Report by Milan Đorđević, Tijana Cvetković & Noa Treister

Building the cooperative did not begin with a strict program but with a series of conversations about how artists might reorganise their work and the relationships around it. So, this text turns to one specific attempt to rethink artistic exchange and the conditions under which art is produced and circulated in Serbia.

Our research study within the Association of Fine Artists of Serbia (ULUS, 2023) has shown that the visual arts field is marked by a high level of centralisation, dependence on a few major institutions, and the gradual erosion of public cultural infrastructure. As market logic expanded into areas once shaped by collective investment, cultural participation narrowed, particularly for the working class. In such a landscape, artistic value tends to be defined by visibility and demand rather than by social relevance. This is the background against which we began to explore whether practices of exchange outside the monetary frame might open different relationships between art and its surroundings.

In defining the scope and modes of operation of the co-op, we began to experiment with barter as a tool for rethinking exchange. The question we placed at the centre of this process was simple but fundamental: how can barter, as a form of non-monetary exchange, function both as a critique of existing art economies and of the way they define the role of art and artists in society, while also prefiguring alternatives?

Our first public experiment was conducted in Požega in the autumn of 2025, under the title Ponudi, razmeni, ponesi – Offer, Exchange, Take Away. Visitors were invited to offer something of their own in return for an artwork. It could be a haircut, a home-cooked meal, help with repairs, a professional service in a non-art-related field, or money if they wished. The format resembled an auction, but its rhythm and meaning were different. Each artwork was accompanied by space for offers; after the exhibition closed, the artists reviewed the proposals and decided which to accept.

The exhibition took place in a space that had previously been a hair salon in the centre of Požega. It had been empty for months, and the owner was considering turning it into an art space. That circumstance gave us a kind of freedom that is rare when working within established institutions. There were no curatorial or administrative expectations, only the practical question of how to make the exchange visible and accessible. We organised the exhibition to be open a few afternoons and evenings during a period of three weeks. A person from the local community was engaged for a modest fee to keep the space open, welcome visitors, and explain how to make an offer and how the exchange would unfold. At the same time, we promoted the event through social media, direct letters sent to local entrepreneurs, and through personal networks. In small towns like Požega​​ (≈12,300 inhabitants), we realised that word of mouth still functions as the most effective form of public communication – slower but more durable than any campaign. By the end of the three weeks, around fifty people had visited the space, and several of them made their offers.

After the exhibition, we gathered for a workshop that opened one of the most persistent questions among artists: how to define the value of one’s own work. Most participants admitted they find it difficult to put a price on something that does not fit into standard market categories. One artist said she rarely sells her work as an object, and that her decisions depend on “who approaches her and whether they understand each other”. Others spoke about the challenge of balancing artistic integrity with livelihood. As one participant noted, “you can’t measure everything in hours, but you can’t ignore the time and materials either”.

For us, this conversation was central. A cooperative is not built around the idea of profit but around the need for sustainability. As we discussed, we don’t have to be profit-oriented, but we do have to cover our basic living costs. This simple statement cuts through much of the ambiguity that surrounds the notion of artistic value. It recognises that art, like any form of labour, depends on material conditions, but also that value is not fixed – it is negotiated in relation to others, to context, and to shared purpose. And barter became a way to make these relations visible: a two-day truck trip to Durrës in Albania; twenty professional hair colorings and haircuts with no time limit; a curatorial text for the next exhibition; documentation for building legalisation up to 200 square metres; a personal herbarium; a weekend stay with breakfast for up to eight people, and many more proposals that carry different understanding of value and relation. None of them could be translated neatly into monetary terms, and that was precisely the point. The exchanges showed what people were ready to give and how they imagined their connection to art, as care, as time, as skill, as hospitality. Whether professional artistic work becomes a matter of survival arithmetic (as was mentioned during the workshop) or remains unrecognised as labour, the question is the same: how to live from what one creates. As one artist put it, few people see art as work at all, and that is precisely where the cooperative finds its role – to shift perception and rebuild the link between artistic value and the conditions of life that sustain it.

Even though some visitors offered money for the artworks, the non-monetary exchanges shaped the atmosphere of the event in a different way. Instead of fixed prices, artists provided approximate starting points for negotiation, which opened space to focus less on monetary value and more on the people who approached them. Buyers were no longer anonymous figures but individuals whose interests, skills or forms of care said something about why they wanted a particular work. Several artists accepted offers that were modest or unconventional, simply because they felt a sense of recognition in them. From a conventional entrepreneurial standpoint, accepting less than the assumed market value might be seen as diminishing one’s worth, but this concern did not play a central role here. The exchange was not framed as a market transaction to be optimised, but as a space in which value could be shaped through relation rather than price. That shift loosened the usual distance between artist and audience and made the encounter feel grounded in mutual attention instead of market logic.

The co-op should bring artistic labour back into the everyday economy of life and exchange, without romanticising precarity or denying the need for income. Its way of selling art should test how art might live when its value comes from relations rather than from market recognition. This intention became clearer when we proposed to repeat the experiment in one of the central art spaces in Serbia. The response from its curators exposed precisely the tension we wanted to address. They worried that the idea of exchanging artworks for homemade goods or services could “devalue” art and “encourage amateurism”. Their concern was not unique; it reflected a broader institutional anxiety about how artistic value is defined and protected in a system that already struggles to sustain its own workers.

What the experiment left us with was not a ready-made model but a clearer sense of the questions that need to be worked through: how to organise exchanges that recognise artistic labour without falling back on market metrics; how to involve communities without reproducing hierarchies; and how to build structures that make such practices sustainable rather than exceptional. For the next iteration of the exhibition, we turned to a public library in Bor, a mining town with a growing community of Chinese workers, as a place to continue the experiment. The interest shown by artists during the open call, their questions, suggestions, and willingness to engage even when they could not participate, confirmed that the need for such spaces is real. Rather than closing a cycle, the workshop and exhibition in Požega marked the beginning of a longer process; in the coming period, we plan to develop a series of these kinds of events that deepen this exploration of alternative economies of art.

JOURNAL 16 décembre 2025 Introspection

C’est revenu le temps du kotatsu : ma princesse et son laptop, moi les coudes autour d’un bouquin (je tiens ma tête les coudes sur la table). On a baissé la lampe pour être bien éclairées, A porte des lunettes pour travailler, elle ne veut pas que je me fatigue les yeux. On a mis les hanten doublés Ça c’est le décor.

Dans ma tête c’est moins clair J'ai plus eu de cauchemar depuis je sais pas et plus d’hallucinations non plus. Je me sens beaucoup plus stable, plus tranquille. Je m'endors sans crainte.

Mes psys me disent que je n'ai pas fini. Je veux bien le croire, puisque je n’arrive pas à en parler avec mon frère, pourtant je crois que mon interprétation est juste, alors qu'est-ce qui ne va encore pas? C'est vrai j’ai reçu ces coups et ces brimades comme une preuve d'intérêt alors que je me croyais inexistante. J'en ai même été fière. C’est dingue hein ? C’est vrai. J’ai fait plus que supporter, j'ai aimé ça. Je trimbalais mes marques comme des médailles, j'étais fière de savoir endurer.

