Somewhere in the American desert, a building the size of a small town hums in the dark. It has no windows and almost no people. Inside, tens of thousands of processors run hot, churning through the requests of strangers half a world away: a marketing executive in London asking for a punchier subject line, a student in Toronto summarising a textbook, a hobbyist in Sydney conjuring a cartoon dragon for no particular reason. Pipes carry water through the building to keep the silicon from cooking itself. Transformers the size of lorries pull electricity off the grid in quantities that would once have powered a city. The dragon appears on the hobbyist's screen in about four seconds. The cost of producing it does not appear anywhere at all.

That invisibility is the point, and it is also the problem. For most of the people typing into a chatbot, generative artificial intelligence feels like the most weightless technology ever invented. There is no exhaust pipe, no smokestack, no spinning meter on the wall. You ask, it answers, and the bill, if there is one, seems to be a few pennies on a subscription. But the bill is real, and it is enormous, and it is being paid in a currency most users never see: water drawn from stressed aquifers, land scraped flat for server halls, electricity wrenched off ageing grids, and a rising tide of toxic electronic waste. The question the technology industry has been remarkably good at avoiding is a simple one. Who, exactly, is footing it?

On 3 June 2026, the United Nations University Institute for Water, Environment and Health published a report that tries to answer that question with the kind of hard numbers the debate has mostly lacked. Its title, “Environmental Cost of AI's Energy Use: Carbon, Water and Land Footprints”, is dry. Its findings are not. The report argues that the environmental costs of the AI boom are not only larger than commonly understood, but are being distributed in a way that is profoundly, structurally unjust. The wealthy generate the prompts. Someone else, very often, pays the bill.

The timing was pointed. The report landed in the same week as World Environment Day, an annual fixture in the United Nations calendar, and its authors clearly intended the juxtaposition. While the world's environment ministers issued their usual statements, a team of UN scientists was quietly publishing evidence that one of the fastest-growing pressures on the planet's water, land and atmosphere is a technology that most of those ministers were probably using to draft their speeches. The report is not a polemic. It is an attempt at accounting, an effort to put a defensible number on a cost that the industry has been content to leave uncounted, and then to ask what follows once the number is on the table.

The Myth of the Weightless Machine

There is a stubborn assumption baked into how we talk about software, and it goes roughly like this: bits are cheap, the cloud is somewhere else, and digital things do not have a physical body. Kaveh Madani, director of UNU-INWEH and one of the report's authors, puts the counterargument bluntly. “Though often described as weightless and virtual,” he says, “the reality of AI is profoundly physical.”

That physicality starts with electricity. The International Energy Agency, in its landmark “Energy and AI” analysis published in April 2025, estimated that the world's data centres consumed roughly 415 terawatt-hours of electricity in 2024, about 1.5 per cent of global demand. That figure is already growing at around 12 per cent a year, far faster than overall electricity use. The IEA's central projection is that data centre consumption will roughly double by 2030, reaching around 945 terawatt-hours. That is more than the entire current electricity consumption of Japan. The UNU report adopts the same headline number and spells out what it means: were the world's AI-driven data centres a country, they would rank around eleventh in the world for electricity use, sitting behind France and ahead of Saudi Arabia.

The IEA's analysis is careful to note that AI is the single most important driver of this surge, and that the United States accounts for by far the largest share of the projected increase, with China following. In the United States, the agency found, data centres are on track to account for nearly half of all electricity demand growth between now and 2030. This is the part that ought to alarm anyone who follows the energy transition. The grid was already straining to decarbonise. Now it is being asked to absorb a vast new load on top of everything else, and that load does not wait politely for clean power to come online. It plugs into whatever is available, which in most of the world still means gas and coal.

None of this is hypothetical. The build-out is happening now, in concrete and copper, across Virginia and Texas, across Inner Mongolia and Ningxia, in Ireland and in the Gulf. And here the UNU report makes its first genuinely clarifying move. The public conversation about AI's energy appetite has fixated on training, the months-long, headline-grabbing process of building a large model from scratch. Training is expensive and dramatic, and it makes for good copy. But it is not where most of the energy goes.

It Was Never About Training

The report's central technical insight is that the day-to-day running of AI models, the part engineers call inference, accounts for somewhere between 80 and 90 per cent of the technology's total energy demand. Training a model is a one-off cost, however large. Inference is what happens every single time anyone, anywhere, uses the thing. And the using has become astronomical.

This matters because it reframes the entire problem. If training were the dominant cost, then the environmental footprint of AI would be lumpy and occasional, a series of expensive sprints punctuating long quiet stretches. You could imagine regulating it the way you might regulate a handful of large industrial projects. But inference is not lumpy. It is continuous, ambient and growing without limit, a constant background draw that scales directly with adoption. The more useful AI becomes, the more it is used, and the more it is used, the heavier its footprint, regardless of how cleverly the original model was trained. The cost is not in the building of the machine. It is in the running of it, forever.

Consider a single product. The report notes that ChatGPT alone fields on the order of 2.5 billion prompts a day, and that running it consumes something in the region of 383 gigawatt-hours of electricity a year. That is one application from one company. Multiply the logic across the entire ecosystem of chatbots, image generators, coding assistants, search summaries and the AI features now wedged into every productivity suite on Earth, and the scale of the inference problem comes into focus.

It is also wildly uneven from task to task. The report draws on research showing that the energy cost of an AI interaction depends enormously on what you ask for. A simple text query is relatively cheap. Generating an image is, by some measures, more than a thousand times more energy-intensive than a basic text-classification task. Producing even a short, high-resolution AI video can require an order of magnitude more energy again, the report putting a single clip at over 415 watt-hours. Even the quiet creep of AI into ordinary web search carries a cost: the report notes that an AI-enhanced generative search can use roughly ten times the energy of a conventional one. The casual user has no way of knowing any of this. The interface is identical. A request that boils a notional kettle and a request that barely warms a teaspoon look exactly the same on screen, and cost the same nothing at the point of use.

Mir Matin, another of the report's authors, frames the accumulation problem precisely. “Every prompt, default setting, generated image, video, and query,” he says, “accumulates when multiplied by billions of users.” This is the crux. No single interaction matters. All of them together matter immensely. And because the cost is spread across billions of weightless-seeming moments, it never lands anywhere a user can feel it. The default settings are perhaps the most insidious detail. When a search engine or an operating system switches on an AI feature by default, billions of people begin paying its resource cost without ever choosing to, and without anyone telling them the choice was made.

The Thirst Nobody Mentions

If electricity is the part of AI's footprint that gets the headlines, water is the part that gets buried. Data centres are thirsty in two distinct ways. First, the servers inside them generate prodigious heat, and many facilities use evaporative cooling, which works by turning water into vapour and letting it drift away into the atmosphere. That water is gone from the local system. Second, and less obviously, the electricity that powers the centres is itself water-intensive to produce, because thermal power plants use vast quantities of water for cooling. Every kilowatt-hour drawn from a coal or gas plant carries an invisible water cost upstream, before a single drop touches the servers themselves.

The pioneering work on this hidden cost came from Shaolei Ren, a researcher at the University of California, Riverside, whose 2023 paper bore the memorable title “Making AI Less 'Thirsty'”. Ren and his colleagues calculated that training GPT-3 in Microsoft's state-of-the-art American data centres could have evaporated around 700,000 litres of clean freshwater, and that the figure would have roughly tripled had the training run been done in the company's less water-efficient Asian facilities. To make the number concrete, his team noted that this was comparable to the water used to manufacture hundreds of cars. Crucially, Ren extended the analysis beyond training to the everyday business of answering queries, and projected that global AI demand could be responsible for the withdrawal of between 4.2 and 6.6 billion cubic metres of water in 2027, more than the total annual water withdrawal of a country the size of Denmark several times over.

What makes Ren's work so important is not just the figures but the method. Because operators almost never disclose the water consumption of individual sites, he and his colleagues had to infer it from the efficiency of cooling systems, the local climate, and the water intensity of the electricity feeding each facility. The same prompt, run in a cool and hydro-powered region, might cost a fraction of what it costs in a hot, fossil-fuelled one. The footprint, in other words, is not an intrinsic property of the software. It is a property of where and how the software is run, a point that turns out to matter enormously when you ask who ends up paying.

