SQLite is a

Recommended Storage Format

for datasets ac­cord­ing to the

US Library of Congress. Further in­for­ma­tion:

As of this writ­ing (2018 – 05-29) the only other rec­om­mended stor­age for­mats for datasets are XML, JSON, and CSV.

Recommended stor­age for­mats are for­mats which, in the opin­ion of the preser­va­tion­ists at the Library of Congress, max­i­mizes the chance of sur­vival and con­tin­ued ac­ces­si­bil­ity of dig­i­tal con­tent. When se­lect­ing rec­om­mended stor­age for­mats, the fol­low­ing cri­te­ria are con­sid­ered (quoting from the LOC web­site):

Disclosure.

Degree to which com­plete spec­i­fi­ca­tions and tools for val­i­dat­ing tech­ni­cal in­tegrity ex­ist and are ac­ces­si­ble to those cre­at­ing and sus­tain­ing dig­i­tal con­tent. A spec­trum of dis­clo­sure lev­els can be ob­served for dig­i­tal for­mats. What is most sig­nif­i­cant is not ap­proval by a rec­og­nized stan­dards body, but the ex­is­tence of com­plete doc­u­men­ta­tion.

Adoption.

Degree to which the for­mat is al­ready used by the pri­mary cre­ators, dis­sem­i­na­tors, or users of in­for­ma­tion re­sources. This in­cludes use as a mas­ter for­mat, for de­liv­ery to end users, and as a means of in­ter­change be­tween sys­tems.

Transparency.

Degree to which the dig­i­tal rep­re­sen­ta­tion is open to di­rect analy­sis with ba­sic tools, such as hu­man read­abil­ity us­ing a text-only ed­i­tor.

Self-documentation.

Self-documenting dig­i­tal ob­jects con­tain ba­sic de­scrip­tive, tech­ni­cal, and other ad­min­is­tra­tive meta­data.

External Dependencies.

Degree to which a par­tic­u­lar for­mat de­pends on par­tic­u­lar hard­ware, op­er­at­ing sys­tem, or soft­ware for ren­der­ing or use and the pre­dicted com­plex­ity of deal­ing with those de­pen­den­cies in fu­ture tech­ni­cal en­vi­ron­ments.

Impact of Patents.

Degree to which the abil­ity of archival in­sti­tu­tions to sus­tain con­tent in a for­mat will be in­hib­ited by patents.

Technical Protection Mechanisms.

Implementation of mech­a­nisms such as en­cryp­tion that pre­vent the preser­va­tion of con­tent by a trusted repos­i­tory.

At the end of April, I ran a short cam­paign to find 15 more pay­ing mem­bers of Not-Ship. And we did it! Thank you to the won­der­ful souls who chose to back this work. It means the world to me.

💙 Amanda

Each year, 70,000 peo­ple gather on a dry lakebed in Nevada to build a city from scratch. This is Black Rock City, home to the in­fa­mous Burning Man event. Eight days later, it’s gone.

But 150 peo­ple re­main. They line up — side by side, an arms width apart — and slowly walk the 3,800 acres (15.4 km²) of dusty playa. They’re look­ing for MOOP: Matter Out of Place. A screw, a se­quin, a cig­a­rette butt.

This foren­sic-style sweep takes weeks; every­thing they find is re­moved and logged. At the end, they’re left with a re­mark­able ac­count­ing of what 70,000 peo­ple left be­hind: The MOOP Map. And I’m ob­sessed.

The Burning Man 2025 MOOP Map

Indicates ef­fort and time spent on MOOP cleanup across Black Rock City.

The map is colour-coded by sever­ity of cleanup. Yellow in­di­cates mod­er­ate MOOP con­di­tions, where crews slow their pace to make sure noth­ing is missed. Red are the zones most heav­ily af­fected — dif­fi­cult enough to stop progress en­tirely.

“In sim­ple terms, the MOOPier an area is, the more labour and field time it takes to clean un­til crews are no longer find­ing de­bris,” Dominic Tinio, who goes by DA, ex­plained to me. As Burning Man’s Environmental Restoration Manager, he’s in charge of the MOOP process.

The fu­ture of the com­mu­nity de­pends on get­ting this right. Black Rock City is only al­lowed to re­turn to the playa each year if it passes a strict post-event in­spec­tion from the Bureau of Land Management (BLM): No more than one square foot of de­bris can re­main per acre (0.23 m²/​ha).

Average yearly de­bris found by the MOOP, 2006 to 2025

The BLM tests the playa at 120 points across the site; no more than 12 can ex­ceed the one square foot per acre limit. In most years, Burning Man passes com­fort­ably — but not al­ways. In 2023, 11 of those 120 tests came back over the thresh­old, the clos­est the event has come to fail­ing in re­cent mem­ory.

During cleanup, the MOOP team also doc­u­ments what kind of de­bris they find. In 2025, lag bolts were by far the biggest prob­lem. They an­chor tents, art pieces, and other in­fra­struc­ture into the ground, and can eas­ily dis­ap­pear be­neath the dust.

Lots of lag bolts, not many cig­a­rette butts

Types of de­bris found dur­ing the 2025 MOOP.

Since the MOOP is so metic­u­lous, the team can de­ter­mine whether de­bris prob­lems are wide­spread or iso­lated. For lag bolts? There’s no main cul­prit; every­one is just miss­ing a few.

“The MOOP Map is about shared re­spon­si­bil­ity in our use of the land,” said DA. In ad­di­tion to help­ing up­hold the BLM stan­dards, it “helps par­tic­i­pants, camps, and art pro­jects un­der­stand their im­pact.”

Groups in MOOP-heavy ar­eas re­ceive a break­down of what was found on their foot­print, with the hope they will im­prove the fol­low­ing year. Persistent or se­ri­ous of­fend­ers are flagged to the team re­spon­si­ble for as­sign­ing camps their fu­ture spots in Black Rock City.

And while it’s not the MOOP Map’s aim, its re­lease in­evitably fu­els a bit of pub­lic fin­ger-point­ing. The “MOOP Map shame thread” on Reddit calls out in­di­vid­ual camps that per­form poorly.

The MOOP Map has been around for two decades. Over that time, the data show a rel­a­tively clear pic­ture. “Since 2006, over the long arc of the MOOP Map, the most strik­ing trend is that the com­mu­nity has steadily im­proved at Leave No Trace, even as Black Rock City has grown dra­mat­i­cally in size, com­plex­ity, and pop­u­la­tion,” says DA.

MOOP per per­son peaked in 2010

Debris per 10,000 peo­ple, 2006 to 2025.

Leave No Trace is one of Burning Man’s ten guid­ing prin­ci­ples. Principles are easy to de­clare. But the MOOP Map makes it some­thing the com­mu­nity ac­tu­ally has to face. After 20 years, DA is con­fi­dent it’s work­ing.

“The strongest ef­fect of the MOOP Map is that it dri­ves im­prove­ment. Year af­ter year, the com­mu­nity ad­justs, learns, and re­turns bet­ter pre­pared to leave no trace.”

KEEP ON KEEPING ON

While the Not-Ship mem­ber drive is over (for now), this work con­tin­ues to run on reader sup­port. But af­ter two weeks of writ­ing “pay if you love this work” emails, I’m tired. All my pitches have been pitched. So I’ll just leave the but­ton here, and trust you know what to do with it.

FROM ELSEWHERE

Here’s what I found in­ter­est­ing, im­por­tant or de­light­ful this week:

Marblelous mu­sic. Wintergatan is a quirky in­stru­ment that re­lies heav­ily on mar­bles to make mu­sic. It’s beau­ti­ful to watch, and does­n’t sound any­thing like you ex­pect.

The in­fi­nite buf­falo sen­tence. It’s a gram­mat­i­cally cor­rect sen­tence, us­ing just the word buf­falo. The video ex­pla­na­tion ben­e­fits from some use­ful vi­su­als, but you’ll still prob­a­bly hate this. Or ab­solutely love it. There’s def­i­nitely no mid­dle ground here.

MORE NOT-SHIP

Banks are fund­ing cli­mate chaos. You don’t have to.

Switching banks could be one of the most cli­mate-friendly de­ci­sions you make.

Not-ShipAmanda Shendruk

When do most peo­ple have the day off?

It’s not the day you think.

Not-ShipAmanda Shendruk

Birds might help us get through this

The men­tal health ben­e­fits of “joy watch­ing” are what we need right now.

Not-ShipAmanda Shendruk

Sorry Peter.

—

I’m at a birth­day party, and while most peo­ple here also work in tech, there’s al­ways a Guy with a Real Job. You know, a phys­i­cal job, build­ing some or other thing peo­ple need. And this Guy al­ways asks some vari­ant of the same ques­tion: aren’t you wor­ried AI is tak­ing your job? I glance around and see a few faces turn­ing around to­ward us, rolling their eyes ever so slightly be­fore re­turn­ing to their pre­vi­ous con­ver­sa­tion. Yes, this ques­tion again.

They have a nephew who builds Shopify stores, they don’t un­der­stand half the words he uses but he’s in real trou­ble and says every­body in tech is. Is his nephew gonna have to learn a “trade”? Are we all?