Dans le hokkaido ils ne m’ont jamais sorti un cri, peut-être des gémissements que j'arrivais à étouffer. C'était comme un défi. Quand on m'a violée je n’ai pas pu retenir des larmes, mais pas un son, je le sais, on m'a forcée à voir les vidéos ignobles, ils me traitaient de petite salope, petite arrogante, petite aristo de merde. Ils me tiraient les cheveux. Ça les mettait en rage, et moi pas un son et je baissais pas les yeux. Ils devenaient fous, je recevais des gifles, des raclées, ils me jetaient par terre… Bref Alors quoi maintenant, qu'est-ce qui manque ? Qu'est-ce qui est enfoui si profondément que je ne vois rien ressortir, pas un indice. Mes psys semblent avoir une idée mais peut-être bien qu'ils bluffent, je suis seule en face de cette question. Pourquoi je n’ose pas en parler à mon frère ? Pourquoi je n’ose pas de lui dire que j'ai aimé sa tyrannie violente ? Pour pas perdre mon statut de victime héroïque ? — Tu parles comme je m'en fous Je ne comprends pas Je ne vois pas où est le point. Ma chérie ne peut plus rien pour m'aider, bien qu'elle voudrait tellement. Personne ne peut plus rien. C'est entre moi et moi, merde alors.

The rain sizzled against my exposed cybernetic forearm, the hydraulics whining like a dying dog. Across the street, the target’s retinal implants flickered—glitchy. Cheap knockoffs. “You gonna pull that trigger or philosophize all night?” growled my onboard AI, its voice sandpaper-rough from last week’s malware attack. The .357 Magnum trembled in my grip, not from fear but from the feedback loop—their tech was inside me now. The target smiled, lips splitting like overripe fruit. “We’re the same, Murphy.” Wrong. I was 37% meat. The gun roared. His skull splintered like cheap polymer. Another ghost in the machine.

#Scratch

tal parece que al que socava alguien le ayuda y así vamos por la empinada cuesta regañados de esperanzas entre brumas

E and I had an issue again about therapy, and how she forgot about why it was important in the first place, and how she had not put in effort for it. It hurt a lot because early on in our relationship, she did something really bad that hurt my trust a lot, and we almost broke up over it. We agreed that if she went to therapy, then I would feel comfortable and could trust her again. It’s been almost 3 months, and it hasn’t been a good look. It honestly hurt a lot, and also the way that she handled it. I broke down crying for almost an hour. She also talked with her mom about it, and explained only the fact that I wanted her to get therapy, and not why, or explaining the “problems” that we had. Not the fact that she did something super fucked up and that would have been normally grounds for breaking up, and how this was something we both agreed upon as a way to show that things like that wouldn’t happen again. I feel this horrible pit in my chest, and it threatens to constrict me fully. It’s such a powerless position to be in to see a situation be represented so one-sided to a very biased jury, and to be helpeless other than to just watch.

In Summary: * A pretty good Monday, though it stll feels odd not to have this as a big laundry day. My chess load may be bigger now than it has ever been. With several tournaments running in my different online chess clubs, I have between 50 and 60 games to work on every day. That's about the maximum number I can handle.

Prayers, etc.: * My daily prayers

Health Metrics: * bw= 222.67 lbs. * bp= 158/93 (68)

Exercise: * kegel pelvic floor exercise, half squats, calf raises, wall push-ups

Diet: * 05:30 – 1 blueberry muffin * 06:45 – 1 more blueberry muffin, 1 bowl of oatmeal * 08:05 – baked salmon w. mushroom sauce * 12:30 – noodles and cheese sauce * 16:45 – 1 more blueberry muffin

Activities, Chores, etc.: * 05:00 – bank accounts activity monitored * 05:15 – read, pray, follow news reports from various sources * 12:30 to 14:30 – watch old game shows and eat lunch at home with Sylvia * 16:20 – listening to The Jack Riccardi Show * 17:00 – listening to The Joe Pags Show * 18:30 – follow news reports from various sources * 20:00 – listening to relaxing music and quietly reading until bedtime

Chess: * 16:15 – moved in all rated CC games

Desire is not failure. It is the body remembering it was made to be touched.

A wolf prowls Porto— not vicious, but hungry— moving through stone and salt and old iron streets.

This morning he finds himself still, at a hotel bar, the city passing through him rather than the other way around.

His usual den—the bank where wild thyme grows, where oxlips and violet nod beneath woodbine and musk-rose— This dawn there are others here, And it belongs now to those.

The flower room, the mortals call it.

It fills with silk and chiffon, with the soft architecture of bodies in motion. Bare shoulders. Open backs. Arms meeting torsos without shame. Hems rising like a tide that does not ask permission.

The wolf does not consume. He observes. His gaze is sufficient.

Peeling from the dense joinery of bodies, a man slips away to the bar. He is suited, befitting a man of some renown, though the wolf knows nothing of it—only the sense that he carries a certain gravity.

He takes a seat and drinks as if he has run aground, as if breath itself might be returned to him through glass and foam. Perhaps it is less thirst for spirits and more the calm draw of the tender— a young woman whose skin glows in the low light, smoked honey, warm and quiet, with a smile that could hold a Rabelo steady against wind or current.

The man mutters something, coyness flickering in his eyes. Smoked honey answers with that smile and a single word.

“Nepal.”

A moment opens.

Will the man hunt? Or is he only being kind?

It hangs, full and unresolved— no bridge built, only the long chasm of silence where two observers stand stunned by the distance and depth between them.

A distant wind, like a dream, sprinkles the whispered word Namaste. But the moment has passed. Smoked honey returns to polishing her crystal treasures.

Nothing passes between them, and so the air holds what might have been.

There is a pressure now that did not exist a moment before— sustained, contained, with nowhere yet to go.

Then the room changes.

Not suddenly. Not loudly. But profoundly.

A woman enters, and the space rearranges itself around her. Energy shifts outward, displaced, as her presence stirs a wind that moves the sage and trembles the wheat.

Even the wolf, in his quiet corner, feels it.

Gravity has slipped— just a little.

She does not drift. She does not search.

She approaches with intent.

Her dress—midnight blue, scattered with small white flowers, like a third-watch meadow under a full moon— clings to her skin without effort, remembering her shape as she moves.

She comes to rest beside the man, close enough that breath becomes shared. The wolf senses the change in him— a soft yielding, almost imperceptible. He is opening. She unarmors him with little more than awareness.

Her hand rises.

Not to seize. Not to hold.

To settle.

Fingers find the back of his head, knitting briefly into short dark hair. A palm rests at the nape of his neck, where a pulse answers without words.

And in that answering, the room dissolves.

This is not conquest. Nor possession, asserted or implied.

It is awareness without declaration.

The wolf is awed by the slow, unmistakable alignment of want and permission.

The resonance reaches him. His breath deepens. His weight shifts forward a fraction, as if his body remembers this language without ever being addressed.

And there, behind his ribs, the wolf finds it— a longing oft felt and long quelled.

Not the sex— but the recognition. The unfiltered want between two.

Desire moves like heat through matter, lingering, spreading, until something softens and opens enough to receive it.

The wolf realizes he is open and unnamed, still wanting— not because he lacks, but because the wanting itself has warmed him, has replaced ache with presence, and left him altered by what passed through the room when someone disarmed and let themselves be found.