The UNU report takes this body of work and pushes the timeline to 2030, arriving at a figure designed to stop the reader cold. By the end of the decade, it estimates, the annual water footprint of AI could reach 9.3 trillion litres. To make that abstraction tangible, the authors compare it to the basic annual domestic water needs of every one of the 1.3 billion people who live in sub-Saharan Africa. The image is deliberate and devastating: a technology marketed in Silicon Valley and consumed in the world's richest cities, drinking, in effect, the daily water of an entire subcontinent that has barely been consulted about its construction.

The geography sharpens the injustice. Data centres are frequently sited where land is cheap, energy is abundant and tax incentives are generous, and those conditions often coincide with regions that are already water-stressed. Matin, whose expertise is in exactly this kind of spatial analysis, has pointed to the danger of mapping where data centres are being built against where water is scarce, and finding the two maps overlapping. A facility that evaporates millions of litres a year in a temperate, rain-soaked region is a manageable nuisance. The same facility in a drought-prone basin is a direct competitor with farms and households for a resource there is not enough of. Communities in such places have already begun to push back, querying why a hyperscale operator should be granted the water their own crops are rationed.

Land, Carbon and the Mountain of Waste

Water and electricity do not exhaust the inventory. The UNU report adds two further footprints that rarely make it into the conversation at all.

The first is land. Server farms are not small. The report projects that the physical land footprint of AI infrastructure could exceed 14,500 square kilometres by 2030, an area it likens to roughly twice the metropolitan expanse of Jakarta, home to more than 32 million people. That is land taken out of other uses, reshaped, fenced, paved and wired, often on the rural fringes of communities that gain a handful of permanent jobs in exchange for a permanent neighbour that never sleeps. The footprint extends well beyond the perimeter fence, too, taking in the substations, transmission corridors and access roads that a facility of this scale demands, and in many cases the dedicated power generation built specifically to feed it.

The second is carbon. For all the talk of powering data centres with renewables, the grids they plug into remain substantially fossil-fuelled, and the sheer scale of new demand is, in many regions, keeping coal and gas plants running that might otherwise have closed. The report projects that AI-related activity could be responsible for around 400 million tonnes of carbon dioxide equivalent emissions annually by 2030. To offset that volume of carbon, the authors calculate, would require growing on the order of 6.7 billion trees over a decade. The “green” technology, in other words, is leaning heavily on a decidedly un-green energy system. There is a bitter irony in the fact that some of the same companies championing AI as a tool to fight climate change are, through that very tool, adding materially to the emissions driving it.

Then there is the rubbish. Artificial intelligence runs on specialised hardware, principally graphics processing units, that becomes obsolete with brutal speed as each new generation outperforms the last. When the chips are retired, they become electronic waste, a category laced with lead, mercury and other hazardous materials. The scale of the looming problem was quantified in a 2024 study published in Nature Computational Science, led by Peng Wang of the Chinese Academy of Sciences, which projected that the rapid expansion of generative AI could create between 1.2 and 5 million tonnes of additional e-waste over the period to 2030. Under an aggressive-growth scenario, the study found, the annual e-waste stream attributable to generative AI could reach 2.5 million tonnes by 2030, the very figure the UNU report cites. As with water and land, the burden of dealing with that waste tends not to fall on the cities that generated the demand. The world's discarded electronics have a long and grim habit of ending up in informal recycling yards across the global South, where they are picked apart by hand, often by people with no protective equipment and no choice, releasing toxins into the soil, the water and the bodies of the workers themselves.

The Two-Country Cloud

All of this might be merely alarming if the costs and the benefits were borne by the same people. They are not, and this is where the UNU report moves from environmental accounting into something closer to political economy.

The capacity to build and run frontier AI is astonishingly concentrated. The report finds that more than 90 per cent of the world's AI-specialised computing capacity sits in just two countries. The picture is corroborated by independent analysis: a study of the global data centre landscape drawn on by Oxford University researchers found that only 32 countries host AI data centres at all, and that the United States and China between them operate the overwhelming majority of the specialised facilities. By contrast, more than 150 nations have no significant domestic AI compute infrastructure whatsoever. The IEA's own figures show the United States accounting for the largest single share of global data centre electricity consumption, followed by China, with Europe a distant third and the rest of the world barely registering.

The concentration runs deeper than geography. The same handful of corporations that own the compute also own the leading models, the training data, the cloud platforms on which everyone else builds, and increasingly the energy deals that keep the whole edifice powered. Oxford's analysts have argued that this clustering of compute, talent, data and capital means that even mid-sized economies, let alone poor ones, face barriers to independent frontier development that are close to insurmountable. The result is a world in which AI is not a general-purpose technology that diffuses outward to everyone, the way electricity or the internet eventually did, but a service piped out from a couple of national hubs, on terms set by their owners.

Think about what that distribution actually means. The intelligence is manufactured in a tiny number of places, owned by a tiny number of companies, and rented out to the rest of the planet as a service. The economic returns, the share prices, the productivity gains, the strategic advantage, accrue overwhelmingly to those two countries and the firms headquartered in them. But the environmental costs, as the report documents, are not so neatly contained. They leak. The carbon enters a shared atmosphere that warms everyone. The water is drawn from local basins that, increasingly, sit in the very regions least able to spare it. The discarded hardware migrates down the global waste stream to the poorest places on Earth.

This is the asymmetry at the heart of the report, and it deserves to be stated plainly. When someone in a wealthy country generates an image, summarises a document or asks a chatbot for advice, the water, land and energy costs of that interaction are being distributed across communities and ecosystems that had no say in the choice and will see little of the benefit. The convenience is privatised. The cost is, in large part, socialised, and socialised on to exactly the populations with the least power to refuse it. It is a near-perfect inversion of the polluter-pays principle that environmental law spent half a century trying to establish: here, the polluter mostly does not pay, and the payer mostly does not pollute.

Why Efficiency Will Not Save Us

There is a comforting story the industry likes to tell about all this, and it goes like this: the chips keep getting more efficient, the models keep getting leaner, and so the problem will shrink itself out of existence. Every generation of hardware does more computation per watt. Every clever algorithmic trick squeezes more capability from less silicon. Surely, the argument runs, efficiency will win.

It will not, and the reason has a name. It is called the Jevons paradox, after the nineteenth-century English economist William Stanley Jevons, who noticed something counterintuitive about coal. As steam engines became more efficient and burned less coal per unit of work, Britain did not use less coal. It used vastly more, because cheaper, more efficient steam power made coal worth using for a thousand new purposes. Efficiency did not curb consumption. It unleashed it.

The same logic stalks artificial intelligence, and the parallel is not merely rhetorical. A 2025 paper presented at the ACM Conference on Fairness, Accountability and Transparency, titled “From Efficiency Gains to Rebound Effects”, examined precisely how Jevons' paradox applies to AI, arguing that the efficiency improvements the industry trumpets as environmental wins are systematically reinvested to expand markets, stimulate new demand and drive aggregate resource consumption upward rather than down. When a model gets cheaper to run, it does not get used the same amount more cheaply. It gets used more. Features that were too costly to ship get shipped. AI gets stuffed into products that never had it. The summary, the autocomplete, the always-on assistant proliferate precisely because each one became cheap.

The episode that made this concrete for the whole industry arrived in early 2025, when the Chinese firm DeepSeek released a model that matched the performance of far costlier systems at a fraction of the computational expense. The market's first instinct was to assume this would mean less demand for chips. The more sophisticated reading, which gained ground quickly, was the opposite: drastically cheaper AI would mean drastically more of it, everywhere, all the time. Cheaper inference is not a brake on consumption. It is an accelerator. Madani's co-authored framing captures the trap exactly: more efficient and more affordable AI does not mean less consumption, it means more.

This is why the report insists that judging AI's sustainability by efficiency metrics alone, or by carbon alone, is a category error. A model that uses half the energy per query but is used twenty times as often has not solved anything. It has made the problem worse while looking, on the relevant dashboard, like progress. The footprint that matters is the total one, and the total one is going up. The rebound effect is not a quirk to be engineered away. It is the structural reason that efficiency, on its own, can never be the answer, and that some external limit, whether regulatory, economic or physical, will eventually have to do the work that efficiency cannot.

The Trouble With Measuring Anything

If the costs are this large and this skewed, an obvious question follows: why has it taken so long for anyone to say so clearly? Part of the answer is that the numbers are genuinely hard to pin down, and the companies that hold the best data have shown little appetite for sharing it.

