“Fire made us human, fossil fuels made us modern, but now we need a new fire that makes us safe, secure, healthy and durable”*…
A number of entrenched interests have been playing a long game. There’s (all too appropriately) a good bit of attention trained on efforts like The Federalist Society‘s attempts to remake the legal and judicial landscape and The Heritage Foundation‘s “Project 2025” plan to reshape the federal government along right-wing lines. Both reflect the careful cultivation, over decades, first of sympathetic “scholarship” and opinion, then of political action.
But as Kate Yoder of Grist explains, there’s another– longer, deeper– program at work: from the family car to the dream kitchen, fossil fuel companies have sold a vision of prosperity that depended on their own products. Over a century of evidence shows how they have done it…
What does going on a date have to do with fossil fuels? Everything, according to the petroleum industry.
One advertisement from the pipeline company Energy Transfer follows two people getting ready for a date, the man primping with hair gel, the woman applying lipstick, before meeting at a bar. “That connection was brought to you by petroleum products,” the narrator says. “But what if we lived in a world without oil and natural gas?”
The story rewinds to the beginning, except this time, the woman looks bewildered as her phone with the dating app evaporates in her hands. She gets lipstick all over her cheek when the car she’s riding in hits the pavement without its tires. As his hair gel disappears, the man looks into the mirror, baffled. When they sit down across from each other, makeup, hair dye, and glasses fade away. In the game playing on a TV in the bar, a football disintegrates a second before the kicker swings his leg at empty air.
The commercial, which has racked up 7.4 million views since it appeared four years ago, taps into the fact that fossil fuels have become embedded in American life (what’s more American than football?). Oil and gas not only influence how people get around town, but also where they live, how they dress, and how they cook food in their kitchens. This all feels so ordinary that most people don’t notice how pervasive petroleum is, powering our lives while hiding in plain sight. Though it might seem inevitable that we live this way, a Grist investigation found that this idea of what’s “normal” was shaped by decades of advertising, public relations propaganda, and broader efforts to sway American culture, from radio programs to Hollywood films.
“Our dependence on oil didn’t just happen,” said Robert Brulle, an environmental sociologist at Brown University.
This campaign started about a century ago, when companies began strategizing how to create long-term demand for fossil fuels and the products that ran on them. Billboards showcased happy families on the road in their cars, films showed stylish women cooking over the flame of a gas stove, and magazines featured men pushing their gas-powered mowers across soon-to-be perfectly manicured lawns. The message was often left unsaid: The American way of life runs on fossil fuels.
There’s a well-documented history showing that Exxon and other oil giants understood the dangers of global warming by the 1970s based on their own research and still spent decades publicly downplaying, or outright denying, the science. But the story of how oil and gas companies coaxed Americans into accepting — even desiring — a life built on fossil fuels has largely escaped attention, buried in the pages of obscure trade journals.
In the 1940s and 1950s, the oil industry spent millions of dollars a year on campaigns to “educate” the public about the wonders of petroleum and how it advanced the “American way.” The natural gas industry promoted all-gas “dream kitchens” and paraded them in front of the editors of Better Homes and Gardens, Good Housekeeping, and The Ladies’ Home Journal. They sold a vision of the American Dream that required their products — a cultural legacy that has been devastating for efforts to rein in climate change and shift to a cleaner future.
This history offers an explanation for why Americans have had such a strong reaction to the idea of banning polluting gas ranges (“they can pry it from my cold dead hands”) or requiring more sales of electric vehicles over gas-powered cars. Is this debate really just about technology, or about what the burning of fossil fuels represents — freedom and a sense of identity? President Donald Trump’s Make America Great Again agenda is deeply nostalgic for what oil once promised: economic might, a higher standard of living, the chance to rise above your station and maybe make a fortune. In his inauguration speech last year, Trump promised a return to these ideals. “We will be a rich nation again, and it is that liquid gold under our feet that will help to do it,” he said.