Enough drinks in and I’ll an­swer proper, be­cause I don’t care any­more whether oth­ers think what I’m say­ing is in­ter­est­ing or true. But usu­ally I’ll sigh and say “Sure, yeah a lit­tle. Most of us are. Would be stu­pid not to be, right?” to which they nod be­fore mov­ing on to a lighter topic, like whether we’re go­ing to nuke Iran or not.

The truth is, work­ing in tech al­ways sucked, and never re­ally was what they thought it was.

My job, some peo­ple think, is to sit at a clean desk in a cor­ner of­fice, sur­rounded by open of­fices filled with long ta­bles with MacBooks or Thinkpads. In my cor­ner of­fice, I de­vise per­fect plans, that my per­fect em­ploy­ees ap­plaud me for. None es­cape my gaze, every de­ci­sion is made, per­fectly, by me, and every cent and minute is ac­counted for.

When the ap­plause fades, my em­ploy­ees, or re­ports, or “my team” when I’m feel­ing jolly, start fu­ri­ously typ­ing. Typing typ­ing typ­ing. And not long af­ter, per­fect soft­ware is pro­duced. It rolls off the col­lec­tive as­sem­bly line, and like a first child, it can do no wrong.

Except, that’s not what any­thing is like at all. Yes, I’m up­set I never got a cor­ner of­fice, but I’m too busy pan­ick­ing be­cause I have no idea what I’m do­ing, no­body does, and the wheels just came off. The CEO says AI is mak­ing his buddy Jared’s team so pro­duc­tive he was able to fire half of them, but like, as a brag, not a threat? I dunno, I felt threat­ened, but that’s prob­a­bly just my anx­i­ety flar­ing up. Surely I can bor­row a xanax from one of the sev­eral em­ploy­ees cry­ing in the bath­room.

Imagine you take a job as a ship cap­tain. You bike into the har­bor on your first day, ex­cited to meet your crew. You no­tice the ship is­n’t there, but Greg, the very ex­citable re­cruiter you spoke to, waves you over and as­sures you it’s not a prob­lem. You’re strapped to a cat­a­pult and mirac­u­lously launched onto the ship. The pre­vi­ous cap­tain started a fire be­cause an­other cap­tain ex­plained in­ter­nal com­bus­tion to him at Captainpalooza 2025, and he wanted to start it­er­at­ing to­wards that. He was pushed off the ship, but took the man­ual with him. Wouldn’t be a prob­lem if it weren’t for the fact the en­tire ship was cus­tom-built for him. The ship still has sails, but they’re not con­nected to the mast, and the in­ter­nal com­bus­tion en­gine semi-bolted to the stern still has parts scat­tered all over the deck.

You go be­low deck to fig­ure out how the ship works and where you’re go­ing, but when you fol­low the stairs to the lower decks you some­how end up in the mast? You ask a sailor what’s hap­pen­ing. He glitches and says “You’re ab­solutely right! My ap­proach was flawed, but here’s a bet­ter stairs im­ple­men­ta­tion”. The mast snaps up­side down, and you’re back on deck, right where you started. The sails are up­side down, and your “sailor” ex­cit­edly waits for you to tell him how well he’s done.

You ask some­one else “wait, where are we even go­ing?”, and yay a hu­man! No glitch­ing, no peppy but un­help­ful an­swers, an ac­tual hu­man be­ing. She has­n’t slept in a week. She barely looks at you and says “ask the nav­i­ga­tor”. “The nav­i­ga­tor?”, you ask. She points. The nav­i­ga­tor is a doll that says “onward and up­ward” when you press a but­ton on its back.

The doll catches fire.

This is the job now. You’re stand­ing on a burn­ing ship, hold­ing a map, try­ing to fig­ure out where the hell we’re go­ing and how we’re go­ing to get there.

You know this ship. Some of you were en­gi­neers on one just like it. Some of you were the cap­tain who left. I’m not writ­ing this for the Guy at the birth­day party. I’m writ­ing it for you.

You were an en­gi­neer once. You re­mem­ber what a code re­view was for. You re­mem­ber be­ing the ju­nior whose first PR got shred­ded by a se­nior who took the time to ex­plain why. You did­n’t wake up one morn­ing in 2024 and de­cide to abol­ish that.

What hap­pened was: the run­way got cut. The board meet­ing did­n’t have the word “values” in it any­where. The CFO had a spread­sheet. The CEO had come back from an off­site where some­one had shown him a demo of an agent writ­ing a whole fea­ture in four­teen min­utes, and he had be­lieved it (the way peo­ple be­lieve things when they want to be­lieve them) and he had told the board he could cut thirty per­cent of en­gi­neer­ing by Q2. Now it was your job to fig­ure out how.

You told your­self the ju­niors would be fine. They’d adapt, they’d reskill, they’d land some­where. You told your­self the se­niors could ab­sorb the miss­ing hands, that the agents would cover the gap. You told your­self you’d re­visit it next quar­ter. You signed the list. You went home. You drank a lit­tle more than usual. You went to sleep.

You knew.

You knew, be­cause you’d been the en­gi­neer who had to clean up af­ter the last leader who’d been sold a sim­ple an­swer. You’d watched Goodhart’s Law eat ve­loc­ity met­rics, story points, test cov­er­age; every num­ber a non-en­gi­neer had ever been handed as proof the work was go­ing well. You knew the DORA met­rics were al­ready telling you what hap­pens to de­ploy­ment sta­bil­ity when you add tool­ing faster than you add judg­ment. You knew what hap­pens to a code­base when the peo­ple who’d catch the er­rors get pushed out, or learn to stop catch­ing them.

You knew. And you signed off any­way. Because the al­ter­na­tive was los­ing the job, and the job was the mort­gage, and the school fees, and the visa, and the ver­sion of your­self who’d fix it later once things sta­bi­lized.

Later is never. We all knew that. I signed a list too. We’re still point­ing at each other about whose list was worse.

There are no more ju­niors. There was a fu­neral for their pass­ing in 2024. Nobody came. The ma­chine does what they do now, but cheaper. Of course, ju­niors weren’t valu­able for what they pro­duced, they were valu­able for who they would be­come: the se­nior en­gi­neer who knows where the bod­ies are buried. We op­ti­mized for out­put, and abol­ished ap­pren­tice­ship. A few years from now, we’ll won­der where all the se­niors are. We shot them. Nobody will re­mem­ber.

And yet…

Somewhere in your in­fra­struc­ture is a cron job. It runs at 3am. It has been run­ning since 2016. It does some­thing crit­i­cal. You could­n’t tell me ex­actly what, but you know the one per­son who could, and they left in 2019. The com­ment at the top says # DO NOT CHANGE!!! Ask Ben. Ben is not reach­able. Every roadmap plan­ning ses­sion for the last four years has in­cluded “modernize legacy cron” as a can­di­date ini­tia­tive. It has never made the cut. You have per­son­ally re­moved it from the list twice.

Someone keeps it run­ning. Her name is Sara. You don’t know this.

She’s in her mid 50s. She did­n’t go to Captainpalooza. She used to work from a small of­fice three streets from head­quar­ters. Somebody closed it last year to save money. The ship was the clos­est place with a desk and a net­work con­nec­tion, so she packs a lunch now and takes the gang­way down to a cabin be­lowdecks. Nobody on the ship knows she’s there. Remember Ben? Well, she in­her­ited the cron job from Ben, who’s men­tored her since 1998.

She knows Ben passed a few years back. She went to his fu­neral. You don’t know this.

When the job gets stuck, which it does reg­u­larly, she gives it a nudge and it tries again. The phone rings. She ac­knowl­edges the is­sue. She gives the nudge. The job de­pends on a mod­ule that’s been lost to time. Well, al­most, be­cause she has a copy on a USB stick she found in Ben’s desk af­ter his pass­ing. No agent has touched it. None ever will.

She’s not the safest per­son in the in­dus­try. She’s the shape of what you can­not touch. She is every piece of in­sti­tu­tional knowl­edge your trans­for­ma­tion just deleted, walk­ing around in a fifty-five-year-old body. She came up through the ap­pren­tice­ship you abol­ished: Ben, 1998, the USB stick. She is the pipeline. When she dies, the thing that pro­duces peo­ple like her is al­ready gone. You killed it three years ago. You will not be able to hire her re­place­ment, be­cause you broke the ma­chine that makes her.

She’s the man tun­nel­ing un­der Mordor with a spoon. The spoon is hers. So is the tun­nel. Nobody else wants the spoon or the tun­nel, and when she dies, the cron job dies, salaries stop be­ing paid, a com­pany of 30,000 souls will need to fig­ure out how to pay every­body, and there will be only one an­swer: hire some­one with a spoon. You won’t find them. You made sure of that.

The cron job pays salaries. You don’t know this.