Operators rarely disclose the water consumption of individual facilities, the energy mix powering them, or the per-query resource cost of their models. Researchers like Ren have had to reverse-engineer estimates from patchy public filings, regulatory disclosures and educated assumptions about cooling systems and grid composition. The result is a literature full of ranges rather than precise figures, and those ranges are routinely weaponised by industry defenders who point to the uncertainty as a reason to wait. The argument is circular and convenient: the companies decline to publish the data, then cite the resulting uncertainty as grounds for inaction, all while the build-out accelerates.

Aczel, the report's lead author, locates the deeper hazard in the metrics themselves, warning that the choices which look greenest on a narrow accounting can disguise real costs that a fuller reckoning would expose. Judge AI's sustainability by carbon alone, and you will systematically miss the water and the land and the waste. Her broader point is that the environmental footprint of AI is not a fixed fact of nature. It is shaped, she argues, by infrastructure decisions, by the energy sources chosen, and by how models are designed, which means it can be shaped differently. That is, in its way, an optimistic claim. If the footprint were destiny, there would be nothing to do but despair. Because it is the product of choices, it is open to better ones.

The opacity is not accidental. A technology whose costs are invisible to its users and unmeasured by its public is a technology that faces very little pressure to change. The first act of accountability, then, is simply measurement. You cannot govern what you refuse to count, and for the moment the people best placed to count have every incentive not to.

What Accountability Would Actually Look Like

The UNU report does not stop at diagnosis. It proposes a framework built on six principles: transparency, efficiency by design, equity and environmental justice, lifecycle responsibility, global cooperation, and sustainable use. The list can read as the usual policy boilerplate, but underneath it sits a genuinely radical proposition, which is that the relationship between AI's beneficiaries and its bill-payers should be made visible and then made fair.

Transparency comes first because nothing else works without it. If operators were required to disclose, in standardised and audited form, the energy, water and carbon footprint of their facilities and ideally of their models, the entire debate would shift from contested estimates to verifiable fact. Users could, in principle, see the resource cost of a request the way a car displays its fuel consumption. Regulators could site facilities with full knowledge of local water stress. Investors could price environmental risk properly. The information asymmetry that currently protects the industry would begin to close. None of this requires a technological breakthrough. It requires a disclosure regime, and the political will to impose one.

In the weeks after the report appeared, something close to that political will began, tentatively, to surface. On 23 June 2026, at London Climate Action Week, the United Nations Secretary-General, António Guterres, launched what he called the AI Environmental Transparency Initiative, a charter inspired directly by the UNU-INWEH findings. It asks every major AI company to do two things: to measure and publicly disclose the full carbon, water and land footprint of its systems, and to commit to powering every data centre with renewable energy by 2030. “No more hidden costs,” Guterres said. “If AI is to help build a better future, it must be honest about what it costs us now.” Madani, whose report had supplied much of the initiative's intellectual scaffolding, called it “a gift” and “an opportunity to be proactive instead of reactive”, returning to the principle that had animated the whole project: “We cannot properly manage what we do not measure.” The significance is real, and so are the limits. The initiative is a voluntary call rather than a binding rule, an invitation to companies to come clean rather than a mechanism that compels them to. It is the sound of the political will clearing its throat, not yet the disclosure regime itself, and the distance between an industry being asked to disclose and an industry being made to is precisely the distance this report has spent its length measuring.

Efficiency by design and lifecycle responsibility push the engineering upstream. The e-waste research is instructive here: Wang's team found that extending the working life of AI hardware, and refurbishing and redeploying ageing chips for less demanding tasks rather than scrapping them, could cut projected e-waste dramatically, by more than 40 per cent in some scenarios. The point generalises. A great deal of AI's footprint is the product of decisions, where to build, what to cool with, how long to run the hardware, whether to bolt an AI feature on to a product that did not need one, and decisions can be made differently. Lifecycle responsibility means the firm that profits from a chip's first life is also accountable for its last, rather than letting the carcass become someone else's problem in a recycling yard half a world away.

But the principles that carry the real moral weight are equity, environmental justice and global cooperation, because they speak directly to the asymmetry the rest of the report documents. If 90 per cent of the compute and almost all of the profit sit in two countries, while the water stress, the e-waste and the climate impact land disproportionately on the 150-plus nations with no AI infrastructure of their own, then any honest framework has to grapple with redistribution. That might mean siting standards that steer facilities away from water-scarce regions and on to genuinely surplus renewable power. It might mean the wealthy beneficiaries of AI financing water security, grid resilience and proper e-waste recycling in the places absorbing the downstream costs. It might mean giving those nations a real voice in the governance of a technology that is reshaping their environment without their consent. At minimum, it means refusing to pretend the costs are not there.

What the report stops short of, sensibly, is pretending that any of this will be easy. Each principle cuts against a powerful commercial interest. Transparency threatens a competitive secret. Lifecycle responsibility threatens a margin. Equity threatens a status quo from which the powerful benefit enormously. A framework is not a mechanism, and the gap between the two is where most well-meaning governance goes to die. But the value of naming the principles is that it makes the trade-offs explicit. It turns a set of invisible, deferred costs into a visible political question, and visible political questions can at least be argued over, which is more than can be said for costs nobody admits exist.

Paying the Bill

Return, for a moment, to the windowless building in the desert, and to the four-second dragon. There is nothing wrong with wanting the dragon. The case against the hidden bill is not a case against artificial intelligence, which is already delivering genuine value in medicine, science, accessibility and a hundred mundane corners of working life. The case is against the invisibility. A technology this physical, this thirsty and this geographically lopsided should not be allowed to present itself as weightless, because the weightlessness is a kind of accounting trick, and the trick has victims.

The deepest finding of the UNU report is not any single number, alarming as the numbers are. It is the structure those numbers reveal: a global system in which the pleasure of generating is decoupled, almost completely, from the pain of providing. The user in London or Toronto or Sydney experiences AI as frictionless because the friction has been exported, to an aquifer in a dry country, to a grid burning fossil fuel to meet demand it never planned for, to a recycling yard where someone breaks apart a dead processor with their bare hands. The friction did not disappear. It moved to where it could not be seen and could not be refused.

Building accountability into that relationship means, in the end, putting the friction back where it belongs. It means the price of a prompt, somewhere, somehow, reflecting the water it evaporated and the carbon it emitted. It means the firms reaping the trillion-dollar valuations carrying the cost of the cleanup, the refurbishment and the repair, rather than letting it flow downhill to people who never typed a word into a chatbot. It means measuring honestly, siting responsibly, and granting the communities on the receiving end something they have never been offered: a say.

The world is not about to stop using artificial intelligence. The 2.5 billion daily prompts will become more, not fewer, and the rebound effect guarantees that every efficiency gain will be spent on more usage rather than less impact. The only real question is whether the bill will keep arriving, silently, at the doorsteps of people who never ordered anything, or whether the world musters the will to redirect it to the address where the dragon was actually conjured. The report's authors have done the arithmetic, and in the weeks since, a first move has been made: a United Nations Secretary-General asking the industry to come clean. But it remains an asking, not a requiring, a voluntary charter rather than a bill redirected, and the choice about who pays is still, for now, ours to make. It is worth remembering that someone is already paying, and they are not the ones holding the phone.

References

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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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Its 3 am, and again, i cant sleep. i cant help it. i just cant sleep when it comes to this hour, So, ill stay here, talking nonsense and complaining until it makes me feel something either miserable or frustrated, and eventually ill sleep it off. maybe ill dream of that lovely woman, shes closer to me in my dreams, and if thats the only way i can have you, then i wont complain, i love it. if its just my own delusion keeping me closer to you, then ill stay delusional. it was never suffocating to love you. it was never suffocating to be by your side. whats suffocating is being away from you. Not hearing your voice. not seeing your beautiful face anywhere except in my dreams. And god, How miserable that makes me feel. you lose everything around you, one thing after another, and then somehow you lose the only person who made staying alive feel easy. and yet we make promises to ourselves. Silly little promises. how much longer am i supposed to stay alive when my heart tears itself apart ever time it remembers im not yours anymore? i could wait years for you, i could wait until my heart stops beating, until i rot in my own bed. i’d waste my last breath just calling your name. Today, july 4th. was supposed to be our day, the day we’d laugh about old memories. Ther day you’d remind me of the first time we met and tell me how miserable it was putting up with me. and id still. id still tell you that every time we spoke, it felt like falling in love for the first time. well, you’re probably somewhere out there, living your life while im here turning memories into bedtime stories. laughable. isnt it. i spend more time talking to someone who isnt here than to the people standing right in front of me. I should probably stop writing before morning comes and i start wondering who possessed me at three in the morning. thats usually how this goes. i write something embarrassingly honest, fall asleep and ten wake up and pretend i wasnt the one who wrote it.

what a great timing. honestly. i was just getting sentimental, then i saw something and ruined my own mood. now everything in my head just snapped off at once.