As the world enters an “age of electricity” powered increasingly by solar, wind, and other low-carbon energy sources, the United States often appears to be stuck in the past. The Trump administration has prolonged the life of coal plants and opened up new areas to oil drilling, while paying companies billions of dollars to stop offshore wind projects. The explanation, when it’s offered, often returns to the same theme. Earlier this year, when the Trump administration scrapped Biden-era rules to cut emissions from cars, along with the Environmental Protection Agency’s authority to regulate climate change, it touted the effort as “restoring the American Dream.” White House spokesperson Taylor Rogers summed up the sentiment this summer: “President Trump was given a mandate to roll back the radical climate policies that are burning a hole through taxpayers’ wallets and jeopardizing the American Dream for future generations.”
The words echo what the oil industry has been telling Americans for a century: Without fossil fuels, there is no “good life,” only sacrifice…
Read on for the remarkable tale: “The hidden history of how Big Oil invented the American Dream,” from @grist.org.
See also: “How Big Oil Shaped America’s Parks.”
###
As we look behind the curtain, we might that it was on this date in 1895 that George Selden was granted the first patent for a gasoline-powered automobile. In the patent, which Seldon had filed several years earlier, on May 8, 1879 (eight years before the public introduction of the Benz Patent Motorwagen in Europe, built in 1886 and widely considered the first automobile), he described not only the engine but also a complete automobile incorporating such features as a clutch, compressed air self-starter, and steering system (No. 549,160). He maintained that it was the combination of these elements, together with his engine, made the road-engine patentable. Selden’s day job was as a patent attorney, so he knew to delay the issue of the patent by sending amendments and other communications every two years. Meanwhile, others did the hard work of developing the automobile, and his patent became more valuable. Years of legal wrangling for profits followed.
“Once men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.”*…
The estimable Tim O’Reilly argues that, while we’re right to be concerned with AI as it’s currently being developed, we needn’t resort to a Butlerian Jihad…
In 2019, the computer scientist Richard Sutton wrote a short essay called “The Bitter Lesson.” Looking back over seventy years of AI research, he concluded that general methods that scale with raw computation beat methods built on human expertise, and by a large margin. The AI industry as a whole is bitter-lesson-pilled, to borrow the internet’s slang for a true believer. I am human-pilled.
I believe in the bitter lesson. Brute force wins out in the end, and I have wrestled with that fact throughout my career. But we humans still have to figure out our role in the AI economy, and I find it rather disturbing that the AI community isn’t spending more time asking how to make this future friendlier for humans. The labs think about how to keep AI from going rogue, and their chief economists study job losses from AI. They don’t study what mechanisms we could introduce to create new economic opportunities for humans.
The question matters to us at O’Reilly Media. We don’t think of ourselves as a publisher, a conference producer or an online learning platform so much as a company that transfers knowledge from the people at the cutting edge to the people who want to follow them. So we are very interested in what human expertise is worth, even in the face of AI.
Human expertise was used to train AI, which makes AI a fabulous cultural technology. Thousands of years ago, the only knowledge people had was what they could keep in their heads. Since then we have built better and better ways to share knowledge across time and space, and AI continues that. With each of these transitions, we have to ask again what the truly human is still worth. People often say judgment, or taste. That’s true, but I think it goes deeper:
AI is a sea of possibility. All of that knowledge sits in the model, and nothing sets it in motion except a human. (That is changing a little as we start giving AI agents long-running tasks, and we will have to come to grips with it.) If you and I used Claude or ChatGPT for the same research project, we would each bring different experience to it, tell it what we want and why, and give it context in different ways. I see that as the unique focusing power of human consciousness and attention.
Earlier this year I spent an hour or so talking this question over with Claude. When it offered to write up a first draft for me, I said no. I wanted an essay from its own point of view about what it took away from our conversation. The result, “Why AI Needs Us”, opens, “He came in through Powys,” and a few paragraphs later says, “The choice of entry point was already the argument.” That captured what I’m getting at. I had come into the conversation through a book I love, John Cowper Powys’s The Meaning of Culture, which distinguishes culture from education. Powys quotes one definition: “Culture is what is left over after you have forgotten all you have definitely set out to learn.” It is what you absorbed. Each of us absorbs a small and particular slice of everything. Large language models (LLMs) try to absorb everything, and so become overly general; we give them focus. Human knowledge provides them with a lens...
