To overcome these problems, researchers have long experimented with vessels that could transport drugs to their destination while shielding them from the body’s defense system. These include nanoparticles, which are tiny structures made from metals, polymers or lipids that are about a thousandth of the width of a single human hair; liposomes, which are fatty spherical pouches whose walls are made from the same material as cell membranes; and nanobots, hypothetical miniature machines that could perform tasks at the molecular or cellular level.

But all of these face challenges. The liver and spleen intercept a large fraction of nanoparticles before they ever reach the target (though they still show promise for certain breast and lung cancers, as they can more easily permeate blood vessels). Liposomes face a similar problem: macrophages in the liver recognize and engulf most of them on the journey. Working nanobots are still a distant prospect. And most are blocked from reaching the brain. These are some of the barriers that microbubbles may be able to cross.

Boy in the bubble

Microbubbles are just what they sound like: tiny gas-filled bubbles. Scientists have engineered them further, to be coated with a protective outer shell and made capable of carrying drugs or genetic material to cells in the body. They are microscopic, roughly the width of spider silk, but still hundreds or thousands of times larger than nanoparticles or liposomes. This means they’re too large to leave the bloodstream. Instead, microbubbles deliver drugs by bursting on command.

As they burst open, they briefly force open biological barriers that are otherwise impenetrable, such as the blood-brain barrier, allowing treatments to pass through. The force of their bursts can even be the treatment itself, as they could also be used to break apart kidney stones.

Microbubbles were first developed to help radiologists read scans. In the late 1960s, doctors at the University of Rochester were using ultrasound to take pictures of heart structures when they made an accidental discovery. When they injected saline into a vein near the heart, their ultrasound image lit up with a cloud of bright signals. The flashes had been created by tiny air bubbles, formed by the rush of fluid from the injection: sound waves passed through blood and tissue fairly smoothly, but once they encountered gas, the change in density reflected the waves back to the sensor.

That discovery became a standard technique for spotting structural defects in the heart: if bubbles crossed from one chamber to the other on the scan, it indicated a hole. But the bubbles were short-lived and inconsistent in size, so researchers began experimenting with other injectable substances, including blood and medical dyes, to produce stronger, more stable signals. These efforts to engineer reliable contrast agents for ultrasound imaging mark the beginning of what we now call medical microbubbles.

Over the following decades, researchers moved from experimenting with whatever was at hand to deliberately designing microbubbles from scratch, giving them thin shells of lipids, proteins, or polymers to control their size and keep them stable long enough to be clinically useful.

One approach to create a protective shell was to use albumin, which is familiar as the protein in egg whites but is also the most common protein in the bloodstream, where it is used to ferry molecules through the body. Since the body already produces it in large quantities, it doesn’t provoke an immune response and can be used medically. It also has useful structural properties: it unfolds and hardens into a shell sturdy enough to survive circulation, but is brittle enough that it can fall apart when hit by focused sound waves. Albunex, an albumin-coated and air-filled microsphere, was approved by the FDA in the early 1990s for use in cardiac ultrasounds, specifically to make the inner walls of the heart’s left ventricle visible on a scan. Unlike air bubbles, these albumin-coated microbubbles were stable with refrigeration for at least two years.

Researchers also found they could make even sturdier shells through sonication: blasting a protein-rich liquid with high-energy sound waves. The intense energy causes the protein molecules to assemble spontaneously with their water-repelling sides facing inward toward the gas, and their water-loving sides facing out, and as they do, the acoustic energy chemically cross-links them in place, forming a rigid shell. Unfortunately, air inside dissolves readily into the surrounding blood, causing the bubbles to collapse within seconds. Scientists found they could dramatically extend bubble lifetime by replacing the air with heavier, less soluble gases, such as perfluorocarbons and sulfur hexafluoride, which linger inside the shell long enough to be clinically useful. These second-generation microbubbles can persist in the bloodstream for several minutes, and can meaningfully enhance ultrasound images of the heart and liver.

Microbubbles, being bubbles, have many other interesting properties beyond reflecting sound and carrying material: they can expand, contract and burst.

This behavior, known as cavitation, was already familiar to physicists: when a bubble collapses, it generates a brief pressure pulse that can push on surrounding material. Lawrence Crum, a researcher from the University of Washington, had shown this in larger bubbles, but the question was whether the same forces could be harnessed usefully in living tissue.

A group at Stanford found that they could. At lower intensities, cavitation didn’t destroy cells. Instead, it temporarily loosened the walls of blood vessels and punched small, reversible pores in cell membranes, in a process called sonoporation. This opened a new possibility for drug delivery, especially in the brain, where the blood-brain barrier tightly regulates what can enter. Sonoporation offered a way to open that barrier temporarily and locally, letting drugs through without permanently disrupting it.

Bubbles also move with what surrounds them: wind, water, blood. In the bloodstream, that would usually mean being swept along by the current, with no control over where they end up. Scientists from Northwestern hypothesized that by steering the bubbles, they could control the drugs. They eventually cracked it in the early 1980s by attaching magnetic nanoparticles to microbubble shells made of albumin and treating rats with tail tumors by injecting microbubbles into a nearby artery and using a magnet to capture the bubbles at the tumor site.

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A microbubble future

Microbubbles have been used in diagnostics since the 1990s, but haven’t yet been approved for delivering medical treatments. Part of the reason comes down to how they’re tested. Imaging microbubbles, which are already in clinical use, are relatively straightforward to evaluate. Therapeutic bubbles are harder, because their success depends on both whether the bubbles reach their target and whether the treatment they carry actually works. The external ultrasound system adds another layer of complexity, as researchers need to make sure the ultrasound pulses are working correctly and reliably too. Imaging bubbles also had a head start: they were developed first, and built up a safety record in thousands of patients through large multicenter trials in the 1990s, while therapeutic microbubbles are still catching up.

But researchers are exploring their use across a wide range of conditions: dissolving blood clots in stroke patients, delivering chemotherapy directly to tumors, opening the blood-brain barrier for brain cancer treatments, and even targeting genetic material like mRNA to specific tissues.

Microbubbles are different from many other delivery platforms because they can be steered. But some use cases are more promising than others: treatments where the target is physically accessible, such as a tumor with a clear boundary or a clot in a vessel, are better suited to microbubbles than diffuse conditions where the problem is spread across many tissues.

Brain cancer is likely one promising area: microbubbles can open the blood-brain barrier and early trials in glioblastoma patients have shown the approach is feasible with manageable side effects such as passing headaches. In one small pilot trial, the cavitation effect from bursting bubbles was used to oxygenate tumors, which are otherwise harder to treat with radiation.

Pancreatic cancer is another: in a small 2016 pilot trial, patients treated with microbubble-delivered gemcitabine survived on average eight months longer than the control group, and tolerated more treatment cycles. These are small trials, and results like these need to be replicated at scale.

The same idea is likely to extend beyond cancer. To treat ischemic strokes, doctors currently deliver a clot-dissolving protein called tPA intravenously, but because it circulates through the whole body, it also interferes with healthy clotting elsewhere. Microbubbles could release tPA directly at the clot site, avoiding that tradeoff. Similarly, they also offer a way to deliver chemotherapy drugs like doxorubicin and gemcitabine directly to tumors, sparing the heart, liver, and bone marrow from the damage that comes with high systemic doses. And for mRNA therapies, including vaccines like those developed against Covid-19, current delivery systems distribute the vaccines across many tissues, wasting much of it.

Kidney stones are another option, as a physical object that could be broken apart with microbubbles. Researchers have proposed equipping microbubbles with chemical tags that bind specifically to the mineral in most kidney stones, then triggering cavitation with an ultrasound pulse to burst them from inside. Focused ultrasound devices for kidney stones have already received FDA clearance, which suggests regulators are comfortable with the broader approach.

Most drug delivery is systemic: drugs circulate through the entire body, and only a fraction reaches the intended site; the rest is either wasted or can cause off-target side effects. Microbubbles, on the other hand, could carry a therapy through the bloodstream and release it precisely where it’s needed, guided by an external ultrasound pulse. It turns out that to solve some of medicine’s unsolved problems, you sometimes need to think very, very small, and then burst through.

Ambika Grover is an undergraduate at Harvard University.

The Ogallala Aquifer sits under eight states and 111.8 million acres of US farmland. A windmill can lift only a few gallons per minute, useful for drinking water but useless for agricultural purposes. In the 1940s, electrification reached the Great Plains and a Colorado farmer invented center pivot irrigation, a sprinkler line on wheels that rotated around a central wellhead. The 1949 version could lift thousands of gallons per minute and irrigate 40 acres.

Since then the aquifer has lost 286.4 million acre-feet of water, comparable to draining Lake Erie entirely. The parts of it beneath arid states have seen much bigger drops. Large parts of Western Kansas have lost 50 percent of their aquifer depth. Texan wells are down as much as 265 feet. On current trajectories, the water there will be gone in 20–30 years.

Before center pivot irrigation, everyone could use as much of the Ogallala Aquifer as they were physically able to extract without any risk of depletion. An incredible invention created a tragedy of the commons. The southern Great Plains will have to ration water use by some mechanism, probably water charges, or face the total end of irrigated farming.

This is only one example of a common historical story. Fish catch sizes were limited until radar, sonar, and diesel engines; the North Sea Cod population collapsed a few decades after their invention. The telegraph led to the extinction of the passenger pigeon by letting hunters easily communicate about the whereabouts of the flocks. Chlorofluorocarbons almost killed the ozone layer. Technologies can collide with common-pool resources and drive them into extreme scarcity.

The Roadgallala aquifer

This is about to happen again. Road transport, especially the private car, is the dominant mode of transport in every country around the world. None of these countries charge at the point of use for the bulk of their road networks. When traffic gets slow enough – ten miles per hour in Tokyo and eight in Paris – people switch to other modes of transport because they can’t do much else when they are stuck behind the wheel.

This constraint is about to be lifted. Self-driving cars are not a hypothetical future but a familiar part of the urban background in San Francisco. I have driven in them several times and the novelty of seeing a steering wheel turn itself has pretty much worn off. During 2026, Waymo service will expand to Dallas, Houston, San Antonio, Orlando, and Miami, joining Atlanta, Austin, Los Angeles, San Francisco, and Phoenix.

Right now, self driving is a premium experience, more expensive than a human driver, in part because Waymo uses new cars, and in part because there are still relatively few Waymos on the road, spreading operational overheads thickly on a small fleet. Over time, Waymo and its competitors will become cheaper than human-driven taxis.

You make driving fun

Self-driving cars need not look like traditional cars inside. Normal cars are heavy and bulky, in large part due to safety requirements. Despite sharing the road with human drivers, Waymos already have 80 percent fewer accidents. When self-driving cars become 90 percent of the cars on the road, they will be able to platoon and join up into little trains, saving the space usually spent on gaps between vehicles and doubling road capacities.

They can be more comfortable as well. The Volkswagen GEN.TRAVEL has seats that fold out into flat beds, with passenger restraints for safe sleeping while moving and lighting designed to generate natural circadian rhythms. The Volvo 360c offers a first-class private cabin with a classic Volvo touch: a special safety blanket that acts like a seatbelt, usually loose and comfortable but tightening instantly on impact. In theory it can be an entertainment space or a mobile office too. Simpler, working versions of this idea, like the Amazon Zoox, are already driving around Las Vegas and San Francisco.

With imagination, you can see how a wide range of functions could be performed in a car: working, sleeping, eating, and even socializing, effectively bringing back the bar cars once enjoyed by New York commuters to Connecticut. I already buy cans of beer for long train rides with my friends. Train lines created entirely new seaside resorts like Atlantic City in the US, and Heringsdorf, Ahlbeck, and Bansin in Germany. Just imagine the trips people would make with the ability to effectively travel business class in their cars, driving overnight.

Our gridlocked future

Autonomous vehicles are the centrifugal water pump of the roads. Just like the Ogalalla Aquifer, most roads are currently free at the point of use. And just like the Ogalalla Aquifer, they will be overused if we do not charge for the privilege of drawing on them. Anyone who needs to get where they’re going quickly will be stuck in traffic with all the people enjoying a beer, working from a mobile office, or having a nap. There will be total gridlock.

Though taxes on fuel and registering cars are universal across the developed world, imposing charges at the point of use has been trickier. It took New York City 60 years to impose congestion pricing, and it was almost revoked several times along the way. London’s congestion charge has survived, but attempts to extend it out of the very inner core have not. Dutch voters destroyed per-mile charges, the Kilometerheffing, in 2010. Hong Kongers rejected such a scheme in the 1980s, despite an effective trial.

These attempts failed for a range of reasons. But a major one is that they aimed to change the rules of the game for everyone at the same time, creating a lot of people who lost out under the policy while giving them nothing in exchange.

Tax doesn’t have to be taxing

There are two tricks to making new levies politically durable. First, a quid pro quo: drivers are much happier to pay if they get something in exchange, usually infrastructure. Second, grandfathering: drivers don’t like the price of anything they have already accounted for, including road access, to change, but they don’t mind high prices on new things. Fuel taxes are an example of a quid pro quo: in most developed countries, they entirely cover the cost of road construction and maintenance. Tolls, which are usually charged on new tunnels, roads, lanes, or bridges, are an example of both.

The Harris County Toll Road Authority, created by referendum in 1983 to fund the construction of two new roads, now manages 128 miles of roads around Houston, Texas. Voters have continually opted to expand it. Forty-three percent of the lanes added to California highways between 2018 and 2023 have restricted access, whether by requiring vehicles to carry multiple passengers or charging a toll.

Nearly all of France’s motorway system was funded by tolls, as are Japan’s and Austria’s. Voters accept these charges because they both generate a quid pro quo, new infrastructure in exchange for new money, and they keep old infrastructure free.

Voters will even tolerate variably priced toll lanes. Colorado added dynamic tolling, calculated by an algorithm to balance supply and demand, to a congested stretch of a major highway. The state’s Department of Transportation says that throughput there has gone up by 20 percent. The I-4 near Orlando has two express lanes that run for 21 miles. They range from $0.50 to $3.00 per three-mile segment. Cars on these segments go eight miles per hour faster than on the regular lanes during the evening peak. These Lexus Lanes have faced grumbling, but no serious opposition.

One simple trick to make road pricing popular

Grandfathering can work not just by location – new bridge, new tax; old network, no tax – but by vehicle type, if that new vehicle type is not currently being used by most drivers and voters. This is exactly what the UK government did in late 2025, despite being one of the country’s most unpopular governments ever, by imposing a charge of £0.03 per mile on electric vehicles. The new charge was possible because only 5.2 percent of the market is electric.

This shows the path for other countries: imposing a charge that falls only on autonomous vehicles. Since current drivers will not face any unexpected charges, they will tolerate the new tax. If governments want to charge the tax at a high rate, they should give autonomous vehicle owners and users something in return, most likely new road infrastructure. This needs to happen now. When AVs are dominant, users will balk at a big change.

If governments follow these rules, they can charge variable surge prices in busier locations and at busier times, clearing the market so roads flow, as surge pricing already does for Ubers and Lyfts, and as variable pricing does on Singaporean expressways. And if they wish, governments can dispense with gantries and numberplate cameras and use location trackers. Voters are comfortable with location tracking that they opt for themselves, as in ride shares or many of their apps.

If we continue to treat our roads as a common-pool resource, we will drain them like the Ogallala Aquifer. The good news is that if we act quickly, before autonomous vehicles become dominant, we can prevent this surprisingly easily.

Ben Southwood is an editor at Works in Progress.

By late January 1945, the end of World War II finally seemed in sight. American business leaders began thinking about introducing products delayed by the war. The most anticipated was nylon stockings, which debuted in 1939 only to have the new fiber diverted to military applications. Another was television, which had entranced visitors at the 1939 World’s Fair. But the new medium was a much tougher sell than high-tech hosiery.

‘Television presents a vicious triangle’, JJ Nance, a Zenith Radio Corp executive explained to Wall Street analysts. Television shows were far more expensive to make than radio programs. Producers needed advertising revenue to cover the costs. But advertisers demanded large audiences. ‘We can’t get a mass audience’, Nance said, ‘until we have provided the American peo­ple with assured continuous entertainment, pleasing enough to stimulate the buying of receivers by the million’. Hence the vicious triangle: attracting viewers required programs, which required advertising, which required viewers...

It’s a dilemma every new technology platform faces – only more so. To catch on, television needed to sell hardware, create content, and find revenue. Few contemporary platforms have to do all three. Most build on an installed base of hardware. Social media gets its content free from users. In theory, TV might have paid for programming with a license fee on sets, like the tax that still funds the BBC. But Americans, accustomed to free, ad-supported radio programming over public airwaves, fiercely resisted any such suggestion.

Yet just a decade after Nance’s speech, two thirds of American homes had a TV set, including 78 percent of those in cities. As early as 1948, public housing officials were already debating whether tenants in subsidized apartments should be allowed sets and antennas. Television was one of the most quickly adopted technologies in history.

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To escape the vicious triangle, broadcasters exploited ready-made productions, complete with their own stages, fan bases, and well-established stars: sports. Showcasing athletic competition was the new medium’s killer app. ‘For the next few years, at least, sports coverage will be far and away the most important single element in television programming’, the sports manager for Chicago’s WGN station wrote in 1948. ‘It’s a safe bet that up to 50 per cent of television hours, both live shows and films, will be in the field of athletics’.

The postwar rematch between heavyweight boxers Joe Louis and Billy Conn in June 1946 was an early success. Broadcast from New York’s Yankee Stadium, the fight reached north to Connecticut and south to Washington, DC. Fans ‘saw everything that went on in that 24-foot square, and they saw it in much better detail than most of the 45,266 persons who paid their way’, enthused a New Jersey sports reporter, putting the TV audience at about 100,000. ‘You could hear the roar of the crowd; the count of the referee; the ring of the bell’, he wrote. A Brooklyn bar owner who crammed in 150 fans to watch his television said he’d turned away at least 500 more.

Bars were critical to television’s early success. ‘More people see television sets in bars than would ordinarily see them in showrooms’, said the director of a Chicago station. ‘The bars are helping sell sets to private homes’. Although some bartenders complained that sports fans contented themselves with a single beer rather than multiple cocktails, most reported that television brought in more customers, ultimately raising sales. Sometimes a bar would place a large magnifying glass in front of the screen to make the broadcast more visible at a distance.

TV’s early appeal can strain the twenty-first-century imagination. Broadcasts were in blurry black and white, with pictures plagued by shadows, snow, and jitters. Screens were tiny, typically about 52 square inches, and a basic set cost around $325 (about $4,400 in today’s dollars). An exceptionally well-capitalized bar might splurge on the UST Tavern Tele-Symphonic, featuring a 25” x 19” screen, at a cost of $1,995, or nearly $30,000 today. But those were rare luxuries.

With their one-on-one action and limited ring size, boxing and wrestling were well suited to the small screen. New wrestling fans, particularly women, were a common trope in newspaper reports. ‘A lot of frail women are enjoying the sight of Danny MacShane cracking a man’s head into a steel post and having his head cracked in turn’, observed a sports columnist. Wrestling might or might not be a sport, but it was definitely entertainment.

Amid widespread fears of ‘juvenile delinquency’, television promised to keep kids out of trouble. ‘There’s no juvenile delinquency here’, proclaimed an ad for TV sets, portraying a family seated around their living room console. The tavern connection contradicted that wholesome image. Minors weren’t supposed to enter bars, but young sports fans often peered in the windows.