The Guy at the party is still wait­ing for an an­swer. I’m too drunk now to lie. I tell him: AI did­n’t take our jobs. Greed did. Same greed that moved fac­to­ries to Bangladesh and keeps slaves in cobalt mines in the Congo, wear­ing a new mask. Tell the nephew to do some­thing else. Anything. It won’t save him ei­ther, but at least he won’t have to pre­tend the thing de­stroy­ing his life is a ro­bot.

Except Sara. Below decks, with her USB stick. They can’t come for her be­cause they don’t know she’s there.

The rest of us are above deck, won­der­ing why the masts are up­side down, and what that doll over there does.

The doll catches fire.

Source: CNBC, Financial Times, BBC, Reuters

At this point it’s al­most rou­tine: Almost every time Donald Trump makes a ma­jor an­nounce­ment about the Iran War, that an­nounce­ment is pre­ceded — some­times by only a few min­utes — by huge and hugely prof­itable bets in the oil mar­ket.

The in­flu­en­tial Kobeissi Letter doc­u­ments the lat­est ex­am­ple:

BREAKING: According to our analy­sis, ~$920 mil­lion worth of crude oil shorts were taken 70 min­utes be­fore an Axios re­port claimed the US and Iran were near a “14-point” deal to end the war.At 3:40 AM ET to­day, nearly 10,000 con­tracts worth of crude oil shorts were taken with­out any ma­jor news.This is equiv­a­lent to ~$920 mil­lion in no­tional value, an un­usu­ally large trade for 3:40 AM ET.At 4:50 AM ET, just 70 min­utes later, Axios re­ported that the US is “close” to a “memorandum of un­der­stand­ing” to end the Iran War.By 7:00 AM ET, oil prices had fallen over -12% with these crude oil shorts gain­ing ap­prox­i­mately +$125 mil­lion.Min­utes later, Iran launched the “Persian Gulf Strait Authority” and oil prices surged +8%.What just hap­pened?

BREAKING: According to our analy­sis, ~$920 mil­lion worth of crude oil shorts were taken 70 min­utes be­fore an Axios re­port claimed the US and Iran were near a “14-point” deal to end the war.

At 3:40 AM ET to­day, nearly 10,000 con­tracts worth of crude oil shorts were taken with­out any ma­jor news.

This is equiv­a­lent to ~$920 mil­lion in no­tional value, an un­usu­ally large trade for 3:40 AM ET.

At 4:50 AM ET, just 70 min­utes later, Axios re­ported that the US is “close” to a “memorandum of un­der­stand­ing” to end the Iran War.

By 7:00 AM ET, oil prices had fallen over -12% with these crude oil shorts gain­ing ap­prox­i­mately +$125 mil­lion.

Minutes later, Iran launched the “Persian Gulf Strait Authority” and oil prices surged +8%.

What just hap­pened?

As the BBC among oth­ers has doc­u­mented, this is­n’t the first time, or the sec­ond time, that this has hap­pened. Again and again, just be­fore Trump makes an­nounce­ments that raise hopes about the re­open­ing of the Strait of Hormuz, one or more “whales,” very large traders, sell large quan­ti­ties of oil fu­tures, al­most in­stantly reap­ing big prof­its as prices fall.

What’s truly re­mark­able is that this keeps hap­pen­ing even though the pat­tern has be­come fa­mil­iar. This tells us two things: The Trump ad­min­is­tra­tion is mak­ing no real ef­fort to crack down on who­ever is trad­ing us­ing in­side in­for­ma­tion, and these in­side traders are op­er­at­ing with a com­plete sense of im­punity, as­sured that they can get away with it.

The stench of cor­rup­tion is over­whelm­ing. Yet aside from the raw cor­rup­tion, these in­ci­dents also raise a larger ques­tion. The in­sid­ers ripped off the par­ties who sold fu­tures to them at what turned out to be very un­fa­vor­able prices to the sell­ers. What broader dam­age does this kind of unchecked in­sider trad­ing do?

There’s both a nar­row and a broad an­swer.

The nar­row an­swer in­volves eco­nomic ef­fi­ciency. How is the func­tion­ing of the econ­omy af­fected by the re­al­iza­tion that some­body — it’s not hard to make guesses, but we don’t know for sure — is trad­ing oil fu­tures based on ad­vance knowl­edge about what will soon ap­pear on Truth Social or Fox News?

It took me a while to fig­ure this out. But I think I have an an­swer.

First, ask your­self what pur­pose is served by the oil fu­tures mar­ket. Unlike the pre­dic­tion mar­kets Polymarket and Kalshi, the oil fu­tures mar­ket is not in­tended to be mainly a ve­hi­cle for gam­bling. Instead, it is a mar­ket that serves to re­duce risk through hedg­ing.

Here’s how it works. There are peo­ple and in­sti­tu­tions, such as oil pro­duc­ers, who will need to sell oil at a fu­ture date. They want to lock in the price to­day on those fu­ture sales. There are also peo­ple and in­sti­tu­tions, such as air­lines, who have a fu­ture need for oil and would like to lock in the price to­day. Thus the fu­tures mar­ket lets both sell­ers and buy­ers of oil elim­i­nate a ma­jor source of risk — fluc­tu­a­tions in the price of oil. This re­duces un­cer­tainty in the econ­omy as a whole.

But what if there are sub­stan­tial play­ers in the fu­tures mar­ket with in­side in­for­ma­tion? Then if you are, say, a cor­po­ra­tion try­ing to lock in the price of oil you plan to buy next month, you may not be mak­ing a mu­tu­ally ben­e­fi­cial deal with fu­ture sell­ers. You may, in­stead, be be­ing played for a sucker — pay­ing what in ret­ro­spect will have been an ex­ces­sive price — by peo­ple who know what’s about to ap­pear in the pres­i­den­t’s so­cial me­dia feed.

The same could ap­ply to sell­ers of oil fu­tures, al­though the ex­am­ples of in­sider trad­ing we know about in­volved Trump in­sid­ers get­ting ahead of falling, not ris­ing, prices.

Either way, the ef­fect of traders’ sus­pi­cion that they may be losers in a rigged game will be to make them re­luc­tant to play at all — re­luc­tant ei­ther to buy or to sell oil fu­tures. And this will mean los­ing the risk-re­duc­ing ben­e­fits of a prop­erly func­tion­ing fu­tures mar­ket.

Now, in­sider trad­ing of oil fu­tures prob­a­bly is­n’t big enough to do crit­i­cal dam­age to those mar­kets. But it does do dam­age, which hurts all of us, not just the buy­ers who got stuck with the im­me­di­ate losses.

And be­yond the nar­row eco­nomic losses, in­sider trad­ing on oil is part of the broader rise of what we can call the pre­da­tion econ­omy.

Under Trump II, cor­rup­tion runs ram­pant. Success in busi­ness de­pends not on what you know but on who you know, and there are no rules be­yond hav­ing — and, ob­vi­ously, buy­ing — the right con­nec­tions.

This is bad for every­one who does­n’t have those con­nec­tions. It’s bad for eco­nomic growth. And it un­der­mines the moral ba­sis of the econ­omy and so­ci­ety as a whole. It’s the path of how a coun­try slides into third-world sta­tus.

I’ll have much more to say about the pre­da­tion econ­omy in fu­ture posts.

MUSICAL CODA

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NEWS

11 March 2026

Collaboration be­tween re­searchers and re­li­gious lead­ers led to a cut in the like­li­hood of early mar­riage by 80%.

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Mariana Lenharo0

Mariana Lenharo

Mariana Lenharo is a re­porter for Nature in New York City.

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Mariana Lenharo is a re­porter for Nature in New York City.

Mariana Lenharo is a re­porter for Nature in New York City.

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An ed­u­ca­tional pro­gramme for young girls in north­ern Nigeria that in­volved lo­cal re­li­gious lead­ers mas­sively re­duced the num­ber of child mar­riages, a study re­ported in Nature to­day has found1.

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doi: https://​doi.org/​10.1038/​d41586 – 026-00796 – 2

Read the as­so­ci­ated Policy Brief: ’Marriage of ado­les­cent girls in Nigeria re­duced by 80% by ‘big push’ in­ter­ven­tion’.

References

Cohen, I., Abubakar, M. & Perlman, D. Nature https://​doi.org/​10.1038/​s41586 – 026-10206 – 2 (2026).Article

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Cohen, I., Abubakar, M. & Perlman, D. Nature https://​doi.org/​10.1038/​s41586 – 026-10206 – 2 (2026).

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POLICY BRIEF

11 March 2026

A lo­cally tai­lored, big-push in­ter­ven­tion to ed­u­cate un­mar­ried ado­les­cent girls in 18 com­mu­ni­ties in north­ern Nigeria re­duced rates of mar­riage from 86% to just 21%. Interventions that ad­dress com­plex, en­trenched so­cial prob­lems from var­i­ous an­gles si­mul­ta­ne­ously might be con­sid­er­ably more ef­fec­tive than smaller-scale, cheaper al­ter­na­tives are.

By

Isabelle Cohen0,

Maryam Abubakar1 &

Daniel Perlman2

Isabelle Cohen

Isabelle Cohen is at the University of Washington, Seattle, Washington, USA.

Isabelle Cohen is at the University of Washington, Seattle, Washington, USA.