[Tim unpacks his thesis, explaining both what he means and how he came to believe it…]
… I think a lot about a concept from economics called mechanism design, which has also been described as reverse game theory. Game theory asks how players will act under a given set of rules. Mechanism design starts from the outcome you want and works backward to rules that will tend to produce it as people pursue their own interests. Al Roth, who shared a Nobel Prize for this kind of work, used it to design a kidney exchange that more patients and donors would join. Economists mostly apply the idea to auctions and similar markets, but I think every new technology requires new mechanisms, and the best ones are not invented by economists. We tend to fall into them without really understanding them.
Think about the economic mechanisms that made earlier technological revolutions work. The web gave us the ability to connect computers, but it took inventions like PageRank to help people find what they were looking for, pay-per-click advertising to connect businesses with customers, and online payments to make transactions easy. Smartphones gave us GPS, but somebody had to invent the matching marketplaces that made Uber and Lyft possible. YouTube’s Content ID turned copyright infringement from a problem of takedowns into an opportunity for creators and rights holders to get paid. These weren’t simply technological advances. They were new arrangements of incentives that made entirely new markets possible.So what are the equivalents for AI? How will agents discover the best expertise and skills, establish their quality, and pay the people who created them? How will they find services without the platform steering them toward whoever pays the most? We don’t know the answers yet. And that’s precisely the point. We’re spending enormous amounts of money making AI more capable, but comparatively little effort figuring out the mechanisms that will turn those capabilities into opportunities for everyone else.
Take open source software. Most people think its mechanism was the free software licenses, but I was around before those licenses, and people were already sharing software. Ken Thompson and Dennis Ritchie created Unix, the predecessor of Linux, at Bell Labs under AT&T’s proprietary license. They designed it to run on many kinds of hardware, and without meaning to, they built what I came to call an architecture of participation…
[Tim explains Model Context Protocol (MCP) and the way that it can bring participation to AI…]
…
With MCP, which lets any model connect to anyone’s tools and data, the emerging web of AI agents began to take on the shape of the participatory economy of open source software and the web. People can bring their own models and infrastructure as an alternative to the big centralized players.
This is another side of grappling with the bitter lesson: what are the missing mechanisms of the human-AI economy? Some of them are standards, because standards and protocols are a big part of what makes an architecture of participation. I have a group working on portable memory, so that what your AI knows about you can move with you from one tool to another.
That story is just beginning. We are in an exploratory phase of mechanism design for AI, and it would be a mistake to settle on answers too early. Somebody is going to figure out the next mechanism, and we’ll all say, “Oh, that’s so damn obvious.”
Mechanism design starts by asking what outcome you want. So what game ought we to be playing in the AI market?
We’ve been told that the game is the quest for superintelligence: a winner-takes-all contest that will bring untold riches to the winners and maybe impoverish, or even kill, everyone else. We’ve seen mechanisms designed to support that game. Massive investments in data center capacity mean that only the well-capitalized can play. There is colonialist-style appropriation of existing intellectual property. Access to models is sold through expensive APIs, and closed models come with terms of service that forbid others from learning from their outputs. Advertising may be creeping into answers, and memory locks your context inside one provider’s walls. Is that the game we ought to be playing?
I think the game we should be playing is human flourishing, and I think the game of human flourishing is creating new affordances for people to create and share with each other. We’re a social species. History teaches us that we will find our way there, but we can get there more quickly or more slowly depending on the choices we make. Getting there takes mechanisms that create a circulatory economy of value exchange between humans and their agents, with humans in partnership with AI rather than replaced by it.