In response, churches, Boys Clubs, youth centers, and YMCAs began buying their own sets. On a summer evening in 1948, a Methodist church outside Philadelphia attracted a crowd of 125, mostly teenagers, to watch a baseball game between the Philadelphia Phillies and the Cincinnati Reds. Pastors around the country reported that TV was drawing in the kids. ‘Our church set is used primarily for hockey games, prize fights, and other sports events’, said a Presbyterian minister in Chicago. ‘We’re sorry we didn’t think of it before’.

Sports were so perfect for television that many feared the new medium would devastate ticket sales. ‘It’s inevitable that sports attendance will crash to a national calamity’, declared a columnist, reporting that boxing authorities in the nation’s capital were lobbying for legislation requiring broadcasters to cover match expenses. Football coach Rip Engle, then at Brown University and soon to move to Penn State, foresaw a shakeout. ‘I won’t be surprised if there are only ten college football teams left in a few years’, he said in 1949. ‘That’s what’s going to happen if games involving the big schools are widely televised’. Others predicted the death of minor league baseball. Why turn out for the local farm team when the big leagues were on TV?

Nonsense, said optimists. Veteran sports columnist Ed Danforth cited history and initial results. Baseball owners were always against change. ‘Look how they resisted the avalanche of money night baseball brought them’, he wrote. He ticked off the televised events of 1947 – the World Series, the Notre Dame–Army football game, the Joe Louis–Jersey Joe Walcott fight, the Sugar Bowl featuring the University of Georgia’s undefeated football team – and noted that they all set attendance records. ‘Big events played to capacity, whether they were televised or not’, he wrote. Television was ‘publicity for these sports and publicity that was PAID for at the source’. Television, he predicted, would only increase the popularity of sports.

Eight decades later it’s safe to say he was right. In 2024, US sports events attracted a staggering 292 million in-person fans, reports sports-marketing firm Two Circles. Far from shrinking to a handful of teams, college football games endure as a major cultural experience, and sell the most tickets of any US sport. At the same time, sports continue to support television in its many forms. Whether viewed on an enormous flat screen or a palm-sized phone, sports offer a compelling form of visual entertainment, with real stakes and unknown outcomes. And they still draw fans to bars.

Virginia Postrel is a contributing editor and author at Works in Progress.

When How Asia Works appeared in 2013, the prevailing mood was one of considerable optimism. China seemed a triumph of economic development. Between 1990 and 2013, China averaged a real annual growth rate of ten percent. It added almost half a billion urban residents and quintupled its manufacturing output. And other Asian economies were moving along comparable trajectories, if less spectacularly. Growth in India and parts of sub-Saharan Africa lent further weight to the idea that the developing world was at last catching up.

How Asia Works was Studwell’s theory of what drove this growth: land reform, export discipline, and states willing to impose hard constraints on capital. Beneath Studwell’s specific prescriptions lay a bolder claim: that countries were not condemned by geography, history, or culture to particular economic outcome, and a relatively small number of well-chosen policies could make an enormous difference. Tyler Cowen called it the best treatment of Asian industrial policy available. Noah Smith named it his favorite book on development. Bill Gates made the agriculture team at his foundation read it.

But a decade on, China’s growth has decelerated from over ten percent per year to around five. The rest of East Asia has settled into the one-to-three-percent range typical of mature economies. South and Southeast Asia continue to grow, but less spectacularly. And Africa, which once seemed poised to follow the same path, has not grown at all in per capita terms. Against this backdrop comes Studwell’s sequel, How Africa Works.

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Against Afro-pessimism

How Africa Works opens with an account of the continent’s historical constraints. Studwell responds to what can be called the Afro-pessimist view: that postcolonial Africa was at least as wealthy as East Asia at independence, and that the subsequent divergence was a story of misgovernment. This widely held position, he argues, is premised on a mistaken reading of the limited quantitative evidence, driven by mismeasurement and temporary commodity booms at the moment national accounts were first assembled. The supposedly high incomes per person in Africa don’t match, for example, with the fact that life expectancy was two years lower than in South Asia and between 6 and 20 years lower than the level of countries in East and Southeast Asia.

What Africa inherited at independence was considerably worse than what most other regions had to work with. Population densities were less than 25 percent of those in East and South Asia, driven by limited arable land, disease burdens, the enslavement and export of 12.5 million people, and even the abundance of crop-destroying elephants. This blunted incentives to build states capable of projecting authority over territory.

Colonial and postcolonial land policy concentrated wealth among large holders rather than diffusing it broadly. Ethnic and linguistic fragmentation locked post-independence politics into patronage networks. And on top of all that, Africa entered sovereignty as the world’s least educated region. Africans who attended school did so for half as much time as South Asians, the second least educated population in the world. Out of a population of 15 million, what is now the Democratic Republic of Congo had just 30 university graduates when Belgium departed in 1960.

But Studwell thinks that the essential preconditions for growth – literacy, governance, and especially population density – are gradually falling into place across much of Africa. Today, Africa is about where east Asia was in the 1960s and. What is needed, according to Studwell, is the disciplined application of the three-part model that already worked in Asia: redistributing agricultural land to smallholders, who farm more intensively and whose rising incomes create domestic demand; channeling state support toward manufacturers that must compete in international markets, rather than sheltering them behind tariffs indefinitely; and directing credit toward investment by suppressing consumption.

Studwell illustrates the argument with four African cases: Mauritius, Rwanda, Botswana, and Ethiopia, countries that have either begun this process, or, in the case of Mauritius, more or less finished it.

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The Asian model in Africa

The usefulness of the Asian model in Africa seems to hold up best for agriculture. Across the continent, governments often subsidized large farmers who were not necessarily more productive. In Ghana, for example, the Savannah Zone Agricultural Productivity Improvement Project was meant to benefit smallholders in the region, but only farmers with over 40 hectares and a tractor were eligible for subsidies.

Consolidation resulted in much more land held at medium-scale by urban elites, rather than by smallholders who had scaled up through accumulated expertise. But these farms weren’t necessarily more productive. Among medium-scale farmers in Zambia, only 11 percent of such farms were cultivated, compared to 91 percent of smallholder land.

When smallholder farmers did receive tenure security, training, and market access, they achieved remarkable successes. In Ethiopia, crop production more than doubled between 2004 and 2014, for example, and continued to grow during periods of crisis afterwards. Extreme poverty fell by over 25 percentage points between 2000 and 2015.

Beyond agriculture, the link between the East Asian model and Africa’s successes is harder to trace. Botswana is one of the richest countries in Africa, but didn’t start that way. It managed its diamond wealth with unusual discipline, by partnering with an experienced foreign firm, De Beers, on favorable terms, building reserves, investing in education and infrastructure, and maintaining a frugal bureaucracy. In negotiating with De Beers, the government was able to secure two thirds of the profits of diamond extraction. The returns were remarkable, as life expectancy rose from 48 to 65 in barely twenty-five years.

These are impressive achievements, especially given the country’s poor starting position. But Botswana neither supported smallholder agriculture nor created a manufacturing base. It devalued its currency to help beef exporters, not to spur industry. The government preferentially leased grazing land and directed subsidies to large farms. The result was a rapid concentration of livestock ownership: by the 1990s, five percent of the population owned half of all cattle, and nearly half of rural households owned none. Manufacturing subsidies were tied to headcount rather than exports, in a system that rewarded loyalty more than efficiency. It is telling that Studwell himself describes the country as a ‘gatekeeping state’ that managed wealth without knowing how to grow it.

Rwanda fits awkwardly too. It adopted something of the rhetoric of the Singaporean developmental state, attracted substantial foreign aid, and made itself, by the standards of the region, relatively easy to do business in. But with energy costs roughly five times those of neighboring Ethiopia, and a remote, landlocked position that gives access only to an extremely impoverished regional market, most of the resulting growth has come through tourism and services rather than manufacturing.

Mauritius comes closer to validating the model, given that it actually pursued export-oriented manufacturing and achieved real industrialization. But it did so at an early stage of development, as a small island economy. It never progressed far beyond basic manufacturing, pivoting instead to tourism and offshore finance, which happen to be precisely the sectors that Studwell, in How Asia Works, is most dismissive of.

The most compelling case, however, is Ethiopia. In 1991 it was by many reckonings the poorest country in the world. Under Meles Zenawi, the government consciously modeled its approach on the East Asian experience: devaluing the currency to support manufacturing, directing resources toward smallholders, channeling development finance into productive investment, and building, with some success, an administration oriented around growth rather than corruption.

In agriculture, the government expanded fertilizer distribution almost a thousandfold between 1995 and 1999. While droughts historically led to famines with death tolls in the hundreds of thousands, increased food reserves all but eradicated this concern.

But even in Ethiopia, the manufacturing story is thin. While massive industrial projects, including one of the largest dams in the world, reduced Ethiopia’s electricity cost to among the lowest on the continent, the results are limited. The successes he highlights are in low-value-added sectors like cement. Whether one looks at manufacturing as a share of output or at manufacturing value added per capita, there is little evidence that any large African country is genuinely following the East Asian path. The highest rate of manufacturing as a share of output for any African country with a population in excess of 10 million is Zimbabwe at 16 percent, compared with China’s 25 percent with 80 times the population.

‘It is likely that manufacturing – or its absence – will be the single biggest divider between African economic success stories and the nations that are left behind,’ Studwell writes at the end of chapter nine. But he spends remarkably little time in the book interrogating the extent to which that manufacturing growth is actually happening.

New headwinds to export-oriented manufacturing

Studwell contends that export-oriented manufacturing is the fastest route to broad-based growth, as it allows countries to build capacity on a scale that domestic demand could never absorb. Poor countries have an enormous pool of cheap labour, and that advantage can offset the productivity gaps, infrastructural deficiencies, and institutional weaknesses that would otherwise make competition with technologically advanced and better capitalized rivals impossible. This process tends to begin in the simplest industries. But expertise in one area of production generates spillovers into related ones, and the act of making simple goods builds the capabilities required to attempt more complex ones.

Even if Studwell’s view was once true, manufacturing-led growth has empirically become much harder. The evidence for this is visible in what economists have called premature deindustrialization, the phenomenon whereby poor countries are beginning to deindustrialize at substantially lower levels of manufacturing output, and substantially lower per capita incomes, than the West and other mature economies did.

If Studwell is right, African countries must now do to China what China did to the United States, Japan, and Europe. It is not obvious that the conditions for this are in place. While labor costs in Africa are between a half and a tenth of Chinese levels, this is far smaller than the fiftyfold difference between Chinese and American wages in 2000. All this must happen in competition with a country that has, by most measures, among the best logistics infrastructure in the world, very high labor productivity, and an industrial ecosystem without parallel.

China remains by far the world’s largest textile exporter, comparable to its position in 2008, even as it has become the largest exporter of smartphones, semiconductors, and electric motors and batteries. Even where countries like Bangladesh have found niches, they have often struggled to move into more complex manufacturing the way the East Asian countries once did.

Nor is China the only headwind. The pace of globalization has slowed, and poor countries may not be able to compete on labor costs alone, as manufacturing now generates far fewer jobs per unit of output than it did in the 1960s. Automation is eroding the advantages that cheap labor once conferred. In America, manufacturing output roughly quintupled between 1960 and 2015, while employment fell by nearly a third. The implication is that wage competition may no longer provide the foothold it once did.

Several of these difficulties may be reinforcing one another, and addressing them would require a degree of generosity from wealthy countries that is not obviously forthcoming. The current American posture – sweeping tariffs and sharp cuts to foreign aid – is closer to the inverse of what the East Asian model would seem to require than to anything that might help it along.

The wrong kind of development

Africa’s starting endowment was uniquely difficult. Studwell’s considerable achievement is to show that this need not be fatal: that a state genuinely focused on development can exist in the African context, and that the obstacles, formidable as they are, are not insuperable.

But the development he charts is rarely of the kind he wants. He is dismissive of the services-led growth that Rwanda has pursued, insisting that countries need to focus singularly on manufacturing, without recognizing that the path may be much harder than before. While countries continue to deindustrialize earlier than before, services offer viable, if unspectacular, alternatives, and India’s experience suggests that a services-oriented economy can sustain growth well above the African average, even if well below China’s.

The book is most persuasive as a historical and agricultural diagnosis.The account of colonial land policy, resource extraction, and patronage politics is careful, and the case for smallholder agriculture is the strongest thing in it. But the manufacturing argument is much thinner. Studwell never quite confronts the possibility that the East Asian path is considerably more difficult to follow today than when it was first travelled. That the honest answer to his book’s central question may be that nobody knows is not a failure of the argument so much as a reflection of the moment. But a book more willing to acknowledge this would have served its subject better.

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Saarthak Gupta is an analyst and quantitative researcher.

I recently published a long piece on urban government in the nineteenth century. I have always been interested in nineteenth-century architecture and urbanism, but I wanted to get into the details. I knew the Victorians built gigantic cities very quickly, and that the resulting urbanism was usually a lot better than what we have managed since 1945. But I wanted to study the institutional mechanics behind this. How were the streets planned? Who paid for the pumping stations? Who operated the trams?

Doing so has affected my opinions quite a lot. Here are a few examples:

1. It made me more pro-planning

Living in 2020s Britain, it is easy to become sceptical about planning. Our planning system enormously constricts housing supply, impoverishing the country. The housing and industrial buildings that do get built are often distributed around the country according to political imperatives rather than economic logic. It is natural to think that some sort of Hayekian emergent order would be preferable.

In the nineteenth century, however, we see planning performing its true function, solving the collective action problems inherent in urban life. Planned street networks turn out to be straightforwardly better than unplanned ones: the most planned street networks of the nineteenth century are some of the most successful systems in the history of the world. Urban transit systems also manifestly work better when they are planned by a single authority, and most nineteenth-century governments unified transit ownership accordingly (of which more below).

There is also the interesting fact that most nineteenth-century people voluntarily paid premiums to live in ‘covenanted’ neighbourhoods, which had forms of private-sector development control. This shows that they valued protection from disruptive development by their neighbours more than they valued the development rights foregone thereby.

Covenanting wasn’t very effective, but its prevalence reveals that there was genuine and broad demand for development control before the state started providing it. That doesn’t necessarily mean that such development control was morally good – maximising economic value need not realise the morally best outcome. Nor does it mean that the degree of development control we have today is value-maximising, even in the narrow economic sense. But it does mean that some level of development control has genuine popular support, and is not an extraneous state imposition.

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2. It made me care less about public or private ownership

I was aware that a lot of nineteenth-century infrastructure was built by private companies, and also that the Victorians were great infrastructure builders. In Britain, Parliament famously granted compulsory purchase powers for 9,500 miles of railways in 1846, 67 times longer than the catastrophic HS2 railway it is trying to build today. In America, most cities had superb public transport in the nineteenth century, actually much better than they do now. This suggested to me that private ownership worked a lot better than public ownership has.

Closer inspection reveals that the public/private distinction was not as important as I thought. Some nineteenth-century infrastructure was owned by private companies, but other infrastructure was owned by municipalities. Intracity transport and utilities in Germany were normally owned by municipal companies called Stadtwerke, and by the early twentieth century this was increasingly true in England too; in France they were also owned by the state, though operated by private concessionaires. There is no clear evidence that these systems were worse than the private franchises that predominated in the USA, and indeed the German Stadtwerke were often seen as world-leading.

The real differences seem to be elsewhere. Nineteenth-century urban infrastructure was funded almost entirely by user fees, not subsidies. It was far less price-controlled than modern infrastructure, so it was generally profitable to supply, and suppliers raced to meet rising demand. If they were particularly incompetent, they went bankrupt. This was true even if they were municipalities: if a city went bankrupt in the nineteenth-century, that was its problem, not the national government’s. These features generated a set of benign incentives that were surprisingly similar across both the public and private sectors, leading both to operate infrastructure fairly efficiently.

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3. It made me more interested in monopolies

We are all familiar with the idea that monopolies are bad, and no doubt they have some serious disadvantages. Because monopolies are not under competitive pressure, their incentives to be efficient are weaker, and because they almost never go bankrupt, they are not subject to selection effects. They may also have opportunities to exploit their market position to charge higher prices than is socially optimal.

Interestingly, however, the hugely successful urban infrastructure of the nineteenth century was nearly all operated by monopolies. A given city would usually have a single company operating its trams, another one operating its gas, another its water, and so on. Governments encouraged and sometimes explicitly required this. One justification for this was that infrastructure has so many positive spillover effects that monopolistic pricing was in fact efficient in this case: you want infrastructure to be more profitable to supply than it is in a competitive market, because it is just so good to have more of it. Another justification was that it led to a better coordinated network, rather than the chaotic duplication that occurred in competitive markets.

Some countries even found ways of partly replicating the pro-efficiency incentives and selection effects of competitive pressure. Under the French concession system, virtually all urban infrastructure was owned by the municipalities but operated by private companies. Municipalities awarded time-limited concessions to whichever company offered the best deal. This clever system, which still exists today, got many of the advantages of competition while preserving the advantages of infrastructure monopolization.

Samuel Hughes is an editor at Works in Progress. Follow him on Twitter.

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The problem with buses is that they are slow. For example, buses in New York City and San Francisco crawl along at a paltry eight miles per hour, only about double walking speeds in the fastest countries. There are lots of ways to speed up buses, including bus lanes and busways, congestion pricing, transit-priority signals, and all-door boarding. But one of the most powerful solutions requires no new infrastructure or controversial charges and has minimal cost: optimizing where buses stop.

Buses in some cities, particularly those in the US, stop far more frequently than those in continental Europe. Frequent stopping makes service slower, less reliable, and more expensive to operate. This makes buses less competitive with other modes, reducing ridership. This is why, despite having fewer bus stops, European buses have a higher share of total trips than American ones.

Bus stop balancing involves strategically increasing the distance between stops from 700–800 feet (roughly 210–240 meters; there are 3.2 feet in a meter), common in older American cities or in London, to 1,300 feet, closer to the typical spacing in Western Europe, such as in Hanover, Germany. Unlike many transit improvements, stop balancing can be implemented quickly, cheaply, and independently by transit agencies. By removing signs and updating schedules, transit agencies can deliver faster service, better reliability, and more service with the same resources.

American bus stops are too close together, driving low bus ridership

American bus stops are often significantly closer together than European ones. The mean stop spacing in the United States is around 313 meters, which is about five stops per mile. However, in older, larger American cities, stops are placed even closer. In Chicago, Philadelphia, and San Francisco, the mean spacing drops down to 223 meters, 214 meters, and 248 meters respectively, meaning as many as eight stops per mile. By contrast, in Europe it’s more common to see spacings of 300 to 450 meters, roughly four stops per mile. An additional 500 feet takes between 1.5 and 2.5 minutes to walk at the average pace of 2.5 to 4 miles per hour.

Frequent stopping is part of a strategy that maximizes coverage – giving everyone some access to the bus – even at the expense of overall ridership, which is largely a function of how useful the bus is relative to other transport options. In England, where 28 percent of all bus passengers are on concessionary fares for age or disability, Prime Minister Margaret Thatcher is supposed to have said, ‘If a man finds himself a passenger on a bus having attained the age of 26, he can count himself a failure in life’. This pattern, of only those without good alternative options riding the bus, is especially pronounced in the US. But close stop spacing creates problems.