• 👕 I promised myself that the reward for completing the 750 Words private journaling last month was to buy myself an Iron Maiden t-shirt. I used to have one way back then, and I just had this wish to wear one again. So I did it! I found a local store that still sells licensed rock/metal bands t-shirts and got a pair (I wanted to avoid buying online).
• ☑️ I noticed that the Nirvana app was looking a bit more colourful than usual. So, the iOS version already had colours on the menu and now that is matched on the web and also on the Windows app. Cool!
• ⏰ I sometimes wish Nirvana offered stronger reminders. Or at least a quicker way to add simple ones and receive persistent notifications. To fill that gap, I’ve been using the Reminders app on my phone, or occasionally Microsoft To Do, since both make it much easier to add a reminder. And that brings me to…
• 🐧 ... I want to try out Linux again. It's been years since I've been on Linux, and now I feel like I have the headspace to start my switch from Windows to Linux. I don't have major issues with Windows 11 at the moment, other than how bloated it has become, the endless updates that appear out of nowhere and take forever to finish, the constant insertion of Copilot AI buttons everywhere I look, and an overall concern about privacy and how little control I have over my own desktop. (Well, those might actually be Major problems!). I’m not extreme when it comes to privacy or ideology. I just want the bare minimum: a fast, predictable system that stays out of my way, lets me decide what runs on my machine, and doesn’t treat my computer like an advertising surface.
• 🎓 I finished an online course that was offered by my company about Leadership: “Harvard ManageMentor (HMM) Leadership Experience”. It was okay, I got somethings out of it. There was an author interviewed talking about anxiety and I identified with her ideas. I'm reading her e-book “The Anxious Achiever” by Morra Aarons-Mele. It is helping me recognize anxiety as a manageable personality trait rather than a problem to solve. Anxiety might be part of my personality. And that's okay, as long as I understand it and learn how to manage it. It can help me sometimes, and in the moments where it hinders me, I can use tools to mitigate it.
• 🎉 Me and my partner attended my company's Holiday Party, which was nice. We are not party people at all, but this one has become a tradition for us. And one thing I like to do is wear the same dress every year, to kinda prove that we don't need (especially women) to have a different outfit every fricking event we go to! It may be a women's thing, but there is a lot of pressure for us to “dress pretty” and god-forbid if we wear the same dress! I've been wearing the same outfit since 2018, and I was not excluded from society.
• 🎿 I enrolled in Intro Cross Country Ski Classes that will start early January! I finally moved this project from my Someday/Maybe! Now I need to get some skis, but I'll wait until the craziness of Christmas shopping season is over. I'm super excited about skiing! I have no clue how it works.

📌 Cool online reads:

• Desert Island games (feat. some of you!) by Joel: This is an awesome post with the collaboration of a bunch of people talking about video games (including me!). It’s a great list and Joel’s comments are super fun, I had a great time. Go read it!
• My approach to GTD – capturing | zkbro: I loved this todo.txt style system using Obsidian, mixing the PARA method and daily notes. I am following to read the rest of the series of posts about this GTD system.
• My approach to GTD – processing | zkbro: This is post 02 of the above, talking about processing. It’s very complete with contexts and priority tags.
• IndieWeb Carnival: where do I wish to see the IndieWeb in 2030 – Manu: Some interesting reflections here. The one that most caught attention is the tendency of creating or replicating major corporate platforms rather than creating something genuinely different. I honestly feel that Mastodon resembles Twitter too much, and I always wonder what could be different?
• A roadmap of the Roman Empire – 82MHz: So interesting to know about Itiner‑e, a project mapping all the roads of the Roman Empire, essentially a “Google Maps” of antiquity. Andreas is so lucky to be near an actual ancient Roman road. It feels so special to me to be in archaeological sites or heritage buildings. Fascinating!

📺 Videos I enjoyed:

• A Brief History of the Concert Film by Polyphonic: I’ve been watching a lot of recordings of live performances, so this was a nice video that goes back into the origins of recording live music and creating these films.
• Heisenberg Made a Discovery in 1925. We Still Can't Explain It by PBS Space Time: Quantum Physics is crazy and amazing!
• The Windows 11 Crisis by ColdFusion: this video encouraged me to start thinking about Linux again, after years being in the Microsoft environment. I used to be a minor Linux enthusiast, having set up dual boot gaming desktops back in the day where I couldn’t play games on Linux. Well, now the reasons not to use Linux feel smaller than ever, and the reasons to leave Windows feel harder to ignore.

—

#weeknotes

The summer of 2025 brought an unlikely alliance to Washington. Senators from opposite sides of the aisle stood together to introduce legislation forcing American companies to disclose when they're replacing human customer service agents with artificial intelligence or shipping those jobs overseas. The Keep Call Centers in America Act represents more than political theatre. It signals a fundamental shift in how governments perceive the relationship between automation, labour markets, and national economic security.

For Canada, the implications are sobering. The same AI technologies promising productivity gains are simultaneously enabling economic reshoring that threatens to pull high-value service work back to the United States whilst leaving Canadian workers scrambling for positions that may no longer exist. This isn't a distant possibility. It's happening now, measurable in job postings, employment data, and the lived experiences of early-career workers already facing what Stanford researchers call a “significant and disproportionate impact” from generative AI.

The question facing Canadian policymakers is no longer whether AI will reshape service economies, but how quickly, how severely, and what Canada can do to prevent becoming collateral damage in America's automation-driven industrial strategy.

Manufacturing's Dress Rehearsal

To understand where service jobs are heading, look first at manufacturing. The Reshoring Initiative's 2024 annual report documented 244,000 U.S. manufacturing jobs announced through reshoring and foreign direct investment, continuing a trend that has brought over 2 million jobs back to American soil since 2010. Notably, 88% of these 2024 positions were in high or medium-high tech sectors, rising to 90% in early 2025.

The drivers are familiar: geopolitical tensions, supply chain disruptions, proximity to customers. But there's a new element. According to research cited by Deloitte, AI and machine learning are projected to contribute to a 37% increase in labour productivity by 2025. When Boston Consulting Group estimated that reshoring would add 10-30% in costs versus offshoring, they found that automating tasks with digital workers could offset these expenses by lowering overall labour costs.

Here's the pattern: AI doesn't just enable reshoring by replacing expensive domestic labour. It makes reshoring economically viable by replacing cheap foreign labour too. The same technology threatening Canadian service workers is simultaneously making it affordable for American companies to bring work home from India, the Philippines, and Canada.

The specifics are instructive. A mid-sized electronics manufacturer that reshored from Vietnam to Ohio in 2024 cut production costs by 15% within a year. Semiconductor investments created over 17,600 new jobs through mega-deals involving TSMC, Samsung, and ASML. Nvidia opened AI supercomputer facilities in Arizona and Texas in 2025, tapping local engineering talent to accelerate next-generation chip design.

Yet these successes mask deeper contradictions. More than 600,000 U.S. manufacturing jobs remain unfilled as of early 2025, even as retirements accelerate. According to the Manufacturing Institute, five out of ten open positions for skilled workers remain unoccupied due to the skills gap crisis. The solution isn't hiring more workers. It's deploying AI to do more with fewer people, a dynamic that manufacturing pioneered and service sectors are now replicating at scale.

