Why the world’s biggest EV maker is getting into shipping

Earlier this month, a massive ship picked up over 5,000 electric cars from two ports in northern and southern China. Five days later, it passed through Singapore, and it is now headed for India. However, its final destination is in Europe, where most of the cars will be sold. 

The ship’s name is BYD Explorer No.1. As the first of a massive fleet that BYD is building, it reflects the Chinese company’s ambition to establish a seafaring business that supports its new role in the global car trade.

There’s rising appetite for BYD’s cars overseas. In 2023, BYD exported over 240,000 vehicles, up from 55,000 in 2022. But it’s run into a snag: to get the most financial benefit from its exploding popularity abroad, it’s having to expand beyond the car trade into the shipping business. Read the full story.

—Zeyi Yang

To read more about BYD’s shipping ambitions, check out the latest edition of China Report, our weekly newsletter giving you the inside track on all things happening in China. Sign up to receive it in your inbox every Tuesday.

How new magnets could accelerate climate action

The motor in your vacuum cleaner and the one in your electric vehicle likely have at least one thing in common: they both rely on powerful permanent magnets to function. But the materials for those magnets could soon be in short supply. 

The permanent magnets used in high-end motors today are built using a class of materials called rare earth metals. Demand for these materials is expected to skyrocket in the coming decades, fueled in particular by the growth of electric vehicles and wind turbines. But there’s good news: work is underway to address this looming shortage. Read the full story.

—Casey Crownhart

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Big Tech is preparing to face a grilling in the US Senate over child safety
X boss Linda Yaccarino will testify alongside fellow leaders today for the first time. (Insider $)
+ The Senate and the House can’t agree on what should be done. (FT $)
+ Here’s a handy who’s who of who’s testifying today. (WP $)
+ Why child safety bills are popping up all over the US. (MIT Technology Review)

2 Wuhan is becoming a major autonomous vehicle test bed
So much so that China poses a mounting challenge to the west’s driverless dominance. (FT $)
+ General Motors is slashing its spending on Cruise robotaxis. (Reuters)
+ A race for autopilot dominance is giving China the edge in autonomous driving. (MIT Technology Review)

3 Fake AI-generated images of celebrities are spreading across Google
All fingers point to an aspiring movie star. (Motherboard)
+ These six questions will dictate the future of generative AI. (MIT Technology Review)

4 How a missing chip shipment sparked a US probe
Authorities stepped in to investigate suspicions that it was ultimately bound for China. (WSJ $)
+ New kinds of chips are on the way. (IEEE Spectrum)
+ The next big thing? Origami computers, obviously. (Quanta Magazine)
+ China’s big volley in the semiconductor exports war. (MIT Technology Review)

5 Apple’s Vision Pro headset gathers reams of data
And it could end up revealing much more than anticipated. (WP $)
+ Apple is relying on its cool cachet to get people to wear them in the first place. (Bloomberg $)
+ Meanwhile, Meta’s AR glasses division looks like it’s struggling. (The Information $)

6 A single pig butchering scam made fraudsters $40 million
But the true amount is likely to be even higher. (404 Media)
+ The involuntary criminals behind pig-butchering scams. (MIT Technology Review)

7 Is AI drug discovery really better than humans?
Just because it’s faster doesn’t necessarily mean it’ll be more effective. (Bloomberg $)
+ AI is dreaming up drugs that no one has ever seen. Now we’ve got to see if they work.  (MIT Technology Review)

8 A new theory of how everything came to be is emerging
It’s a riff on quantum theory using the laws of thermodynamics. (New Scientist $)
+ Why is the universe so complex and beautiful? (MIT Technology Review)

9 The JWST has captured some beautiful spiral galaxies
Prepare to be dazzled. (The Atlantic $)
+ Contrary to what you may have heard, aliens have not visited Earth. (NY Mag $)

10 TikTok’s bite-sized soap operas are gripping fans
The minute-long clips are formulaic, but extremely compulsive viewing. (NYT $)

Quote of the day

“We’ve been better, Elmo.”

—An X user responds to Elmo the lovable muppet’s mistake of asking how everyone was doing on the social network, the Washington Post reports.

The big story

Inside the cozy but creepy world of VR sleep rooms

March 2023 

People are gathering in virtual spaces to relax, and even sleep, with their headsets on. VR sleep rooms are becoming popular among people who suffer from insomnia or loneliness, offering cozy enclaves where strangers can safely find relaxation and company—most of the time.