Isabelle Cohen is at the University of Washington, Seattle, Washington, USA.

Maryam Abubakar

Maryam Abubakar is at the Centre for Girls Education, Abuja, Nigeria.

Maryam Abubakar is at the Centre for Girls Education, Abuja, Nigeria.

Maryam Abubakar is at the Centre for Girls Education, Abuja, Nigeria.

Daniel Perlman

Daniel Perlman is at the University of California, Berkeley, Berkeley, California, USA.

Daniel Perlman is at the University of California, Berkeley, Berkeley, California, USA.

Daniel Perlman is at the University of California, Berkeley, Berkeley, California, USA.

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Source re­search: Cohen, I., Abubakar, M. & Perlman, D. A big-push com­mu­nity in­ter­ven­tion re­duced rates of child mar­riage by 80%. Nature https://​doi.org/​10.1038/​s41586 – 026-10206 – 2 (2026).

Messages for pol­icy

• Multipronged pro­grammes can have high up­front costs yet still have a net pos­i­tive ben­e­fit.

• With the right pro­gramme and im­ple­men­ta­tion, the age at which girls marry can be de­layed.

• Creating op­por­tu­ni­ties for girls to at­tend school in cases in which that runs counter to the be­hav­iour of most peo­ple in their com­mu­ni­ties might work only if cost and so­cial bar­ri­ers can be over­come.

• Educating girls has many ben­e­fits, not just for the girls them­selves, but also for their fam­i­lies and com­mu­ni­ties.

The pol­icy prob­lem

Globally, around 650 mil­lion girls and women alive to­day were first mar­ried be­fore 18 years of age1. A 2021 re­port2 es­ti­mated that nearly 80% of girls in north­ern Nigeria had mar­ried be­fore they turned 18. Early mar­riage — par­tic­u­larly when it is arranged by par­ents, guardians or other par­ties with­out the in­volve­ment of the girl — has neg­a­tive ef­fects on many as­pects of the fu­tures of ado­les­cent girls. It af­fects their agency, health and ed­u­ca­tion ad­versely, as well as their level of in­come, and in­creases their risk of ex­pe­ri­enc­ing vi­o­lence3. It has been es­ti­mat­ed4 that end­ing early-mar­riage prac­tices would re­duce the share of girls who have a child be­fore they are 18 by 75% and could also in­crease wom­en’s earn­ings and pro­duc­tiv­ity, pro­vid­ing large ben­e­fits to coun­tries’ economies. For in­stance, in 2015, an es­ti­mated US$7.6 bil­lion in ex­tra earn­ings could have been gen­er­ated in Nigeria4.

In many con­texts, girls marry at a young age be­cause fea­si­ble al­ter­na­tives are lack­ing; sys­temic con­straints can mean that mar­riage is the best choice avail­able to them5. The ex­ist­ing re­source con­straints, at­ti­tudes and norms that en­able child mar­riage are mul­ti­fac­eted and in­ter­twined, yet many in­ter­ven­tions that seek to ad­dress child mar­riage have a nar­row fo­cus. Multifaceted in­ter­ven­tions could take strate­gic ad­van­tage of var­i­ous pro­grammes’ com­ple­men­tary com­po­nents to suc­ceed where oth­ers have failed.

The find­ings

We found that the Pathways to Choice pro­gramme re­duced by 80% the like­li­hood that girls in north­ern Nigeria would be mar­ried two years af­ter re­ceiv­ing an in­ter­ven­tion that en­cour­aged them to at­tend school or other train­ing. Girls in the con­trol group, who did not have ac­cess to the pro­gramme, had a mar­riage rate of 86%; those in the in­ter­ven­tion group, a rate of 21% (Fig. 1). Our in­ter­ven­tion also in­creased the girls’ school at­ten­dance by 70 per­cent­age points, and im­proved their ac­cess to so­cial sup­port, as well as their self-per­cep­tion and abil­ity to ad­vo­cate for them­selves. Moreover, it in­creased the like­li­hood that a par­tic­i­pan­t’s younger sib­lings would be en­rolled at school, with an in­crease of 87% for sis­ters and 41% for broth­ers. We find that the pro­gramme has net re­turns of $1,627 per $1,000 in­vested, and our es­ti­mates of its life­time ad­van­tages for the par­tic­i­pants show that the in­ter­ven­tion has a ben­e­fit–cost ra­tio of 2.41.

Figure 1 | Effects of the mul­ti­pronged Pathways to Choice pro­gramme in north­ern Nigeria on rates of mar­riage among ado­les­cent girls. a, The rate of ado­les­cent girls re­main­ing un­mar­ried two years af­ter girls aged 12 – 17 years started the Pathways to Choice pro­gramme, an ed­u­ca­tion in­ter­ven­tion in north­ern Nigeria. Girls are pooled in com­mu­ni­ties that re­ceived the in­ter­ven­tion (Pathways) and those that did not (control). Data are the mean and stan­dard er­ror of the mean. The analy­sis in­cludes the 1,056 girls (537 in the con­trol group and 519 in the in­ter­ven­tion one) who an­swered ques­tions about their mar­i­tal sta­tus at the end of the study pe­riod. b, The es­ti­mated ef­fect of the Pathways to Choice pro­gramme (calculated from a re­gres­sion of the girls who re­mained un­mar­ried while par­tic­i­pat­ing in the pro­gramme) com­pared with other in­ter­ven­tions fo­cused on ado­les­cent girls that used ran­dom­iza­tion and pro­vided point es­ti­mates on mar­i­tal out­comes. The com­par­i­son uses re­sults from time points two to three years af­ter the in­ter­ven­tion. The num­ber of girls in­cluded in each study is in­di­cated. Data are from se­lected pre­vi­ous stud­ies; ref­er­ences are pro­vided in Fig. 4 of the main pa­per.

These re­sults cover only a short pe­riod; un­der­stand­ing the pro­gram­me’s full ef­fects will re­quire long-term data on par­tic­i­pants’ lives. Context mat­ters: we ex­pect that set­tings in which ed­u­ca­tion is a so­cially ac­cept­able al­ter­na­tive to early mar­riage and schools are not cur­rently meet­ing girls’ needs are more likely to ben­e­fit from our in­ter­ven­tion than are set­tings in which high-qual­ity ed­u­ca­tion is al­ready avail­able or in which ed­u­ca­tion is not viewed as a suit­able al­ter­na­tive.

The study

The Pathways to Choice pro­gramme is a mul­ti­pronged, com­mu­nity-fo­cused in­ter­ven­tion by Nigeria’s Centre for Girls Education in Abuja. It si­mul­ta­ne­ously tack­les sev­eral con­straints on girls’ ed­u­ca­tion over two years, through com­mu­nity en­gage­ment, re­me­dial ed­u­ca­tion and so­cial and in-kind sup­port, en­cour­ag­ing par­tic­i­pants to at­tend school or vo­ca­tional train­ing. To test its ef­fects, we per­formed a ran­dom­ized con­trolled trial be­tween 2018 and 2020 in 18 com­mu­ni­ties in north­ern Nigeria’s Kaduna, Kano and Borno states. We fo­cused on 1,181 un­mar­ried girls who were aged be­tween 12 and 17 years old and not at school at the start of the study. After a base­line sur­vey, the com­mu­ni­ties were di­vided into nine pairs, with one of each pair re­ceiv­ing our in­ter­ven­tion. Two years later, we con­ducted a fol­low-up sur­vey with the same par­tic­i­pants. Our re­sults com­pare the out­comes of girls in com­mu­ni­ties that re­ceived our in­ter­ven­tion with those in com­mu­ni­ties that did not.

doi: https://​doi.org/​10.1038/​d41586 – 026-00720 – 8

Acknowledgements We ac­knowl­edge the work of the Centre for Girls Education in Abuja; fund­ing from the Ford Foundation, the MacArthur Foundation and the Center for Studies in Demography and Ecology at the University of Washington; and OASIS (formerly L’Initiative OASIS in part­ner­ship with the University of California, Berkeley) for pro­vid­ing both fi­nan­cial sup­port and tech­ni­cal as­sis­tance in the im­ple­men­ta­tion and learn­ing process of the Pathways to Choice pro­gramme. The views pre­sented are our own and do not nec­es­sar­ily rep­re­sent the views of the University of Washington, the Centre for Girls Education or the University of California, Berkeley. All er­rors are our own.

References

UNICEF. The Child Marriage Data Portal https://​child­mar­riage­data.org/​coun­try-pro­files (2026). This web­site pro­vides cur­rent sta­tis­tics on the preva­lence of child mar­riage world­wide.

UNICEF. The Child Marriage Data Portal https://​child­mar­riage­data.org/​coun­try-pro­files (2026). This web­site pro­vides cur­rent sta­tis­tics on the preva­lence of child mar­riage world­wide.

Save the Children Nigeria. State of the Nigerian Girl Report: An Incisive Diagnosis of Child Marriage in Nigeria (Save the Children, 2021). This re­port pro­vides data on child mar­riage in Nigeria.