The big labs, whatever the motives of the people who run them, are all driven by the imperatives of our financial system. They have raised enormous sums that they somehow have to pay back, so building a hugely successful business has to be their overriding goal, and that shapes all their incentives. In some ways AI was enshittified from the beginning, because it was built on the backs of so much capital that has to be repaid. That’s why open source AI matters so much, and sovereign AI too, built and controlled within individual countries. The open models, which anyone can download and run, aren’t as capable as the best closed models yet, but they keep getting closer, and they are already good enough for a lot of productive work.
Open source, open protocols, and open memory give users the freedom to shape and control the technology they use. The game I want us to play is one in which all of us build the future together, so that we control this wonderful new wave of technology for ourselves. I’m starting to see the shape of an economy where AI belongs to people rather than to the big labs, where we have personal AI agents working for us and with us, and we build an economy around that. I think it’s going to happen not because of the big labs, but in spite of them…
AI for everyone- the Bitter Lesson meets Architectures of Participation: “Human-Pilled,” from @timoreilly.bsky.social.
Pair with this consideration (from Henry Farrell) of AI’s current “flavor of the month”: “Agentic AI is myth set in motion.”
* Frank Herbert, Dune
###
As we open AI, we might recall that it was on this date in 1952 that the National Security Agency– the NSA– was formed by President Harry Truman. Created from a unit that deciphered coded communications in World War II, it had predecessors (with names like “Cipher Bureau,” “Black Chamber,” and “MI-8”) that date back to World War I. Charged with global monitoring, collection, and processing of information and data for intelligence and counterintelligence purposes, specializing in a discipline known as signals intelligence (SIGINT), the NSA is also tasked with the protection of U.S. communications networks and information systems.
By the end of the Cold War, the NSA had became the largest of the U.S. intelligence organizations in terms of personnel and budget. While it appears that CIA may now have surpassed it, the NSA has some 32,000 employees.
The NSA’s actions have been a matter of political controversy on several occasions, including its role in providing intelligence during the Gulf of Tonkin incident, which contributed to the escalation of U.S. involvement in the Vietnam War. Declassified documents later revealed that the NSA misinterpreted or overstated signals intelligence, leading to reports of a second North Vietnamese attack that likely never occurred. The agency has also received scrutiny for spying on anti–Vietnam War leaders and the agency’s participation in economic espionage. In 2013, the NSA had many of its secret surveillance programs revealed to the public by Edward Snowden, a former NSA contractor. According to the leaked documents, the NSA intercepts and stores the communications of over a billion people worldwide, including United States citizens. The documents also revealed that the NSA tracks hundreds of millions of people’s movements using cell phone metadata. Internationally, research has pointed to the NSA’s ability to surveil the domestic Internet traffic of foreign countries through “boomerang routing.”
“Never underestimate the power of a fresh coat of white paint”*…
A new twist on an old-school climate adaptation technique– Lara Williams reports…
In a co-working space overlooking the west London neighborhood of White City, a host of startups are at work on flashy technologies ranging from a breath test that can detect multiple cancers to a pain-free tattoo. Surrounded by that kind of innovation, a visitor might overlook the lab stocked with little more than tubs of white powder and paint pots. After all, how interesting can white paint be?
When it comes to adapting to a hotter planet, the answer is: very.
As record temperatures baked Europe this summer, people desperately sought ways to cool their homes and workplaces. I stuck emergency foil blankets to my windows in an attempt to stop the heat from getting in; others tried coating the glass in yogurt or chalk. But of course, the most popular and effective option was air conditioning.
Sales of both conventional and portable units shot up this year, and the need for that cool breeze is only going in one direction: By 2035, the International Energy Agency predicts that global cooling demand could grow by about 2,300 terawatt-hours. (For context, that’s more than India’s total electricity demand in 2025.)
This is bad news for the energy transition. Consider that in 2023, the UK fired up a coal plant during a heatwave to meet AC demand. Yes, air conditioning can be a literal lifesaver, but if we want to avoid making the planet even hotter, it can’t be our only strategy.
That’s where paint comes in.
People in countries like Greece and Spain have been painting their homes white to keep them cool for centuries. White reflects most sunlight, making it better than other colors at preventing solar energy from being absorbed as heat. Commercial “solar-reflecting” paints reflect up to 90% of sunlight, but recent innovations in materials science promise to make white paint’s cooling properties even stronger.