Close stop spacing slows buses down. When a bus stops, it loses time as passengers get on and off the bus (dwell time). The bus also needs to decelerate and accelerate; it may need to kneel (hydraulically lower itself to the floor and back up again to let strollers, wheelchairs, and mobility vehicles on); it may need to leave traffic and return into traffic; and it may miss a light cycle (non-dwell time). Buses spend about 20 percent of their time stopping then starting again.

Slow buses make transit less competitive with driving and reduce the number of places riders can get to in a given amount of time, making the network less useful.

Labor is transit agencies’ largest cost. For example, close to 70 percent of the 2026 operating budget of Washington DC’s transit system will go toward labor and associated fringe benefits and overhead. Drivers are paid by the hour. Thus, slow buses increase the cost of running services, reducing the amount of service that agencies can run.

Close stop spacing also creates lower quality bus stops. In the US, the sheer number of bus stops means that agencies can’t invest meaningfully in each one. This results in many stops being ‘little more than a pole with a sign’, lacking basic amenities like shelters, benches, or real-time arrival information. Uneven and cracked sidewalks and a lack of shelter or seating present a particular challenge for elderly and disabled riders.

By contrast, a bus stop in a French city like Marseille will have shelters and seating by default. Higher quality stops in the city also include real time arrival information, better lighting for safety, level boarding platforms, curb extensions that prevent illegal parking at bus stops, and improved pedestrian infrastructure leading to the stops. Marseille is not a particularly wealthy French city, but because it has wider stop spacing and fewer stops, it can invest more money into each one.

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Stop balancing addresses these issues and more

Many of the solutions to these problems require money – running more buses, improving stop amenities, or upgrading signals – or the political will to take away street space for busways and transit lanes. But stop balancing can have a meaningful impact on these issues for a fraction of the price.

Bus stop balancing saves riders’ time. Riders save between 12 and 24 seconds per stop removed. San Francisco saw a 4.4 to 14 percent increase in travel speeds (depending on the trip) by decreasing spacing from six stops per mile to two and a half. Vancouver’s transit operator ran a stop-balancing pilot that removed a quarter of stops and saved passengers five minutes on average and ten minutes on the busiest trips. Portland saw a six percent increase in bus speeds from a project which increased average stop spacing by just 90 feet.

Limited stop services – aggressive forms of stop consolidation, effectively express buses – can see even more impressive savings. Los Angeles saw operating speeds increase by 29 percent and ridership by 33 percent on its Wilshire/Whittier Metro Rapid corridor. Washington DC pursued a limited stop service on its Georgia Avenue Line that increased speeds by 22 percent in the base and 26 percent in the peak. Colombia’s Bus Rapid Transit, based on this idea, is famous worldwide.

Because stop balancing speeds up buses it can actually increase the access of the transit network.

Access may be thought of in terms of the number of access points to the system, for example the number of bus stops or metro stations. But planners also think about access in terms of where the system can take you. This idea can be visualized as isochrones – shape maps that show the distance one can travel in a set time. By speeding buses up, stop balancing actually increases the number of destinations reachable within a given timeframe.

Stop balancing need not even reduce the number of access points much. Many North American bus stops have overlapping ‘walksheds’ (the areas within walkable distance of them) and are competing with each other. The combination of many stops and a street grid means that many riders have two or more stops that they can use, so that closing one only requires a marginally longer walk to the next.

A McGill study found that even substantial stop consolidation only reduced system coverage by one percent. A different study modeled a stop balancing proposal for San Luis Obispo, and found that even a 44 percent reduction in stops would have only a 13 percent reduction in coverage area. New York’s transit authority increased the distance between stops on a local route from ten to seven stops per mile (a 42 percent increase in distance between stops) but estimated that the average walking distance went up by only 12 percent.

Buses that move more quickly can traverse their routes more times per day. That means that achieving the same frequency requires fewer drivers as the speed of the journey goes up. Because labor is the largest expense of running a service, faster buses are cheaper to run.

You can determine the peak number of vehicles (and therefore the number of operators on a route) by dividing the time needed for a full round trip (including the layover) by the desired interval between every bus.

Layover varies by operating company but is usually a fifth of round trip travel time, subject to a minimum for short routes (something like ten minutes).

In Vancouver, stop balancing on one route saved the transit operator $700,000 CAD (about $500,000) in annual operating costs owing to peak vehicle savings. They estimate they will save a further $3.5 million each year by cutting stops across their 25 most frequent routes. In the study from McGill on Montreal’s operator, stop balancing had the potential to ‘save a bus’ (reduce the total buses needed each day by one) on 44 routes.

These savings can be reinvested to improve service frequency on those routes or elsewhere in the system. Or they can prevent a bus service from having to reduce frequency when facing budget cuts.

Beyond speed, stop balancing improves reliability. Each potential stopping point introduces uncertainty. When stops are closer together, this uncertainty multiplies by spreading passengers out between locations, making it difficult for agencies to provide accurate schedules.

Vancouver found that stop balancing improved the reliability of Line 2, especially on the slowest trips. This helps passengers plan their journeys and agencies maintain more accurate schedules, reducing the need for excess recovery time at the end of routes. If agencies want to maximize the benefit of stop balancing on reliability, they can incorporate passenger boarding variability into their stop consolidation program, as McGill University did in their proposal for Montreal’s Bus Network.

For passengers, improved reliability may be even more valuable than speed. Studies show that waiting time feels two to three times longer to passengers than in-vehicle time, and unpredictable waits feel longer still. By making bus arrival times more predictable, stop balancing directly addresses one of the most frustrating aspects of bus travel. Operators tend to favor these changes as well, describing stop balancing as helpful for staying on schedule.

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With fewer stops per mile, European agencies can create high-quality waiting environments that are prominently displayed on transit maps similar to rail stations. This enhances the visibility and permanence of the bus network, potentially supporting development along transit corridors. With stop balancing, North American agencies could do the same.

Bus stop balancing is a rare example of a transit reform that is at once fast, cheap, and effective. Fewer, better-placed stops can improve the speed and reliability of buses, while freeing up resources to improve the stops that remain. In practice, that can mean the difference between a service people tolerate and one they’re happy to use.

Nithin Vejendla is a transit planner.

In the summer of 1760, a French military officer named Nicolas Husson was brewing his Eau Médicinale, a medicinal draught that would eventually find its way across the Atlantic to Benjamin Franklin’s Philadelphia doorstep. Franklin, tormented by gout and desperate for relief, had heard whispers of this mysterious European remedy. He could not have known that he was importing one of humanity’s oldest medicines, recorded as a poison roughly around 1500 BC, and that it would, more than two centuries after Franklin’s death, prevent heart attacks in American patients.

Colchicine is extracted from the autumn crocus, a purple flower native to Europe, and its story spans three millennia of medical history. Today, it stands as one of the few substances that can claim both ancient pedigree and modern FDA approval, having navigated the treacherous waters of contemporary pharmaceutical regulation to emerge as a treatment for gout, rare genetic diseases, and cardiovascular conditions.

The origin story

The earliest surviving reference to colchinine appears in the late fourth century BC, when botanist Theophrastus wrote of a deadly plant called ephemeron, meaning ‘one-day killer’. By the first century AD, Dioscorides had given it the name that stuck: kolchikon (‘plant from Colchis’) and later called colchicum, warning it ‘kills by choking, similar to mushrooms’. For the next 1,500 years, Western medicine treated colchicum strictly as poison. Medieval herbalists warned against its use; renaissance physician John Gerard declared its roots ‘very hurtfull to the stomacke’.

This reputation began to shift in the late eighteenth century, when French army officer Nicolas Husson created a wildly popular secret gout remedy called Eau Médicinale. Selling for the equivalent of 22 shillings per tiny bottle, then a fortune, the mysterious potion baffled Europe’s chemists, who guessed its active ingredient might be everything from white hellebore to digitalis to tobacco.

In 1814, Englishman John Want finally solved the puzzle through a combination of scholarly research, chemical analysis, and possibly industrial espionage, reportedly obtaining information through a nursemaid who had previously worked for Husson. Want identified colchicum as the secret ingredient and published his findings in medical journals, sparking a revolution in gout treatment. The plant physicians had avoided for nearly two millennia had suddenly become their most effective remedy for gouty attacks.

In medicine, as in chemistry, dosage makes the poison. Colchicine binds to an essential protein that forms the skeleton of cells – tubulin – and prevents the formation of microtubules, which make up the scaffolding that enables everything from cell division to the movement of cells toward sites of injury. By disrupting this process, colchicine causes cascading effects. Neutrophils, which are the body’s first-line inflammatory responders, find themselves unable to move, to attach to the walls of blood vessels, or to release critical signals that help in wound repair and inflammation control.

What makes colchicine compelling as a drug is that it accumulates specifically in neutrophils, which are less able to pump the drug out as they have limited quantities of a protein, P-glycoprotein. This makes the drug able to reduce inflammation at doses that have minimal side effects, even though its ‘therapeutic window’, the dose range at which it can be safely used, is narrow.

The same mechanism it uses to halt inflammation also explains the drug’s most notorious side effect: by blocking microtubules, colchicine interferes with cell division, which disrupts rapidly dividing tissues in the gut and bone marrow. The gut relies on constant cell renewal to maintain its protective lining, so when this process is disrupted, it suffers intestinal inflammation and damage. Hence the legendary diarrhea that has plagued colchicine users for millennia.

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The clinical renaissance

Despite centuries of use, rigorous clinical evidence for colchicine remained scarce until recent decades. The modern renaissance began in the 1970s, when doctors discovered that daily colchicine could almost entirely prevent the recurrent fever and inflammatory attacks of Familial Mediterranean Fever, a rare inherited autoinflammatory disease, and help prevent secondary amyloidosis, an often fatal complication of the disease where abnormal proteins accumulate in vital organs. This finding established that colchicine was not just an old gout remedy but also a precise anti-inflammatory drug.

The pivotal moment was the AGREE trial, published in 2010, the first modern randomized controlled trial of colchicine in acute gout attacks. The study revealed that a low-dose regimen – 1.8 milligrams total over one hour – was nearly as effective as the traditional high-dose regimen of 4.8 milligrams over six hours in aborting gout attacks, while producing far fewer toxic side effects.

More surprisingly, colchicine has found new life in cardiology. Reasoning that the drug’s anti-inflammatory properties might benefit patients with pericarditis (inflammation of the lining around the heart), Italian researchers conducted a series of landmark trials beginning in 2005. The ICAP trial, published in the New England Journal of Medicine in 2013, showed that adding colchicine to conventional therapy halved the rate of pericarditis recurrence, from 37 to 16 percent. The drug’s impact on pericarditis is an example of successful drug repurposing: finding new uses for established drugs.

The cardiovascular applications expanded further as researchers investigated colchicine’s potential benefits in treating patients with coronary disease. The LoDoCo2 and COLCOT trials demonstrated that a daily 0.5 milligram dose could reduce cardiovascular events, such as heart attacks and strokes, by around 30 percent in patients with stable coronary disease and by around 23 percent after myocardial infarction.

The cost of compliance

Despite its eventual success, colchicine’s drug’s regulatory journey has also become a cautionary tale about the unintended consequences of pharmaceutical policy.

For decades, colchicine existed in a regulatory gray area: widely used but never formally approved under modern FDA standards. It was available from multiple generic manufacturers at remarkably low cost, often mere pennies per pill.

This changed with the FDA’s Unapproved Drugs Initiative, launched in 2006 to bring older, unapproved drugs into compliance with contemporary standards of safety and efficacy. The initiative offered companies a period of market exclusivity, in return for conducting rigorous studies to confirm their effects and thus secure FDA approval for these legacy drugs. Philadelphia-based URL Pharma identified colchicine as a prime opportunity: the drug was widely prescribed, particularly by rheumatologists, and its safety risks at higher doses were well-documented. This suggested that a modern approval could both improve patient care and prove commercially valuable.

URL Pharma, through its subsidiary Mutual Pharmaceutical, conducted the required studies, including absorption and metabolism tests and the AGREE trial in acute gout. Based on these data, the FDA officially approved colchicine for the first time in July 2009, under the brand name Colcrys. The approval covered two indications: the treatment of acute gout flares and the prophylaxis of Familial Mediterranean Fever. Notably, because  FMF qualified as a rare disease, Colcrys was granted seven years of orphan exclusivity, an extended period to reward the development of drugs for rare diseases, and FMF patients faced the $4.85‑a‑pill brand until 2016, even after cheaper generics began reentering the gout market. Meanwhile, the data on gout, not a rare disease, earned URL only a three-year term for that usage.

Critically, upon approval, the FDA ordered all other manufacturers to cease marketing unapproved colchicine tablets, effective October 2010. URL Pharma had secured a complete monopoly on oral colchicine in the United States.

The regulatory victory came with a cost to patients. Overnight, colchicine prices soared from approximately ten cents per tablet to five dollars, transforming an affordable generic into a luxury medication.

The pricing strategy sparked fierce political backlash. In 2011, Senator Sherrod Brown of Ohio, along with Senator Herb Kohl of Wisconsin and Representative Henry Waxman of California, publicly accused URL Pharma of price gouging and exploiting the Unapproved Drugs Initiative. If three million gout patients required daily therapy at the new pricing, the annual cost would approach eleven billion dollars. This was wildly disproportionate to the tens of millions URL Pharma had spent on clinical trials to secure approval for a drug that had been in continuous use for millennia.

URL Pharma defended the pricing by pointing to patient assistance programs and emphasizing the value of ensuring a uniform, FDA-vetted product with updated safety guidelines. The company noted that the approval process had led to important safety improvements, including clearer warnings about drug interactions and revised dosing guidelines for people with kidney problems, changes that could prevent potentially fatal complications. The FDA and rheumatology experts acknowledged these safety benefits, though many questioned whether they justified the price increase.

The controversy intensified when lawmakers discovered that over twenty generic manufacturers had been producing colchicine before the Colcrys approval, and had all been forced to cease production. The Unapproved Drugs Initiative, originally conceived as a program to improve drug safety and quality, was increasingly criticized as a mechanism that allowed companies to game the system, improving drug regulation at the expense of patient access.

Despite its controversies, Colcrys quickly became a lucrative product, with annual sales reaching approximately $430 million in 2011. This success attracted attention from Takeda Pharmaceutical, Japan’s largest drugmaker, which agreed to acquire URL Pharma for $800 million dollars upfront in April 2012. For Takeda, the acquisition offered immediate revenue boost and strategic synergy with its existing gout portfolio that included Uloric, a drug for chronic gout management. The deal allowed Takeda to offer a complete suite of gout therapies: Uloric to lower uric acid levels and Colcrys to prevent acute flares.

The monopoly eventually eroded as competitors found ways to challenge Colcrys’s exclusivity. In 2014, Hikma Pharmaceuticals obtained FDA approval for a colchicine capsule called Mitigare, relying on published literature rather than conducting new trials. In response, Takeda sued both the FDA and Hikma, unsuccessfully, arguing that the approval violated Colcrys’s exclusivity rights. By 2015, the temporary exclusivity had run out, and generic colchicine tablets returned to the US market, though prices remained several times higher than the pre-2009 generic cost.

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The future

The Colcrys episode had lasting implications for pharmaceutical policy. The pricing controversy, along with similar cases involving other drugs brought under the Unapproved Drugs Initiative, led to growing criticism of the program. In late 2020, the Department of Health and Human Services announced it was ending the initiative altogether, partly due to the cost inflation seen with colchicine and other drugs. The program had achieved its stated goal of improving drug safety and quality, but at a cost that many deemed unacceptable.

There are likely many more long-standing generic drugs that could be repurposed, but at the moment, there is little incentive to invest in the research and trials needed to discover them. Many of the problems with Colcrys could have been avoided with different policy designs, such as shorter exclusivity periods, prizes, or vouchers.

Colchicine’s evolution from a crude plant extract to a precision anti-inflammatory drug is not an unusual one, as various ancient herbs have been refined and improved with better tools and understanding. But its story shows how specific policy decisions can change the calculus for investment and pricing, resulting in unintended consequences that affect the lives of millions of patients.

Alex Kesin is a biotech writer. Follow him on Twitter.

Soap is an ancient innovation: a Sumerian text from around 2200 BC gives a basic recipe for making soap. But early soap was mostly used to wash clothes, and sometimes for bathing. For kitchen dishes and eating utensils, people made do with cheaper and more readily available materials.

Sand has been used to scour dishes for thousands of years. It’s easy to find and great for physically scrubbing food detritus off of wooden or metal dishes. Many other natural abrasive substances have been used too. In India, traditional dishwashing materials ranged from jute fiber to rice husk to eggshells. In England, the horsetail plant, Equisetum hyemale has been known as ‘scouring rush’ or ‘pewterwort’, and John Gerard’s 1597 botanical reference book explains that the plant’s roughness ‘is not unknowen to women, who scowre their pewter and wooden things of the kitchen therewith’.

When scouring with physical abrasives was not enough to remove grease, the women described by Gerard could turn to the chemical properties of ash. Wood ash contains potassium carbonate. When it’s leached in water, it creates lye, an alkaline solution of potassium hydroxide, which can be combined with an oil or fat to form soap. In essence, washing a greasy dish with ash and water creates soap on a micro scale. The use of wood fires to heat homes and cook food meant that ash was available in abundance.

That would change in the early modern period, when households started switching from wood to coal. In London, the shift began around 1570 and was almost complete by 1600, making wood ash more scarce. Without ash to cut the grease, Londoners began using ready-made soap to wash dishes.

Soap introduced a new requirement: hot water. Hot water is helpful when washing with ash, but not needed when scouring with sand. In fact, Ruth Goodman, in her book The Domestic Revolution, reports that for sand-scouring, cool water actually works better. The soaps available at the time, by contrast, only worked effectively when activated by hot water. So the new soap-and-hot-water dishwashing regime was both prompted by the switch to coal and fueled by it.

In the mid-nineteenth century, inventors made the first steps towards mechanizing dishwashing. In the United States, the first dishwasher patent was granted in 1850. This dishwasher (or ‘table furniture cleaning machine’, as its inventor called it) was a large tub with a rotatable dish rack in one half and a paddle wheel in the other half. The user would load the dishes, heat up some water separately, pour the hot water into the machine, and then crank the paddle wheel with one hand to throw water onto the dishes, while their other hand (or an assistant) spun the dish rack. This was an awkward process, and probably also ineffective – the water splashed onto dishes with the little scoop wouldn’t have enough power to replace scrubbing.

In the next patent for a dishwasher, granted 13 years later in 1863, inventors Gilbert Richards and Levi Alexander proposed a stationary dish rack around the edges of a tub, with curved paddles attached to a vertical shaft in the middle. The operation would be similar: heat water, pour it into the tub, hand-crank the paddles to splash water onto the dishes.

Richards and Alexander must have realized that this process couldn’t fully replace scrubbing, because their patented machine also had a little side compartment where the operator could scrub one dish at a time using a completely separate mechanism: with one hand, holding the dish up to the revolving sponge-arms; with the other, cranking the handle to spin the sponges.

Their design was the beginning of a flurry of new dishwasher patents. Between 1863 and 1888, the US Patent Office granted more than 60 patents for dishwasher designs and improvements. Many of the designs were remixes of the same key elements: dish racks, tubs of water, various hand-cranked mechanisms for splashing the water up onto the dishes. Some designs involved submerging the entire dish rack, and spinning it around underwater to clean the dishes. Others expanded on the ‘revolving sponge’ idea: for example, a machine that sandwiched a plate between two brushes, and dipped the whole plate-and-brush sandwich underwater while the brushes rotated in opposite directions. Still others invoked centrifugal force, conveyor belts, or springs.