What was i writing about again?

Sincerely, i am miserable and frustrated.

Lao Tzu, Literally: Chapter 1

Chapter / Line. Ivanhoe, Chapter 1. “Always eliminate desires in order to observe its mysteries / Always have desires in order to observe its manifestations.”

What the Day Did. I ran the couplet as a switch I could flip, desireless first, then desire, and tested it three times.

Jasper's litter boxes. Mask on, I paused five seconds and let what was actually there arrive: cat piss hitting through the mask, the texture of the litter, the tracks, the litter he kicks out of the box. The holistic view, everything I normally block out by cleaning in haste. Then I let desire kick in. I wanted it done and the smell gone. Baking soda in each box, and my vision narrowed on the spot. Scoop, poop, bag. I no longer saw the litter box, only its contents. Without desire, more was revealed and I knew better what was needed. With desire, two clean boxes got manifested.

Old Testament study, fifteen minutes, Elijah and the priests of Baal. The desireless look at the lesson landed like an unappetizing plate of food. Lots to read, a story I already knew, no interest. I skimmed it. Not a failure, though, because the skim exposed the real mechanism: my active desire was never to study Elijah. It was to get the lesson finished, and once that desire took over, skimming became the shortest route to done.

Saint John's Kitchen, Kitchener, scorching Friday, 1pm. In with no desire, no expectations. People everywhere, chatting, dogs, bikes brought inside so they don't get stolen, volunteers working the kitchen, tables covered in half-eaten food and used containers. I found an empty table, sat, surveyed, and looked at my watch. Not a good sign. Barely in the door and already clocking time. So I looked with desire and immediately saw the need to clean, my own table included. I asked a cook if I could help, got a pail and cloth, and went to work. Cleared tables, emptied garbages, mopped up a dog's spilled water and gave him a fresh container full. I was trying to clear as many tables as I could. I can get very goal oriented. Mid-work, I though of Mary and Martha in Luke 10. Martha careful and troubled about many things, Mary at the feet of Jesus choosing the good part. I wondered if all this busyness was me missing the better part, sitting with the clients, friendly conversation, the humanity in the room instead of wiping the crumbs on the tables.

The Snag. Being desireless is the part I have difficulty with. I'm not in that state long enough. The watch-glance came inside the first minute. Desire arrives uninvited and narrows me without asking, and the same tunnel vision that clears tables efficiently is the tunnel vision that misses the people sitting at them. Elijah showed the quieter version: desire will substitute “finished” for the thing itself, and I only catch the swap afterward. Going in desireless first, unrushed, reveals a truer picture of how things really are. Remembering to hold that stance is the hard part.

In Summary: * Another scorching hot day outside, and I got no yard work done. All my work was done inside and was mostly laundry related.

Looking forward to wrapping up the night prayers and turning in early.

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

Health Metrics: * bw= 227.41 lbs. * bp= 145/88 (70)

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

Diet: * 05:45 – 1 ham & cheese sandwich * 07:35 – cooked, sliced sweet potatoes * 11:30 – 1 pb&j sandwich * 14:00 – scrambled eggs and white bread

Activities, Chores, etc.: * 04:30 – listen to local news talk radio * 05:30 – bank accounts activity monitored. * 05:50 – read, write, pray, follow news reports from various sources, surf the socials, nap * 08:15 – load weekly pill boxes * 08:45 – pack winter clothes * 12:00 – doing laundry * 14:00 – now listening to 104.3 The Score The Score is Chicago's No. 1 and most-listened to sports station. The Score is also the exclusive audio home of the Chicago Cubs. I'll stay here for the radio call of this afternoon's Cubs /Cardinals. * 18:13 – and the Cardinls win, 17 to 1.

Chess: * 13:30 – moved in all pending CC games

Our Father Who art in Heaven Hallowed be Thy name Thy Kingdom come Thy will be done on Earth as it is in Heaven Give us this day our daily Bread And forgive us our trespasses As we forgive those who trespass against us And lead us not into temptation But deliver us from evil

Amen

Jesus is Lord! Come Lord Jesus!

Come Lord Jesus! Christ is Lord!

Move On

Stereo time and Santa’s big war In entry by the stadium,- we wished for a start And were promptly muted- for rain at four And what is meaning, but this Songs to our order The tin at will,- at time’s release Justice to the heart And covert insert to the pledge Fine nights of her And Invictus the Hard- Laying for torture,- This move that was Showing no gold but to them The proven boy and analogue Dented by players in the hut And a IIe at breakfast to apprehend The visions of Small And an interlude for war And surely a misunderstanding Every great poet in power And time as well Victory to the great mutiny- Time at the self and rod regret The happenstance of the heart And making lines amend; what is it for And they play with the dots- of a sudden fodder by light A twinkling in his hair Blessed hair, for religion and famous Three is the time to play Myth A cousin of war in the lit But made admin, a sixth person in tow A night for solid free Mittens and garland to the end The worry of a paranoid year Children who can’t eat A Labrador as Jim And shoes to know memory that remains But in a solid hold, The Eucharist Days of portend and uncommon Ceded power to God From the free and able Abstentions to glow in this through A blessed country, for comets revisit And the Earth shall remain Lights to our symphony but remain Christ is in store and I remember Fading lights at that man And running to be free Perpetuance of sin Victory knows I am near But therefore in endurance And a faithful regret Life in deliverance to the poor Deception cease Lighting our doors such as this Mayhem as a blunder And sympathy draw There is lemon in the summertime and at will I know where this has been Time’s regret to the antecedent Victory I know has a story Long be forgotten The World for all close A beckon of thirst to the Cup Victory is The Lord Let not be last, those in sin I would try as they are to be that Simply willed but unsure This is our Victory Day in the Summer A crucifixion unto you The Son of God in proclaim Night’s war and free Laying all weapons to the pond The lost would in their Hearts Making the right turn Burning free And turning to them The borne dedication to our lot Crucified- in dust to the ear at our home Victory South to the victims- Such terrible wrong Nights in return to that River The funeral and accompaniment of valour In a Spring year we folded Times of unfaith and in London Paris for the grey orange and forget Sympathy Magog to our Spare Exulted benew Time says amen, and be free The simplest code, Giving Nature her way And Heaven at the door saying “Come in.” In virtue we can; in mercy Trusted to shallows of the sea, the merciful one Gifts of God and tempered bet A faithful run to the end Simple sharing of Hers is by day Citizens implore, and Earth to be Devon Solace unfold to our star This and Hearts believe Dedication to the Blessed Virgin Mary Christ carrying our Cross to the end; no faithful and further Peace for the living Genuflect to our Saviour The Earth as sacred, what it was And miserable deep in prayer North Korea is no longer In time at war like this And hitmen to the day Peace lumbering On this day made of gold And early in May Life is giving- And sympathy still- The Blood of Christ.

In final stanza of Longfellow's long poem, “The Building of the Ship,” we find out this page was long poem is not about building a ship but about building a nation. These words ring just as true as they did nearly 200 years ago when Longfellow first penned them

Many are cynical and discouraged about the future of America. I used to be, though I am not now. But we must no longer be complacent. I have realized that what our Founding Fathers struggled to establish, we must similarly struggle to maintain. Entropy, entitlement, historical amnesia, and indifference threaten our blessed inheritance as much as Socialism, division, and foreign threats. Ours is the time to re-learn from books and put into practice through political involvement before we have to re-learn from suffering and put into practice through arms.

Read Longfellow's words, then read them again, then re-read the Declaration, and have a blessed Independence Day, America!

Thou, too, sail on, O Ship of State! Sail on, O Union, strong and great! Humanity with all its fears, With all the hopes of future years, Is hanging breathless on thy fate! We know what Master laid thy keel, What Workmen wrought thy ribs of steel, Who made each mast, and sail, and rope, What anvils rang, what hammers beat, In what a forge and what a heat Were shaped the anchors of thy hope! Fear not each sudden sound and shock, 'T is of the wave and not the rock; 'T is but the flapping of the sail, And not a rent made by the gale! In spite of rock and tempest's roar, In spite of false lights on the shore, Sail on, nor fear to breast the sea! Our hearts, our hopes, are all with thee, Our hearts, our hopes, our prayers, our tears, Our faith triumphant o'er our fears, Are all with thee, — are all with thee!