The secret is something called daytime radiative cooling. Any object with a temperature above absolute zero emits heat as thermal infrared radiation. Some infrared wavelengths transfer more heat because they are able to pass through the atmosphere into the freezing depths of space. That process is how our planet cools itself.
Typically, net cooling only happens at night, when there’s no incoming sunlight — and therefore solar radiation — adding more heat. But in 2014, researchers at Stanford University demonstrated that it was possible to chill a surface to 5C below the ambient air temperature during the day by combining the power of reflective cooling (i.e. when white paint reflects sunlight) and radiative cooling (what happens when infrared radiation passes through the atmosphere).
More than a decade later, this technology is making its way into the marketplace…
[Williams describes the entrepreneurial efforts underway, examines their challenges, and explores their potential. She concludes…]
… Innovations that improve our lives don’t always look like talking computers or flying cars. As someone who suffered through too many sweaty, sleepless nights this summer, that humble bucket of white paint is starting to look pretty exciting.
“Why I’m Excited About a Bucket of White Paint” (gift link, or archived link), from @lararhiannon.bsky.social in @opinion.bloomberg.com.
###
As we stay cool, we might spare a thought for Sir John Leslie; he died on this date in 1832. A Scottish mathematician and physicist, he best remembered for his research into heat. Leslie gave the first modern account of capillary action in 1802 and froze water using an air-pump in 1810, the first artificial production of ice. Then, in 1804, he helped lay the scientific groundwork for the advances considered in the article linked above: he experimented with radiant heat using a cubical vessel filled with boiling water. One side of the cube was composed of highly polished metal, two of dull metal (copper), and one side painted black. He showed that radiation was greatest from the black side and negligible from the polished side. The apparatus is known as a Leslie cube.
“Man is a Religious Animal. He is the only Religious Animal. He is the only animal that has the True Religion–several of them.”*…
Further, in a fashion, to last Saturday’s post, a look at how religions have changed from their inceptions until now– and how we know…
Five histories told in order, a chapter at a time: Hinduism from the farmers of Mehrgarh, Judaism from the hill villages of Iron Age Canaan, Buddhism from the Ganga plain, Christianity from Galilee and Islam from late antique Arabia. Every claim names the verse, inscription, excavation or study behind it, and says how settled the evidence is…
… How It Evolved tells the history of religions the way a good historian would explain it to a curious friend: chronologically, with the evidence on the table, and honest about where the evidence runs out.
Most writing about religion falls into one of two camps. Devotional accounts describe a tradition as it sees itself, often as timeless and unchanging. Polemical accounts go looking for ammunition. Neither is much use to someone who simply wants to know what changed, when, and how we know. That is the only question this site sets out to answer.
Every claim shows its receipt. Statements cite the specific verse, excavation, inscription, manuscript or peer-reviewed study they rest on, with numbered references on every page.
Every claim says how sure we can be. Confidence tags (Consensus, Majority, Contested, Speculative, Political) mark how far the evidence stretches.
Disagreements are stated, not resolved by fiat. Where scholars disagree, each chapter gives the strongest form of each position, including the ones we do not adopt.
Primary sources in the original. Key passages are quoted in their original script, transliterated and translated, followed by what the passage does and does not prove.
Each religion gets a series: a sequence of chapters from its earliest traceable roots to the present, with shorter pages that answer the questions people most often ask about it.
The five series published so far:
- How Hinduism Evolved, 7000 BCE – present, in 13 chapters. From Neolithic Mehrgarh and the Rigveda to bhakti, the Raj and the present.
- How Buddhism Evolved, c. 600 BCE – present, in 14 chapters. From the śramaṇa movements of Magadha to Theravāda, Mahāyāna, Zen and Tibet.
- How Christianity Evolved, c. 30 CE – present, in 14 chapters. From a Jewish apocalyptic movement to councils, schisms, reformations and a global church.