These rooms are created to induce calm. Some imitate beaches and campsites with bonfires, while others mimic hotel rooms or cabins. 

The opportunity to sleep in groups can be particularly appealing to isolated or lonely people who want to feel less alone, and safe enough to fall asleep. The trouble is, what if the experience doesn’t make you feel that way? Read the full story.

—Tanya Basu

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Omg it’s an actual baby shark! (doo doo doo doo).
+ A potted history of beds, and why they’re so wonderful
+ Drop everything: this is how your precious cat experiences the world.
+ Some essential tips on what to do should you ever come across an escaped monkey (above all, don’t panic.)
+ Yes chef! Here are the brightest rising culinary stars you’ll want to keep an eye on.

For people who have been watching BYD for a long time, it won’t be surprising that the company has just ventured into a new field. 

The Chinese electric-vehicle maker has been particularly good at expanding into different, related businesses. Not only can it make high-performing and safe batteries for cars, but it also does almost everything in house, from designing car chips to mining lithium and other materials. The fact that it has subsidiaries in every step of the EV supply chain enables the company to keep its costs down and sell cars at more competitive prices.

Now, to pull that off once again, BYD is starting a sea freight business. As I just wrote in a story published today, the company is assembling a fleet of at least eight car-carrier ships that will transport BYD cars from factories in China to sell in Europe, South America, and other markets.

BYD has had a meteoric rise to become the Chinese EV sector’s poster child in recent years, and 2023 was particularly good for the company. It sold 3 million electric cars and plug-in hybrid models last year, up from 1.8 million in 2022. BYD managed to beat Tesla to become the world’s top-selling EV company in the fourth quarter of 2023. 

While the majority of those cars were sold in China, BYD’s export business has been expanding significantly. It exported over 240,000 cars in 2023, more than a fourfold increase from 55,000 cars in 2022; and the latter number was itself more than a fourfold increase from 13,000 in 2021.

But one thing has been getting in the way of these bonkers numbers: the lack of car-carrier ships internationally. A bust cycle in the international shipping industry since 2008, the technological challenge of making ships greener, and the fact that existing vessels are often already reserved by automakers in other countries—these factors have collectively resulted in ever-rising costs to hire a ship that can transport Chinese EVs abroad.

So Chinese companies like BYD and SAIC Motor are following in the footsteps of Japanese and Korean automakers: they’re building, chartering, and managing their own fleets of ships. This January, one boat operated by BYD and another operated by SAIC Motor set sail for the first time, between them carrying over 10,000 vehicles toward Europe. 

These two massive ships are a symbol of just how competitive and successful China’s EV industry has become. And that’s likely to continue for some time, as other countries and traditional car brands are belatedly playing catch-up.

This is not to say China’s EV industry has nothing to fear. As I’ve laid out in previous articles, there are still factors that could slow down or even derail the export of Chinese EVs. Geopolitics is a major one. For example, in Europe, where many of the new car-carrier ships are heading, there’s already an anti-subsidy investigation against Chinese cars going on, which could end up making it much more costly to sell there.

Chinese companies going into sea shipping should note at least one cautionary tale from recent history. Before BYD, there was another Chinese car company called Chery, which started exporting its cars in the 2000s. In 2007, it acquired a shipbuilding company for the exact same reason: it wanted to increase the capacity to ship cars abroad. But the financial crisis doomed Chery’s burgeoning export business, and it didn’t build its first ship until a decade later. 

Chery is still around today. It has made the pivot from gas to electric cars and is competing with BYD both domestically and in the export market. But its ill-fated shipbuilding attempt could be a lesson for other Chinese companies that are now making similar moves: even though the future looks bright, building and maintaining these massive ships is a risky, expensive business if their car sales don’t keep up.

Do you think it’s the right decision for companies like BYD and SAIC Motor to build their own car-carrier fleet? Tell me your thoughts at zeyi@technologyreview.com.