Texas, South Carolina, and Mississippi emerged as top 2025 states for reshoring and foreign direct investment. Access to reliable energy and workforce availability now drives site selection, elevating regions like Phoenix, Dallas-Fort Worth, and Salt Lake City. Meanwhile, tariffs have become a key motivator, cited in 454% more reshoring cases in 2025 versus 2024, whilst government incentives were cited 49% less as previous subsidies phase out.

The manufacturing reshoring story reveals proximity matters, but automation matters more. When companies can manufacture closer to American customers using fewer workers than foreign operations required, the economic logic of Canadian manufacturing operations deteriorates rapidly.

The Contact Centre Transformation

The contact centre industry offers the clearest view of this shift. In August 2022, Gartner predicted that conversational AI would reduce contact centre agent labour costs by $80 billion by 2026. Today, that looks conservative. The average cost per live service interaction ranges from $8 to $15. AI-powered resolutions cost $1 or less per interaction, a 5x to 15x cost reduction at scale.

The voice AI market has exploded faster than anticipated, projected to grow from $3.14 billion in 2024 to $47.5 billion by 2034. Companies report containing up to 70% of calls without human interaction, saving an estimated $5.50 per contained call.

Modern voice AI agents merge speech recognition, natural language processing, and machine learning to automate complex interactions. They interpret intent and context, handle complex multi-turn conversations, and continuously improve responses by analysing past interactions.

By 2027, Gartner predicts that 70% of customer interactions will involve voice AI. The technology handles fully automated call operations with natural-sounding conversations. Some platforms operate across more than 30 languages and scale across thousands of simultaneous conversations. Advanced systems provide real-time sentiment analysis and adjust responses to emotional tone. Intent recognition allows these agents to understand a speaker's goal even when poorly articulated.

AI assistants that summarise and transcribe calls save at least 20% of agents' time. Intelligent routing systems match customers with the best-suited available agent. Rather than waiting on hold, customers receive instant answers from AI agents that resolve 80% of inquiries independently.

For Canada's contact centre workforce, these numbers translate to existential threat. The Bureau of Labor Statistics projects a loss of 150,000 U.S. call centre jobs by 2033. Canadian operations face even steeper pressure. When American companies can deploy AI to handle customer interactions at a fraction of the cost of nearshore Canadian labour, the economic logic of maintaining operations across the border evaporates.

The Keep Call Centers in America Act attempts to slow this shift through requirements that companies disclose call centre locations and AI usage, with mandates to transfer to U.S.-based human agents on customer request. Companies relocating centres overseas face notification requirements 120 days in advance, public listing for up to five years, and ineligibility for federal contracts. Civil penalties can reach $10,000 per day for noncompliance.

Whether this legislation passes is almost beside the point. The fact that it exists, with bipartisan support, reveals how seriously American policymakers take the combination of offshoring and AI as threats to domestic employment. Canada has no equivalent framework, no similar protections, and no comparable political momentum to create them.

The emerging model isn't complete automation but human-AI collaboration. AI handles routine tasks and initial triage whilst human agents focus on complex cases requiring empathy, judgement, or escalated authority. This sounds promising until you examine the mathematics. If AI handles 80% of interactions, organisations need perhaps 20% of their previous workforce. Even assuming some growth in total interaction volume, the net employment impact remains sharply negative.

The Entry-Level Employment Collapse

Whilst contact centres represent the most visible transformation, the deeper structural damage is occurring amongst early-career workers across multiple sectors. Research from Stanford economists Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen, drawing on ADP's 25 million worker database, found that early-career employees in fields most exposed to AI have experienced a 13% drop in employment since 2022 compared to more experienced workers in the same fields.

Employment for 22- to 25-year-olds in jobs with high AI exposure fell 6% between late 2022 and July 2025, whilst employment amongst workers 30 and older grew between 6% and 13%. The pattern holds across software engineering, marketing, customer service, and knowledge work occupations where generative AI overlaps heavily with skills gained through formal education.

Brynjolfsson explained to CBS MoneyWatch: “That's the kind of book learning that a lot of people get at universities before they enter the job market, so there is a lot of overlap between these LLMs and the knowledge young people have.” Older professionals remain insulated by tacit knowledge and soft skills acquired through experience.

Venture capital firm SignalFire quantified this in their 2025 State of Talent Report, analysing data from 80 million companies and 600 million LinkedIn employees. They found a 50% decline in new role starts by people with less than one year of post-graduate work experience between 2019 and 2024. The decline was consistent across sales, marketing, engineering, recruiting, operations, design, finance, and legal functions.

At Big Tech companies, new graduates now account for just 7% of hires, down 25% from 2023 and over 50% from pre-pandemic 2019 levels. The share of new graduates landing roles at the Magnificent Seven (Alphabet, Amazon, Apple, Meta, Microsoft, NVIDIA, and Tesla) has dropped by more than half since 2022. Meanwhile, these companies increased hiring by 27% for professionals with two to five years of experience.

The sector-specific data reveals where displacement cuts deepest. In technology, 92% of IT jobs face transformation from AI, hitting mid-level (40%) and entry-level (37%) positions hardest. Unemployment amongst 20- to 30-year-olds in tech-exposed occupations has risen by 3 percentage points since early 2025. Customer service projects 80% automation by 2025, displacing 2.24 million out of 2.8 million U.S. jobs. Retail faces 65% automation risk, concentrated amongst cashiers and floor staff. Data entry and administrative roles could see AI eliminate 7.5 million positions by 2027, with manual data entry clerks facing 95% automation risk.

Financial services research from Bloomberg reveals that AI could replace 53% of market research analyst tasks and 67% of sales representative tasks, whilst managerial roles face only 9% to 21% automation risk. The pattern repeats across sectors: entry-level analytical, research, and customer-facing work faces the highest displacement risk, whilst senior positions requiring judgement, relationship management, and strategic thinking remain more insulated.

For Canada, the implications are acute. Canadian universities produce substantial numbers of graduates in precisely the fields seeing the steepest early-career employment declines. These graduates traditionally competed for positions at U.S. tech companies or joined Canadian offices of multinationals. As those entry points close, they either compete for increasingly scarce Canadian opportunities or leave the field entirely, representing a massive waste of educational investment.

Research firm Revelio Labs documented that postings for entry-level jobs in the U.S. overall have declined about 35% since January 2023, with AI playing a significant role. Entry-level job postings, particularly in corporate roles, have dropped 15% year over year, whilst the number of employers referencing “AI” in job descriptions has surged by 400% over the past two years. This isn't simply companies being selective. It's a fundamental restructuring of career pathways, with AI eliminating the bottom rungs of the ladder workers traditionally used to gain experience and progress to senior roles.

The response amongst some young workers suggests recognition of this reality. In 2025, 40% of young university graduates are choosing careers in plumbing, construction, and electrical work, trades that cannot be automated, representing a dramatic shift from pre-pandemic career preferences.

The Canadian Response

Against this backdrop, Canadian policy responses appear inadequate. Budget 2024 allocated $2.4 billion to support AI in Canada, a figure that sounds impressive until you examine the details. Of that total, just $50 million over four years went to skills training for workers in sectors disrupted by AI through the Sectoral Workforce Solutions Program. That's 2% of the envelope, divided across millions of workers facing potential displacement.