None of those designs caught on. Instead, the first commercially successful dishwasher, created and sold by Josephine Garis Cochrane, used jets of pressurized water to clean the dishes. Although Cochrane was not the first to propose using water jets, she was granted seven US patents for various other dishwasher designs and improvements. Her first patent, in 1886, covered the idea of using two separate water systems: one for soapy water, and one for clean hot water to rinse away the soap. A small lever on the outside of the machine controlled whether it was in washing mode or rinsing mode, engaging the appropriate pump and channeling water to return to the appropriate tank to be reused.

Unlike previous dishwasher inventors, Cochrane manufactured her machine at scale and built a company. She established her factory near Chicago, and traveled throughout the Midwest to demonstrate and sell the machines. The 1893 Chicago World’s Fair was a great showcase for her dishwashers: they were on display in the Machinery Hall and in the Women’s Building, and they were in use behind the scenes at the fairground’s restaurants. They were also installed in many of the hotels that Chicago built for World’s Fair visitors.

In fact, although Cochrane had imagined her dishwasher as an aid to women managing households, she found that restaurants and hotels were her core customers. The dishwashers were expensive for a household: we have records listing them for $350 in 1911 (equivalent to about $12,000 today). Restaurants and hotels, with their industrial quantities of dishes to wash, benefited more from the purchase.

Access to utilities was also a factor. Cochrane’s first patent described a machine that the user pours hot water into, but by 1903 her dishwasher received its hot water from a hot-water-supply pipe. Similarly, the first design was powered by hand, but by 1894 the machine was ‘driven by an engine or any other suitable motor or power’. These changes made the machines easier to operate and more effective, but were also prohibitively expensive for many households. When Cochrane was selling her dishwashers around the turn of the century, fewer than ten percent of American homes had electricity, and even fewer would have had electricity, piped hot water, and the money for the up-front cost of a dishwasher. With all of these barriers to adoption, the dishwasher didn’t become a common appliance during Cochrane’s lifetime.

But by 1925, electricity had reached more than half of American homes, and by the 1960s it was close to universal. Over the following decades, dishwashers were widely adopted. They’re still not nearly as ubiquitous as electricity, but the share of homes with dishwashers has grown from about 7 percent in 1960 to about 73 percent in 2020.

Alongside other household appliances and cultural shifts, dishwash­ers have allowed Americans, especially American women, to spend significantly less time on housework. In 1965 (when 14 percent of families had dishwashers), the average married American woman did 34 hours of housework per week, while the average married man did 5. For comparison, in 2010 (when 70 percent of families had dishwashers), the average married man did 10 hours of housework per week, and the average married woman did 18. This certainly shows shifting gender dynamics, but it also shows that a typical married couple spends 11 fewer hours per week on housework than they did in 1965.

In addition to saving time, modern dishwashers save water and energy. Studies collected by a group of California utilities companies found that washing dishes by hand uses about three times as much energy, and seven times as much water, compared to washing them in a dishwasher. Environmentalists now aim to convince more people to buy dishwashers, use them regularly, and trust them enough to load the dishes without pre-rinsing.

This is a case where resource efficiency happily goes hand-in-hand with domestic ease: we don’t have to gather horsetail for scouring, we don’t have to heat water over a coal fire, and we don’t even have to rinse our dishes before we load the dishwasher.

Erin Braid is a writer and researcher.

Charles Darwin saw evidence of evolution in all the animals and plants he studied. He boxed, bottled, and pressed thousands of specimens: mockingbirds and iguanas from the Galápagos, corals from the Indian Ocean, lichens and seaweeds from Tierra del Fuego, and even the skull of an extinct giant sloth from Argentina. He turned the gardens and greenhouses at Down House into personal laboratories for breeding pigeons, fertilizing orchids, and dissecting barnacles.

But one form of life was conspicuously absent from Darwin’s work: microorganisms.

Darwin might be impressed at how these invisible creatures have come to reinforce and shape his theory. Over the past four decades, scientists have used microbes to reproduce evolution under laboratory conditions and test hypotheses about how natural selection works, in evolution experiments that have led to surprising new discoveries.

Natural selection is driven by a few basic processes: births, deaths, mutation, selection, and competition. Individuals better adapted to their environment tend to survive and reproduce more successfully than their competitors, passing their advantageous traits down to their offspring. Over generations, beneficial traits increase in frequency in the population until traits that were once found in just a few are shared by many.

In the large organisms Darwin studied, natural selection happens over many thousands of years. This is because these species’ reproductive cycles are long and those with the most adaptive genes do not have many more children than those with the least. More time between generations means more time is needed for genes to spread through a population. However, in species with shorter generation times, it can progress much more quickly.

For example, elephants have a generation time of 20 to 30 years, while the fruit fly grows from egg to adult in a mere ten days. Tens of generations of fruit flies can pass in a month or two, and one elephant takes up as much space in a lab as millions of fruit flies. Geneticists have a long and successful history using flies to study natural selection, but large-scale evolutionary changes, such as the origin of new functions and new species, typically require thousands of generations. Even with fruit flies, experiments attempting to capture this spread of evolutionary time could take centuries.

William Dallinger, a minister and amateur scientist, hypothesized in 1880 that microorganisms might make evolution experiments possible. A population of E. coli can experience seven to ten generations overnight. An individual E. coli bacterium is about 100 times smaller than the width of a human hair, and half a cup of broth can hold billions of them. Larger populations contain more genetic diversity than smaller ones, thanks to random mutations during the DNA replication process. They are therefore more likely to include at least one individual with mutations that make them better able to survive a changing environment.

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Dallinger tested his hypothesis by growing water-dwelling microbes called flagellates in a custom-built copper incubator, exposing them to progressively hotter and hotter water. After much trial and error, his evolved flagellates were thriving at temperatures lethal to ordinary ones (and when they were put back into lukewarm water, they died). Today’s evolution experiments operate on similar principles.

The longest-running and most celebrated of modern evolution experiments is the appropriately named Long-Term Evolution Experiment (LTEE). Started by Richard Lenski in 1988 at the University of California, Irvine, and continuing in the hands of Jeffrey Barrick at the University of Texas at Austin, the LTEE has been running nearly continuously for 80,000 generations of E. coli over nearly 40 years. This is equivalent to two million years of human evolution.

The experiment began when 12 genetically identical populations of E. coli were grown in liquid medium. Every day since then, one percent of the previous day’s culture has been transferred into fresh medium. The medium is a dilute sugary solution limited in glucose, which E. coli uses as its primary carbon source. After about seven generations the glucose runs out and the bacteria stop growing until the next day, when they are transferred into fresh medium. Like Dallinger’s warm water, glucose-limited media is a selective pressure on the microbes, spurring the evolution of adaptations that compensate for a lack of their preferred food source.

Every 75 days (about 500 generations), a portion of LTEE’s cloudy soup of bacteria is stored in a minus-80-degree-centigrade freezer. These remain as frozen fossil records that can be used for direct comparison to their descendants.

The LTEE has shed light on many unanswered questions about the dynamics of evolution, and experimentally validated long-running speculations. Do species improve indefinitely in a constant environment or will they stop at some maximum level? By comparing evolved E. coli with their ancestors, LTEE found that the rate of adaptation to the environment slows over time, but doesn’t plateau. Even after tens of thousands of generations in a stable laboratory environment, natural selection seems to be able to continuously eke out improvements.

Another major finding was that not all replicate populations follow the same evolutionary trajectory. In one replicate, named Ara-2, the population diverged into two coexisting lineages: one that rapidly consumes glucose and afnother that feeds on a byproduct of glucose metabolism called acetate. From a single population came a community of two.

But the most surprising finding was the observation that after about 31,000 generations, a different replicate, Ara-3, gained the ability to grow on citrate. Natural E. coli can’t metabolize citrate—in fact, it’s one of the defining features of the species—so the emergence of a strain which thrives on this carbon source could represent an entirely new species.

Simple, long-running experiments like the LTEE show what can be learned about evolution if given enough time. Other scientists, such as Roy Kishony, at Technion-Israel Institute of Technology, further accelerate the rate of evolution in their experiments by combining the intense selective pressure of antibiotics with cleverly designed experimental apparatuses. Kishony’s group has designed many selection devices, often with elaborate names like ‘morbidostat,’ but the most well-known is the Microbial Evolution and Growth Arena (MEGA) plate.

The MEGA plate is a two-by-four-foot rectangular petri dish that is divided into nine bands of gelatinous nutrient agar. The outermost bands have no antibiotics; the next inward has an antibiotic concentration barely high enough to kill E. coli; the bands inward have ten times that concentration, then a hundred times; and the middle band has the same antibiotic concentrated to 1,000 times. Spread over the top of each layer of agar, the bacteria can swim in.

At the start of the experiment, a drop of E. coli is placed on the outermost band. The bacteria multiply and spread right up to the boundary with the first antibiotic concentration band, but no further. The starting E. coli isn’t antibiotic resistant, and neither are most of its descendants. But thanks to random mutation a select few are, and these are able to cross the barrier and fan out into the next band. The descendants of these mutants themselves spread and mutate, crossing bands—or getting stuck behind them—until some reach the band that’s 1,000 times more concentrated than the first. The whole process takes just ten to twelve days, and can be recorded by a camera mounted above the plate to track the spread of each lineage.

We already knew that higher levels of resistance usually come at the cost of slower growth. With the MEGA plate, this evolutionary trade-off has immediate consequences: more-resistant but slower-growing strains get boxed in and trapped behind less-resistant but faster-moving ones. This is one reason why evolution may not always favor the most antibiotic-resistant bacteria.

No individuals in the initial population of E. coli could jump directly from the antibiotic-free agar to 1,000-times-concentration antibiotics. Adaptation to such a different environment is possible, but requires several specific mutations in multiple genes and these are extremely unlikely to occur together by chance under normal conditions. But when evolution is steered in that direction by a gradual gradient of intermediate concentrations, the E. coli reliably get there in a matter of days.

Evolution experiments are easily adaptable to new technologies. Whole-genome sequencing, for example, has been an enormously powerful tool for evolutionary biologists because it enabled them to connect changes in phenotype (observable characteristics, like antibiotic resistance) with genotype (underlying genetic mutations). New technologies can not only be used with future experiments, but also the frozen stocks from previous generations. Whole-genome sequencing may not have been feasible when the LTEE began, but 20 years later the researchers are able to sequence the genomes of the initial frozen E. coli generations just as easily as they could the latest generation. Whatever the next great technological revolution in biology may be, freezer shelves full of bacteria stand ready to be studied in a whole new light.

Today, labs around the world are running evolution experiments of all shapes and sizes, each using microbes to understand a specific facet of evolution. Some study predation by mixing predator and prey species, and observing how each adapts to the other. Other groups have studied starvation by growing bacteria for long periods of time without the addition of any nutrients, nor the removal of dead cells. And by selecting yeasts for increased size, others have directed the evolution of macroscopic multicellularity from single-celled ancestors.

Evolution by its nature takes time. With microbes we’ve been able to condense it down to more manageable timescales, but even 80,000 generations is a blip on the evolutionary clock. As these experiments continue to run, the more we’re sure to learn from them.

Kevin Blake is scientific editor at Washington University in St Louis.

But what makes this Nobel win so remarkable, and so pleasantly surprising, is that Mokyr’s work is not the kind that is often published by economics journals, or even many economic history journals anymore. Over the past few decades, journal editors and peer-reviewers have increasingly insisted that papers must present large datasets that have been treated using complex statistical methods in order to make even the mildest claims about what caused what. Although Mokyr is a master of such methods – he was one of the early pioneers of economic history’s quantitative turn – the work for which he has won the prize is firmly and necessarily qualitative.

Mokyr’s is the economic history that gets written up in books – his classics are The Lever of Riches, The Gifts of Athena, The Enlightened Economy, and A Culture of Growth – and in readable papers shorn of unnecessary formulae. His is history accessible to the layman, though rigorously applying the insights of economics. The prize is a clear signal from the economics profession that it doesn’t just value the application of fancy statistical methods; its highest prize can go to works of history.

Whereas most of the public, and even many historians, think of the causes of modern economic growth – the beginnings of the Industrial Revolution – as being rooted in material factors, like conquest, colonialism, or coal, Mokyr tirelessly argued that it was rooted in ideas, in the intellectual entrepreneurship of figures like Francis Bacon and Isaac Newton, and in the uniquely precocious accumulation in eighteenth-century Britain of useful, often mechanically actionable knowledge. Britain, he argued, through its scientific and literary societies, and its penchant for publications and sharing ideas, was the site of a world-changing Industrial Enlightenment – the place where progress was thought possible, and then became real. Indeed, this publication – Works in Progress – was itself founded on the principle that Mokyr identified, that airing and sharing useful knowledge, and of the idea of progress, are what makes all the difference.

One of Mokyr’s big early insights, first appearing in Lever of Riches, was that many inventions could not be predicted by economic factors. Society could enjoy remarkable productivity improvements from simply increasing the size of the market, leading to division of labour and specialization – what he labelled ‘micro-inventions’ – in the vein popularised by Adam Smith. But this could not explain an invention that appeared out of the blue, like Montgolfier’s hot air balloon in the 1780s – what he called a ‘macro-invention’, not for the magnitude of its impact, but for its novelty. Macro-inventions often required further development to make them important, but the original breakthrough could not be predicted by looking at changes in prices or the availability of resources. It ultimately came down to advances in our understanding of the world. Mokyr put the Scientific Revolution – and the factors that contributed to it – on the economist’s map.

Mokyr also looked at the relationship between different kinds of knowledge. A scientist might know, through observation, that the air has a weight. A craftsman might know, through long training and experience with glass, how to make a long glass tube. Each could not get far alone. But combining them, by creating means to ensure that scientists and craftsmen talked with one another and collaborated – through connecting their propositional and prescriptive knowledge, their heads and hands – very quickly led to the invention of thermometers, barometers, and much more besides, in an ever expanding field of knowledge. What Mokyr taught economists is that it’s not knowledge per se that makes the difference, but the way it is organized. Much of his later work has shown just how deep a pool Britain’s scientists could draw on, of skilled artisans.

In a way, Mokyr himself has practised what he preached. As editor of Princeton University Press’s book series on the Economic History of the Western World, Mokyr has for decades provided an all-important space for economists and historians to write the kinds of research that would never have been publishable in economics journals – including of explanations of the Industrial Revolution that are the polar opposite to his own. He helped keep the connection between history and economics alive.

Mokyr’s case for the primacy of knowledge and ideas was not an easy one to make to economists. They are naturally drawn to data that can be counted, and not to narrative, often no matter how well evidenced. But it appears that Mokyr’s persistence, elevated by his infectious, irrepressible sprightliness, has paid off. His prize is a long overdue recognition of the history in economic history, and a remarkable testament to the power of ideas to persuade.

Anton Howes is a historian. He writes Age of Invention.

Toronto has one of the world’s great commercial downtowns. Two metro lines, eight suburban heavy railways, an extensive bus system, a highway, and North America’s greatest surviving tram network all converge on a tiny area by the shores of Lake Ontario. Hundreds of thousands of commuters pour into the downtown every day, filling the great towers that line its nineteenth-century streets.

As with many downtowns, this causes congestion. Streets and pavements are thronged at peak times. Bicycles, pedestrians, cars, trams and buses compete for scarce space. As with all traditional radial transport systems, there is an enormous concentration of movement in a tiny area. Pedestrians make slow progress across the urban fabric, stopping every block for a minute or two to wait to cross the road.

In the early twentieth century, Toronto’s businesses developed a novel response to this. They began to create pedestrian tunnels from their offices to the metro stations so that their employees could flow in smoothly, avoiding the congested streets (and, in winter, the cold). Shops quickly started to be added. After a few businesses had done this, a ‘network effect’ emerged whereby other businesses started to add their own tunnels to the system, benefiting from the existing tunnels while also making them more useful. It became routine for downtown developers to tie new office blocks into the network. Over many decades, a sort of ‘pedestrian metro’ emerged.

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Known as the Path, the network today stretches for more than 30 kilometers, linking nearly all central metro and railway stations with many of the major office buildings. Although the Path forms a unified network, it is not in unified ownership: it is divided into some 35 chunks, each of which is still owned and managed separately by descendants of whichever business originally contributed it. Many branches of the Path thus terminate in the lobbies of office buildings, with the curious result that these grand spaces function as metro entrances for the general public. The municipal authorities play only a limited regulatory role.

The Path is unlike the gloomy and malodorous underpasses with which most of us are familiar. It is expensively decorated and feels like a high-end shopping mall, which in a way it is. It is extremely clean and closely policed by dozens of private security teams. Until recently, it was thronged with shoppers: this use suffered in the pandemic and has not wholly recovered, but the Path is still used for its original commuting purpose by hundreds of thousands of people every weekday.

Urbanists are normally sceptical about pedestrian tunnels, fearing that they kill off street life. This is a reasonable concern and may often be a decisive reason to avoid them. But in a downtown like Toronto’s, human density is so enormous that this worry seems exaggerated. The pavements of Toronto are still busy, even on weekends, despite hundreds of thousands of pedestrians going underground. The carriageways are still congested with vehicles. It is facile to see this as a simple trade-off between walking and driving. The Path frees up space for bicycles, buses and trams as well as cars. It complements the metro and railway system by shaving off five minutes from the station-to-office walk. The Path may well be substantially net positive for a radial system of public and active transport.

The Path is also interesting for what it tells us about transport economics. It is exceptionally unusual in forming an integrated network without having been developed by a single body. The equivalent would be a railway that was created piecemeal by uncoordinated landowners, with each adding small chunks until it stretched from one city terminus to another – a thing which, to my knowledge, has never happened.

There are at least two reasons for the Path’s distinctive economics. First, pedestrian tunnels are clearly exceptionally valuable to individual landowners, such that they are prepared to bear the entire cost of providing transport infrastructure from which other landowners could subsequently benefit. It wasn’t necessary for the whole network to exist in order for the first landowners to get started: in downtown Toronto, pedestrian tunnels are so good that there was no first-mover problem. This is generally untrue of transport infrastructure: for example, any given stretch of a railway is virtually useless until the entire railway is finished, which is why public authorities usually have to plan entire railways from the start.

Second, pedestrian tunnels have an extremely high upper limit on how many people they can take. As a famous 2003 advert illustrated, a human travelling in a vehicle requires space for their vehicle as well as themselves. A human travelling by foot does not, and is thus much more spatially efficient. This means that additional chunks can be added to the Path without normally creating ‘pedestrian jams’ in the existing stretches: there is nearly always space for more people. This is often untrue for roads and railways, where planners constantly worry that adding additional branches will cause congestion on central trunks.

This means the Path’s model isn’t easily replicable for other transport modes: roads and railways really do need unified planning. But it isn’t clear why pedestrian metros should be impossible in other cities. In fact, to some extent, they do exist. Montreal has a similar system, while Tokyo, Osaka, Seoul, Hong Kong, Singapore and Houston have systems that resemble the Path in some respects. A few European cities also make considerable use of pedestrian tunnels, including Helsinki, Stockholm and Munich.