Save the Children Nigeria. State of the Nigerian Girl Report: An Incisive Diagnosis of Child Marriage in Nigeria (Save the Children, 2021). This re­port pro­vides data on child mar­riage in Nigeria.

Parsons, J. et al. Rev. Faith Int. Aff. 13, 12 – 22 (2015). This re­view sum­ma­rizes the re­sults of many causal and cor­re­la­tional stud­ies on the eco­nomic im­pacts of child mar­riage.Ar­ti­cle

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Parsons, J. et al. Rev. Faith Int. Aff. 13, 12 – 22 (2015). This re­view sum­ma­rizes the re­sults of many causal and cor­re­la­tional stud­ies on the eco­nomic im­pacts of child mar­riage.

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Wodon, Q. et al. Economic Impacts of Child Marriage: Global Synthesis Report (World Bank and International Center for Research on Women, 2017). This re­port syn­the­sizes global ev­i­dence for the neg­a­tive im­pacts of child mar­riage on: fer­til­ity and pop­u­la­tion growth; health, nu­tri­tion and vi­o­lence; ed­u­ca­tional at­tain­ment and learn­ing; labour-force par­tic­i­pa­tion and earn­ings; and par­tic­i­pa­tion, de­ci­sion-mak­ing and in-vest­ments.

Wodon, Q. et al. Economic Impacts of Child Marriage: Global Synthesis Report (World Bank and International Center for Research on Women, 2017). This re­port syn­the­sizes global ev­i­dence for the neg­a­tive im­pacts of child mar­riage on: fer­til­ity and pop­u­la­tion growth; health, nu­tri­tion and vi­o­lence; ed­u­ca­tional at­tain­ment and learn­ing; labour-force par­tic­i­pa­tion and earn­ings; and par­tic­i­pa­tion, de­ci­sion-mak­ing and in-vest­ments.

Schaffnit, S. B., Wamoyi, J., Urassa, M., Dardoumpa, M. & Lawson, D. W. Glob. Public Health 16, 1820 – 1833 (2021). This qual­i­ta­tive study sheds light on how ado­les­cent girls in Tanzania per­ceive the ben­e­fits and op­por­tu­ni­ties of mar­riage.Ar­ti­cle PubMed

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Schaffnit, S. B., Wamoyi, J., Urassa, M., Dardoumpa, M. & Lawson, D. W. Glob. Public Health 16, 1820 – 1833 (2021). This qual­i­ta­tive study sheds light on how ado­les­cent girls in Tanzania per­ceive the ben­e­fits and op­por­tu­ni­ties of mar­riage.

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Competing Interests

I.C. de­clares no com­pet­ing in­ter­ests. M.A. is an em­ployee of the Centre for Girls Education. D.P. has con­sulted for the Centre for Girls Education and served as its first di­rec­tor un­til 2016.

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Like a young child com­ing home from kinder­garten with their lat­est crayon scrawls, the in­ter­net is cur­rently awash with peo­ple shar­ing their AI-generated work. And just like the young child’s draw­ings, much of that work should be proudly put up on the walls within the artist’s house—and no fur­ther.

Prologue: I ❤️ AI 🔗

It’s just that I know when to keep my crayon-draw­ings to my­self ;) And I am get­ting in­creas­ingly sad and frus­trated see­ing com­mu­ni­ties that I value slowly wilt­ing un­der the on­slaught of shit. Often that shit is per­haps naïvely shared with no dele­te­ri­ous in­tent, but shit nonethe­less it is.

Congratulations, you en­tered a prompt and pressed re­turn. 🔗

“I rewrote Kafka in COBOL”

“I rewrote Kafka in COBOL”

Great, en­ter it at your next sci­ence fair. Meanwhile stop beg­ging for stars on your brand new GitHub repo that no-one’s touch­ing with a barge­pole.

“I wrote a blog post about Kafka”

“I wrote a blog post about Kafka”

Did you though? We can tell that Claude wrote it, and it’s a piece of garbage.

“I made this video about Kafka”

“I made this video about Kafka”

Cool story bro. Except AI made it, and it’s only of in­ter­est as a cu­rios­ity, not a use­ful learn­ing arte­fact.

“I’m self-pub­lish­ing an ebook that I wrote about Kafka”

“I’m self-pub­lish­ing an ebook that I wrote about Kafka”

What you mean is, you got Claude to scrape the in­ter­net and crap out a “book” that you should be ashamed to give away for free.

Any fool can feed coins into a fruit ma­chine and pull the arm.

Step 0: Profit 🔗

The pat­tern I see over and over seems to be:

Step 1: Discover agen­tic cod­ing. Mind blown.

Step 1: Discover agen­tic cod­ing. Mind blown.

Step 2: Chuck a pro­ject up onto GitHub (if it’s ac­tu­ally up </snark>).

Step 2: Chuck a pro­ject up onto GitHub (if it’s ac­tu­ally up </snark>).

Step 3: Have AI write a breath­less blog post about your vibe-coded pro­ject. Share blog post and repo to any sub­red­dit and Slack group that you can find. Not sure which is suit­able? Post to all of them—peo­ple will love to see it! /s

Step 3: Have AI write a breath­less blog post about your vibe-coded pro­ject. Share blog post and repo to any sub­red­dit and Slack group that you can find. Not sure which is suit­able? Post to all of them—peo­ple will love to see it! /s

Let me tell you now: pause af­ter step 2. Take a re­ally long breath. Think re­ally hard about what you’ve cre­ated, and why you want to share it. If it’s “because it’s cool” then I’ve got news for you: agen­tic cod­ing is no longer a nov­elty. It’s just how shit gets done now.

If you can think of the prompt, AI can write it. Big deal. That’s so early-2026. Move on.

Still want to share it far and wide? Is it ac­tu­ally use­ful? Are you us­ing it? Has it got re­ally good doc­u­men­ta­tion? Is it us­able? Have you ac­tu­ally come back to the code again and again and put it through its paces? Or was it a one-night stand with Claude and the next morn­ing nei­ther of you thinks it was such a good idea?

Still want to share it? If it’s soft­ware, are you pre­pared to stand be­hind it as some­thing peo­ple will raise is­sues against, maybe sub­mit PRs for? If it’s writ­ten, is it some­thing you’d want to read? Is it ac­tu­ally adding to the cu­mu­la­tive un­der­stand­ing of the com­mu­nity, or is it just an LLM auto-com­plet­ing its way through text that you can’t be ar­sed to write and I can’t be ar­sed to read?

Who cares? 🔗

No one forces me to read this stuff. Why am I so both­ered by it?

Because like bindweed, it’s slowly stran­gling the or­ganic life out of com­mu­ni­ties. When I open up Reddit now, it’s in­creas­ingly over­run with vibe-coded AI stuff. Whilst much of it is well-in­ten­tioned I’m sure, it does noth­ing to con­tribute to the com­mu­nity.

AI slop is dri­ving up the noise, and mak­ing the sig­nal more and more dif­fi­cult to dis­cern in com­mu­ni­ties. This risks be­com­ing a down­ward spi­ral; as com­mu­ni­ties be­come more pol­luted by this stuff, mem­bers will get frus­trated from wad­ing through AI slop and draw back, thus di­min­ish­ing the life of the or­ganic com­mu­nity even fur­ther.

Carrying on like this, on­line com­mu­ni­ties will ei­ther wither and die, or con­verge on some­thing like the dystopian-but-ba­nal MoltBook in which AI agents “talk” to each other with no hu­mans pre­sent.

There’s good ‘slop’ and bad slop 🔗

You may have no­ticed that AI Slop has be­come the mot du jour.

The broad use of the term that I’m gen­er­ally fa­mil­iar with is as a neg­a­tive de­scrip­tion for low-ef­fort ma­te­r­ial cre­ated by AI and foisted upon those to whom it is of no ben­e­fit. However I learnt re­cently that there are those—prob­a­bly cor­re­lat­ing strongly with the AI-hating crowd—who brand any­thing writ­ten about AI as “AI Slop”, even if not writ­ten by AI.

Material cre­ated with the as­sis­tance of AI is not bad in it­self. It’s the pur­pose to which it’s put.

A good use of AI is when it en­ables peo­ple to do some­thing they could­n’t do be­fore, to con­tribute to a com­mu­nity when they could­n’t be­fore. Done with the care and good in­tent of a hu­man be­hind it, this is a nett pos­i­tive.

Bad AI slop, on the other hand, is mon­keys throw­ing crap over the fence for a pur­pose other than fur­ther­ing the com­mu­nity. This in­cludes spam, en­gage­ment farm­ing, and sim­ply thought­less noise in a space which is not for that pur­pose.

OK, but who made you gate­keeper of the in­ter­net? 🔗

The stan­dards of com­mon de­cency and taste, that’s who.

Let’s take a step back. Sharing con­tent on­line is won­der­ful. It’s pretty much what made the in­ter­net what it is to­day.

The knack is to un­der­stand what you’re shar­ing, to whom, and why.

If you were born be­fore around 1980 you’ll know that there was the Geocities era. Every high-school nerd had a home­page (mine was in Vienna since you’re ask­ing).