The federal government's Canadian Sovereign AI Compute Strategy, announced in December 2024, directs up to $2 billion toward building domestic AI infrastructure. These investments address Canada's competitive position in developing AI technology. As of November 2023, Canada's AI compute capacity represented just 0.7% of global capacity, half that of the United Kingdom, the next lowest G7 nation.

But developing AI and managing AI's labour market impacts are different challenges. The $50 million for workforce retraining is spread thin across affected sectors and communities. There's no coordinated strategy for measuring AI's employment effects, no systematic tracking of which occupations face the highest displacement risk, and no enforcement mechanisms ensuring companies benefiting from AI subsidies maintain employment levels.

Valerio De Stefano, Canada research chair in innovation law and society at York University, argued that “jobs may be reduced to an extent that reskilling may be insufficient,” suggesting the government should consider “forms of unconditional income support such as basic income.” The federal response has been silence.

Provincial efforts show more variation but similar limitations. Ontario invested an additional $100 million in 2024-25 through the Skills Development Fund Training Stream. Ontario's Bill 194, passed in 2024, focuses on strengthening cybersecurity and establishing accountability, disclosure, and oversight obligations for AI use across the public sector. Bill 149, the Working for Workers Four Act, received Royal Assent on 21 March 2024, requiring employers to disclose in job postings whether they're using AI in the hiring process, effective 1 January 2026.

Quebec's approach emphasises both innovation commercialisation through tax incentives and privacy protection through Law 25, major privacy reform that includes requirements for transparency and safeguards around automated decision-making, making it one of the first provincial frameworks to directly address AI implications. British Columbia has released its own framework and principles to guide AI use.

None of these initiatives addresses the core problem: when AI makes it economically rational for companies to consolidate operations in the United States or eliminate positions entirely, retraining workers for jobs that no longer exist becomes futile. Due to Canada's federal style of government with constitutional divisions of legislative powers, AI policy remains decentralised and fragmented across different levels and jurisdictions. The failure of the Artificial Intelligence and Data Act (AIDA) to pass into law before the 2025 election has left Canada with a significant regulatory gap precisely when comprehensive frameworks are most needed.

Measurement as Policy Failure

The most striking aspect of Canada's response is the absence of robust measurement frameworks. Statistics Canada provides experimental estimates of AI occupational exposure, finding that in May 2021, 31% of employees aged 18 to 64 were in jobs highly exposed to AI and relatively less complementary with it, whilst 29% were in jobs highly exposed and highly complementary. The remaining 40% were in jobs not highly exposed.

These estimates measure potential exposure, not actual impact. A job may be technically automatable without being automated. As Statistics Canada acknowledges, “Exposure to AI does not necessarily imply a risk of job loss. At the very least, it could imply some degree of job transformation.” This framing is methodologically appropriate but strategically useless. Policymakers need to know which jobs are being affected, at what rate, in which sectors, and with what consequences.

What's missing is real-time tracking of AI adoption rates by industry, firm size, and region, correlated with indicators of productivity and employment. In 2024, only approximately 6% of Canadian businesses were using AI to produce goods or services, according to Statistics Canada. This low adoption rate might seem reassuring, but it actually makes the measurement problem more urgent. Early adopters are establishing patterns that laggards will copy. By the time AI adoption reaches critical mass, the window for proactive policy intervention will have closed.

Job posting trends offer another measurement approach. In Canada, postings for AI-competing jobs dropped by 18.6% in 2023, followed by an 11.4% drop in 2024. AI-augmenting roles saw smaller declines of 9.9% in 2023 and 7.2% in 2024. These figures suggest displacement is already underway, concentrated in roles most vulnerable to full automation.

Statistics Canada's findings reveal that 83% to 90% of workers with a bachelor's degree or higher held jobs highly exposed to AI-related job transformation in May 2021, compared with 38% of workers with a high school diploma or less. This inverts conventional wisdom about technological displacement. Unlike previous automation waves that primarily affected lower-educated workers, AI poses greatest risks to knowledge workers with formal educational credentials, precisely the population Canadian universities are designed to serve.

Policy Levers and Their Limitations

Within current political and fiscal constraints, what policy levers could Canadian governments deploy to retain and create added-value service roles?

Tax incentives represent the most politically palatable option, though their effectiveness is questionable. Budget 2024 proposed a new Canadian Entrepreneurs' Incentive, reducing the capital gains inclusion rate to 33.3% on a lifetime maximum of $2 million CAD in eligible capital gains. The budget simultaneously increased the capital gains inclusion rate from 50% to 66% for businesses effective June 25, 2024, creating significant debate within the technology industry.

The Scientific Research and Experimental Development (SR&ED) tax incentive programme, which provided $3.9 billion in tax credits against $13.7 billion of claimed expenditures in 2021, underwent consultation in early 2024. But tax incentives face an inherent limitation: they reward activity that would often occur anyway, providing windfall benefits whilst generating uncertain employment effects.

Procurement rules offer more direct leverage. The federal government's creation of an Office of Digital Transformation aims to scale technology solutions whilst eliminating redundant procurement rules. The Canadian Chamber of Commerce called for participation targets for small and medium-sized businesses. However, federal IT procurement has long struggled with misaligned incentives and internal processes.

The more aggressive option would be domestic content requirements for government contracts. The Keep Call Centers in America Act essentially does this for U.S. federal contracts. Canada could adopt similar provisions, requiring that customer service, IT support, data analysis, and other service functions for government contracts employ Canadian workers.

Such requirements face immediate challenges. They risk retaliation under trade agreements, particularly the Canada-United States-Mexico Agreement. They may increase costs without commensurate benefits. Yet the alternative, allowing AI-driven reshoring to hollow out Canada's service economy whilst maintaining rhetorical commitment to free trade principles, is not obviously superior.

Retraining programmes represent the policy option with broadest political support and weakest evidentiary basis. The premise is that workers displaced from AI-exposed occupations can acquire skills for AI-complementary or AI-insulated roles. This premise faces several problems. First, it assumes sufficient demand exists for the occupations workers are being trained toward. If AI eliminates more positions than it creates or complements, retraining simply reshuffles workers into a shrinking pool. Second, it assumes workers can successfully transition between occupational categories, despite research showing that mid-career transitions often result in significant wage losses.

Research from the Institute for Research on Public Policy found that generative AI is more likely to transform work composition within occupations rather than eliminate entire job categories. Most occupations will evolve rather than disappear, with workers needing to adapt to changing task compositions. This suggests workers must continuously adapt as AI assumes more routine tasks, requiring ongoing learning rather than one-time retraining.

Recent Canadian government AI consultations highlight the skills gap in AI knowledge and the lack of readiness amongst workers to engage with AI tools effectively. Given that 57.4% of workers are in roles highly susceptible to AI-driven disruption in 2024, this technological transformation is already underway, yet most workers lack the frameworks to understand how their roles will evolve or what capabilities they need to develop.

Creating Added-Value Roles

Beyond retention, Canadian governments face the challenge of creating added-value roles that justify higher wages than comparable U.S. positions and resist automation pressures. The 2024 federal budget's AI investments totalling $2.4 billion reflect a bet that Canada can compete in developing AI technology even as it struggles to manage AI's labour market effects.

Canada was the first country to introduce a national AI strategy and has invested over $2 billion since 2017 to support AI and digital research and innovation. The country was recently ranked number 1 amongst 80 countries (tied with South Korea and Japan) in the Center for AI and Digital Policy's 2024 global report on Artificial Intelligence and Democratic Values.