- How Islam Evolved, c. 300 CE – present, in 14 chapters. From late antique Arabia to the caliphates, law schools, Sufism and modern reform.
- How Judaism Evolved, c. 1250 BCE – present, in 14 chapters. From Yahweh among the gods to the Torah, the rabbis, the diaspora and the modern movements.
Series on Sikhism are in preparation. Each is published only when every chapter meets the same standard.
The series are written to be read together. Where traditions grew up side by side, as Buddhism did beside the Vedic religion of ancient India, the same evidence appears in more than one series, told from each side, and the chapters link to each other…
Plus there are maps shows the spread of each religion and a (very large) chart tracing the development of all five, side by side.
Absolutely fascinating: “How It Evolved“… puts one in mind of the telephone game.
(Image above: source)
* Mark Twain
###
As we get religion, we might recall that today is (in the Christian tradition) All Souls Day, a day of prayer and remembrance for the departed. It is also (the final day of) All Souls Day’s predecessor (and variation on its pagan inspiration), The Day of the Dead…
The Day of the Dead (el Día de los Muertos), is a Mexican holiday where families welcome back the souls of their deceased relatives for a brief reunion that includes food, drink and celebration.
A blend of Mesoamerican ritual, European religion and Spanish culture, the holiday is celebrated each year from October 31-November 2. While October 31 is Halloween, November 1-2 is All Souls Day or the Day of the Dead. According to tradition, the gates of heaven are opened at midnight on October 31 and the spirits of children can rejoin their families for 24 hours. The spirits of adults can do the same on November 2.
The roots of the Day of the Dead—celebrated in contemporary Mexico and among those of Mexican heritage in the United States and around the world—go back some 3,000 years to the rituals honoring the dead in pre-Columbian Mesoamerica.
The Aztecs and other Nahua peoples living in what is now Mexico held a cyclical view of the universe and saw death as an integral, ever-present part of life. Upon dying, a person was believed to travel to Chicunamictlán, the Land of the Dead. Only after getting through nine challenging levels, involving a journey of several years, could the person’s soul finally reach Mictlán, the final resting place.
In Nahua rituals honoring the dead, traditionally held in August, family members offered food, water and tools to aid the deceased on this difficult journey. This inspired the modern Day of the Dead practice of leaving food and other offerings on loved ones’ graves or setting them on makeshift home altars, called ofrendas.
In ancient Europe, pagan celebrations of the dead also took place in the fall and featured bonfires, dancing and feasting. Some of these customs survived after the rise of the Roman Catholic Church, which informally absorbed the pagan traditions into its observances of two holy days—All Saints Day and All Souls Day—celebrated on the first two days of November. – source
“In reality, there is no such thing as not voting: you either vote by voting, or you vote by staying home and tacitly doubling the value of some Diehard’s vote.”…
… but even when we do vote, as Alex Stone reports, there’s an issue: how we vote…
Mathematically speaking, democracy is next to impossible.
That may sound like the premise of a Silicon Valley billionaire’s six-hour podcast, but it’s actually a statement about a remarkably stubborn problem: How do you translate a group of individual preferences into a single choice?
In 1785, the French mathematician and philosopher Nicolas de Condorcet [see also here] discovered that a majority can sometimes vote itself into a logical loop. In elections with three or more candidates, each voter might rank the candidates in a perfectly clear and consistent way — yet when all the votes are tallied, every candidate loses in a head-to-head contest against one of their rivals. Changing the rules only gets us so far: As the economist Kenneth Arrow later proved, any method for combining individual rankings into a collective order must sacrifice at least one seemingly reasonable democratic requirement.
Now three researchers have shown that Condorcet’s 240-year-old paradox has a shape, and it’s suitably peculiar: a Klein bottle, a surface with no distinct inside or outside. The result gives mathematicians a geometric way to explore why seemingly reasonable rules for collective decision-making can become impossible to reconcile.
When there are only two choices, the will of the people is easy to divine: Barring a tie, the candidate preferred by a majority wins. Add a third contender, however, and things get weird. Suddenly, even agreeing on what it means to win becomes a problem.