Catch up with China

1. The White House plans to cut off Chinese entities’ access to American cloud services to train AI models. (Reuters $)

2. Some legislators in the US want to reactivate the Justice Department’s China Initiative. (NBC News)

• The controversial program was built to protect national security. But it strayed from its focus and ended in 2022. (MIT Technology Review)

3. Another proposed bill in Congress seeks to ban Chinese biotech firms from federal contracts. (South China Morning Post $)

4. After an almost five-year import freeze on Boeing’s 737 MAX, Chinese airline companies have restarted purchasing the controversial jet model. (Reuters $)

5. The Chinese movie market used to be a cash machine for Hollywood blockbusters. Not anymore. (New York Times $)

6. The Taiwanese government is funding efforts to build its own Chinese AI model that’s free of China’s political influence. (Bloomberg $)

• Meanwhile, US spies want an AI model of their own to use against China without leaking national secrets. (Bloomberg $)

7. Elon Musk has praised Chinese electric vehicles, again. He says Chinese EV makers will “pretty much demolish” most competitors if there are no trade barriers. (CNBC)

Lost in translation

Another type of device is getting an AI transformation in China: student tablets. Commonly called “learning machines” (though they have no connection to machine learning), these are tablets specifically designed to tutor children in school subjects, supporting functions like electronic dictionaries and virtual classes. According to Chinese outlet IQ Tax Research Center, many of these sorts of products have embraced AI in the past year, including devices made by China’s leading AI companies like Baidu and iFlytek. 

However, some parents have found these “AI-powered devices” prone to errors and inaccuracies. For example, one user mentioned that a math problem was solved with different answers each time the AI explained it. Others felt the educational content recommended by the AI was not always suitable for their children’s needs. At the end of the day, these “learning machines” are often still inadequate, despite how they are marketed.

One more thing

Do you stick to reserving dinner at restaurants with 4.5+ stars on Google? In China, some young people have had too many disappointing experiences chasing after viral restaurants with inflated reviews. Instead, they are starting a trend of choosing restaurants with review scores around 3.5. Their justification? “If a restaurant can survive for decades with such a low review, there must be something really special about it,” one comment on social media reads. It’s also about rebelling against the ubiquitous digital platforms that dictate where everybody goes, reports China’s Lifeweek magazine.

Permanent magnets can maintain a magnetic field on their own without an electric charge. They’re commonly used in motors, making them spin when an electric field is applied. The permanent magnets used in high-end motors today are built using a class of materials called rare earth metals. Demand for these materials is expected to skyrocket in the coming decades, fueled in particular by the growth of electric vehicles and wind turbines. As mines and processing facilities struggle to keep up, supplies may stretch thin.

One Minnesota startup has been working to address this looming shortage. Niron Magnetics is building a large-scale manufacturing facility to produce iron nitride, a magnetic material derived from common elements, while also working to improve the material’s properties so that it can be used in stronger magnets to power more products. The results may help address yet another coming supply crunch that threatens to slow down action on climate change.

A growing gap

The permanent magnets you’re probably most familiar with are the cheap ones made from materials called ferrites that are holding up postcards and wedding announcements on your refrigerator.

But many of the devices sprinkled through our daily lives, like our vacuums and EVs, require much higher-powered magnets. Motors that generate motion using permanent magnets tend to be more powerful and efficient, so rare earth metals, such as neodymium and dysprosium, have become vital for a wide range of devices. In a wind turbine, for instance, magnets in the generator harness motion from the blades and turn it into electricity.  

Like many of the other materials needed for clean energy technologies, we can expect a meteoric rise in demand for rare earth metals used in magnets as the world rushes to address climate change.

In the case of neodymium and dysprosium, supply will need to increase sevenfold by 2050 just to meet demand for wind turbines, says Seaver Wang, co-director of the climate and energy team at the Breakthrough Institute, an environment and policy think tank.

In addition, rare earth metal demand for electric vehicles could increase 15-fold from today’s levels by 2040, according to an analysis from the International Energy Agency. And it’s not just clean energy technologies—increased access to electricity and cheap electronics means demand for rare earth metals will rise across other sectors, too. 

The world is unlikely to exhaust the geological reserves of rare earth metals anytime soon, Breakthrough’s Wang says—rare earth metals aren’t actually all that rare, at least when it comes to the entire planet’s supply. But they don’t tend to be very concentrated even in the places they are found, so scaling the supply of rare earth metals quickly and economically enough will be a major challenge.

In the near term, global demand for magnets made with neodymium could triple by 2035, while production will likely only double by then, given the long lead times required to build new mines, according to materials research firm Adamas Intelligence.