These achievements have not translated to commercial success or job creation at scale. Canadian AI companies frequently relocate to the United States once they reach growth stage, attracted by larger markets, deeper venture capital pools, and more favourable regulatory environments.

Creating added-value roles requires not just research excellence but commercial ecosystems capable of capturing value from that research. On each dimension, Canada faces structural disadvantages. Venture capital investment per capita lags the United States significantly. Toronto Stock Exchange listings struggle to achieve valuations comparable to NASDAQ equivalents. Procurement systems remain biased toward incumbent suppliers, often foreign multinationals.

The Artificial Intelligence and Data Act (AIDA), introduced as part of Bill C-27 in June 2022, was designed to promote responsible AI development in Canada's private sector. The legislation has been delayed indefinitely pending an election, leaving Canada without comprehensive AI-specific regulation as adoption accelerates.

Added-value roles in the AI era are likely to cluster around several categories: roles requiring deep contextual knowledge and relationship-building that AI struggles to replicate; roles involving creative problem-solving and judgement under uncertainty; roles focused on AI governance, ethics, and compliance; and roles in sectors where human interaction is legally required or culturally preferred.

Canadian competitive advantages in healthcare, natural resources, financial services, and creative industries could theoretically anchor added-value roles in these categories. Healthcare offers particular promise. Teaching hospitals employ residents and interns despite their limited productivity, understanding that medical expertise requires supervised practice. AI will transform clinical documentation, diagnostic imaging interpretation, and treatment protocol selection, but the judgement-intensive aspects of patient care, in complex cases remain difficult to automate fully.

Natural resources, mining and forestry combine physical environments where automation faces practical limits with analytical challenges where AI excels at pattern recognition in geological or environmental data. Financial services increasingly deploy AI for routine analysis and risk assessment, but relationship management with high-net-worth clients and structured financing for complex transactions require human judgement and trust-building.

Creative industries present paradoxes. AI generates images, writes copy, and composes music, seemingly threatening creative workers most directly. Yet the cultural and economic value of creative work often derives from human authorship and unique perspective. Canadian film, television, music, and publishing industries could potentially resist commodification by emphasising distinctly Canadian voices and stories that AI-generated content struggles to replicate.

These opportunities exist but won't materialise automatically. They require active industrial policy, targeted educational investments, and willingness to accept that some sectors will shrink whilst others grow. Canada's historical reluctance to pursue aggressive industrial policy, combined with provincial jurisdiction over education and workforce development, makes coordinated national strategies politically difficult to implement.

Preparing for Entry-Level Displacement

The question of how labour markets should measure and prepare for entry-level displacement requires confronting uncomfortable truths about career progression and intergenerational equity.

The traditional model assumed entry-level positions served essential functions. They allowed workers to develop professional norms, build tacit knowledge, establish networks, and demonstrate capability before advancing to positions with greater responsibility.

AI is systematically destroying this model. When systems can perform entry-level analysis, customer service, coding, research, and administrative tasks as well as or better than recent graduates, the economic logic for hiring those graduates evaporates. Companies can hire experienced workers who already possess tacit knowledge and professional networks, augmenting their productivity with AI tools.

McKinsey research estimated that without generative AI, automation could take over tasks accounting for 21.5% of hours worked in the U.S. economy by 2030. With generative AI, that share jumped to 29.5%. Current generative AI and other technologies have potential to automate work activities that absorb 60% to 70% of employees' time today. The economic value unlocked could reach $2.9 trillion in the United States by 2030 according to McKinsey's midpoint adoption scenario.

Up to 12 million occupational transitions may be needed in both Europe and the U.S. by 2030, driven primarily by technological advancement. Demand for STEM and healthcare professionals could grow significantly whilst office support, customer service, and production work roles may decline. McKinsey estimates demand for clerks could decrease by 1.6 million jobs, plus losses of 830,000 for retail salespersons, 710,000 for administrative assistants, and 630,000 for cashiers.

For Canadian labour markets, these projections suggest several measurement priorities. First, tracking entry-level hiring rates by sector, occupation, firm size, and geography to identify where displacement is occurring most rapidly. Second, monitoring the age distribution of new hires to detect whether companies are shifting toward experienced workers. Third, analysing job posting requirements to see whether entry-level positions are being redefined to require more experience. Fourth, surveying recent graduates to understand their employment outcomes and career prospects.

This creates profound questions for educational policy. If university degrees increasingly prepare students for jobs that won't exist or will be filled by experienced workers, the value proposition of higher education deteriorates. Current student debt loads made sense when degrees provided reliable paths to professional employment. If those paths close, debt becomes less investment than burden.

Preparing for entry-level displacement means reconsidering how workers acquire initial professional experience. Apprenticeship models, co-op programmes, and structured internships may need expansion beyond traditional trades into professional services. Educational institutions may need to provide more initial professional socialisation and skill development before graduation.

Alternative pathways into professions may need development. Possibilities include mid-career programmes that combine intensive training with guaranteed placement, government-subsidised positions that allow workers to build experience, and reformed credentialing systems that recognise diverse paths to expertise.

The model exists in healthcare, where teaching hospitals employ residents and interns despite their limited productivity, understanding that medical expertise requires supervised practice. Similar logic could apply to other professions heavily affected by AI: teaching firms, demonstration projects, and publicly funded positions that allow workers to develop professional capabilities under supervision.

Educational institutions must prepare students with capabilities AI struggles to match: complex problem-solving under ambiguity, cross-disciplinary synthesis, ethical reasoning in novel situations, and relationship-building across cultural contexts. This requires fundamental curriculum reform, moving away from content delivery toward capability development, a transformation implemented slowly

The Uncomfortable Arithmetic

Underlying all these discussions is an arithmetic that policymakers rarely state plainly: if AI can perform tasks at $1 per interaction that previously cost $8 to $15 via human labour, the economic pressure to automate is effectively irresistible in competitive markets. A firm that refuses to automate whilst competitors embrace it will find itself unable to match their pricing, productivity, or margins.

Government policy can delay this dynamic but not indefinitely prevent it. Subsidies can offset cost disadvantages temporarily. Regulations can slow deployment. But unless policy fundamentally alters the economic logic, the outcome is determined by the cost differential.

This is why focusing solely on retraining, whilst politically attractive, is strategically insufficient. Even perfectly trained workers can't compete with systems that perform equivalent work at a fraction of the cost. The question isn't whether workers have appropriate skills but whether the market values human labour at all for particular tasks.

The honest policy conversation would acknowledge this and address it directly. If large categories of human labour become economically uncompetitive with AI systems, societies face choices about how to distribute the gains from automation and support workers whose labour is no longer valued. This might involve shorter work weeks, stronger social insurance, public employment guarantees, or reforms to how income and wealth are taxed and distributed.

Canada's policy discourse has not reached this level of candour. Official statements emphasise opportunity and transformation rather than displacement and insecurity. Budget allocations prioritise AI development over worker protection. Measurement systems track potential exposure rather than actual harm. The political system remains committed to the fiction that market economies with modest social insurance can manage technological disruption of this scale without fundamental reforms.