You might simply elect whoever receives the most votes, as in a typical American election. But suppose Alice receives 35% of the vote, Bob 34%, and Carol 31%. Alice wins. Yet if Carol’s supporters all prefer Bob to Alice, then 65% of the electorate would rather have Bob. By one perfectly reasonable definition of majority rule, the wrong candidate has won.
Before anyone reaches for a tinfoil hat, let’s be clear: Every ballot is counted correctly. The question is what should count as winning.
One solution is to ask voters to rank the candidates, then choose whoever would defeat every rival in a head-to-head contest. But consider the following scenario:
- One-third of voters rank Alice over Bob over Carol.
- One-third rank Bob over Carol over Alice.
- One-third rank Carol over Alice over Bob.
Now compare the candidates in pairs:
- Alice beats Bob, because the first and third groups prefer Alice to Bob.
- Bob beats Carol, because the first and second groups prefer Bob to Carol.
- Carol beats Alice, because the second and third groups prefer Carol to Alice.
Every voter has a perfectly coherent ranking, yet together they have produced a result that runs in circles.
This is the paradox that Condorcet, a passionate believer in democracy, encountered in the late 18th century. As the secretary of the French Academy of Sciences, he’d been looking for ways to make sure the group was choosing new members fairly. (More enlightened than most, Condorcet would also question the democratic arithmetic of excluding half the population, explicitly defending women’s political rights in a 1790 essay. A few years later, during the Reign of Terror, the revolution he had supported put him in a prison cell; he was found dead two days after his arrest.)
Over the centuries, mathematicians, political scientists, and reformers have devised an astonishing variety of voting systems in hopes of breaking Condorcet’s impasse. Yet every method brings its own vulnerabilities. Change the system and you may well change the winner, even when the voters and their preferences remain exactly the same.
In 1951, the economist Kenneth Arrow showed how deep the problem ran. He sought a voting system that stayed consistent while meeting just a few simple democratic requirements. Voters should be free to rank the candidates in any order. No single voter should unilaterally dictate the outcome of an election. (Read: no kings.) If everyone prefers one option to another, the group’s ranking should reflect that preference. And the ranking of two candidates should depend only on how voters compare those two: Where voters place Carol on their ballots shouldn’t affect whether the group ranks Alice above Bob.
Each requirement sounds reasonable enough on its own. But, Arrow showed, no method can satisfy them all. “Quite often the will of the people doesn’t exist,” said Iain McLean of the University of Oxford.
Arrow’s impossibility theorem, as this result is now known, extended Condorcet’s paradox beyond majority rule, establishing a fundamental limit on how individual votes can be combined into a group decision. Different voting systems can change which of Arrow’s requirements fail, but no single system can ever preserve them all. “You have to make a choice as a system designer as to which of the conditions it’s most harmless to fail,” McLean said.
In 1980, to better understand this phenomenon, the mathematician and economist Graciela Chichilnisky turned to topology, an area of math in which shapes are considered equivalent if one can be stretched into another without tearing. In a footnote, she mused that Condorcet’s paradox in particular could be thought about as a topological problem.
Now mathematicians have proved her intuition true…
[Stone unpacks the (admittedly rather heady) math; he concludes…]
… So where does that leave democracy?
Topology makes the paradox tangible, but choosing a voting system still means picking your poison. Mathematics can tell us what the trade-offs entail. Our priorities determine which ones are worth making. And that’s something no theorem can settle for us. “It’s not really a mathematical debate,” McLean said. “It’s a debate about values.”
A new topological model connects a centuries-old voting paradox to a surface with no distinct inside or outside: “How Voting Is Like a Klein Bottle,” from @quantamagazine.org.
Tuesday’s election is largely a “binary choice” affair– do vote!
* David Foster Wallace, Consider the Lobster and Other Essays
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As we celebrate suffrage (with all of its shortcomings), we might recall that it was on this date in 1897 that the first Library of Congress building opened its doors to the public; the library had previously been housed in the Congressional Reading Room in the U.S. Capitol.
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