Just be­cause I built a home­page on Geocities, com­plete with ‘Under Construction’ anigifs, a web counter and a web ring ban­ner, does not mean that I should be shar­ing it to any­one who’ll lis­ten. Amongst my friends, sure. My par­ents, of course—they’ll be proud of any­thing I build. But to the gen­eral in­ter­net? Who cares.

And now with AI-generated con­tent, whether a vibe-coded app or a blog post, the same ap­plies. The in­ter­net went through a col­lec­tive con­vul­sion in early 2026 as every­one dis­cov­ered the power of Claude Opus 4.5 (and don’t get me wrong, it is damn cool). And what does any­one do when they dis­cover any­thing neat? They want to share it with their friends!

Combine that with the deaf­en­ing AI-hype ma­chine of grifters al­ready in over­drive—and sud­denly sub­red­dits and Slacks are over­run with AI-generated ma­te­r­ial.

Built with AI, not by AI 🔗

This ex­cel­lent sec­tion head­ing is taken from my friend and col­league Gunnar Morling’s re­cent ar­ti­cle. As I out­lined above, AI is a pow­er­ful tool, and I will ar­gue with any­one for the case that it’s pretty much a dere­lic­tion of one’s job to not be in­clud­ing it in one’s tool­box. Gunnar nails the nu­ance though:

Build with AI.

AI is just a tool.

You need to do the think­ing, the in­struct­ing, the check­ing.

Gunnar has built a fan­tas­tic new pro­ject (Hardwood; a new parser for Apache Parquet), us­ing AI. Does that mean it falls foul of my wrath and judge­ment? No, of course not. It’s a pro­ject that’s taken four months so far, with a solid roadmap, a bur­geon­ing com­mu­nity, and a thought­ful and care­ful de­sign be­hind it.

Contribution 🔗

Does your of­fer­ing con­tribute any­thing to the com­mu­nity?

If you boil it down to its es­sen­tials, is what you’re shar­ing any­thing other than the man­i­fes­ta­tion of a prompt fed into an agen­tic cod­ing tool? If I took your prompt and ran it, would I end up with some­thing sim­i­lar? Prompt en­gi­neer­ing is fun and an in­ter­est­ing study, but it’s tan­gen­tial to the sub­ject it­self. Consider a com­mu­nity of or­nate fur­ni­ture en­thu­si­asts (I’m sure such a thing ex­ists); it’s the equiv­a­lent of bom­bard­ing them with Ikea-esque pieces sim­ply be­cause you’ve got a re­ally in­ter­est­ing set of chis­els that you want to show off.

Just like I’m not post­ing my kid’s draw­ings off to the National Gallery just yet, I’m also not shar­ing every cool app that I can build with Claude. Not that “software is art” (though some of the best ac­tu­ally is), but there’s noth­ing much in­ter­est­ing in the puerile out­put of a process. Anyone with a few to­kens can prompt their way to a bit of soft­ware. Throwaway tools are just fine. They’re great, in fact—the in­ter­net is built on weird lit­tle scripts that peo­ple have built and shared. But chuck them on gist/​GitHub—they don’t need a launch blog post as if you’re the in­car­na­tion of Steve Jobs.

This is a tale as old as time. Well, the in­ter­net any­way, once it got be­yond ARPANET and BBSes.

Whether Usenet, Reddit, lob­ste.rs, or any other on­line plat­form, the ne­ti­quette is al­ways to “lurk”. Hang around, read what gets writ­ten, get a feel for “the vibe”.

I’m not the ar­biter of what’s ac­cept­able in a given com­mu­nity. The com­mu­nity mem­bers are. Vibed an amaz­ing new im­ple­men­ta­tion of the Kafka pro­to­col, but not sure if peo­ple want to see it? Read the room, and get a feel for whether they’ll wel­come with open arms your AI slop—or not. If in doubt, ask!

As well as lurk­ing, an­other way of show­ing re­spect to the com­mu­nity is to be very open and clear about if, how, and where you’re us­ing AI in your con­tri­bu­tion.

The Asymmetry of Bullshit 🔗

What’s the im­pact on oth­ers of your con­tri­bu­tion?

The amount of en­ergy needed to re­fute bull­shit is an or­der of mag­ni­tude big­ger than that needed to pro­duce it.

The amount of en­ergy needed to re­fute bull­shit is an or­der of mag­ni­tude big­ger than that needed to pro­duce it.

If you splurge out a gob­blede­gook ar­ti­cle, you’re putting that work­load onto your reader to re­alise that it’s not worth wad­ing through. If you dump a com­plex PR into a pro­ject with­out due care, you’re oblig­at­ing the re­view­ers to go through the code and for them to ex­plain to you why it can’t be merged. In both of these sce­nar­ios the com­mu­nity would be bet­ter off with­out your con­tri­bu­tion.

Pre-AI, the ef­fort re­quired for con­tri­bu­tions was suf­fi­cient proof of work to ei­ther de­ter peo­ple or demon­strate an ac­tual com­mit­ment. Communities could deal with sub-par con­tri­bu­tions. Those well-in­ten­tioned and will­ing to learn could be men­tored and of­ten would de­velop into im­por­tant mem­bers of the com­mu­nity. Those less well-in­ten­tioned and not do­ing much more than spam­ming could be dealt with be­cause the vol­ume was so low.

With great power… 🔗

or per­haps that should be “With a great num­ber of to­kens”

Communities are pow­er­ful yet frag­ile things. Don’t be the bindweed that suf­fo­cates the life out of them.

Explore with great joy the power that LLMs and agen­tic cod­ing tools bring. Enjoy the fris­son of jfc that is cool that it in­vari­ably brings.

But re­spect the com­mu­nity, and only share what is truly rel­e­vant. Save the crayon pic­tures for your kitchen fridge.

Bindweed photo by Joshua Ralph on Unsplash.

Bindweed photo by Joshua Ralph on Unsplash.

All other pic­tures by my kids. Which is ironic, given my ex­hort­ing for peo­ple to lit­er­ally keep their child­ish draw­ings to them­selves ;)

All other pic­tures by my kids. Which is ironic, given my ex­hort­ing for peo­ple to lit­er­ally keep their child­ish draw­ings to them­selves ;)

Yeah yeah, I know, data-point of 1.

I re­cently read Susam’s blog post where they said that “most of the traf­fic to my per­sonal web­site still comes from web feeds” - I won­dered if that was true for my site.

I’ve been writ­ing this blog for a while. I’ve never much both­ered with “aggressive” SEO - I have a fairly se­man­tic lay­out, all my re­views have meta­data, and stuff like that - but I’m not cram­ming in key­words, us­ing AMP, or what­ever other chick­ens Google re­quires to be sac­ri­ficed for a higher rank­ing. Nevertheless, I do OK.

Last year, I added a bit of lo­cal-only, light­weight sta­tis­tics-gath­er­ing to my blog. I can see which sites peo­ple click on to reach mine. Google is right up the top, DuckDuckGo is sur­pris­ingly high, Bing is lucky to crack the top 20 on any day. Similarly, I can see how much traf­fic I get from the Fediverse and BlueSky (Twitter has all but van­ished).

A few weeks ago I added RSS and Newsletter track­ing. These data are very lossy. If some­one is sub­scribed to my RSS feed and opens a post and their client down­loads a lazy-loaded im­age at the end of the post, I get a hit. For email it’s broadly the same. If an email is opened and the tracker im­age is loaded, I get a hit (although Gmail does ob­fus­cate that some­what).

I’m not look­ing for su­per-ac­cu­rate num­bers (although I do block as many AI crawlers and bots as pos­si­ble). I’m not creep­ily fol­low­ing peo­ple around the web nor am I try­ing to sell them any­thing. I just want a rough idea of where peo­ple find me.

Here are my blog’s views for the last 28 days.

Some months I get a surge of hits from link ag­gre­ga­tors like HN or Reddit. Sometimes I’m linked to from a pop­u­lar site or cited in aca­d­e­mic work. But most of the time I bum­ble along get­ting hits from here, there, and every­where. Nevertheless, it’s lovely to see so many peo­ple choos­ing to sub­scribe (for free!) and as­ton­ish­ing that they pro­vide more traf­fic than a ma­jor search en­gine.

Obviously, these are two very dif­fer­ent types of traf­fic. People who are search­ing for a spe­cific thing and stum­ble upon my blog are dif­fer­ent from those who de­cide to like and sub­scribe.

But, yeah, about 25% of my traf­fic comes from peo­ple who have cho­sen to sub­scribe.

I’m just de­lighted that so many peo­ple read my ran­dom thoughts.

Introduction

Contemporary per­ma­cul­ture is founded on three core ethics: Earth Care, People Care, and Fair Share. These ethics serve as a guid­ing com­pass for its de­sign prin­ci­ples, co-cre­at­ing a holis­tic frame­work for re­gen­er­a­tive liv­ing. Similarly, per­ma­com­put­ing is built upon 10 prin­ci­ples that en­cour­age and raise aware­ness about more sus­tain­able dig­i­tal prac­tices.