#culture #history #politics

Concise working reference for ongoing research and eventual synthesis.

Identity & Properties

Cadmium is a bioaccumulative toxic metal absorbed by plants from soil. It concentrates in kidneys, bones, and blood, with a biological half‑life measured in decades.

Heavy metal — soft, silver‑white, naturally occurring. Bioaccumulation — slow clearance; long-term body burden. Carcinogenicity — classified as Group 1 (IARC).

French Context

France treats cadmium as a structural food-chain contaminant, not an episodic pollution event. Population exposure: ~1 in 2 adults exceed recommended urinary thresholds. Children: higher dietary exposure relative to body weight. Primary source: food, not water or air, for non-smokers. Policy posture: ANSES frames it as a long-term agricultural and industrial legacy issue.

Pathways Into Food

Phosphate fertilizers — naturally contain cadmium; accumulate in soil over decades. Industrial deposition — metallurgy, incineration, battery recycling. Root uptake — cereals, rice, potatoes are efficient cadmium absorbers.Soil pH — acidic soils increase cadmium mobility.

High-Contribution Foods

Cereals (bread, pasta, biscuits, pastries) Rice Potatoes Leafy vegetables (variable by soil conditions) These foods are both high-uptake and high-frequency, explaining population-wide exposure.

Health Effects

Kidney damage — proximal tubule dysfunction. Bone demineralisation — fractures, osteomalacia. Cardiovascular risk — hypertension associations. Cancer — lung, prostate (inhalation vs ingestion pathways differ). Cadmium’s danger is chronic accumulation, not acute poisoning.

French Biosurveillance

ESTEBAN study — ~47.6% of adults exceed urinary reference values. ANSES 2026 — confirms widespread exceedance and rising long-term risk. Testing — reimbursed blood/urine tests available (~€27.50).

Policy Levers (France & EU)

Fertilizer regulation — tightening cadmium limits in phosphate imports. Soil remediation — slow, expensive, politically difficult. Agricultural guidance — crop selection, soil pH management. Food-chain monitoring — EAT3 study expansion. Industrial emissions — stricter controls on cadmium-emitting sectors.

Irish Context

Environmental background

Ireland’s soils are generally less cadmium‑rich than parts of continental Europe, but two structural factors matter: Phosphate fertilizers — Ireland imports almost all of its phosphate, and imported phosphate rock varies widely in cadmium content. Legacy industrial sites — smelting, waste incineration, and historic landfills contribute localised hotspots. Soil pH — Irish soils tend to be acidic, which increases cadmium mobility and plant uptake.

Ireland’s agricultural profile

(grassland-dominant) reduces exposure compared with cereal-heavy countries, but tillage regions (Wexford, Carlow, Kildare, Meath) are more relevant.

Dietary exposure

Ireland’s exposure pattern mirrors France’s but at lower intensity: Cereals — bread, porridge oats, breakfast cereals. Potatoes — Ireland’s high per‑capita potato consumption makes this a key vector. Vegetables — especially leafy greens grown in acidic soils. Ireland does not have national biomonitoring data equivalent to France’s ESTEBAN study. Exposure estimates rely on EU-wide EFSA modelling, which places Ireland in the mid-range of European dietary cadmium intake.

Industrial context

Ireland’s cadmium emissions are low by EU standards, but relevant sources include: Battery recycling (small-scale, regulated) Waste incineration (Poolbeg, waste-to-energy plants) Historic smelting sites (e.g., Avoca) Landfill legacy — older sites with mixed industrial waste These are localised risks, not population-wide drivers.

Regulation & Monitoring

Ireland follows EU cadmium limits rather than setting its own: EU food cadmium limits — strict thresholds for cereals, vegetables, baby foods. EU fertilizer regulation — gradual tightening of cadmium content in phosphate fertilizers. EPA monitoring — soil and water cadmium tracked at industrial and agricultural sites. No national biomonitoring — Ireland lacks a French-style population-level cadmium testing programme.This means Ireland may not detect a rising trend until EU-wide studies flag it.

Irish-specific dynamics

Three features make Ireland interesting: High potato consumption — potatoes are efficient cadmium accumulators. Acidic soils — increase cadmium uptake. Imported phosphate — Ireland depends entirely on external sources, making fertilizer policy a geopolitical issue. These factors suggest Ireland could be more vulnerable than it appears, especially if fertilizer cadmium limits remain loose.

Open Questions for Marshall on Policy & Essays

Exposure inequality — Are certain French regions more affected? Agricultural economics — Costs of fertilizer reform. Soil legacy — How long until soils recover? Risk communication — How France frames chronic contaminants. Comparative policy — EU vs US cadmium thresholds. Dietary mitigation — Practical consumer-level strategies.

Irish exposure, EU regulatory history, soil chemistry

Research gaps

Ireland has not done the equivalent of France’s ESTEBAN biosurveillance. Key gaps: Human biomonitoring — no national urine/blood cadmium dataset. Soil cadmium mapping — EPA data exists but is patchy. Agricultural uptake studies — limited crop-specific research. Regional exposure differences — tillage vs grassland dynamics not fully studied.

Feature: These gaps are should be explored in policy brief

Next steps

Treat this as a modular dossier: Add new sections as I discover more (soil chemistry, EU trade, industrial sources). Keep short, factual entries rather than prose. Mark items that feel like policy levers vs essay themes. When the note becomes too dense, split into: 1: Marshall Policy Brief (regulatory, agricultural, biosurveillance) 2: dm.ie/marshall.ie Essay (food-chain fragility, environmental legacy, chronic toxicity)

I feel super down and low today. I don’t know if it is everything going on, or maybe depression sneaking in. Or maybe it is just one of those days. I am trying to keep optimistic. I am trying to find positivity in my day to day, in the content I’m consuming, the activities I am involved in, and even just within myself. I have to admit, it is one of the hardest things I have had to do.

I would love nothing more than to come on here and be negative, but I have been reading up on neuroplasticity and how our brains are affected by how we perceive things, and how our inner thoughts shape the experiences around us. For those reasons, I am trying to remain positive. I believe things will work out even better than I imagine and I will overcome these emotions and these struggles.

Thank you for your message. I am currently out of office with no set return date. I will get back to you when the time is right.

This afternoon, a Rivalry game.

The Chicago Cubs vs the St. Louis Cardinals, a classic MLB rivalry game, is scheduled to start this afternoon at 3:05 PM CDT. As I usually do, I'll follow the game's score and stats in real time via MLB's Gameday Service where we can also find a link to the radio-call of the game.

And the adventure continues.

I was listening today, on my last day of work, to the Irreligious album by Moonspell. It’s my favourite one, not because the best track is on there, but rather because every single track (except Raven Claws) is 100/100

And that’s my firm conviction

My cousin, a great philosopher, he played me this album a long time ago and it blew my mind then.

It was during my most eccentric period of life, I had a green cape and green nail polish which miscoloured my nails, a green jacket, hair which was also green, cut in a Romulan fashion (from star trek of course), and green hoodie.

I don’t know why I was so strangely clothed back then, I think it may have been a natural progression of the style I adopted in high school, a rejection from a norm which I felt had rejected me. I wasn’t aware of anyone dressing like this.

Only by becoming very strange, I found a sense of self deep within.

Or something, I felt like something.

This was not to get attention, but rather a way to not disappear. Or maybe a way to seize control of my life. Or maybe a ward against ”normal” people.

So we lent this CD or a copy to the girl I was in love with at the time, she who spat in my food. I remember lending it to her because her favourite track was Raven Claws.

But this is of course all in the past, just like the job I just finished.

And I just try to navigate this life as best I can.

Lydia's Weekly Lifestyle blog is for today's African girl, so no subject is taboo. My purpose is to share things that may interest today's African girl.