Given the growing demand, “the world needs a different solution and technology,” says Jonathan Rowntree, CEO of Niron Magnetics.

Few alternatives to permanent magnets exist today. Recycling can help reduce the need for future rare earth mining and processing, but there won’t be enough used material to meet the growing demand for decades.

Tesla announced in 2023 that it would move away from rare earth metals in its motors in the future, though the company hasn’t shared details about how it will do so. Some experts have speculated that it plans to use lower-powered ferrite materials, which would add bulk and weight to the motor. 

Rowntree and his colleagues see iron nitride as part of the solution to the anticipated problem of constraints in the supply of rare earth metals. Iron nitride magnets don’t use those metals, and they don’t require cobalt, another metal sometimes used in magnets (and in lithium-ion batteries) that’s under growing scrutiny because of the environmental and humanitarian issues often associated with its mining. And some experts say these iron-based materials might end up creating magnets just as strong as those that include rare earth metals. 

An attractive alternative

Though iron nitride (specifically, a phase called alpha double prime) was discovered in the 1950s, it wasn’t until the 1970s that researchers discovered its strong magnetic properties, says Jian-Ping Wang, a professor at the University of Minnesota and the technical founder and chief scientist at Niron Magnetics.

Even then, scientists couldn’t explain the physics underlying the material’s magnetic properties, and they struggled to recreate magnetic samples reliably through the 1990s. Intrigued by this problem, Wang began work on iron nitride materials at the university in 2002.

After making hundreds of samples and working for nearly a decade, Wang cracked the code to reliably make iron nitride materials in thin films. He presented his findings at a major conference in 2010, the same year geopolitical tensions between Japan and China sparked a huge increase in the price of rare earth metals.

Suddenly, there was a greater appetite for alternatives to rare earths that could be used to make strong permanent magnets. The US Department of Energy’s ARPA-E office sponsored grants to develop such materials, awarding one to Wang and the research that would eventually become Niron Magnetics.

Rare earth metals became ubiquitous across technologies because they represented “a huge jump” in the energy density of magnets when they were discovered in the 1960s, says Matthew Kramer, a senior scientist at Ames National Laboratory.

One of the primary gauges of a magnet’s properties is its energy density, measured in mega-gauss-oersteds (MGOe). While the ferrite magnets on your fridge likely have an MGOe of around 5, neodymium-based magnets are much stronger, reaching around 50 MGOe.

Rare earth metals like neodymium are currently a crucial ingredient in permanent magnets because they can wrangle other metals into an arrangement that helps generate a strong magnetic field.

Permanent magnets produce magnetic fields because of spinning electrons, small charged particles in atoms. Different elements have different numbers of free electrons that in some circumstances can be made to spin in the same direction, generating a magnetic field. The more electrons that are free and spinning in the same direction, the stronger the magnetic field.

Iron has a lot of free electrons, but without an overarching structure they tend to spin in different directions, canceling each other out. Adding in neodymium, dysprosium, and other rare earth metals can help arrange iron atoms in a way that allows their electrons to work together, resulting in powerful magnets.

Iron nitride does what few other materials can: it arranges iron into a structure that gets electrons spinning together in this way and keeps them aligned—no rare earth metals required.

“If you could get the nitrogen to spread these irons out in the appropriate way, you should be able to potentially get a really, really good permanent magnet,” Kramer says. That has proven to be a challenge though, he adds, because it’s difficult to make these materials in bulk and to harness the complex chemistry in a way that forces them to retain their magnetization. 

Idea to execution

After Wang was able to reliably create thin films of iron nitride, the next step was to figure out how to make it in bulk, grind it up, and squish it together to make magnets.

Finding a manufacturing process was a challenge in part because iron nitride degrades at high temperatures, which limits the options available in traditional magnet manufacturing, Wang explains. He developed several methods to make iron nitride in bulk, one of the most promising of which involves diffusing nitrogen through iron oxide (rust is a type of iron oxide) under very specific conditions.

In recent years, Niron has focused on perfecting and scaling up the manufacturing process, Rowntree says. A significant remaining challenge is determining how to help iron nitride reach its full potential.