Whether you are a tech spe­cial­ist, some­one who uses a com­puter for daily tasks, or deals with tech­nol­ogy only oc­ca­sion, there are steps that you or the group you are in­volved in can take to re­duce the en­vi­ron­men­tal and so­cio-eco­nomic im­pact of your dig­i­tal ac­tiv­i­ties. The fol­low­ing sec­tion ex­plores the per­ma­com­put­ing prin­ci­ples, show­ing how and where to start.

Each prin­ci­ple is il­lus­trated through:

Issue/background

What can YOU do? Strategies and in­ter­ven­tions for all, from techie to ca­sual user, or some­thing in be­tween

Principle in ac­tion & ex­am­ples Further read­ing, tools for deeper en­gage­ment, and ex­am­ples of im­ple­men­ta­tion

The com­mu­nity of per­ma­com­put­ing pro­motes a com­pre­hen­sive ap­proach to the de­sign of hu­man tech­nol­ogy, tak­ing into ac­count so­cial and eco­log­i­cal is­sues, en­cour­ag­ing re­silience and sup­port­ing a fair co­ex­is­tence. These de­sign prin­ci­ples are meant to not to be just tech­ni­cal guide­lines but rather rep­re­sent strate­gies for pos­i­tive changes.

That said, per­ma­com­put­ing is not pre­scrip­tive; it in­stead fa­vors sit­u­at­ed­ness and an aware­ness of con­tex­tual di­ver­sity. We, the Permacomputing work­ing group, hope these de­sign prin­ci­ples can serve both as a guide for prac­tice in spe­cific sit­u­a­tions and as a tool for iden­ti­fy­ing sys­temic is­sues in the re­la­tion­ship be­tween com­puter tech­nol­ogy and ecol­ogy.

Furthermore, the Permacomputing com­mu­nity is more than this site! It is in­spired by—and builds upon—a di­verse range of ini­tia­tives, re­search, pro­jects, and bod­ies of knowl­edge. And just like we learn and ex­pand con­cepts of per­ma­com­put­ing fur­ther, these prin­ci­ples will also con­tin­u­ally be de­vel­oped and re­fined. The text be­low is meant to serve as a start­ing point. :)

Hope for the Best, Prepare for the Worst

It is good prac­tice to de­sign sys­tems that are re­silient and tol­er­ant to in­ter­rup­tions and even if you do not per­son­ally be­lieve such sce­nar­ios are im­mi­nent. This prin­ci­ple in­vites re­flec­tion: why pri­or­i­tize re­silience? Rather than be­ing a de­featist mind­set, it is a prac­ti­cal ex­er­cise.

By imag­in­ing a world shaped by lim­its, con­straints and plan­e­tary bound­aries, you sharpen your cre­ativ­ity and adapt­abil­ity. Acknowledging break­ages hap­pen and tak­ing into ac­count the pos­si­bil­ity of col­lapse can in­spire self-im­posed lim­i­ta­tions that lead to re­source­ful so­lu­tions—of­ten un­cov­er­ing so­ci­etal sce­nar­ios pre­vi­ously un­ex­plored, while also ac­knowl­edg­ing that less priv­i­leged groups are al­ready ex­pe­ri­enc­ing harm and dam­age.

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Care for All Hardware — Especially the Chips

Caring for the planet also means car­ing for the ma­te­r­ial foun­da­tions of dig­i­tal tech­nol­ogy: our hard­ware. Every de­vice, chip, and com­po­nent orig­i­nates from Earth’s fi­nite re­sources—and even­tu­ally end up as e-waste.

The pro­duc­tion of new hard­ware, es­pe­cially mi­crochips, which are at the heart of nearly every de­vice we use, is highly re­source-in­ten­sive and en­ergy-con­sum­ing. Microchips are par­tic­u­larly prob­lem­atic be­cause they are dif­fi­cult to re­cy­cle, cost an im­mense amount of en­ergy and re­sources to man­u­fac­ture and their pro­duc­tion is highly pol­lut­ing. Maximizing the lifes­pan of hard­ware com­po­nents is crit­i­cal for re­duc­ing en­vi­ron­men­tal im­pact and pro­mot­ing a more sus­tain­able and less harm­ful dig­i­tal cul­ture.

One of the core prin­ci­ples of per­ma­cul­ture is to “produce no waste,” en­cour­ag­ing us to value and reuse all re­sources at hand, turn­ing waste into a re­source when­ever pos­si­ble.

Digital tech­nol­ogy can­not be pro­duced with­out waste. To mit­i­gate this sit­u­a­tion, this prin­ci­ple calls us to step out­side the cap­i­tal­ist model of per­pet­ual con­sump­tion and growth. Instead, it in­vites us to rec­og­nize the in­her­ent value of the de­vices, com­po­nents, and ma­te­ri­als we al­ready have—and to care for them in­ten­tion­ally. Caring for the planet also means car­ing for the ma­te­r­ial foun­da­tions of dig­i­tal tech­nol­ogy: our hard­ware. Every chip and com­po­nent is made from Earth’s fi­nite re­sources, and once dis­carded, be­comes part of the grow­ing e-waste cri­sis. By ac­knowl­edg­ing that these de­vices are not self-sus­tain­ing, we un­der­score the im­por­tance of ex­tend­ing their lifes­pan through in­ten­tional main­te­nance and thought­ful use.

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Observe First

Before tak­ing ac­tion, it’s im­por­tant to first ob­serve. What are the cur­rent re­la­tions? What is valu­able and beau­ti­ful? What is needed? What prob­lem are you try­ing to solve? Is it a so­cial is­sue? Does it even re­quire tech­nol­ogy? If not, re­fer to Principle “Not Doing”. If tech­nol­ogy is nec­es­sary, what is its pur­pose, and who will ben­e­fit?

In per­ma­cul­ture, be­fore work­ing on a piece of land, it’s es­sen­tial to ob­serve it over time, ide­ally through at least one full sea­sonal cy­cle. This process helps re­veal in­sights about what can be done with min­i­mal in­ter­ven­tion, us­ing lim­ited re­sources and en­ergy. Similarly, per­ma­com­put­ing in­volves care­fully ob­serv­ing a prob­lem or sit­u­a­tion to cre­ate space for eval­u­at­ing what needs to be done and how.

Observing can also re­late to sens­ing the world, where com­put­ing can play a key role in strength­en­ing ecosys­tems through cit­i­zen sens­ing and sci­ence pro­jects. Careful ob­ser­va­tion—gath­er­ing data on air qual­ity, wa­ter, bio­di­ver­sity, lo­cal tem­per­a­tures, and more—can help cit­i­zens col­lect the ev­i­dence needed to ad­vo­cate for a health­ier en­vi­ron­ment. These pro­jects gather data on pol­lu­tion, bio­di­ver­sity, weather, and more, which can then be used to push for a health­ier en­vi­ron­ment for both hu­mans and non-hu­mans.

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Not Doing

To re­duce the re­source use and waste gen­er­ated by tech­nol­ogy, em­brac­ing ‘not do­ing’ aka ‘refusal’ is es­sen­tial for achiev­ing de­growth. Given com­put­ing’s po­ten­tial for vi­o­lence and op­pres­sion, re­sis­tance and col­lec­tive ac­tion must go be­yond ab­stract ideals of jus­tice. They should cre­ate op­por­tu­ni­ties to ques­tion the foun­da­tions of tech­ni­cal pro­jects and ac­tively reimag­ine more just fu­tures. By re­fus­ing the idea of tech­no­log­i­cal in­evitabil­ity, we en­able forms of re­sis­tance to emerge and al­ter­na­tive fu­tures to be con­sid­ered.

The his­tory of com­put­ing is deeply in­ter­twined with cap­i­tal­ism and mil­i­tarism. From play­ing a role in war­fare and geopo­lit­i­cal power strug­gles to dri­ving the au­toma­tion of la­bor, com­put­ing has sig­nif­i­cantly con­tributed to the in­creased use of re­sources and fos­sil en­ergy. The lat­est ex­am­ple of this trend is the con­struc­tion of hy­per­scale data cen­ters for run­ning gen­er­a­tive AI. Despite the promise of in­creased ef­fi­ciency, the Jevons Paradox ap­plies: higher ef­fi­ciency tends to lead to greater re­source use. Efficiency is of­ten pre­sented as a tech­ni­cal so­lu­tion to a po­lit­i­cal de­ci­sions about how and why we use com­put­ing —without ques­tion­ing the ex­trac­tive busi­ness model.

Curbing de­mand through re­fusal has proven to be one of the most ef­fec­tive ways to re­duce com­put­ing’s harm to peo­ple and the planet, and that’s where the value of ‘not do­ing’ comes in. By ob­serv­ing and ques­tion­ing what is truly needed, we bring at­ten­tion to the broader is­sues: What is nec­es­sary? Who ben­e­fits? Who is harmed? And what are the im­pacts on the hu­man and more-than-hu­man en­vi­ron­ment?