This week's contributors: Lydia, Pépé Pépinière, Titi. This week's subjects: Soft Power Dressing for the Accra Girl, African cultural heritage for sale, free of charge, And what to do if your baby is an idiot? Beans and blue zones, and Jollof Goat, delivery from Nyonyo

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Soft Power Dressing for the Accra Girl. Who said corporate fashion has to be stiff, stressful, and smelling faintly of printer ink? Enter the kimono — the effortlessly chic fashion piece quietly transforming office wardrobes from “HR-approved” to “main character energy.” Why the Kimono Works for Corporate Wear. A kimono adds instant sophistication without trying too hard. It’s that magical piece that says: “I closed deals today… but I also know the best cocktail spot in Osu.” The “I’m Busy but Stylish” Hack The beauty of kimonos is that they make lazy dressing look intentional. Running late for work? Throw a kimono over: A plain midi dress Sleeveless top and pants Pencil skirt and tank top Suddenly everyone thinks you planned the outfit for days. Fashion is funny like that. Kimono Length Matters Short kimonos = playful Friday office energy Mid-length kimonos = polished everyday chic Long flowing kimonos = dramatic “don’t disturb me unless it’s important” energy. Choose wisely depending on your mood — and whether your office AC is fighting for its life. Fashion memo: So next time your wardrobe feels boring, skip the predictable blazer and reach for a kimono instead. Because spreadsheets are temporary. Style is forever. African cultural heritage for sale, free of charge. Great was my surprise when I saw a woman dressed as per attached photograph. In a mini village in the French countryside, 600 km from Paris. I’d be very surprised if she had visited family or friends in Ghana and brought this as a souvenir. And it was different, it was printed, not woven. So what are we going to do? Those involved in the production of these local garments, be they kente, adinkra batakari or the recently launched bambolse are quite a few and are earning a little bit of money from it, through local sales and from a few cheap sales at a local tourist market. Whilst a dress as per picture, rightly marketed, should retail for at least 1000 GHC in Europe. But there’s a bit of light in the tunnel. Since September 2025 our kente is WIPO protected (World Intellectual Property Organization), meaning whoever produces whatever can not call it kente unless it is kente made in Ghana. And this WIPO thing is UN recognized (just hoping that Trump does not blow up the UN). Ayeeko to the people behind this, it must have been a lengthy and frustrating process, these things are not done overnight. And pray they will also seek protection for our adinkra, batakari and bambolse. And anything we do officially overseas, cultural events, things organized by our embassies and everything else should show our heritage. Put Ghana on the map. Not only in the knock out.

And what to do if your baby is an idiot? You've taken all the precautions, no sickle or noted madness in your or his family, you did not take alcohol or certain medications during pregnancy and you ate healthy. And still, disaster, your child is born with Down Syndrome or something else which will make it never perform normally in society and which will make it need constant care. Fact is that abnormal children is happening more often these days than 30 years ago. Figures are difficult to get, Down Syndrome is about 0.15% (15 per 10,000), but if you add other problems you get to about 1.5 %, 15 per 1000 (per thousand), or 8000 “abnormal” children born every year in Ghana). You are the mother, so you are going to give that care. So here you are, you are now doomed. Till you die. Is that fair? Or should you rather put the child up for adoption, relinquishment? And continue with your life? Or send it to the village where people are more used to have abnormal children live amongst them, care for them, than in the cities? In some of the far-off villages they still have their own way to solve such problems, at night the child is taken away by ghosts or similar, and not seen again. Food for thought? Anyway, eat healthy during your pregnancy.

Beans and blue zones. Blue zones are areas in the world where many people become an easy hundred years old. Famous are Loma Linda in the USA, Costa Rica, Sardinia in Italy, Ikaria in Greece and Okinawa in Japan. Apart from healthy life styles like lots of walking and moving and busy social lives researchers have of course looked at what these people eat. What really sticks out is that the average blue zoner eats 5 times more beans than the rest of the world. Ghanaian doctors mostly do not recommend beans. It is true that they can be a bit heavy to digest if you are not used to them, so take it easy in the beginning. A little more after a few days and so on. And soak them for at least 24 hours before cooking to get rid of the oligosaccharides, a form of sugar we find difficult to digest, and phytic acids which block iron and zinc absorption. Throw the soaking water away. Beans are also good against constipation, but here again, go easy in the beginning or you may even be misdiagnosed with appendicitis (I know of such a case). An odd fact is that Cubans, who are poor, live about as long as Americans, who have all the modern health gadgets. The staple in Cuba is beans, maybe with a side dish of some rice and veggies. And some fish or meat. Maybe time to re-evaluate our rice with chicken or chicken with rice?

Jollof Goat, delivery from Nyonyo. More bone than goat meat, and the rice not sufficiently cooked, and the oil had a funny taste. Anyone know of an evaluation list of food delivery providers?

Lydia...

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The National Press Club holds its 27th annual members photography exhibit again this September, which we've organized for the 11th straight year. The exhibit is NPC's celebration of visual storytelling, with the show's theme this year of “Life, liberty, and the pursuit of happiness.”

NPC's annual exhibit highlights special images produced by its members, displayed in the Club's main lobby in downtown Washington, D.C. for the entire month of September. Images in the exhibit are displayed digitally on four large monitors in continuous slideshows. Participants are asked to submit up to five of their best photos, not previously shown in the Club's annual show. The event is an exhibit, and not a contest. No judging, juries, or prizes are involved.

The exhibit gives Press Club members a chance to display their photography skills to professional colleagues, as well as employer and client prospects among the membership and the thousands who visit the Club for events. But you have to be an NPC member to take part. Here's more about membership.

The show draws participants from throughout the Club's journalist and communicator members. While there are still news photographers out there (myself included), many reporters are also asked to do their own photography. Plus, editors and publishers need to commission and recognize quality photography, and use visual media effectively to tell their stories.

Since it began in 1999, the Club's exhibit displayed outstanding photojournalism, but in recent years also shown street, art, landscape, and wildlife photography. Starting last year, the show introduced a theme to help focus contributions. This year, the theme is “Life, liberty, and the pursuit of happiness,” reflecting the nation's 250th anniversary of independence. But photos on any subject are accepted.

The exhibit has become one of the Press Club's most participative events, with 50 or more participants each of the past few years exhibiting some 200 photos each year. We first organized the exhibit in 2016, and since then added digital image displays to print photos shown earlier and online exhibit catalogs beginning in 2019. Links to the catalogs are on the TechNewsLit exhibits page.

Copyright © Technology News and Literature. All rights reserved.

Today’s the third day of the heat emergency in Boston. It’s supposed to hit 96 today with a dewpoint of 70 degrees, which equates to: miserably hot.

The city of Boston has 18 cooling centers open. Good for them. The city also has a partnership with five museums, so the Museum of Science, the ICA, the JFK Library and the Edward Kennedy Museum of Sexual Harassment—sorry, Edward Kennedy Institute for the US Senate (tomato tomahto) are all open for free so people can get cool.

All of this is good. But today is a holiday, so public libraries are closed. Which means vital, possibly lifesaving cooling is unavailable to a lot of people. Check out the City’s own map and look at the huge chunk of densely-populated Dorchester that doesn’t have an indoor cooling center open (City cooling centers are represented by snowflakes):

Also note that there are five libraries in the map area (they’re represented by the little “book with a roof over it” icon) with no other free indoor cooling facilities. The spray icons are for spray decks and splash pools, which are good, but maybe not great for an 80 year old or someone in an electric wheelchair.

The city could have opened libraries today. This would have involved paying overtime to a lot of library employees. So the city chose not to do it. Presumably there’s no room in the budget for it.

But remember, budgets don’t just grow organically—they are the result of choices made by the people who make the budgets.

I live near the construction of the new White Stadium, which desperately needed renovation, but make no mistake: the City of Boston is building a stadium instead of helping residents stay cool today.

At this construction site, there are usually two or three Boston Police officers making at least 75 dollars an hour to do nothing. They literally stand there for eight hours doing nothing. Actually sometimes they sit in their cars doing nothing. This is the Boston Police overtime budget at “work.” You’ll see similar scenes all over the city wherever construction or utility work is going on. The police overtime budget was level funded even as the school budget was cut this year because the people who make decisions in our city think that it’s more important to have cops standing idle outside of construction sites than teachers in classrooms. And that it’s more important to have cops standing idle than to open libraries during a heat wave.

But maybe churches are open today. Certainly the mayor could be calling on the city’s faith community to help serve the community at large. After all, they leech off city services without contributing anything to the city’s tax base. The least they could do is throw open their doors to help their neighbors stay cool. Maybe some are doing that—I checked the websites of some prominent churches and found nothing.