This creates a gap between policy and reality. Workers experiencing displacement understand what's happening to them. They see entry-level positions disappearing, advancement opportunities closing, and promises of retraining ring hollow when programmes prepare them for jobs that also face automation. The disconnection between official optimism and lived experience breeds cynicism about government competence and receptivity to political movements promising more radical change.

An Honest Assessment

Canada faces AI-driven reshoring pressure that will intensify over the next decade. American policy, combining domestic content requirements with aggressive AI deployment, will pull high-value service work back to the United States whilst using automation to limit the number of workers required. Canadian service workers, particularly in customer-facing roles, back-office functions, and knowledge work occupations, will experience significant displacement.

Current Canadian policy responses are inadequate in scope, poorly targeted, and insufficiently funded. Tax incentives provide uncertain benefits. Procurement reforms face implementation challenges. Retraining programmes assume labour demand that may not materialise. Measurement systems track potential rather than actual impacts. Added-value role creation requires industrial policy capabilities that Canadian governments have largely abandoned.

The policy levers available can marginally improve outcomes but won't prevent significant disruption. More aggressive interventions face political and administrative obstacles that make implementation unlikely in the near term.

Entry-level displacement is already underway and will accelerate. Traditional career progression pathways are breaking down. Educational institutions have not adapted to prepare students for labour markets where entry-level positions are scarce. Alternative mechanisms for acquiring professional experience remain underdeveloped.

The fundamental challenge is that AI changes the economic logic of labour markets in ways that conventional policy tools can't adequately address. When technology can perform work at a fraction of human cost, neither training workers nor subsidising their employment provides sustainable solutions. The gains from automation accrue primarily to technology owners and firms whilst costs concentrate amongst displaced workers and communities.

Addressing this requires interventions beyond traditional labour market policy: reforms to how technology gains are distributed, strengthened social insurance, new models of work and income, and willingness to regulate markets to achieve social objectives even when this reduces economic efficiency by narrow measures.

Canadian policymakers have not demonstrated appetite for such reforms. The political coalition required has not formed. The public discourse remains focused on opportunity rather than displacement, innovation rather than disruption, adaptation rather than protection.

This may change as displacement becomes more visible and generates political pressure that can't be ignored. But policy developed in crisis typically proves more expensive, less effective, and more contentious than policy developed with foresight. The window for proactive intervention is closing. Once reshoring is complete, jobs are eliminated, and workers are displaced, the costs of reversal become prohibitive.

The great service job reversal is not a future possibility. It's a present reality, measurable in employment data, visible in job postings, experienced by early-career workers, and driving legislative responses in the United States. Canada can choose to respond with commensurate urgency and resources, or it can maintain current approaches and accept the consequences. But it cannot pretend the choice doesn't exist.

References & Sources

• 59 AI Job Statistics: Future of U.S. Jobs | National University
• Reshoring Initiative 2024 Annual Report: 244,000 U.S. Manufacturing Jobs Were Announced in 2024 via Reshoring, FDI
• Reshoring manufacturing to the US: The role of AI, automation and digital labor | IBM
• 2026 Manufacturing Industry Outlook | Deloitte Insights
• Canada | The Essex AI Policy Observatory for the World of Work | University of Essex
• Harnessing Generative AI: Navigating the Transformative Impact on Canada's Labour Market – IRPP
• Budget 2024 aims to upskill Canadian workers affected by AI | Canadian HR Reporter
• The Keep Call Centers in America Act: A Turning Point?
• US Reshoring Bill Sparks Debate on Future of Offshore Call Centers
• Gartner Predicts Conversational AI Will Reduce Contact Center Agent Labor Costs by $80 Billion in 2026
• AI in Customer Service | IBM
• AI is not just ending entry-level jobs. It's the end of the career ladder as we know it – CNBC
• First-of-its-kind Stanford study says AI is starting to have a 'significant and disproportionate impact' on entry-level workers in the U.S. | Fortune
• Who's Losing Jobs to AI? New Stanford Analysis Breaks It Down | TIME
• Yes, AI is affecting employment. Here's the data. – ADP Research
• New study sheds light on what kinds of workers are losing jobs to AI – CBS News
• The SignalFire State of Tech Talent Report – 2025
• Sorry, grads: Entry-level tech jobs are getting wiped out – SF Standard
• Exposure to artificial intelligence in Canadian jobs: Experimental estimates – Statistics Canada
• Experimental Estimates of Potential Artificial Intelligence Occupational Exposure in Canada – Statistics Canada
• What's in #Budget2024 for Canadian tech? | BetaKit
• Deputy Prime Minister announces action to protect and create good-paying jobs for Canadian workers – Canada.ca
• Federal Budget 2024: AI Update – McCarthy Tétrault
• Canadian Sovereign AI Compute Strategy – Innovation, Science and Economic Development Canada
• Federal government outlines $2 billion in AI compute spending commitment | BetaKit
• The state of AI in 2025: Agents, innovation, and transformation – McKinsey
• Generative AI and the future of work in America | McKinsey
• The economic potential of generative AI: The next productivity frontier – McKinsey
• Keep Call Centers in America Act of 2025 – Senator Gallego
• Gallego, Justice Introduce Bipartisan Bill to Protect Americans' Access to Quality Customer Service – Senator Ruben Gallego
• Can retraining programs ease the fear of AI job loss? – Northeastern University
• Jobs Lost to Automation Statistics in 2024 | TeamStage
• Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages – McKinsey
• AI Voice Agents: 2025 Update | Andreessen Horowitz
• Voice AI Technology: Cutting Call Center Costs by 60% in 2025 | SideTool
• Reshoring Initiative 2024 Annual Report, Plus 1Q2025 | Reshoring Initiative
• Reshoring Reality: What's Fueling the Manufacturing Revival? | Camoin Associates
• AI Job Displacement 2025: Which Jobs Are At Risk? | Final Round AI
• 73 AI Job Replacement Statistics (2025 Reports & Data) | DemandSage
• The Future of Jobs Report 2025 | World Economic Forum
• Artificial Intelligence 2025 – Canada | Chambers and Partners

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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

The Day the Laughter Stopped: Mourning Rob Reiner and Confronting the Violence Around Us

I woke up today hoping the news was just a mistake, a bad rumor. But the reality is setting in, and it is heavier than I know how to carry. Rob Reiner, the man who taught us to laugh at ourselves as “Meathead,” who showed us the magic of The Princess Bride, and who captured the very essence of human connection in When Harry Met Sally, is gone.

It is devastating enough to lose a cultural icon. It is shattering to lose him and his wife, Michele, to such a dark and personal tragedy.

For those of us who felt like we knew him, the details are hard to read. This wasn't a random act of nature. It was an act of violence in their own home, allegedly at the hands of their own son, Nick. And because of that, we have to talk about something harder than just “loss.” We have to talk about the crisis of violence and mental health that is tearing families, and nations apart.

It’s Not Just About the Weapon

In the immediate aftermath, there is often a rush to politicize the “how.” But in this case, there was no gun involved. This was intimate, brutal violence involving a knife. It’s a stark reminder that violence isn't defined solely by the weapon; it’s defined by the intent, the breakdown of the mind, and the failure of our support systems. Nick Reiner’s struggles with addiction and mental health were not a secret; he and his father even made a movie about it (Being Charlie). They tried to heal through art. And yet, here we are. It forces us to ask: What are we missing in how we treat severe mental illness? How does a family with resources, love, and awareness still end up in the center of such a nightmare?