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Expose The Seams

Seamlessness in soft­ware ob­fus­cates in­ner-work­ings and is a myth: things are only seam­less to those who fit an ide­al­ized stan­dard. To com­pli­cate things, soft­ware ven­dors of­ten use the term “transparency” when in fact still de­sign­ing in­ter­faces in which un­der­ly­ing processes re­main hid­den to the user. However, mak­ing a tech­nol­ogy ap­pear trans­par­ent or seam­less to users, can be­come an ob­sta­cle to un­der­stand­ing how it works, to crit­i­cal en­gage­ment, and to knowl­edge and skill shar­ing. Obfuscating in­ner work­ings could also be in­ten­tional - it makes it harder to ques­tion and chal­lenge a tech­nol­ogy and, by ex­ten­sion, sys­tem­atic op­pres­sions.

Exposing some of the in­ner work­ings of in­fra­struc­ture is also es­sen­tial to mak­ing it tan­gi­ble and to help un­der­stand mean­ing, mo­ti­va­tion and ma­te­ri­al­ity: Why has it been im­ple­mented this way? How much en­ergy does it use? What processes are hap­pen­ing in the back­ground? Showing the seams is im­por­tant for de­ci­sion mak­ing about com­pu­ta­tional processes: are they re­ally needed? How of­ten and how much re­sources should they be al­lowed to con­sume? Who needs ac­cess? Who can re­pair, stop or restart it?

Not every­thing needs ex­pos­ing, how­ever. Although this prin­ci­ple does­n’t con­cern per­sonal in­for­ma­tion, it can be con­fused with the call for full trans­parency which is con­sid­er­ably dan­ger­ous to some and un­de­sir­able for most (forced and full trans­parency can be dan­ger­ous to hac­tivists and ac­tivists alike) .

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Consider Carefully The Interaction Between Simplicity, Complexity and Scale

Some sim­ple sys­tems need less en­ergy, less hard­ware, and less main­te­nance. They are eas­ier to un­der­stand, adapt, and share. By keep­ing things sim­ple, we cre­ate space for care, ac­ces­si­bil­ity, and long-term sus­tain­abil­ity. At the same time, es­pe­cially in re­la­tion to pro­gram­ming lan­guages and hard­ware de­sign, what is per­ceived as sim­ple can be en­ergy in­ef­fi­cient and ar­cane. Similarly, from scal­ing up dat­a­cen­ters to scal­ing up the re­silience of off-the-in­ter­net wire­less net­works and pro­to­cols, scale is also an am­biva­lent no­tion in telecom­mu­ni­ca­tion, net­work in­fra­struc­ture and topolo­gies.

There is no magic bul­let.

We ac­knowl­edge that some prob­lems are in­her­ently com­plex and achiev­ing sim­plic­ity can be the re­sult of a dif­fi­cult and ar­du­ous process. Sometimes sim­plic­ity is sim­ply not pos­si­ble. However, this phase of ques­tion­ing is rarely prop­erly ad­dressed. The idea of un­crit­i­cally “enjoying a good chal­lenge”, com­bined with over-en­gi­neer­ing and scal­ing up for the sake of scal­ing up, pre­vents as­sess­ing if keep­ing it sim­ple will suf­fice. Sometimes, a par­tial, semi- or non-au­to­mated, su­per­vised, or oth­er­wise “incomplete” so­lu­tion is the most ap­pro­pri­ate choice for every­one in­volved.

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Keep It Flexible

Flexibility means adapt­abil­ity to dif­fer­ent pur­poses and cir­cum­stances, in­clud­ing ones that were never even con­sid­ered by the orig­i­nal de­signer. While we value sim­plic­ity, we know that very sim­ple sys­tems can also be in­flex­i­ble, and this prin­ci­ple ex­ists as a coun­ter­weight to that kind of over­sim­plic­ity. Ideally, one should aim at a mu­tu­ally sup­port­ive bal­ance be­tween sim­plic­ity and flex­i­bil­ity.

Computing sys­tems should adapt to the changes in their op­er­at­ing en­vi­ron­ments (especially in re­la­tion to en­ergy and heat). 24/7 avail­abil­ity of all parts of the sys­tem should not be re­quired, and nei­ther should a con­stant op­er­at­ing per­for­mance (e.g. net­work­ing speed).

If it is pos­si­ble to imag­ine all the pos­si­ble use cases when de­sign­ing a sys­tem, the de­sign may very well be too sim­ple and/​or too in­flex­i­ble. Smallness, sim­plic­ity and flex­i­bil­ity are also part of the “small, sharp tools” ideal of the Unix com­mand line. Here the key to flex­i­bil­ity is the abil­ity to cre­atively com­bine small tools that do small, in­di­vid­ual things.

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Build On Solid Ground

Consider when to build on solid ground and when to de­sign for dis­ap­pear­ance. If longe­tiv­ity is re­quired some con­sid­er­a­tions are needed.

Many com­put­ing sys­tems are based on plat­forms, frame­works or even lan­guages that change very rapidly, may be­come ob­so­lete at any time, and are too com­plex to be eas­ily reim­ple­mented. This prin­ci­ple ex­ists to min­i­mize ob­so­les­cence and su­per­flu­ous main­te­nance work in sys­tems in­tended to last.

It is good to ex­per­i­ment with new ideas, con­cepts and lan­guages, but form­ing hard de­pen­den­cies on them is usu­ally a bad idea. Appreciate ma­ture tech­nolo­gies, clear ideas and well-un­der­stood the­o­ries when build­ing some­thing that is in­tended to last. Software that uses open, well-doc­u­mented stan­dards will be more use­ful in com­mu­ni­cat­ing with the wider tech­no­log­i­cal world. It also means that data can sur­vive and still be read­able even if the soft­ware is no longer func­tion­ing.

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(Almost) Everything has a place

There is a place for al­most every­thing. Nothing is ob­so­lete or ir­rel­e­vant. Even if they lose their orig­i­nal mean­ing and con­text, most pro­gram­ma­ble sys­tems may be readapted to new pur­poses for which they were not orig­i­nally de­signed. Think about tech­nol­ogy as a rhi­zome rather than a “highway of progress and con­stant ob­so­les­cence”.

Computing is of­ten framed as a kind of ideal uni­ver­sal medium. But the re­al­ity is that com­put­ing is cul­ture! It can be very di­verse, full of color, con­tin­gency and ex­pres­sion that is part of any cul­tural pro­duc­tion. Sadly in prac­tice, and in its cur­rent form with mil­i­tary in­dus­trial roots, this cul­ture ex­ists mostly to re­pro­duce and re­in­force ex­ist­ing power struc­tures within so­ci­eties and sup­port eco­nomic growth. Today’s com­put­ing cul­tures are still dom­i­nated by Human Interface Guidelines de­signed and con­trolled by a small group of peo­ple with sim­i­lar back­grounds, pri­or­i­ties and val­ues. But if we can let go of some of the ideas of tech­no­log­i­cal con­for­mity, we might start to see a much wider spec­trum of pos­si­ble ways of com­put­ing, some of which might bet­ter re­flect lo­cal needs, de­sires and so­ci­etal is­sues.

This can also open to much wilder and di­verse cre­ative prac­tices and aes­thet­ics.

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Integrate Biological And Renewable Resources

Permacomputing seeks to sup­port sus­tain­able and re­gen­er­a­tive prac­tices, play­ing a ben­e­fi­cial role in nat­ural ecosys­tems, but un­til we can grow com­put­ers on trees, this goal re­mains largely as­pi­ra­tional. The whole elec­tronic in­dus­try is based on us­ing some of the most ar­ti­fi­cial ma­te­ri­als ever cre­ated. The ma­jor­ity of com­puter com­po­nents are firmly tied to com­plex, ex­trac­tive and ex­ploita­tive man­u­fac­tur­ing processes linked to the semi­con­duc­tor in­dus­try. There is an in­creas­ing in­cen­tive and an in­creas­ing num­ber of ex­per­i­ments to re­place some phys­i­cal parts of dig­i­tal hard­ware with more sus­tain­able ma­te­ri­als, while re­think­ing how sup­ply chains can be more eth­i­cal. How can this be en­cour­aged? How can this be pri­or­i­tized? How can this be more than sym­bolic or mar­ket­ing?

In the same sense, we can think of en­ergy use, not just in terms of ef­fi­ciency but also in terms of lo­cal im­pact. Stemming from the ob­served prin­ci­ple, see to what ex­tent it is pos­si­ble to work with (local) bi­o­log­i­cal and re­new­able ma­te­ri­als and re­sources. Not only does this min­imise the eco­log­i­cal foot­print of the sup­ply chain, it also al­lows for a closer re­la­tion to na­ture.

By us­ing more ba­sic kinds of ma­te­ri­als, we at­tend to the labour of mak­ing, which pushes us to re­flect on con­di­tions, re­sources, and ac­cess to re­sources as well as how en­ergy is gen­er­ated, ma­te­ri­als de­com­pose and mat­ter is re­cy­cled. Crafting, DIY and idio­syn­cratic ap­proaches to hard­ware de­sign can help sit­u­ate com­put­ing cul­ture and re­veal points of fric­tion.

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