This isn’t our first potentially deadly heat wave and it won’t be our last. Hell, it probably won’t be the last one this summer. Our local and state governments have a responsibility to their citizens, and they are failing to meet it. They’re failing to recognize the seriousness of the climate emergency (Yes, the Commonwealth of Massachusetts still operates Hanscom Field, an airport for private jets, lest John Fish have to fly commercial) and they’re failing to prioritize the needs of broke, hot citizens over the needs of Weymouth-dwelling cops with boat payments.

Boston and Massachusetts are villainized nationally by fascists, who talk about our extreme left-wing government. I wish it were true, but I’d settle for even slightly left-wing at this point.

الجمعة 18 محرم 1448

تنبيه

أحدثكم اليوم حديث الكاتب الذي يفضي ببعض تجربته لينتفع بها القارئ والكاتب. وأخصكم بتأملاتي في تجربة ثمانية أشهر في صناعة المحتوى الثقافي مرئيًا ومسموعًا ومكتوبًا في منصة أنى. حديثٌ شخصي متبسط لا يمثل أنى -فحساباتها معروفة مشهورة- بل يمثل تجربة إنسانية فيها.

أنى تكون المقدمة

(أنى ومن أين آبك الطرب *** من حيث لا صبوة ولا ريب

البيت للكميت بن زيد، وهو مطلع إحدى هاشمياته، وأنى: بمعنى كيف. وآبك:

معناه أتاك، والشاهد: استعمال «أنى» بمعنى «كيف)

شرح الشواهد الشعرية في أمات الكتاب النحوية – محمد حسن شراب

لم تكن أنى في حسباني وتقديري سوى أداة استفهام قلّ أن ترد في كلام الناس اليوم، وإن وردت ثمانٍ وعشرين 28 مرة في القرآن كلام الله عزوجل كما أحصاها محمد فؤاد عبدالباقي رحمه الله في كتابه المعجم المفهرس لألفاظ القرآن الكريم.

غير أنني تعلمت معنى جديدًا (1) لأنى وأحب أن يزاد في معاجم اللغة وقواميسها. أنى (مساحة للحكمة والجمال). وعهدي بهذا المعنى الجليل يبتدئ في ليلة من ليالي ربيع الآخر من عام 1447 لما فاتحت أخي سالم باعارمة في شراكة ثقافية مع إحدى الشركات، فدعاني -مشكورًا- إلى شراكة في مشروعه (منصة أنى الثقافية)، وقد تم الأمر في جمادى الأولى من ذلك العام.

ثم حانت ليلة الخميس [17 محرم 1448] فانقضى الموسم الأول، وأسدل الستار على المنصة، وبقيت آثار أمسياتها شاهدة على فضلها وشرف موضوعاتها. ونأمل عودتها قريبًا بإذن الله.

وتكفينا 190 مادة [أو تزيد] مرئية ومسموعة ومكتوبة بثت ونشرت في ثمانية أشهر في أربع منصات للتواصل: يوتيوب، وإكس، وإنستجرام، وتيك توك.

وأفضي إليكم في هذه المقالة بثلاثة أسرارٍ للتحول الذي شهدته بنفسي في هذه الرحلة الممتدة.

1- تجديد التعلم:

تعرفت إلى سالم رئيسًا وزميلًا في نادي اقرأ وفكر، وشهدت مجالسه الفلسفية والفكرية، وأحسب أنه شهد مني براعة في الكتابة، وتلخيصًا حسنًا لمجالس النادي [يسمونها لقاءات وأحب أن أسميها مجالس].

وقد لخصت 21 مجلسًا، وأشرفت على تلخيص الزملاء الفضلاء.

كنت آتي إلى اللقاء، فأعمد إلى هاتفي وألتقط شذرات من حديث الملقي، ثم أنصرف إلى البيت فأحرر الملخص لينشر في اليوم التالي.

وكان التلخيص الفوري -كما لاحظت- يصرفني عن التفاعل في المجلس، ويحملني على بذل الجهد في استخراج الخيط الناظم، وإعادة الكتابة من جديد.

ثم قدمت إلى أنى ممتلئًا بهذه الخبرة الجليلة، وألقيت أعباءها عن كاهلي لما قيل لي: الأمسيات مسجلة محفوظة.

وأدركت بعد قليل أن المجلس المحفوظ كالمجلس المشهود، وكليهما محتاجٌ إلى العناية والاجتهاد!

لقد وجب علي أن أستمع مرات وكرات حتى أظفر بخلاصة تستحق أن تكتب. والكلام الطويل -لا سيما النافع الماتع- يشق على من يريد أن يستخلص العظات والعبر واللطائف المستملحة والفوائد المهمة.

لم تنحصر مهماتي في التلخيص. إذ انفسح مجال الكتابة، واتسع نطاق العمل، وصرت أرتحل محمّلًا بمادة الأمسية إلى عوالم جديدة من المحتوى لم أجربها من قبل.

استغرقت الأمسية الأولى أمسيات عديدة كي أنجزها، وكذلك في الثانية حتى تناقصت المدة وتضاءل الجهد. والحق أن سالمًا لم يكن يتلقى ما أقدمه إليه بعين إعجاب تغض الطرف عن دقائق الأمور بل بعين فاحصة ناقدة، فأفادني ذلك كثيرًا، وأحسب أنني انتفعت منه في التحسين والتجويد.

وامتد العمل في المحتوى إلى الإشراف على تحرير المقاطع المطولة، واستخراج الشائق منها، والكتابة عنها ووصفها بأساليب مختلفة ولأغراض شتى. فاكتسبت مهارةٌ لا تقدر بثمن، والحمد لله رب العالمين.

ولا ينبغي لي أن أنسى مرئيات أخي عبدالوهاب رئيس فريق الإنتاج، وملاحظات الأخت أمجاد قائدة فريق إدارة المحتوى، ومعها الأخت رهف المصممة البارعة. فقد استفدت من هؤلاء جميعًا وإنني أشكر الله عز وجل ثم أخي سالم على الاجتماع في مشروع ثقافي فريد.

ما أكثر ما تعلمته في أنى! وهذه أهم خلاصة أبذلها لكل من يحب أن يدير صناعة المحتوى الثقافي (إن تجديد التعلم باكتساب علمٍ ثانٍ لا يبطل العلم الأول، بل يزيده قوة إلى قوته، ويثبته في القلب، ويجمعه إلى نظائره المتفرقة، ويوسع مداركه في العقل).

2- قوة التكرار والإصغاء:

ما الذي أتذكره من لقاءات أنى؟

أتذكر الأستاذ طارق القرني وهو يحدثنا عن (الامتلاء بالمفاهيم والطريقة المثلى في الحوار)، وحديث الأستاذ رائد العيد عن (الحق في البداية الجديدة وجمال التأمل في الهوامش)، وملاحظة الأستاذ سليمان الناصر لـ(تعدد تعاريف الفلسفة وفلسفة الأخلاق التي كتب فيها الفلاسفة المحدثون)، واقتباس الدكتور عبدالرزاق بلعقروز عن (عراء العدمية التي نعيشها، والكلمة التي تصنع الإنسان)، ولمحة الأستاذة أمل عبدالعزيز عن (بارتلبي النساخ، ومطلع رواية الغريب)، وتساؤل الأستاذ هيثم السيد عن (السكر الذي لا يحيبه الصينيون والتيك توك المحظور في بلادهم!).

وهل أنسى مجلس الأستاذ أسامة الواصلي في (الواقعية التي أعقبت المثالية وشاعرية أفلاطون) ؟ وهل أغفل يومًا عن كلمة الدكتور علي النهابي في (أثر الأدب في واقعنا المعاصر والغرابة التي يحتكم إليها الأدب)؟ أيليق ألَّا أشيد بإلقاء الأستاذ سعد الشريف لقصائد البردوني وإعجابه بذلك (المثقف النافع)؟ أينسى التاريخ تحذير الدكتور سعد البازعي من (تعاقب الأزمات وخوارزميات الذكاء الاصطناعي التي تبتلعنا)؟ وهل يلتفت أهل الدين والأخلاق إلى اجتماعهما في مصنفات علماء الإسلام وإلى مجلس الدكتور حامد الإقبالي؟

إنني لا أكاد أمر بمقطعٍ مرئي أو مسموعٍ لأنى من غير أن أستحضر بدايته أو خاتمته، ومن غير أن أستمتع بما فيه من الإشارات اللطيفة والفوائد العجيبة. ولولا الإنصات لما تحقق شيء من ذلك.

لقد أنصت للمتحدثين لأخرج شيئًا من علومهم وتجاربهم إلى المتلقين، ورأيت في ذلك أمانة في عاتقي، ووسيلة إلى التعريف بهم، والتعريف إليهم.