Overall, though, the list of pedestrian metros is short. It would be interesting to investigate why this is. Why aren’t there pedestrian metros in Manhattan, Boston, Shanghai, Vancouver, Paris and the City of London? Is there some reason why the economics are different? Is the soil already too full of tunnels and utilities? Or are there regulatory constraints that might, in principle, be fixable?

Downtowns were one of the great triumphs of nineteenth-century urbanism. Where they have not been destroyed by cars and modernism and civic mismanagement, they remain enormously valuable urban forms today. But they present, and have always presented, unique and interesting transport problems. Maybe pedestrian metros have a role to play in solving them.

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Samuel is an editor at Works in Progress. He focuses on urbanism and cities. He has previously written The beauty of concrete, Making architecture easy, Against the survival of the prettiest, and In praise of pastiche for Works in Progress.

The supply and demand of electricity must match exactly at every moment. There is no slack in the system: an electricity grid is a unique market with no inventories at all. If demand exceeds supply even briefly, the frequency of the grid drops, causing equipment to shut off and risking widespread blackouts. If supply overshoots demand, the grid becomes unstable in the other direction, forcing operators to quickly scale back production. Since electricity can’t be stored within the grid itself, the system has been built to maintain balance second by second, under all conditions.

To make this work, electricity systems rely on layers of complex rules and processes. Power plants are scheduled hours or days in advance based on forecasts. Others are paid just to stay running in case demand spikes or another plant fails. Some are required to operate even when uneconomic, in order to meet reliability rules. Prices are often fixed or averaged across large regions, so they don’t reflect real-time local conditions. These tools keep the system running, but at a high cost.

Much of the infrastructure – plants, power lines, and reserves – exists only to cover rare events and sits underused most of the time. The cost of this redundancy is passed on to consumers. This complexity also means electricity markets are less efficient than they could be. Prices and investment don’t reliably reflect scarcity, location, or flexibility. The result is an expensive, inefficient grid that is struggling to keep pace with demand and the transition to renewable energy sources.

Batteries offer a way out of this structural bind, giving producers, consumers, and distributors a way of keeping inventories for the first time ever, meaning that their value goes well beyond simply storing excess solar or wind.

They can respond in milliseconds, shift between consuming and supplying power as needed, and are controlled entirely through software. This flexibility allows them to take on a wide range of roles within the system: stabilizing frequency, supporting local distribution networks, reducing peak demand, and easing pressure on transmission lines. Because they require no fuel, emit no local pollution, and can be deployed close to where electricity is used, they can often replace several types of traditional infrastructure at once. Rather than being single-purpose assets, batteries adapt in real time to whatever role is most valuable at that moment.

The just-in-time energy supply chain

Thermal power stations, whether coal‑fired, nuclear, or combined‑cycle gas (a type of plant that uses both gas and steam turbines to improve efficiency and reduce emissions), are fundamentally large heat engines. Like any big piece of industrial equipment, they must be started up slowly. This can involve up to 20 hours of careful temperature ramp‑up to avoid cracking boilers, warping turbine rotors, or shocking reactor vessels.

Once online, they can be surprisingly brittle. In deep freezes, for example, the screens that filter debris from incoming cooling water can clog with slushy ice, restricting flow and forcing plants offline just when electricity demand spikes. At the other end of the spectrum, heat waves can shrink water supplies, raise ambient temperatures, and potentially trigger overheating and shutdown.

Even in good weather, large units are routinely pulled offline for weeks-long shutdowns to inspect and repair critical components. Technicians may need to replace corroded metal tubes that transfer heat from exhaust steam to cooling water, or to examine turbine blades for hairline cracks or deformation. These procedures are essential to prevent catastrophic failure, but they take time, specialized crews, and careful planning.

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Decarbonization is adding further complexity. Utility wind and solar are already reshaping the supply curve. Renewables are expected to provide 25 percent of all US generation this year. Solar generation is set to increase by a third in 2025 alone, followed by nearly a further fifth in 2026. The resulting volatility is evident. The North American Electric Reliability Corporation, an industry body that promotes supply reliability, warned in its 2025 Summer Reliability Assessment the growing fleet of ‘intermittent renewable resources drives a risk of emergency conditions in the evening hours when solar generation ramps down and loads remain elevated’. Between January and mid-May of this year, California’s energy system operator had to curtail 2.4 terawatt hours of wind and solar output, only slightly less than total curtailment for all of 2023.

Maintaining any kind of complex process or system becomes increasingly difficult as inventory falls. Even Toyota, famous for relying on a ‘just-in-time’ model of minimal inventories, operates with some buffers and has weeks of finished goods sitting on dealer lots.

Until recently, the only substantial physical buffer in the grid was pumped-storage hydropower. It works by using surplus electricity to pump water uphill from a lower reservoir to an upper one; when electricity is needed, the water is released back down through turbines, generating power. This is efficient, scalable, and dispatchable on demand, but it’s geographically limited. Viable sites require two large reservoirs at different elevations, close enough together to manage efficiently, and with sufficient water. Even with these constraints, pumped-storage still provides 96 percent of all utility-scale energy storage in the US.

Demand-side flexibility could, in theory, compensate for rigid supply, but utilities have only minimal leverage over when customers actually consume power. Customers simply expect electricity to be available on demand. If a Toyota dealership runs out of parts, it loses sales and disappoints a handful of prospective customers, but a shortfall in the electricity supply risks cascading blackouts.

The combination of expensive storage and inflexible demand creates two problems.

First, inflexible power plants have to match demand perfectly over a wide range of conditions because there is no storage buffer and customers don’t want to change behavior.

To cover these risks, system operators must build and maintain capacity well above peak demand. The North American Electric Reliability Corporation estimates that PJM Interconnection, the largest US power grid, maintains a reserve margin of 24.7 percent. That means it has to hold roughly 125 gigawatts of generation to cover a 100 gigawatt peak. This excess capacity is mostly idle, but still needs to be financed, maintained, and staffed, pushing up system costs, which are in turn borne by billpayers. When these reserves are powered by fossil fuels, this also means higher emissions from plants running inefficiently or idling just to stay warm.

Second, it is shockingly easy to have an outage on a normal day, even with many plants on standby. If there are even slight perturbations, there may not be enough time to bring more units online, resulting in outages. This is a rough description of how the 1965 Northeast blackout, the 1977 New York City blackout, the 2003 Northeast blackout, and the 1999 Southern Brazil blackout all went.

Collapsing the cost of reliability

Electricity markets have developed some partial fixes. System operators now plan which power plants need to run a day ahead, based on demand forecasts. They also pay certain plants to stay ready on short notice or to adjust their output quickly if needed.

This has led to the emergence of a market for ancillary services, which are the grid’s insurance policy. Ancillary services are fast-acting capacity that can be brought online in under ten minutes to prevent swings in frequency and plug capacity gaps before slower acting generation comes online. In practice, this has usually involved paying for modern, fast-start gas turbines to remain on standby.

Utility-scale batteries’ millisecond response allows them to deliver frequency regulation, back up other power sources within minutes, or restart the system after an outage. In December 2017, a coal generator in Victoria, Australia tripped offline, causing 560 megawatts of generation to vanish in an instant. Hornsdale Power Reserve, a major Australian battery storage system, injected 7.3 megawatts within milliseconds to stabilize grid frequency. This bought time while slower conventional generators could ramp up, preventing an outage.

Once even a few gigawatts of storage come online, batteries quickly dominate the ancillary market and cut prices dramatically. In Texas, for example, in the space of a year, the price of ancillary services dropped from $3.74 per megawatt hour to $0.98, while the cost of maintaining the emergency reserve fell from $76.77 to $9.62 per megawatt hour. In California, ancillary service costs in 2024 were roughly one-third lower than in 2023. This is because a system with abundant fast storage no longer needs to commit gas units days in advance or pay plants to stay warm.

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Ending overbuilding

As well as slashing the cost of reliability, batteries can reduce the need for surplus power plants built to cover short-lived peaks in demand. Batteries are already cheaper than new gas turbines per kilowatt, and are better suited to handling the daily rise and fall of electricity use. At 10 percent capacity factor, a gas turbine produces for $250 per megawatt hour, versus about half that for a modern battery. Their ability to charge during low-demand hours and discharge during peaks allows the rest of the system – thermal plants and renewables – to run more efficiently and predictably.

On hot days, the gap between average and peak demand is significant. On 17 July, Texas grid operator ERCOT’s total load was 1,608 gigawatt hours. That is an average of 67 gigawatts, but peak demand reached 79 gigawatts, 18 percent higher. Over the preceding 30 days, the average daily peak was 20 percent above the average load. Batteries can fill much of this gap – the ERCOT record is seven gigawatts out of 70 – reducing the need to keep additional thermal plants online just to meet brief surges.

Today’s batteries already manage daily fluctuations well. Between June and September, solar provided 25 percent of total power needs in Texas during midday hours, while batteries discharged in the evening. During this period, real-time wholesale prices averaged just $28, compared with $97 the year before. Between 6 and 9pm, when battery discharge is strongest, wholesale prices were $80 in 2024 versus $332 in 2023.

Along with overbuilding plants and reliability, another major constraint on electricity grids is inefficient and expensive power lines. In markets with locational pricing, it’s common to see large price differences between market points just 50 miles apart because of limits on how much power the lines can carry. Investment from utilities in new distribution infrastructure now significantly exceeds new investment in generation. But extra batteries are almost always cheaper than extra transmission.

Transmission and distribution lines are built to handle rare peak loads and provide redundancy in the case of outages, so they are heavily unused. Their average capacity factor is often under 50 percent, and in some cases close to 10 percent.

Batteries help solve this in two ways.

When placed on the demand side – closer to homes or businesses – they can charge during off-peak hours and discharge during peaks, letting local demand temporarily exceed what the power line could otherwise deliver. For example, a connection for a residential street that is rated for five megawatts might see six megawatts of demand on hot summer afternoons, as air conditioning systems power up. Without storage, the only solution is upgrading the wires and transformers. But installing one megawatt battery means the grid only needs to supply five megawatts, even as demand grows.

They also reduce the need for redundant circuits: a battery on a line can act as its own backup, so other lines don’t need to be oversized to cover for it. That means existing infrastructure can support much more load without upgrades. Since transmission and distribution costs are mostly fixed, spreading those costs over more delivered energy helps reduce overall system costs, and the batteries also narrow price gaps between congested parts of the grid.

The same logic applies to power plants. The transformers, substations, and other infrastructure required to connect a solar farm to the grid can make up a third of the total project costs. A solar farm paired with a battery can operate with a cheaper, lower capacity connection. Batteries allow the plant to smooth output, store power during low-price hours, and sell more during peak times – all while avoiding the cost of a larger grid connection. This boosts revenue and lowers the average cost per unit of energy delivered.

One reason the value of batteries is often underestimated is that analysts focus only on time-based arbitrage – buying low and selling high across the day – without accounting for location-based price differences. These local price spreads can be much larger and more consistent, and batteries positioned well on the grid can take full advantage of them: storing up power when it is cheap in one area and releasing it when it is expensive there. The result is that the economic case for batteries is frequently stronger than it appears in simplified models.

The combined effect of simplifying market structures and using batteries to arbitrage both time and location is to commoditize daily electricity generation, turning time and location into cost numbers rather than complex planning operations.

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Batteries and their enemies

Despite rapid growth, grid-scale batteries remain unevenly deployed, in large part because policymakers did not design regulatory systems to accommodate them. In several countries, batteries are treated as a curiosity: not quite generation, not quite demand, meaning that they are effectively banned. The Netherlands, for example, taxes residential batteries on the electricity they charge with (although grid-scale batteries can apply for an exemption), which undermines their ability to reduce price spreads. In other countries, the absence of location-based pricing prevents batteries from addressing local grid bottlenecks, even when they could do so efficiently.

The deeper issue is that many electricity markets suppress or distort price signals. These include fixed retail tariffs, uniform national pricing, price caps, and minimum generation requirements. These policies protect thermal fleets by weakening or removing the price signals that would otherwise force them out of business. Fixed tariffs and uniform pricing smooth over volatility and local congestion, shielding high-cost plants from exposure. Without strong locational and real-time prices, flexible alternatives like batteries can’t demonstrate their value, meaning the system continues to fund excessive and inflexible thermal capacity by default.

Embracing the market

A more efficient electricity system depends on embracing, not resisting, price signals and the market. Prices should vary by location, as they already do in most US wholesale markets, so that investors and operators can clearly see where supply is needed most. These signs should also be extended deeper into the distribution network, even down to the neighborhood level, so batteries can respond to local bottlenecks. This would allow the grid to adapt in real time, rather than relying on slow and expensive infrastructure upgrades.

If prices reflect real conditions across time and space, there’s less need for complex mechanisms like capacity markets or day-ahead scheduling. Real-time prices would contain the information needed to guide investment and operations. Letting those prices rise and fall naturally gives generators and storage the incentives to be available when they’re most needed.

Grid connection rules should follow the same logic. Rather than requiring every new project to wait for lengthy studies and upgrades, a more flexible ‘connect and manage’ model would let generators plug in quickly and accept the financial risk for curtailment when the grid is full. With proper locational pricing, developers can judge the risk for themselves and build where the economics make sense, not just where the permitting queue allows.

Texas offers a clear example. It already uses location-based real-time prices and has added more than ten gigawatts of batteries since 2022. Even as peak demand has grown rapidly, grid reliability has improved. Short-term price spikes now last minutes, rather than hours, and the cost of reliability services has dropped sharply.

By simply making prices reflect reality, the system can grow fast, run cheaper, and respond with greater precision. Batteries push investment into flexibility, smooth demand peaks, and keep the grid stable at lower cost. They will be the foundation of a power system that can deliver abundant electricity, with reliability built in, rather than as an afterthought.

Austin Vernon is the CEO of Standard Thermal.

Ben Southwood is a founder and editor of Works in Progress.

Making paint requires combining two elements: a medium (the liquid), and a dry powdered pigment that’s dispersed in that medium. Suitable media, like acrylics, have the property of polymerizing over time, becoming a plastic film. Apart from giving paint its color and opacity, pigment gives physical stability to the film, making it dry to a hard surface. But without pigments the medium simply becomes a varnish, which is translucent and not nearly as tough as paint.

Before the invention of acrylic media in the middle of the twentieth century, the main option for a paint medium was linseed oil, which is made by crushing flax seeds. Linseed reacts slowly with oxygen and takes a week or longer to dry. In industrial applications demanding many coats this is a problem. Many pigments don’t speed up drying at all. Some, like carbon-based blacks, even slow it down further.

To make it durable, manufacturers added lead. Lead speeds up the drying time of paint, allowing subsequent coats to be made in quicker succession. It also reacts with the medium over long periods of time, creating a particularly stiff film through the creation of lead soaps. The pigment also lends paint antifungal, antimicrobial, and anti-corrosion properties.

This is why lead-based paint has been used in Asia and in Europe for thousands of years. Until the nineteenth century, basic lead carbonate was the only reliable white paint available. Even if you wanted a different color, it was typical to add basic lead carbonate to other paints to harness the metal’s useful properties.2

The problem is that lead is poisonous. Flakes of the paint are eaten by children, the dust of the paint enters adults’ lungs, and the heavy metal is absorbed through the skin. When ingested, the material causes cancers, chronic and acute toxicity, and reductions in IQ. But replacing it requires finding a material with similar properties.

Magnetic sand

Titanium was discovered in 1791, when a Cornish vicar called William Gregor noticed a ‘magnetic sand’ in a small stream. This was ilmenite, an ore which contains the element titanium. Gregor described in his first report that this ‘magnetic sand’ had a ‘great resemblance to gunpowder’.

Gregor tested the ore with various chemicals, mostly sulfuric acid, recording the many different colors produced over time. With one solution of sulfuric acid he got a blue color. When he used a yellow solution of sulfuric acid and acid-digested ore, then added a plate of iron, he got the hue of Port wine. Among the many colored precipitates and solutions released by Gregor’s chemical probing was a white powder.

Without knowing it, Gregor was demonstrating the fact that titanium is a transition metal: a type of element that dominates the world of pigments. These metals can exist in stable states with different numbers of electrons missing, resulting in different positive charges. In turn, this changes the way the metals absorb light energy, changing their color.

Initially, only the more exotically colored compounds of titanium were explored. In the 1830s, a deep green compound of titanium and potassium ferrocyanide was discovered by an obscure chemist, Elsner-Lampadius. The inventor of this pigment hoped it might replace Paris green, a highly toxic arsenic compound. In the 1890s, it was suggested by the chemist Joseph Barnes that impure titanium oxides (lacking any use as pigments) could be used as a fixative for wool dyes.

The breakthrough towards a white pigment and a substitute for lead would occur in 1909, when Peder Farup, a chemistry professor in Norway’s first technical school, tried to separate titanium from its ore. This followed a request from a government-backed committee; the new country, which had abundant iron ores of which titanium is a byproduct, was searching for uses. Farup noticed opaque red and yellow by-products: pigments.

Farup reached his next breakthrough in 1910 by mimicking the technique described by the eighteenth century Cornish vicar: digesting titanium ores with sulfuric acid. This yielded near-pure titanium dioxide, a white pigment. Though less exciting than deep green or port wine, white titanium could compete with lead white.

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Mass production began in 1916. The new pigment was not perfect. It was marketed as ‘old India ivory’ – a euphemism for its off-white hue caused by iron impurities. These impurities also resulted in a gritty and unreliable pigment. Unlike lead it was neither tough nor fast-drying. But it was stable, smooth, pure, and could be made cheaply in large quantities. Most importantly, it was not poisonous.

The new titanium pigment manufacturer at Fredrikstad, Norway was bought by the US’s National Lead Company in 1927. From the 1930s onwards, titanium dioxide factories spread around the world; as production processes improved, the pigment became cheaper. In 1920, researchers at the Societé de Produits des Terres Rares, a French company, discovered the Blumenfeld process, which still involved sulfuric acid but which produces (almost) exclusively anatase titanium dioxide, a snow-white crystalline form. In the 1930s and 1940s, new processes were developed by independent laboratories in Germany and Czechoslovakia for making synthetic rutile titanium dioxide, a different crystalline configuration of the same elements but with an even greater opacity than anatase.

This made titanium increasingly competitive with lead. In 1979 the United States banned lead pigment for residential use; in 1989, the European Economic Community banned the use of lead white paint outright. But by this time lead white was already being replaced by the cheaper and safer titanium white.

Titanium dioxide was more expensive by weight than its competitors, but its cost per area covered was lower than other pigments due to its high opacity. With titanium white, the same amount of paint goes much further and fewer layers of paint are needed.

Mass production has continued driving costs down. Lead white now costs about $72 per kilogram of pigment; titanium white prices are down to $16 per kilogram.

The discovery of titanium white is a fortunate one. New pigments are incredibly rare. YInMn blue, discovered in 2009, was the first inorganic blue pigment found for almost 200 years. We still lack good alternatives to cadmium red and cadmium yellow, the highly durable primary red and yellow pigments discovered in the nineteenth century.3 Titanium white’s combination of safety, usefulness, and cost is an achievement that will likely remain unrivaled for some time to come.

Alfie Robinson is a historian.

Many cities face the following problem. They have railway lines that go where people live. But these railway lines end at the edge of the city center, and don’t go out the other side.

