not: “a deeper question to consider is whether AI should be used in these contexts at all.” For some uses, such as drafting a police narrative from body camera audio before the officer has written their own account, the answer may be that the order of operations matters more than the quality of the model. Human recollection first, machine summary second, and a record of both.

Organisations that deploy summaries carry a share too. An employer that switches on recaps without transcripts and relies on them in a disciplinary process has made choices about evidence. A platform that pushes machine summaries of journalism to millions of lock screens has made choices about what its audience will remember. The EU's editorial responsibility test is a good instinct: somebody specific should be answerable for what the summary says.

Keeping Hold of the Afternoon You Lived

There is a version of this story that is merely about quality control: the mistakes will get rarer and the problem will shrink. That may be partly true. But the study is not really about how often summaries are wrong. It is about what happens when they are. A human memory is not a hard drive that a summary sits beside. It is a reconstruction, rebuilt each time it is recalled, and fifty years of research have shown that the materials used in the rebuild include whatever we have been told since. For most of that history, the people doing the telling were other humans: lawyers asking leading questions, police officers suggesting details, newspapers and neighbours. They could be cross-examined. They could be blamed.

The summary is a new kind of teller, present at every meeting and every alert, speaking in a voice that sounds neutral and thorough. When it drops the collision from the crash, or puts a yield sign where a stop sign stood, it does not only produce a bad document. It produces people who remember a slightly different afternoon from the one they lived.

Right now, the burden of noticing falls on the people least able to notice, and responsibility for the error is spread so thinly that it lands on almost nobody. The disclaimers say the content may be inaccurate. The users are told to check. The checking, it turns out, runs through a memory the summary has already touched.

That arrangement looks unlikely to survive contact with a courtroom for long. The better move is to settle the question first: keep the source, mark the machine's words, measure the errors, and put a named person behind any summary that is going to be treated as the record. The past is hard enough to hold on to without software editing it for us.

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References and Sources

1. Sim, Mattea, Yael Eiger and Tadayoshi Kohno. “AI-Enabled Human Memory Manipulation: Misleading AI-Generated Summaries Distort Human Memory.” arXiv:2609.28820v1, submitted 23 September 2026; to be presented at the Ninth AAAI/ACM Conference on AI, Ethics and Society (AIES), October 2026. https://arxiv.org/abs/2609.28820
2. Soong, Kelyn. “New Research Finds That Misleading AI-Generated Summaries Can Distort Human Memory.” Georgetown University College of Arts and Sciences, 25 September 2026. https://college.georgetown.edu/news-story/new-research-finds-that-misleading-ai-generated-summaries-can-distort-human-memory/
3. Neuroscience News. “Flawed AI Summaries Distort Eyewitness Memory.” 27 September 2026. https://neurosciencenews.com/ai-false-memory-llm-31261/
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12. TechCrunch. “Apple pauses AI notification summaries for news after generating false alerts.” 16 January 2025; see also Axios, “Apple pauses AI-generated news alerts after fake headline notifications”, 17 January 2025. https://techcrunch.com/2025/01/16/apple-pauses-ai-notification-summaries-for-news-after-generating-false-alerts ; see also AppleInsider, “Apple brings back notification summaries for news in iOS 26”, 22 July 2025. https://appleinsider.com/articles/25/07/22/apple-brings-back-notification-summaries-for-news-in-ios-26
13. BBC. “Representation of BBC News content in AI Assistants.” BBC Research, February 2025; as reported by The Register, “AI summaries turn real news into nonsense, BBC finds”, 12 February 2025. https://www.theregister.com/2025/02/12/bbc_ai_news_accuracy/
14. European Broadcasting Union and BBC. “News Integrity in AI Assistants.” October 2025; and EBU press release, “Largest study of its kind shows AI assistants misrepresent news content 45% of the time, regardless of language or territory.” https://www.ebu.ch/news/2025/10/ai-s-systemic-distortion-of-news-is-consistent-across-languages-and-territories-international-study-by-public-service-broadcaste
15. Reuters Institute for the Study of Journalism. “Digital News Report 2026: Overview and key findings.” University of Oxford, June 2026. https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2026/dnr-executive-summary
16. Reid, Liz. Google Search blog post on AI Overviews, 30 May 2024; as reported by MIT Technology Review, “Why Google's AI Overviews gets things wrong”, 31 May 2024, and Forbes, 31 May 2024. https://www.technologyreview.com/2024/05/31/1093019/why-are-googles-ai-overviews-results-so-bad/
17. Electronic Frontier Foundation. “Axon's Draft One Is Designed to Defy Transparency.” July 2025. https://www.eff.org/deeplinks/2025/07/axons-draft-one-designed-defy-transparency
18. Guariglia, Matthew. “Victory! California Requires Transparency for AI Police Reports.” Electronic Frontier Foundation, 14 October 2025. https://www.eff.org/deeplinks/2025/10/victory-california-requires-transparency-ai-police-reports
19. California Legislature. SB 524, Law enforcement agencies: artificial intelligence, 2025 to 2026 session; and Office of Senator Jesse Arreguín, “Governor Signs Bill Requiring Law Enforcement to Disclose Use of AI in Police Reports.” https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=202520260SB524
20. Utah Legislature. SB 180, Law Enforcement Usage of Artificial Intelligence, 2025 General Session; and Utah News Dispatch, “Deepfakes, policing, mental health and more: Lawmakers look to further regulate AI”, 26 March 2025. https://le.utah.gov/~2025/bills/static/SB0180.html
21. Information Commissioner's Office. “Right to rectification.” UK GDPR guidance and resources. https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/individual-rights/individual-rights/right-to-rectification/
22. European Union. Regulation (EU) 2024/1689 (Artificial Intelligence Act), Article 50, Transparency obligations for providers and deployers of certain AI systems. https://artificialintelligenceact.eu/article/50/ ; see also Cooley, “EU AI Act: Transparency Obligations Take Effect 2 August 2026”, 3 August 2026. https://www.cooley.com/news/insight/2026/2026-08-03-eu-ai-act-transparency-obligations-take-effect-2-august-2026 ; and Goodwin, “Not Delayed, Not Deferred: EU AI Act Transparency Obligations Are Now in Force”, 3 August 2026. https://www.goodwinlaw.com/en/insights/publications/2026/08/alerts-technology-dpc-eu-ai-act-transparency-obligations-now-in-force
23. European Union. Directive (EU) 2024/2853 on liability for defective products. Official Journal of the European Union, 18 November 2024. https://eur-lex.europa.eu/eli/dir/2024/2853/oj/eng
24. NPR. “Class-action suit claims Otter AI secretly records private work conversations.” 15 August 2025. https://www.npr.org/2025/08/15/g-s1-83087/otter-ai-transcription-class-action-lawsuit ; and Baird Holm, “Core Privacy Claims Against AI Note Taking Platform Survive Dismissal” (In re Otter.AI Privacy Litigation, No. 5:25-cv-06911, N.D. Cal.), 24 August 2026. https://www.bairdholm.com/blog/core-privacy-claims-against-ai-note-taking-platform-survive-dismissal/
25. Lee, Hao-Ping (Hank), and colleagues, Microsoft Research and Carnegie Mellon University. “The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers.” Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, ACM. DOI 10.1145/3706598.3713778. https://dl.acm.org/doi/full/10.1145/3706598.3713778

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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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