A Weekend of senseless Loss

As I sit here trying to process the Reiner tragedy, I can’t ignore the rest of the news cycle. It feels like the world has lost its way this weekend.

Across the ocean in Australia, a Hanukkah celebration at Bondi Beach, a place of joy and light, was turned into a scene of terror. In that case, it was a father and son acting together in violence, leaving devastation in their wake. Whether it’s a knife in a quiet Brentwood home or gunfire on a public beach in Sydney, the end result is the same: innocent lives stolen and communities left traumatized. We are seeing a pandemic of rage and instability. We see it in the tragic shooting at Brown University reported just days ago, and we see it in the loss of one of Hollywood’s most beloved storytellers.

We Have to Do Better

It is easy to feel hopeless today. It is easy to look at the headlines and think the darkness is winning. But Rob Reiner was an activist. He was a man who fought for early childhood education, for civil rights, and for a more compassionate world. He believed we could be better. To honor him, we cannot just look away. We have to confront the uncomfortable truth that our approach to mental health is failing. We have to acknowledge that violence is a disease that mutates sometimes it looks like a mass shooting, sometimes it looks like a domestic tragedy.

We need to invest in mental health infrastructure that actually intervenes before it’s too late. We need to stop treating violence as an inevitable weather pattern and start treating it as the preventable health crisis it is.

Rest in peace, Rob and Michele. Thank you for the laughter. We will miss you, and we will keep fighting for the kind of world you believed in, one where the story ends a little brighter than this.

a quick Fischer Random checkmate

Winning this club server-based correspondence Fischer Random Chess (often called 960 Chess these days) game yesterday made me smile.

The position of pieces on the board at game's end is posted above and shows my White Queen checkmating the Black King as my tenth move of the game.

Our move record up to this point is: 1. c4 g6 2. f3 Qg7 3. Rc3 Ne6 4. Bf2 c5 5. Bg3+ Bc7 6. Bxc7+ Nxc7 7. a4 a5 8.Qxc5 b6 9. Qf2 f5 10. Qxb6# 1-0

Our assigned starting order of pieces here was FEN “rkrbbnqn/pppppppp/8/8/8/8/PPPPPPPP/RKRBBNQN w CAca” which gave us the following board to start with:

And the adventure continues.

Earlier this year, a colleague asked me what “my genre” is. I responded that it must be progressive rock. It's just weird enough to be interesting, just unexpected enough to keep your mind engaged, and just absurd enough to remind you that rules really are sometimes made to be broken.

I've listened to the Pink Floyd catalogue many times over, I've been listening to more King Crimson this year, and I've been especially enjoying “Firth of Fifth” recently. I only really listened to Rush a couple of weeks ago, but they tick a lot of my boxes. I love synthesizers.

I have so much more to discover. Something to look forward to!

#Life

We have just launched DataCenterBoom!, a repository of information for communities and local authorities that are newly faced with the construction of data centers in their territories.

“They have announced the construction of a data center in my community. What do we do?” Data centers and their capacities are multiplying worldwide as artificial intelligence gains importance in the economy. How can we bridge the gap in access to information about the socio-environmental consequences of AI, specifically in Latin America?

Based on case studies from Brazil, Chile, and Querétaro in Mexico, we built DataCenterBoom!, a repository of information for communities and local authorities so that they have information available about why a data center is being built in their community, a catalog of its socio-environmental consequences, a section on how public policy has responded, as well as lessons learned from different local resistance movements to these infrastructures.

It has a Spanish and an English version, and we hope to have a Portuguese version soon 😊. If you are interested in the topic, please subscribe to the website to receive new reports and content, and give us feedback in the About section.

#English

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Oh. What. Fun. Amazon 2025 (1.75 out of 5 Hot Chocolates)

Starring Michelle Pfeiffer, Dennis Leary, Felicity Jones, Dominic Sessa, Joan Chen, and Jason Schwartzman. Directed by Michael Showalter

Read more #100HotChocolates reviews

This movie is a holiday party eggnog left out to curdle. I imagine an Amazon exec dumping 1970s gender stereotypes, check-collecting stars, and meanness as 'satire' into the blender and thinking “Yum.” Gross.

Borrowing plot and themes from The Family Stone, Home Alone, and Planes, Trains & Automobiles, writer/director Michael Showalter doesn’t like the genre enough to craft a compelling family dramedy. It's slice-and-bake Christmas cookies sold as “from scratch.”

Every year, streamers throw money and stars at the Christmas TV movie template, attempting to legitimize something that doesn’t need it. A holiday message: More isn’t always better.

Skip it

#movies #ChristmasMovies #AmazonPrime #RomCom #HolidayMovies #100HotChocolates #100WordReview #Larrys100 #100DaysToOffload

29 November 2025

Today is the first time I've been aware of a creative cycle seemingly closing its loop in a way that feels akin to releasing an album. Or maybe an EP is more accurate, as the by-product was only four paintings. And the first of those was resolved around October 18th, so they're from a relatively short window—less than two months. In that time I completed ten paintings that I at least considered sharing at one point or another, but six of them ultimately didn't have the legs. A body of work...

What is important to note is how those two months feel more fully formed as a period of inquiry than any other period of artistic output that I've been through. This probably has to do with a number of factors, but protecting and maintaining my attention within my privacy seems chief among them. I've plotted out my points of material, aesthetic, and conceptual research regularly here, so I won't get into all of that right now. I mainly want to notice what it feels like to have been fully engaged in the natural stages of making and showing, from the seeds of a set of ideas to their resolution to sharing them with a wider audience.

Since that sharing, (first via my open studio and then to my community via online channels and outreach to interested parties), I've been pretty unsatisfied with what I've made since getting back to work in the past few days. I think that has to do with how hardened my understanding of my work feels in this moment; as much as I try to put what I'm doing into words here, the time developing my work in my studio before sharing it is not explainable, rational, or logical. The best choices made in my own painting are focused, yes, but not on coherent thought. They are made from a lightness, a delighted joy in the what-ifs that swirl around in the mind during a state of play-centric flow. So the time spent exporting the work into digestible language (in public conversation, grant/art prize applications, etc.) is basically the opposite state. It's an unavoidable part of the process of course, so this is not a lament. It's just a way of telling myself how much more can be done to sharpen the ability to toggle between those modes.

27 November 2025

There's an interview with Richard Walker around the time of his 2012 exhibition House Paintings where he talks about the process of making the work in the show during a residency at The Haining house in Selkirk:

I started to light the rooms with a projector and lamps, to create shapes, or to obscure things, And another aspect was that I’m often thinking how to use photography, or what the relationship is in my work to photography; using photographs as light rather than a printed image is interesting. I had photographs of the landscape around the house and I started projecting those into the dark rooms. So I was shutting it out, but putting it back in, in another way. And then I began even taking photos of the interiors and projecting them back on to themselves with maybe a slight shift in alignment.

Have been thinking about this a lot on the heels of what I mentioned in my last post here about finding myself being drawn to reflections recently. I think Walker gets at what I have been beginning to attempt to articulate, which is a desire to find a way to work from deeply attentive and faithful observation while still considering a fracturing and fragmentation of perception in the process.