For cities with this problem, the solution is through running. Terminating a train and turning it around takes a lot of space, space that is usually unavailable in a city center. This means running a railway line through the city often doubles or triples the number of trains it can handle. As a bonus, passengers who are going from one side of the city to the other can do that much more quickly, with no change.

Many cities, such as London, Paris, Munich and Milan, have used through running to turn some of their existing Victorian railway lines into metro-style services, by building tunnels under the city center. A few other cities, like Berlin, built viaducts (bridges that carry roads and railways over obstacles), while others, such as Cologne, have simply added platforms at their main stations to enable suburban trains to run through. But all of these are big cities, with over a million people, where the property value uplift or extra revenues from fares can cover the enormous costs of tunneling. But there is another option, affordable for smaller cities or large towns: the tram-train.

Karlsruhe is a small city of only 300,000 people in southwestern Germany, near the French border. The city’s main station is nearly two kilometers from the city center, following a project in the early twentieth century to build a larger station on a less cramped site. This caused great inconvenience to passengers, who had to change to the city’s tram network in order to get to the old center.

In 1957, the city took the first steps towards creating a new type of transit, the tram-train, when it took over a bankrupt suburban railway, the Albtalbahn, and extended it into the city center over the tram network.

Over the next four years the line’s gauge (the space between the rails) was converted from 1,000 millimeters to 1,435 millimeters, the standard gauge used by the tram network, and it was re-electrified at the same voltage as the tramway. The modernization of the line enabled quicker journey times – the 70 minute journey to Bad Herrenalb, the line’s terminus, was reduced to 46 minutes – but more importantly passengers who wanted to get to the city center did not need to change to a tram.

The idea of a tram that runs outside of a city’s urban area was not new: Vienna, for instance, had been operating a similar line to the neighboring spa town of Baden since 1907. Karlsruhe’s inventive step, which came later, was to extend the tram-train onto railway lines that did not just carry tram traffic. In 1979, the line was extended onto a freight railway north of the city, and in 1992 the first tram-train took over pre-existing passenger services, to the town of Bretten.

Joining the tram and train networks together was tricky. German railways are electrified at 15 kilovolts alternating current, while Karlsruhe’s trams use 750 volt direct current, which meant that the city needed to procure trams capable of using both voltages, which were (and still are) rare. The railway and the tram network used two different signaling systems, the ‘traffic lights’ that are used to control the movement of rail traffic. The trams have to use retractable steps to overcome the big gap between the 2.65 meter-wide trams and platforms which can handle 3 meter-wide trains. These steps also enable later models of the trams, whose floors are 570 millimeters above the ground, to work with both 380 and 760 millimeter-high platforms.

Overcoming these technical problems led to a much better network. Ridership of the Bretten line went up 400 percent after it was extended into the city center on tramlines, and the line now has 18,000 trips per day, up from 2,000 before the tram-train took over. Passenger numbers on the network doubled between 1985 and 1999, after several more lines had been added. The network today, which carries 170 million passengers per year, is over 660 kilometers long, longer than the combined length of Munich’s tram, metro and suburban railway networks.

Tram-trains have trade-offs. Trams are slower than trains, because they have to share road space with cars, pedestrians and bicycles. Where possible, therefore, Karlsruhe runs the tram-trains down wide roads in the suburbs where trams can run in their own lanes, and it gives signal priority to trams at road intersections. Tram-trains manage speeds about the same as the wholly tunneled Paris Metro.

The fact that trams interact with other vehicles also means that they have to be short. The Munich S-Bahn has a maximum capacity of more than 50,000 passengers per hour per direction because of its 200-meter-long trains, similar to London’s Elizabeth Line. Manchester’s Metrolink, which runs 60-meter-long units, can transport 15,000 per hour on its busiest section, while owing to its lower frequency Karlsruhe’s 75-meter-long tram-trains, as long as trams can feasibly get without causing unbearable problems for other road users, carries only 8,800.

Other models of light rail

The Karlsruhe Model involves mixed traffic: the tram-train lines also carry longer-distance trains and some freight. This caps capacity and reliability.

For this reason, some bigger cities such as Manchester, Dublin, Melbourne and Rotterdam, have converted railway lines to tram lines, with no other form of traffic allowed, enabling more frequent services. This often means the railway line needs to be closed to be converted to tram standards: in Manchester, the commuter line to the southern suburb of Altrincham was closed for six months to enable the electrification to be converted to 1,500 volt direct current from the British standard of 25 kilovolts alternating current.

In Manchester, however, the trade-off was worth it. There was no other traffic on the Altrincham Line, and the city is three times as big as Karlsruhe, so needed a more frequent service on its tram-trains: the line now runs a tram every six minutes.

Another model is the ‘tram-metro’. This is common in medium-sized German cities like Düsseldorf. It involves trams that run on the streets in the suburbs of the city, and then go into a tunnel under the city center. Although this is more expensive than running on streets, tunneled trains are never held up by traffic in the center.

Karlsruhe has, in fact, now built a tunnel for its tram-trains. The ‘Kombilösung’, or ‘combined solution’, which was completed in 2021–2022, involved building two tunnels.

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One of them was a 2.1 kilometer-long tunnel under the city center for the tram-trains, which enabled the main shopping street, the Kaiserstraße, to be fully pedestrianized, creating a three-way hybrid: a tram-train-metro. This would not have been justified with the ridership numbers of the 1990s, but by the 2020s passenger numbers had grown so much that it was viable and necessary to prevent the Kaiserstraße from being congested.

The purpose of the other tunnel was to put the city’s main east-west artery, a ten-lane road known as the Kriegsstraße, underground, and to build a boulevard on top where tram traffic can run uninterrupted by cars.

A final model of light rail worth mentioning is interurbans. Interurbans ran on streets within cities, while in suburbs and in rural areas they ran alongside roads or on dedicated rights-of-way. These systems were sometimes staggeringly expansive: at one point, it was possible to travel from Wisconsin to New York State exclusively by interurban. In the American Midwest, they were the main method of rail transport, outcompeting the commuter services offered by the American railroads. Although most of the interurban lines closed in the postwar period, a few of them are still there today: the South Shore Line still runs from Chicago to South Bend.

The case for tram-trains

Choosing between these different models of light rail is a trade off between cost, engineering difficulties, and the ability to reuse pre-existing infrastructure on the one hand, and capacity, speed and reliability on the other. But there is one specific advantage of tram-trains: their similarity in spirit to interurbans.

The key advantage of interurbans over ordinary suburban railway lines was their ability partially to solve the ‘last mile problem’. Railway stations are often awkwardly sited far away from town and city centers. Usually, this is for engineering reasons: railways are unable to navigate steep gradients, so the Victorian builders had to go where the land was flat, not where people wanted to go. Furthermore, railway lines were often optimized to link two big places together quickly, rather than adding connections to all of the smaller towns en route. Because they could travel on streets, however, interurbans could go anywhere within a town or city, with stations nearer to people’s origins and destinations.

Bringing back the interurbans would be prohibitively expensive. Even in Germany, where the average mile of new tramway costs just $32 million, a network as extensive as the motorways – 8,200 miles – would cost around $270 billion. In Britain, it would be more expensive still: tramways cost $118 million per mile, and in Australia, they come in at $165 million.

The Karlsruhe Model allows interurban-like service at much lower costs. In many cities, the suburban railway lines have already been built: they just need linking up to a tram network.

A concrete example of where tram-trains would be useful is Oxford, UK. Oxford is not big enough to justify a metro: there are only 260,000 people within ten kilometers of its center. The city’s main station is quite far from the center, like in Karlsruhe, and currently has little development around it. This means that a through-running network focused on Oxford station would fail to serve all the places people want to go to. A tram-train network, however, could enable people from the towns and cities surrounding Oxford to get directly into the center, plus direct service to the centers of the surrounding towns like Abingdon and Bicester, and possibly Reading.

Something similar could be said for many French cities. France has been undergoing a tramway renaissance: it has built 21 new tram systems since 2000. But, even though France has an extensive high-speed rail network, and excellent transit within urban areas, its suburban railway lines are operated infrequently outside Paris. For this reason, the country is planning to run its suburban trains through the center in 26 metropolitan regions. In smaller cities like Tours, this could be done by running trains onto the existing tram networks. The same goes for many of the smaller cities in the former Eastern Bloc, which often have extensive tram networks as well as suburban railway lines in need of upgrading.

The biggest opportunity, however, is perhaps in North America. Take Charlotte, North Carolina. The American model of huge low-density suburbs means Charlotte only has 380,000 people within ten kilometers of its center, even though its urban area overall has 1.4 million people, similar to Munich’s. The low density of Charlotte means a transport network like Munich’s is not viable, but the city could take its pre-existing light rail network and join it up to the extensive network of railroad lines around the city that are currently used only for moving freight.

Tram-trains are not suitable everywhere. In big cities like Munich, through running needs to use a tunnel, for reasons of speed and capacity. In some smaller cities like Utrecht, then there is no need: the main station is close to the city center, which is compact enough that it can all be reached on foot. Utrecht has therefore implemented through running simply by running trains through the main station, without needing any more infrastructure. Other cities don’t have any wide streets in the center on which to run tram-trains. These need viaducts or tunnels, or need to demolish buildings to make space. Or they will have to do without.

But in Oxford, Tours and Charlotte none of these things are true. Bring on the tram-trains!

Benedict Springbett is a writer and Bar student based in London.

Over the next century, one or both of two faults – the Cascadia and San Andreas – have a nearly 70 percent chance of unleashing the energy equivalent of anywhere from 30,000 to 60,000 Hiroshima bombs onto the American West Coast.

The last time either of these faults had a major rupture (1700 for Cascadia, 1906 for northern San Andreas, and 1857 for southern San Andreas), the high-impact zones had about 550,000 residents in total. Today, approximately 35 million people live in the same regions. (The Hayward fault, which runs directly through the Bay Area and is overdue for a rupture, is also extremely dangerous, but for the purposes of our discussion we’ll focus on just the largest two faults).

The most destructive of these historical ruptures, the 1906 San Francisco earthquake, destroyed half the buildings in the city and killed over 3,000 people. Despite major advances in building codes and hundreds of millions of dollars spent on regulation and new building methods, a vast portion of the built environment remains highly vulnerable. In high-impact zones on the American West Coast, up to 20 percent of buildings are expected to fail in a Cascadia or San Andreas rupture. The remainder are only built to survive a smaller quake, with unclear outcomes given the ultra-large quakes that both faults are rated for.

If either fault were to rupture, it would be the single-worst natural disaster in American history. It would kill anything from 5,000 to 100,000 people, cause over $500 billion in property damage, and destroy some of the country’s most important infrastructure. Combined, these faults pose one of the biggest threats to American well-being and prosperity in the twenty-first century. And yet, efforts to mitigate this risk remain alarmingly limited.

Unlike natural disasters like hurricanes, floods, and tornadoes – which, with some level of accuracy, we are now able to predict – earthquakes seem completely opaque to us. This means that they appear out of the realm of prediction, and by extension the realm of concern – at least for most residents and elected leaders.

As a result, funding for earthquake prediction is close to nonexistent. Science funding is generally risk averse, but in the past 30 years the Federal government has spent approximately $10 million per year on prediction research (broadly defined) – around 0.5 percent of annual earth science spending. Even then, most of the earthquake prediction budget is spent on probabilistic long-term forecasting, fault modeling, and data capture and integration. This helps identify where earthquakes can happen, but not when an earthquake will happen.

Until recently, even with unlimited funding, genuine pathways to the ‘holy grail’ breakthrough have been limited. This grail would be minutes or hours of advance warning, since even just stepping outside would prevent the majority of fatalities and injuries. The reason is simple: earthquakes are complex and difficult-to-observe systems. Scientists still have a relatively primitive understanding of the state and movement of each tectonic plate, and even a robust understanding would be computationally difficult to fully model. Data points are few and far between, often only capturing a limited part of a full-cycle event.

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Current approaches to understanding chaotic systems generally involve manually weighing different data points and deciding how they should be factored into a prediction model. This becomes impossible as data sources scale, but foundation models like Aurora have recently proven to be exceptionally good at understanding and predicting events in chaotic systems. Foundation models, if properly deployed, give us the strongest potential path to 10 minutes or more of advanced warning, but the application of machine learning in earthquake prediction remains limited.

To effectively deploy foundation models for earthquake prediction, a few things need to be true.

First, sensing technology, reach, and infrastructure needs to be an order of magnitude better. There are remarkably few seismometers: California only has about a thousand, roughly one for every 15 miles of fault line. There are even fewer in underwater faults like Cascadia. But more critically, many richer sources of earth movement data, including InSAR, a satellite-based way to capture ground deformation, and distributed acoustic sensing, which uses unused or underutilized fiber optic cable lines from telecom companies to sense movement to the nanometer, are either underutilized or not captured at all.

Second, all the data needs to be in one place. Data from different labs and regions, even when nearby or funded by the same source, is rarely aggregated and properly structured and labeled.

And third, someone needs to convince data providers to share data, install more sensors in relevant places, aggregate the data, and build, run, fine-tune, and fund the model. That is: the area needs more talent and compute, which means that the area needs more funding.

Each of these components is feasible and all are being accomplished on a small scale by individual labs, but with limited coordination or data orchestration and nowhere near enough money to give us advanced warning by the time the next big earthquake comes. Despite the time-sensitivity and potential impact to the well-being and prosperity of millions of Americans, there is no Manhattan Project-level sprint toward a breakthrough.

There are two realistic paths forward.

The first is an open-source project, where individuals and organizations can pool data, compute, and capital to test individual hypotheses. This will make progress, albeit slowly.

The second, and likely the most effective, is a centralized lab. This lab would provide targeted grants to researchers and universities to explore novel sensing, data capture, and model construction methods, including funding for the expansion of existing sensing methods like distributed acoustic sensing and ocean-bottom seismometer. It would also aggregate, structure, and label both historical data and existing data sources and feeds. Finally, it would build and fine-tune a foundation model while making all data freely available to other labs for analysis and research. With great leadership, collaborative partnerships with existing institutions, and $25–50 million of funding, a centralized lab has a reasonable chance of achieving a major breakthrough in three to five years.

A catastrophic seismic event cannot be stopped. But it can likely be predicted, and for the first time, the technology exists to make real progress toward a ‘holy grail’. Few challenges are as well-matched for foundation models as this one, and we have a rare window to predict disaster before it strikes. Let’s not waste it.

Many thanks to Kelian Dascher-Cousineau, Emily Brodsky, Tom Kalil, Neiman Mathew, and Ben Southwood.

Michael Ioffe is the CEO of Arist. You can follow him here.

This all changed in January 2025, when the FDA approved Vertex Pharmaceuticals’s Journavx (suzetrigine): the first non-opioid pain reliever suitable for treating post-surgery pain. Clinical trials found no signs of the problematic side effects associated with opioids: no drug abuse, tolerance, or withdrawal. But this was not an easy win: Vertex and other pharma companies spent decades searching for drugs like this to no avail.

Opioids are used primarily to treat nociceptive pain, pain caused by tissue damage from injury or disease. This damage activates nearby nociceptors: sensory neurons that signal physical or chemical harm. These nociceptors send signals up to the central nervous system – the brain and spinal cord – and the brain then creates a localized sensation of pain, drawing your attention to the threat.

Traditional opioids mimic opium, a compound found in the poppy plant that contains morphine. Opioids alleviate pain by acting on one of the three main opioid receptors, mu (μ) opioid receptors, which are distributed throughout the central nervous system, particularly in the brain. When opioids bind to the brain’s mu receptors, this suppresses incoming pain signals from the damaged site’s nociceptors, preventing the brain from creating the sensation of pain even when tissue damage is present.

Our bodies naturally produce their own opioids – such as endorphins, endogenous morphine – to briefly blunt pain during moments of stress or injury. However, these are far weaker and shorter-acting than prescription opioids since they degrade quickly, remain localized, and are released in short, controlled bursts. Prescription opioids, on the other hand, flood the brain with higher doses that linger for hours.

Crucially, opioids don’t just kill pain: they also incite pleasure. When the mu opioid receptors present in the reward center of the brain are activated, this reduces the secretion of a neurotransmitter called GABA, which works to inhibit dopamine-producing neurons. As GABA release declines, dopamine spikes, lighting up the reward center and inducing pleasure.

With the body’s natural opioids, this is fleeting and unproblematic. When properly prescribed, even synthetic opioids are no issue for most patients: under severe post-surgical pain, opioids mostly function to normalize disrupted brain function, dampening any pleasurable effect. But for some, whether due to genetics or inappropriate administration (e.g. a prescription that goes on after the pain’s source has been relieved), the intensity of prescription opioids produces a prolonged dopamine spike, along with a marked sensation of euphoria: a recipe for addiction.

With chronic use, the body’s natural opioid system becomes dysfunctional. Fewer natural opioids are produced and opioid receptors become desensitized. As a result, the patient develops a tolerance, requiring higher and higher doses to even feel normal.

The nineteenth century witnessed the creation of morphine, codeine, and heroin (which was sold over-the-counter), as well as the invention of the hypodermic syringe. By the turn of the century, 15 percent of all prescriptions dispensed in Boston were for opioids, which were used for everything from menstrual cramps to children’s coughs, and as many as 300,000 Americans, or 0.5 percent of the population, were opiate addicts. Anti-narcotics laws proliferated throughout the states, and the medical community expressed concerns about the liberal provision of addictive drugs. These mounting pressures led to the passage of the Harrison Narcotic Act in 1914, which made opium and opiates the first regulated substances in the United States.

Peripheral solutions

Unlike opioids, which act within the central nervous system, Journavx does not meaningfully interact with the brain. Instead, it targets a specific sodium ion channel found almost exclusively on peripheral nociceptors, the pain-sensing neurons throughout your body. Ion channels, whether sodium, potassium, or calcium, are like tiny doors embedded on the neuron’s membrane: when a door opens, ions rush in or out and the neuron fires, sending an electrical signal to the next cell.

Three sodium channels are found primarily on nociceptors: NaV1.7, NaV1.8, and NaV1.9. Suzetrigine selectively blocks NaV1.8, which stops nociceptors from sending pain signals to the brain. Rather than preventing your brain from receiving pain signals, as opioids do, it prevents your neurons from transmitting them. In essence, Journavx works from the bottom up to alleviate pain, rather than the top down.

Critically, the NaV1.8 channel is largely absent from the central nervous system. This means that suzetrigine does not affect the brain, which means users do not experience the same euphoria that is triggered by opioids. This prevents addiction and abuse, as well as the depressive effects on breathing or heart rate typical with opioids.

At first glance, this may seem like a straightforward solution, especially given the urgent demand for non-opioid alternatives. So why did it take so long?

Unlike diseases with well-defined biological causes, pain is a broad symptom rooted in complex and overlapping pathways. Many of these are deeply intertwined with vital bodily functions like blood pressure, immune response, and respiration. Together, this makes it difficult to isolate a target that can be blocked without collateral damage.

A particularly good example of this predicament involves TRPV1, also known as the capsaicin receptor. It is an ion channel mainly found in nociceptors, and is responsible for the pain you feel when eating spicy foods. In clinical trials, TRPV1 inhibitors effectively alleviated pain, but researchers found that they unexpectedly disrupted thermoregulation, causing patients to experience hyperthermia, or overheating, with one trial participant sustaining a 104 degrees fahrenheit fever for hours.