نعم لست أنكر أنني لم أكن أحصل على الفائدة كلها من أول مرة، لكن الإصغاء مع التكرار أوصلني إلى الكنز المتواري في الحديث.

وإننا أشد حاجة في عصر شتات الذهن وتفرق القلب إلى إصغاء صادق، واستماع باهتمام عسى أن نجد حلاوة الحديث، ونظفر بخلاصاته المهمة.

أكان العمل يخلو من بعض الأخطاء والهنات؟ كلا. فقد استدرك ضيف أو ضيفان على خطأ بعض الكلام الذي نسب إليهما، ووجب تصحيحه ونقله على وجهه.

فإن كنت تحب أن تستخلص أنفس ما في الحديث وأجمل ما في الكلام فأنصت واستمع وكرر الاستماع لتكون ممن قال فيهم الشاعر: (أخلق بذي الصبر أن يحظى بحاجته *** ومدمن القرع للأبواب أن يلجا)؟

3- الشريك الإنسان!

أنى راية نصبها سالم واجتمعتُ تحتها مع أمين شحود وندى القحطاني وداود صالح وأبان قاضي وفريقي الإنتاج وإدارة المحتوى المذكورين. وأرجو أنني لم أنس أحدًا ساهم في رفع الراية والتمسك بها.

نعم لكل واحدٍ منا غايته من الراية، وهدفٌ يتحقق من المشروع، لكن الشراكة التي استشعرتها مع أفراد المشروع ليست شراكة احترافية أو مهنية بل شراكة إنسانية تهتم بالثقافة وصنع الأثر.

شراكة أستشعرها في تفاعل ضيوف أنى مع محتواها الإعلامي.

وأستشعرها أيضًا في اهتمام الأصدقاء والمعارف بما قدمناه فيها.

ومنه تعلم أن إنسانية الشريك تتقدم المنافع التي يقدمها، أو المصالح التي تعود إليه بالنفع.

أنى تكون الخاتمة

لست أرى خاتمًا أليق بهذه المقالة من الإشارة إلى حسابات أنى في مواقع التواصل الاجتماعي، والتفاعل معها عسى أن تعود قريبًا وأن يقال أنى يأتي الموسم الثاني؟

قناة أنى في يوتيوب:

https://www.youtube.com/@anna_cultural

أنى في إكس:

https://x.com/anna_cultural

أنى في إنستجرام:

https://www.instagram.com/anna_cultural

أنى في تيك توك:

https://www.tiktok.com/@anna_cultural

فأنى تكون العودة؟

وكتب البراء بن محمد

في أواخر عصر الجمعة الساعة الحادية عشرة وتسع دقائق قبل غروب الشمس لإحدى عشرة إن بقين من شهر الله المحرم لعام ثمانية وأربعين وأربع مئة وألف.

The octave belongs to nature. The guitar fretboard belongs to culture. The space between them is where the story of music unfolds.

I’ve walked into many a pub session in Ireland, cathedral choir rehearsals in England and Germany, and bluegrass and country-blues gatherings in Kentucky. And whilst I’ve never yet managed a conservatoire in Paris – I’m still waiting for the invitation – I can guarantee that they are all very different musical worlds.

Different instruments. Different customs. Different ideas about what makes a performance good. Different ways of learning. Different musical languages.

Yet beneath all that variety lies a curious fact. Whether the music comes from a sean-nós singer in Connemara, a Bach chorale in Leipzig, or a mandolin player on a Kentucky porch, everyone is listening with the same pair of ears.

And that simple observation has been the thread running quietly through my column on The Story of Music.

When I began the series, I thought I was writing about the theory behind music. Looking back over those ten articles, I realise I was really writing about something older and deeper: the conversation between nature and culture. The octave belongs to nature. The guitar fretboard belongs to culture. The space between them is where the story of music unfolds.

I began with something so ordinary that most of us never think about it: the octave. One note vibrating at exactly twice the frequency of another. Two sounds that are unmistakably different, yet somehow recognisably the same.

The octave appears in every musical culture not because musicians agreed to adopt it, but because it is written into the physics of sound itself. A vibrating string, a column of air, the human voice – all reveal the same relationship. Long before there were music schools, examination boards, manuscripts, orchestras, guitars or YouTube, there was the octave.

That discovery led humans to an even larger question. If the octave provides the frame, what happens inside it?

And here we encountered one of the great surprises in musical history. Nature gives us the boundary, but she does not provide the map. The space between one octave and the next contains no convenient grid, no easy markers. Human beings had to invent one.

Centuries of experimentation, much like you noodling on the fretboard or tinking at a piano. Singers found intervals that felt beautiful. Instrument makers found ways to reproduce them. Theorists searched for numerical relationships that explained them. Every culture developed solutions, and Western Europe developed several. Some favoured purity, others flexibility. Some worked beautifully in a handful of keys, while others made wider musical travel possible. Yet every solution carried the seed of a new problem.

The twelve-step chromatic scale emerged from that long negotiation. It was not inevitable. It was ingenious. By dividing the octave into twelve equal intervals, Western music acquired a shared framework. The wolf intervals that haunted earlier systems could be tamed. Musicians could move between keys without the entire structure collapsing. Instrument makers could build fretted and keyboard instruments capable of speaking a common language.

But it seems to me something curious happened. The new twelve-note framework did not erase the older musical world. Instead it settled over it like a transparent sheet laid upon an older map. The ancient seven note names survived. The old modal melodies survived. Even the strange symbols we call sharps and flats turned out to be fossils from an earlier age when names remained constant and pitches were nudged to suit circumstances.

Again and again we encountered the same pattern. New ideas rarely replaced old ones. They were layered upon them. The modes provided another example. Modern textbooks often present them as theoretical constructions, but history suggests the opposite. People were singing Dorian and Mixolydian long before anyone gave them Greek names. The patterns emerged first. The theory arrived later. Human beings discovered recurring ways of moving through sound and only afterwards developed the language to describe what they had already been doing.

Harmony followed a similar path. A vibrating string contains relationships within itself. The octave, the fifth and the third are already present as natural consequences of vibration. Musicians did not invent these relationships. They discovered them. When they began combining notes into chords they were, in a sense, making audible, possibilities already hiding within the sound.

Here the story became complicated. For all our talk of notes, scales and chords, nobody has yet produced a single explanation of why music moves us. The acoustician points to the harmonic series. The theorist points to the behaviour of chords within a key. The psychologist points to expectation, memory and emotion. All three are probably right, and all three deserve more attention than I could give them in a single article. Part Eight was less a conclusion than the opening of a door I expect to revisit more than once.

From there the journey became increasingly human. The seven degrees of the diatonic scale ceased to be mere positions and became behaviours. Some felt like home. Some invited movement. Some created brightness. Others carried shadow, tension or longing. What began as acoustics became psychology. We were no longer asking what sound is, but what it feels like to be a listener.

And finally we arrived at pitch itself. Modern musicians assume that A is 440 Hz because that is simply what A is. History suggests otherwise. For most of Western music’s existence there was no universal pitch standard. Notes wandered from city to city and generation to generation. Only through an extraordinary process of standardisation did we arrive at the world inhabited by modern guitars, pianos, orchestras and electronic tuners.

Even then, compromise remained. Equal temperament is a compromise. A440 is a compromise. The tuner in your pocket is enforcing a policy decision rather than revealing an eternal truth. Which brings us back to the question that has quietly accompanied every article in the series.

What exactly is music?

I wrote those first ten parts to suggest a simple answer. Music is neither arbitrary nor purely cultural.

It is not arbitrary because it emerges from physical realities that exist whether we recognise them or not: vibration, frequency, resonance, the octave, the harmonic relationships hidden inside sound itself.

Nor is it purely natural. The chromatic scale, note names, accidentals, modes, harmony, notation, pitch standards and instruments are all human attempts to organise, standardise and communicate those physical relationships. Every time I sweet-tune my guitar, I am participating in that long conversation between physics, culture and human judgement.

Nature provides the raw materials. Culture provides the architecture. The story of music is the story of the conversation between the two. The octave asked the question. The rest of music is our attempt to answer it.

Further Reading This essay reflects on the first ten articles in The Story of Music. Readers who would like to explore the journey can begin here:

Part 1: The Octave – Enigma https://go.dm.ie/the-octave Full Index: https://go.dm.ie/the-story-of-music