Another example involves nerve growth factor inhibitors like tanezumab. Although tanezumab alleviated inflammatory pain from conditions like osteoarthritis, Phase III trials revealed an unfortunate side effect: rapidly progressive osteoarthritis. Researchers hypothesized that because patients felt so much better, they overused their arthritic joints, accelerating damage. Although further trials were conducted at lower doses and with restrictions, the FDA ultimately voted against its approval. Tanezumab’s story reflects a difficulty in developing painkillers: while pain can cause excessive suffering, it also serves as a vital warning sign that must be selectively maintained.

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Men on fire

Vertex has historically focused on developing drugs targeting ion channels. These channels play a major role in cellular signaling, meaning that compounds that act upon them can produce large, rapid physiological effects. Ion channels are ‘really good drug targets’, Paul Negulescu, head of Vertex's pain program, says, ‘They just require a lot of care and attention to how you measure them’.

The discovery of the NaV sodium channels, made independently in the early 2000s by two different researchers, opened a new frontier in pain research. Both observed that mutations affecting NaV1.7 caused abnormalities in the experience of pain, a major clue that pain might be mediated through that specific sodium channel.

Stephen Waxman, a professor of neurology, neuroscience, and pharmacology at Yale’s medical school, discovered that a community in Alabama had numerous individuals suffering from erythromelalgia or ‘Man on Fire’ syndrome. These individuals experienced mild warmth – such as from wearing a sweater or shoes – as intense burning pain. Waxman’s research tied this phenomenon to mutations in the SCN9A gene, which is involved in the production of NaV1.7 channels. Meanwhile, Geoff Woods, a clinical geneticist at St. James’s University Hospital in Leeds, uncovered a complementary discovery. He observed congenital insensitivity to pain within specific Pakistani communities, also tracing it back to mutations in the SCN9A gene.

This congenital insensitivity provided a particularly compelling genetic validation for a drug target, as the affected individuals were entirely normal except for their inability to feel pain, unlike prior similar cases. Related channels like NaV1.8 and NaV1.9 were also investigated by Woods’s team and found relevant for pain signaling.

But despite the initial enthusiasm surrounding these discoveries, researchers soon encountered significant obstacles: NaV1.7 inhibitors failed to relieve pain during clinical trials. Researchers eventually uncovered that the congenital absence of NaV1.7 did not eliminate pain signals but instead amplified the production of natural painkillers called enkephalins. They concluded that completely blocking the channel, which would be required to replicate this effect pharmaceutically, was impractical.

So researchers turned their attention to the other promising sodium channel: NaV1.8. Again, research began with setbacks: in 2015, it was discovered that individuals with Brugada syndrome, a disorder characterized by abnormal heart rhythms and sudden cardiac death, also had mutations in the gene encoding NaV1.8.

Despite this challenge, researchers still thought NaV1.8 had potential. Woods’ research genetically validated it, showing that mutations in NaV1.8 affect pain signalling. Researchers at the University of Alcalá confirmed that mice genetically engineered to lack Nav1.8 channels showed virtually no spontaneous nerve activity after injury – activity thought to underlie certain chronic pains. Additionally, NaV1.8's almost exclusive presence in the peripheral nervous system (rather than in the brain) suggested that it might uniquely limit undesirable central side effects.

Ion channels

As Vertex researchers searched for NaV1.8 inhibitors, they made use of Negulescu’s E-VIPR technology, which enabled them to conduct more than 50,000 tests per day to identify compounds that blocked NaV1.8 without affecting other ion channels. This was essential because the human body contains nine known voltage-gated sodium channel types, each with a distinctive ‘personality’ – a unique pattern of rapid opening, closing, and voltage sensitivity – making high throughput key to pinpointing an appropriately selective drug.

But even with this tool, Negulescu described the iterative learning process as ‘painful’. Vertex spent a decade screening millions of compounds before finding a promising class of molecules. Another decade was spent on optimization, conducting tens of thousands of screenings to maximize potency and selectivity (a drug is selective if it binds only to the target proteins and nowhere else).

Vertex faced several failures in preclinical and clinical testing. Between 2018 and 2022, they terminated development for three generations of NaV1.8 inhibitors, VX-150, VX-128, and VX-961, due to dosing and tolerability issues. However, unlike previous attempts with NaV1.7, TRPV1, and nerve growth factor inhibitors, the pathway overall did not exhibit fatal flaws, and so research continued.

Eventually, this iterative process produced VX-548, which was discovered to be many times more selective and potent than earlier candidates. In 2022, two Phase II proof-of-concept studies yielded positive results. In 2024, Phase III trials validated VX-548’s efficacy in treating acute pain with minimal adverse effects. During this process, the FDA granted VX-548, now suzetrigine, Fast Track and Breakthrough Therapy designations, processes designed to accelerate the development and review of crucial pharmaceutical innovations.

On July 30, 2024, the FDA accepted Vertex’s New Drug Application, filing it under priority review. Exactly six months later, on January 30, 2025, it was approved, marking suzetrigine – sold under the brand name Journavx – as the first non-opioid analgesic for treating acute pain.

Pain points

Journavx isn’t a silver bullet. It has not yet been tested or approved for treating chronic pain, from which over 20 percent of Americans suffer. Across its clinical trials, 85 and 98 percent of participants were female. This reflects a broader pattern in painkiller trials, which often rely on surgical models like bunionectomy and abdominoplasty (‘tummy tuck’) – procedures overwhelmingly performed on women. Since 2022, the bipartisan ‘No Pain Act’ has mandated Medicare and other government health plans to cover this class of medication in outpatient surgical settings, private insurance coverage is still in flux: without insurance, a week’s worth of Journavx costs around $230, compared to $10–20 for a low-dose opioid-acetaminophen combination medication.

Journavx failed to outperform that opioid-acetaminophen combination in clinical trials. Todd Bertoch, an anesthesiologist involved in suzetrigine’s Phase III trials, explains that the drug likely won’t serve as an outright opioid replacement, but the first step on the journey to minimizing opioid usage. If paracetamol and ibuprofen are inadequate for pain relief, Journavx can now be prescribed as the next alternative treatment, instead of mild- to moderate-strength opioids.

It will almost certainly improve: Vertex’s scientists are continuing their decades-long project to iterate and screen for even more potent and selective NaV1.8 blockers. They are also investigating complementarities with NaV1.7 inhibitors. A Phase III clinical trial of suzetrigine for diabetic peripheral neuropathy, which involves chronic pain, is currently underway.

Journavx is the product of 27 years, billions of dollars, millions of molecules screened, dozens of monkeys and rats and data from over 2,400 surgical patients, all distilled into a single 50-mg blue tablet.

Vertex chose to keep funding and pushing forward through decades of work that industry professionals describe as ‘tedious’, ‘mind-numbing’, and ‘painstaking’, a slog driven by slow, incremental progress and frequent setbacks. In exchange, humanity now has its first non-opioid painkiller.

Michelle Ma studies economics at the University of Chicago.

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In 1883, Sir Coutts Lindsay, owner of the Grosvenor Art Gallery in Bond Street, decided that he wanted to illuminate his paintings without the smoke produced by gas lanterns. He installed a small generator, first in the yard and then in the basement of the gallery. This was a cutting-edge status symbol at the time. The generator turned out to produce more than enough electricity to power his gallery lights, so he started to supply the excess power to his neighbors via overhead cables.

In 1887, after being pitched by a professional engineering team, Sir Coutts formed the London Electricity Supply Corporation. To spare passersby the noise of the generator, to gain access to cooling water, and to allow it to buy cheaper coal transported by river, the corporation moved to a new base in Deptford. The Deptford facility was linked by cables to substations at the Grosvenor Gallery, Trafalgar Square, and Blackfriars. By 1891, the world’s largest generator and one of the world’s first modern power stations was up and running.

For its first decade, the project struggled as cost overruns, frequent fires, challenges meeting public demand, and a fatality during a government inspection made profits elusive.

The story of Coutts Lindsay and the London Electricity Supply Corporation is typical of the early days of electricity supply, not just in the UK, but around the world. Uncoordinated local efforts struggled with growing demand and the absence of economies of scale. In New York, Thomas Edison’s Pearl Street Station, completed in 1882, became one of the first centralized power plants. It served an area of one square mile.

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The early market for electricity generation and distribution was chaotic. The first two decades of the 20th century saw UK local authorities and a grab bag of private companies locked in bitter and counterproductive competition with each other. Between 1900 and 1913, 224 new generation projects came online, at varying voltages, frequencies of supply, and using different kinds of current, and almost all using their own cables.1 In 1918 London, there were 50 different systems, ten different frequencies, and 24 voltages in operation.

This era saw entirely privately-financed companies expand supply significantly, and prices fell steadily as they did so. In that respect, it is similar to the railway manias of the 1840s and 1860s, when speculative investment in railway projects led to over 6,000 miles of railway line being constructed – but also incinerated the modern equivalent of £300-400 billion of investors’ money, because so many turned out to be uneconomical.

As usage ramped up and resources were squeezed, especially during the First World War, the limitations of the UK’s electricity system became apparent. To understand why, we need to take a brief detour into physics.

Grids and why we need them

The two most common forms of current are alternating current (AC) and direct current (DC). AC works by running a current back and forth, contrasting with DC, which flows in only one direction. Thanks to these frequent direction reversals, AC creates a changing magnetic field that induces voltage in another coil of wire through electromagnetic induction. This field means it is easy to step voltage up or down, depending on the number of coils in this transformer wire. DC, with a static magnetic field, is unable to do this efficiently.

AC is the backbone of modern electricity systems. Power is transmitted over a long distance at a higher voltage to minimize power loss, and then stepped down to lower voltages at substations. The higher voltage means the same power is transmitted with less electrical current flowing through the wires, resulting in less energy being wasted as heat.

The London Electricity Supply Corporation were early pioneers in the use of AC. But they struggled against local operators who would cheaply knock together small DC networks, an approach popularized by Edison. These networks could effectively illuminate local neighborhoods, but not transmit electricity efficiently over any meaningful distance.

DC, however, benefitted from an incumbency advantage. Early electrical devices had been designed for DC, while the development of AC components like electrical motors initially lagged behind. DC proponents like Edison also stoked public fear of AC, arguing that higher voltages would be dangerous. Edison went as far as staging public demonstrations of animals being electrocuted by AC.

The lack of standardization in early electricity systems caused problems. It meant that electric equipment designed for one power source couldn’t work with another. If a motor was built for one frequency, it could run too fast and overheat if operated on another. An electric iron designed for a DC system wouldn’t work on an AC one. Industrial equipment couldn’t easily be standardized across regions. Electricity suppliers rendered themselves uneconomical by building parallel distribution networks.

The First World War drove home the shortcomings of this approach. Coal prices more than doubled when munitions factories faced massively increased demand just as coal miners were being enlisted. These spiraling costs led factories to abandon their private generators and ask to be connected to municipal electricity projects. However, there was a shortage of both generators and factory capacity to manufacture them. Electricity demand increased more in those four years than it had in the prior 32, but thanks to their inefficiency, many local electricity undertakings still failed to be profitable, relying on a mix of municipal subsidy and wealthy investors.

This shortage of generators led the government to restrict the creation of private generation capacity and to strongly encourage manufacturers to move to AC. Meanwhile, municipal electricity projects started to connect to one another (known as interconnection), so they could back each other up during periods of high demand, building resilience into the public system.

Parliamentary reports during 1918 and 1919 proposed the quasi-nationalization of the industry. They concluded that the UK needed to move from local generation projects to a national network. MPs, however, saw this as too radical and opposed any form of coercion. As a result, they passed the weaker Electricity (Supply) Act of 1919. This established regional joint electricity authorities: statutory bodies tasked with expanding interconnection between local projects.

The joint electricity authorities, along with the government’s electricity commissioners, lacked any powers of compulsion. They could hold local consultations to try to persuade operators to interconnect their infrastructure, but would routinely run into local opposition. Companies saw little incentive to change, were reluctant to work with their competitors, and commissioners struggled to navigate a world of petty municipal rivalry.

While the government was frustrated by the intransigence of industry, it arguably only had itself to blame. Private energy projects were regulated by a series of Electricity Acts, introduced between 1882 and 1909. Not only did these geographically restrict companies, they gave local authorities the right to buy a generation project after 42 years at book value. As investors could not be sure of keeping hold of their business once it became profitable, it was hard to raise capital and there was little incentive to build out infrastructure. Meanwhile, municipal projects were regarded as useful sources of revenue by local authorities. While working with their neighbors might make sense from the standpoint of national efficiency, no local authority wanted to export jobs and revenue.

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The first moves towards centralization

This meant that the UK began to lag the US, Germany, Switzerland, Sweden and many others on per capita consumption of electricity.

US companies, which thanks to geography could benefit from larger thermal and hydroelectric power plants, were incentivized to consolidate and build larger plants. This would allow the cash flow from one project to be used to finance the development of another. By 1932, eight holding companies controlled three-quarters of the private electricity generation projects.

Meanwhile in Germany, the government was actively pushing for regional and inter-regional (as opposed to municipal) interconnection with a firmer hand. By the mid 1920s, the mixed public and private interconnected system serving the Ruhr aggregated 3,000 gigawatt hours of electricity, versus 800 gigawatt hours amassed by the UK’s interconnection system in the heavily industrialized north east.

In 1925, the UK Government commissioned an inquiry into the state of the UK electricity market. It concluded that: ‘Of the 438 generating stations owned by authorized undertakings, not more than about 50 can be regarded as being of really suitable size and efficiency. [...] The percentage of stand-by plant is unduly high and the load factor is unreasonably low. Interconnection is not carried out as a definite policy [...] and the resultant loss to the country has been heavy, and becomes daily heavier.’

The inquiry resulted in another Electricity Supply Act, which paved the way for an ambitious national scheme of interconnection, defying Conservative backbenchers who viewed it as dangerous state intervention. The newly established Central Electricity Board was tasked with creating a synchronized AC grid, running at a consistent voltage and frequency. While the ownership of generation companies and local distribution networks would not change, the board would oversee their day-to-day management.

The National Power network (renamed the ‘National Grid’ three years later) began operations in 1933. It spanned over 4,000 miles of transmission lines, crossing 60 rivers with the use of special towers. The transmission towers provoked public opposition, leading the Central Electricity Board to run a competition to select a design. Architecth Sir Reginald Blomfield judged the competition, picking an Ancient Egyptian-inspired design would soften the pylons’ appearance. Astonishingly by modern British standards, all of the wires, towers, substations, and cables were built and connected in six years.

The Grid began life as a series of interconnected regional grids, rather than as a national system. But in one night in October 1937, rebellious engineers decided to synchronize the regional grids as an experiment, allowing electricity to flow freely between them for one night. This became official policy the next year.

Beyond some additional regional interconnection, the infrastructure of the grid would go largely unchanged between the 1930s and the end of the war. This interconnection would prove valuable in the intervening period. When generating capacity was knocked out during an air raid, power could be restored while repairs were carried out. Power generation in south Wales was able to reinforce capacity that had been knocked in the south east of England. Meanwhile, unused electricity generated in blacked-out London could supply factories in the north.

After the war, the Labour government nationalized the grid. This was partly driven by their convictions about the power of state ownership, but also out of practicality. The Grid had integrated 171 generation stations under the authority of the Central Electricity Board and had created an effective electricity generation network. However, local distribution was split across 562 private and municipal entities.

The private entities operated under a franchise system and feared that when these expired, local authorities would scoop up urban distribution, leaving them with only small uneconomic bits of rural infrastructure. This meant that they had little incentive to support interconnection with municipal projects.2

Meanwhile, the supervision of private companies operated under a cumbersome mechanism. The Central Electricity Board would buy the entire output of a power station and then sell back to the owner anything they needed for their own local distribution network. They would have to negotiate the price with every owner individually and these discussions could be protracted.

The incoming Labour government in 1945 concluded that nationalization was the easiest way to end the split between ownership of power stations, control of generation, and management of transmission. It would allow the government to directly invest in new generation capacity and infrastructure, construction of which had been effectively frozen during wartime, without having to coordinate and negotiate with hundreds of private actors.

The Electricity Act 1947 created the British Electricity Authority, which took control of the power generation and grid transmission, and created new area electricity boards would then sell it on to consumers.

By 1950, the grid was running up against its physical limitations. Though it was theoretically a ‘national’ grid, it had been built as distinct networks serving individual regions, with the assumption that flows between these networks would be small (though essential). As the energy demands of London, Manchester, Merseyside, and Tyneside increased, there was a need to transmit electricity generated by coal plants in the East Midlands and Yorkshire, whose grids had surplus power.

The Supergrid was born, the fun name chosen to build public excitement. Built between 1950 and 1960, its main purpose was not to connect local areas to their regional grids, but to move electricity between the regional grids. Since the electricity was all going to be stepped down in one go, it could use a higher voltage of 275 kilovolts (versus the 132 kilovolts of the original grid) to reduce transmission loss.

The Supergrid cost roughly the same to build as the original grid (£1.5 billion in today’s money), but took ten years to complete, despite stretching for only around a quarter of the length. Partly this was just because Supergrid cables were heavier, and needed glass suspension insulators to prevent entire towers going live, but it was also owing to changes in planning rules. The 1947 Town and Country Planning Act threw sand in the gears, as the Central Electricity Generating Board had either to win local authority acceptance or ask the Ministry of Fuel and Power to convene an inquiry, where a government appointed inspector would take evidence on local amenity questions. When the original grid was built in the 1930s, local authorities could raise concerns about projects, but had no power to stop them going ahead.

Over the course of the 1960s and 1970s, the UK would gradually upgrade the supergrid to 400 kilovolts, but structurally the grid remained relatively recognizable for the next 20 years. In 1961, the UK and French governments commissioned ASEA, a Swedish electricity company to build the first UK-France electricity interconnector, allowing the two countries to trade excess power.

Radical change wouldn’t come again until the Electricity Act of 1989, which was part of Margaret Thatcher’s governments’ pushes to privatize utilities. The Central Electricity Generating Board was dismantled, re-creating a competitive generation market while the newly formed National Grid Company took over transmission and was privatized through a 1995 stock market flotation. Regional electricity boards became fourteen private Distribution Network Operators. The Distribution Network Operators underwent multiple ownership changes and consolidations, eventually forming the current structure of six ownership groups operating fourteen license areas, all functioning as regulated private monopolies.

The privatization has gone on to be a matter of controversy ever since, with critics accusing the privatized National Grid public limited company of prioritizing dividends and profits over investment. But this is simplistic. By allowing private companies to invest in the network, transmission and distribution costs have fallen by 30 percent since the 1990s. Meanwhile, nationalization came with its own distortions. For example, to support domestic industry, the Central Electricity Generating Board would pay twice the international price for coal.

Overall electricity prices continued their slow decline until 2002, after which point the centuries-long trend turned around.

The current government made the decision to renationalize the operation (although not ownership) of the electricity network, moving this task out of National Grid into a new National Energy System Operator in October 2024. This takes our model full circle back to a version of the 1920s: national operation with private ownership. As in the early days of the UK’s electricity network, we are now seeing the consequences of fragmented planning, as our account of the breaking of the grid makes clear.

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Alex is an editor at Works in Progress, focused on AI and energy. He’s also the author of Chalmermagne, a Substack covering technology, policy, and finance.

The developed world faces below replacement fertility that is driven by people having fewer children than they would like to have. This has serious social and economic ramifications: it creates aging populations with fewer workers for every dependent and fewer innovators. Already, the aging population accounts for a third of the output gap from pre-2008 trends in the US. Contrary to popular perception, having children does not destroy the environment. And, perhaps most importantly, people are having fewer children than they say their ideal is – a striking gap.

As such, there is growing interest in what policies could support people in their family formation aspirations, including financial measures which can affect how much people on the margin feel sufficiently supported to take the jump to create families.

The United Kingdom, along with a number of other countries with low fertility like Italy and Japan, is under fiscal strain. This make it a tough political sell to spend more public money to support people in having families.

Fortunately, there is a list of zero-cost, politically feasible policies to support family formation. At the top of the list was taking the amount we currently spend on child benefit, and front loading it, so families can get the entire net present value in one go, if they wish.

Front loading child benefit would be popular, it would support families and family formation (to the betterment of our long run economic growth outlook) and it would come at zero or minimal fiscal cost (depending on implementation). The government could expedite its implementation tomorrow by lending its support for an existing bill.

It might seem like merely changing the timing of a benefit rather than its amount, would have no impact. But it can make an enormous difference as it provides a way of maintaining living standards at a time when they would otherwise take a dip.

The direct monetary cost of raising a child is at its highest when a child is young. The Child Poverty Action Group estimated in 2022 that the cost of raising a one year old is £273 a week, falling to £73 a week by age 16. When a child is born, they are expensive. They require their own equipment: cots and push chairs and the like. They require extensive care that is usually delivered at a mix of financial cost (in the case of paid childcare) and opportunity cost (in the case of care done by the parents). As children get older, they increasingly look after themselves (or at least the care they require becomes less intensive). This means that a front-loaded child benefit meets financial need where it is greatest. (This also means that it could be an efficient way to reduce child poverty, fulfilling the original motivation for child benefit.)

The Child Poverty Action Group’s figure is also a large underestimate of the full change in financial burden as a child grows older, because it does not consider the other tradeoffs that new parents undergo. Many parents work less during their children's early years which is an additional burden on parents’ finances. As a child grows older, it becomes easier for parent and child alike to juggle work with family.

Average earnings increase continuously from 18 to 50. In 2022, the average age of becoming a mother was 30.9 years (33.7 for becoming a father) in England and Wales. Given earnings trajectories and age of parenthood, parents are typically earning less when their children are young than they will when their children are older. A front-loaded child benefit would supplement parental income when it is at its lowest.

There is also the discount rate to be mindful of; people decrease the value of a given amount of money in the future by as much as 6.5 percent per additional year of waiting – perhaps more for a government benefit that is insecure. The evidence suggests that this discounting mutes the incentive effects that otherwise exist for ongoing benefits.

Studies looking at ongoing payments show they can have a modest increase in births. One study looking at Western Europe found, on average, there was a moderate boost to birthrates from benefits distributed across the duration of childhood. A rough calculation of OECD figures found that support of 87 percent of GDP per capita, distributed over sixteen years (similar to the over £20,000 of the UK's child benefits for eldest children), only boosts births by 3 percent. Third child births are generally known to be sensitive to financial support, yet the withdrawal of child benefit for third-borns precipitated a four percent fall in third births – noticeable, but not game-changing.

Lump payment benefits, concentrated in the early years, are different. One study of Spanish lump sum payments finds much larger effects. The first investigation looked at birth rates in Quebec following the introduction of large, lump-sum baby bonuses. According to the study, every one percent of GDP per capita offered to parents and prospective parents raised births by 0.25 percent. This implies effects at least three times more powerful than ongoing payments, and perhaps as much as eight times larger.

In 2022, Lord Farmer suggested a British bill to allow parents to bring forward future child benefit payments, such that the overall amount of child benefit would be the same. It remains in committee stage, a fate common for bills introduced by parliamentarians without government endorsement. If it wished to easily and cheaply support young families, the British Government could extend its support to Lord Farmer’s bill, increasing the speed through which the bill would likely pass through parliament and its chances of succeeding.

Peter Brookes is the director of the Centre for Family and Education.

Over 90,000 Americans are waiting for kidney transplants, with thousands dying each year. For those who get dialysis, the treatment is painful and exhausting. Thirty-seven percent of patients were forced to quit their jobs. The five-year death rate is similar to brain cancer.

Now, over 40 years since the National Organ Transplantation Act of 1984 made compensating kidney donors illegal in the United States, there might be hope. The End Kidney Deaths Act, a new piece of legislation to offer a $50,000 refundable tax credit to all non-directed kidney donors, spread out over five years. It has gained bipartisan support and a steadily growing number of cosponsors, including most recently Speaker Emerita Nancy Pelosi. This will hopefully be the year when compensating kidney donors becomes possible again.

The kidney crisis keeps getting worse

The current system of kidney donation based on goodwill has failed. Living kidney donations have stayed flat at around 6,000 per year for a quarter century despite the growing waitlist: 9,000 people were on the kidney waitlist in 1984, while 90,000 are waiting now. From 2010 to 2021, over 100,000 Americans died while on the kidney waitlist or became too sick to remain eligible.

When any form of compensation for kidney donors was banned in 1984, the lead sponsor, of the legislation, then-Congressman Al Gore, acknowledged the possibility that a purely altruistic system might be insufficient, and argued that if voluntary donation efforts failed to meet demand, tax credits should be considered as an alternative approach. After four decades of persistent shortages, we have sufficient evidence to conclude that the current system is inadequate.

We also now know empirically that compensating donors will work. Unlike most countries that rely solely on unpaid donations, the U.S. permits up to $1000 per month as compensation for plasma donors. This policy has been remarkably effective. America supplies approximately 70 percent of the world's plasma needs through its paid donor system, exporting this vital medical resource to countries that lack sufficient domestic supply due to their donor compensation prohibitions.

There is evidence from kidney donations, too. Israel, now the worldwide leader in living kidney donations per capita, enacted a 2008 law providing living organ donors with a month's paid salary and lower health insurance premiums. This reform, combined with nonprofit recruitment efforts, has made Israel unique: in 2022, about 50 percent of all transplants came from living donors, compared to just 15 percent in the United States. In the US, New York increased their living donation rates by 52 percent by merely reimbursing donors for out-of-pocket expenses up to $10,000.

How the End Kidney Deaths Act would work

The End Kidney Deaths Act (H.R. 9275) would establish a five-year refundable tax credit for non-directed living kidney donors – those who donate to strangers rather than to friends or family members. Donors would receive $10,000 annually for five years ($50,000 total) after surgery. These staggered payments are an important safeguard, as it reduces the potential attraction of kidney donation to financially desperate people in need of an immediate payout.

The tax credit is refundable, which means donors receive the full value regardless of their tax liability. This makes the incentive equally accessible across income levels, unlike standard tax credits that only benefit those with sufficient taxes to offset.

In addition to the human cost, the kidney shortage is a massive financial drain. End-stage renal disease occupies a unique position in American healthcare policy. Since 1972, it has been the one of two specific conditions (the other being ALS) for which Medicare provides universal coverage regardless of age, and without the standard 24-month waiting period for Social Security Disability Insurance. Effectively, a limited form of medicare for all. Congress made this exception in 1972 because the treatment for kidney failure, dialysis or transplantation, is essential, costly, and often not covered by private insurance.

Currently, approximately 550,000 Americans receive Medicare-funded dialysis, costing around $82,000 per patient annually. This expense consumes over one percent of the entire federal budget, or more than six times NASA's budget. Because transplants are much cheaper than dialysis, eliminating the kidney shortage by compensating donation would likely save taxpayers tens of billions of dollars.

What’s taken so long?

The four-decade delay in reforming kidney donation policy stems primarily from institutional resistance to change. Living kidney donation peaked in 2004 and has stagnated or declined since, despite technological and medical improvements. The current system does not expand access to living donations. The 1984 framework has remained largely unaltered despite mounting evidence of its inadequacy.

When compensation does get discussed, one counterargument tends to come up more than others: that donation would unduly commodify the human body, hurting the dignity of kidney donors. In other words, kidney donors should be donors, not vendors.

The opposite is actually true: kidney donors have been leading the charge for the End Kidney Deaths Act because they feel neglected by the current system. Everyone in the transplantation process – doctors, hospitals, coordinators – receives payment except the donor. Donating a kidney is safe, but it’s stressful, time-consuming, and painful. Offering compensation to kidney donors would honor the gift they are making.

Elaine Perlman is the President of the Coalition to Modify NOTA and Executive Director of Waitlist Zero

Duncan McClements is a fellow at the Center for British Progress and the Adam Smith Institute.

Jason Hausenloy is an independent AI policy researcher.

John von Neumann’s life was cut short in 1957, when he died of pancreatic cancer at the age of 53. With his passing, the world lost an outlier among prodigies. ‘Most mathematicians prove what they can. Von Neumann proves what he wants,’ quipped his colleagues at Princeton’s Institute of Advanced Study, where von Neumann had assumed a tenured professorship in 1933 at the age of 30. He was a lover of parties and limericks, a genius who proved foundational insights that spawned game theory, nuclear physics, the mathematical foundations of quantum mechanics, and many other fields besides.

Among his many interests, von Neumann had begun exploring the connection between computation and thermodynamics. The inquiry stemmed from his observation that computers, unlike most machines, seemed to generate heat without performing physical work in the conventional sense. While appliances like light bulbs and cars convert electricity into useful forms of energy, computers primarily manipulate information. The link between information processing and energy expenditure intrigued him: if computers play with abstractions rather than matter, why did they get hot?

In this, von Neumann was following a long tradition of engineers and physicists wrestling with how to conserve energy. Over a century earlier, the French physicist Sadi Carnot had demonstrated that any steam engine operating between two temperatures has a maximum possible efficiency that cannot be exceeded, regardless of its design. Von Neumann intuited that a similar limit might govern the efficiency of computers – where, instead of steam, the ‘engine’ involved the movement of information.

Though von Neumann never published these thoughts, his questions echoed in the minds of those who’d worked in his orbit. One such person was Rolf Landauer, a physicist at IBM. Like Von Neumann, Landauer was a Jewish refugee, and had fled Nazi persecution in Germany as a teenager in 1938. After earning his PhD from Harvard, Landauer joined IBM’s research division, where he began to study the thermodynamic costs of computation.

In 1961, Landauer published a paper that formalized what would become known as Landauer's principle. This established that erasing information necessarily releases heat. To understand why this happens, we need to consider what computing means from the perspective of information. A typical chip is made up of multiple logic gates, which perform operations by producing outputs based on inputs. Most logic gates have fewer possible output states than input states. For example, a gate with two inputs (each either 0 or 1) has four possible input combinations (00, 01, 10, 11), but only two possible output states (0 or 1).

What’s more, this operation involves erasing information because you can’t know for sure which inputs yielded the outputs you can see. Imagine calculating 2+2. Once arrived at the answer 4, it is no longer possible to distinguish between that calculation and inputting 3+1, 2+2, or 4-0.

This reduction in possible states affects something called entropy. It’s a complex and contested term, but one way to think about it is as a measure of the number of ways a system can be arranged. Higher entropy means more possible arrangements; lower entropy means fewer. An easy way to illustrate this is with a deck of cards. A new deck arranged in ascending order by suit and number has low entropy, since there’s only one way to sort it; but a shuffled deck has higher entropy, since there are so many ways it could end up. In computing, this is why logical operations lower the system’s entropy. They reduce four possible input states to two possible output states.

But according to the second law of thermodynamics, a system’s total entropy can never decrease. This means that ‘lost’ entropy must be compensated for by generating heat. It can be thought of as nature’s version of double-entry bookkeeping – any reduction in a system’s information content is balanced by an increase in thermal energy. Landauer figured out that every time a computer resets a bit of memory from 1 to 0 the minimum heat dissipated is about 3 × 10^-21 joules at room temperature – roughly equivalent to the energy released when two molecules collide with one another.

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Landauer had transformed an intuition about the physics of computation into a precise and measurable principle. But his solution presented a conundrum. If erasing information always costs energy, then perhaps computation without destruction could proceed with a negligible energy cost. However, for lossless processing, memory would need to grow continually, creating an impractical accumulation of stored states with each calculation – a kind of computational junkyard of past operations.

Enter Charles Bennett – a physicist also working at IBM Research. In the early 1970s, he had an important insight: what if, after completing a computation and recording the result, the computer could run the entire process backward, returning to its initial state? He set out his thinking in a 1973 paper, ‘Logical Reversibility of Computation,’ which became the foundation for a series of papers he would publish over the next decade and beyond. Bennett’s approach was like a hiker who retraces their steps, removing all evidence of their passage through the wilderness. The computation could proceed forward, produce a result, make a copy of the answer, and then ‘decompute’ the whole trace by reversing itself – recycling the energy rather than releasing it as heat.

Consider this in terms of addition. In conventional computing, when we calculate 3 + 5 = 8, the information about which numbers were added is typically discarded once the sum is obtained. In Bennett's reversible paradigm, the computation would temporarily retain enough information to work backward from 8 to recover the original inputs 3 and 5.

By preserving this information, the system avoids the thermodynamic costs associated with erasing data. Bennett offered a way around the limitations that Landauer had identified, and demonstrated that reversible computing was theoretically possible.

In the early 1980s, two MIT researchers, Tommaso Toffoli and Ed Fredkin, would conceptualize so-called reversible logic gates – the fundamental building blocks for reversible computers. Fredkin was born to Russian immigrants in Los Angeles and had dropped out of Caltech to train as a fighter pilot. In 1962 he founded one of the first computing companies, Information International, Inc. Commonly known as ‘Triple I’ or ‘III’, it was an inventive place, developing machines for transferring digital images to film, scanning words on a page, and generating computer graphics. When III went public, Fredkin became a millionaire, and bought himself a private island in the Caribbean. At the age of 34, he was recruited by Marvin Minsky to join MIT as a full professor, despite possessing no formal degree.

Toffoli and Fredkin’s gates had the remarkable property that their outputs uniquely determined their inputs, which meant no information was ever lost. They achieved this by having the same number of output bits as input bits, maintaining a one-to-one correspondence between input and output states. These gates represented a crucial step from theory to reality. While Bennett had proved that reversible computing was theoretically possible, Fredkin and Toffoli showed how it could be built.

Around the same time as Toffoli and Fredkin were devising their reversible logic gates, the physicist Richard Feynman began cultivating his own ideas about the potential of reversible computation. Feynman had crossed paths with von Neumann on the Manhattan project, and had become a legendary figure in his own right. He was also close friends with Fredkin, and served as best man at Fredkin’s (second) wedding in 1980 in the Virgin Islands. Lately, Feynman had also become fascinated by the question of whether computers could efficiently simulate quantum physics.

Quantum mechanics is built on reversible laws, meaning that at the microscopic level, the equations governing subatomic particles work the same whether time moves forward or backward. In everyday life, though, we only see time flowing in one direction. A dropped glass shatters, but it never jumps back together. This is because the macroscopic world is dominated by entropy, which gives time its arrow. But underneath it all, nature does not actually distinguish between past and future. Reversible computing is not just a clever engineering trick; it may be tapping into the same fundamental logic that governs reality itself. It feels strange, but only because the universe is far stranger than how we experience it through our senses.

By the mid-1980s, Feynman had integrated these ideas into his vision for the future of computing.

‘The laws of quantum mechanics are reversible,’ Feynman explained at a lecture delivered in Tokyo, ‘and therefore we must use the invention of reversible gates.’ Acknowledging the work of Charles Bennett, Feynman compared a standard computer to a car ‘which has to start and stop by turning on the engine and putting on the brakes, turning on the engine and putting on the brakes; each time you lose power.’ The reversible alternative would be like connecting the car’s wheels to flywheels – storing energy to be used by the system, rather than wasting it.

Feynman recognized that reversible computing represented an insight into the nature of computation, even if its full implementation would be impossible for a long time.

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Unfortunately, reversible computing proved to be the victim of historical irony. Quantum computing, an outgrowth of the search for reversible computing, would end up distracting from and overshadowing its originator.

The quantum approach dazzled funders with its properties – the ability to exist in multiple states simultaneously through superposition, to exhibit spooky action-at-a-distance via entanglement, and to promise exponential speedups on problems like factoring large numbers. And as quantum computing grew in glamour and status, it cannibalized the field that had spawned it. Reversible computing became unfashionable, while quantum research drew billions in investment.

Outside academia, mainstream computing forged ahead. In 1965, Gordon Moore, the co-founder of Intel, had observed that the number of transistors on integrated circuits, and the corresponding computing power, was doubling approximately every two years – a predictive heuristic that became known as Moore’s Law.

Intel was at the forefront of this boom. At their peak, Intel released new products roughly every six months, with double the performance or half the price of their predecessors. Yet this breakneck pace imposed a certain cost on the computing industry. Intel’s architecture wasn’t intrinsically superior as the foundation for mass computation; after all, it was based on a transistor originally developed by Bell Labs to boost long-distance telephone signals, and was later adapted for computing because it could perform Boolean logic operations.

The pursuit of market dominance made it nearly impossible for alternative frameworks like reversible computing to gain a foothold – even inside Intel itself, where internal teams continued to tinker and experiment with different approaches. But the established infrastructure, supply chains, and continuous stream of improvements in conventional computing created momentum that was difficult to overcome.

To be fair, Intel’s strategy worked spectacularly well for decades. It had its share of competition: Atari was built with Motorola processors, and the iPhone ran and continues to run on chips designed by a British company known as ARM. But it was Intel that catalyzed the PC, the World Wide Web, the personal computing revolution.

Yet as the years roll on, physical limitations are emerging. By the early 2000s, Dennard scaling, which had allowed transistors on chips to become smaller without a corresponding increase in power, broke down. Suddenly, chips hit what the industry called a ‘power wall’: they couldn’t get faster simply by shrinking their transistors, because they’d have ended up melting from the heat. The risks posed by heat, rather than our ability to design faster circuits, became the primary constraint on performance. The industry shifted towards multi-core processors, but the fundamental problem remains: conventional computing is approaching its thermodynamic limit.

The energy required to power AI compute in particular is astronomical – in large part because so much of it is frittered away as heat. This demand has emerged precisely as Moore’s Law is faltering. We find ourselves needing exponential increases in computation, yet our current architecture can’t deliver it without needing large increases in our energy supply.

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The bet on reversible computing is what my team and I at my company Vaire Computing are hoping to redeem. We are working on what we call Near-Zero Energy Chips. Some say reversible computing is a 21st-century technology that was discovered by accident in the 20th century. We are not there yet. While Vaire’s chips can recycle energy, the current challenge is that the reversible logic – the fundamental circuitry – is more complex, which offsets some of the energy savings. When we manage to reduce these overheads, NZECs will start to make commercial sense.

Could we one day process information at energy levels below the Landauer limit? It might sound like a violation of physics, but it is not. Landauer’s limit only applies when information is erased. In reversible computing, nothing is lost, so the limit does not apply in the same way. The real challenge is to build systems that preserve information throughout the computation while remaining practical and efficient.

If we could design computers from first principles with humanity’s long-term needs in mind, we probably would not have built the machines we rely on today. But the path ahead may still lead to the destination that von Neumann glimpsed: computers that process information without waste, and where energy costs are no longer a barrier to progress.

Rodolfo Rosini is the CEO of Vaire Computing.