NIRON MAGNETICS

In theory, iron nitride should be able to produce magnets that are even stronger than neodymium ones. But today, Niron’s magnets can only reach around 10 MGOe, Rowntree says. That’s sufficient for devices like speakers, which the company is exploring as an early product. It displayed small speakers made with Niron magnets at CES in January.

With higher magnet strength, iron nitride magnets will be more useful in devices like electric vehicles and wind turbines. In theory, the material should be able to reach 20 to 30 MGOe using Niron’s current manufacturing method, Wang says, though achieving that will require “a lot of optimization.” The theoretical ceiling is much higher, with iron nitride potentially being able to form magnets stronger than the neodymium ones used today.

Niron recently received over $30 million from investors, including GM Ventures and Stellantis Ventures, for a total of more than $100 million in funding. The company is working to scale up production capacity in its current pilot plant, with the aim of reaching 1,000 kilograms of production capacity by the end of 2024. 

Niron’s work, along with other alternatives and workarounds, could be crucial in loosening a major potential bottleneck for several critical climate technologies. 

“Increased magnets and increased magnet supply are critical to enabling the energy transition,” says Gregg Cremer, an advisor at ARPA-E. “Without more magnets, we’re just not going to be able to meet our objectives.”

The ship’s name is BYD Explorer No.1. As the first of a massive fleet that BYD is building, it reflects the Chinese company’s ambition to establish a seafaring business that supports its new role in the global car trade.

BYD, founded by a Chinese metallurgy researcher named Wang Chuanfu in 1995, started out making small batteries for mobile devices. It later expanded its business to automobiles and eventually combined the two to make electric vehicles. In two decades, it became China’s largest EV maker. By the fourth quarter of 2023, it was the world’s.

BYD offers a lot of options, ranging from affordable sedans to luxury SUVs, and there’s rising appetite for its cars overseas. In 2023, BYD exported over 240,000 vehicles, up from 55,000 in 2022. But it’s run into a snag: to get the most financial benefit from its exploding popularity abroad, it’s having to expand beyond the car trade into the shipping business. 

The shortage of car-carrier vessels

To understand why BYD has made this move, you need to learn a little about how cars are transported across the sea. Usually, the cargo industry uses roll-on/roll-off (RORO) ships. Unlike ships that use a crane to lift up cargo and place it aboard, RORO ships have ramps that allow vehicles to be driven directly on, making the whole process much easier.

But these ships have been in short supply for the past few years. While old vessels have been entering retirement, new ship orders were down because of the 2008 financial crisis and the industry-wide upgrade to more environmentally friendly fuels, leaving a shortfall. 

Also, most car companies have longstanding relationships with shipping firms or own their own fleets of boats. For example, Japanese car makers like Nissan and Toyota each have fleets of RORO ships that can carry tens of thousands of cars. But China’s domestic car-carrier vessels represent only 2.8% of global shipping capacity, leaving the Chinese brands few options for getting their cars across the seas.

As a result, their access to RORO ships has become prohibitively expensive. According to Clarksons Research, the intelligence arm of the world’s largest shipping services provider, the price to rent (or charter, as the industry says) a car-carrier ship for a day skyrocketed to $115,000 in 2023, a historical high and close to seven times the average pre-pandemic price, which was around $17,000 in 2019.

New demand to ship cars predominantly comes from China right now. The country is on the verge of becoming the world’s largest car exporter (in fact, it may already have gained that status in 2023, but we won’t know until the official numbers are finalized). It exports a mix of traditional gas cars, electric cars made by Chinese companies, and Tesla cars manufactured in the Giga Shanghai plant. 

The shortage of shipping capacity is what’s standing in its way.

Venturing out by themselves

That’s why Chinese auto companies, which have become such prominent exporters thanks to the rise of EVs, are starting to form their own shipping businesses. 

News that BYD was looking to buy or charter ships was first reported by the shipping outlet Lloyd’s List in late 2022. In December that year, the company changed its corporate registration to include the business of international cargo shipping and ship management. MIT Technology Review contacted BYD for comment, but it did not respond in time for publication. 

BYD Explorer No.1 was delivered at the beginning of this year. The RORO vessel, which can carry 7,000 cars at the same time, is officially registered under Zodiac Maritime, a UK company controlled by the Israeli shipping tycoon Eyal Ofer, but BYD has leased it for an undisclosed period of time. In a press release, BYD says it plans to add seven more vessels to the fleet in the next two years. It also plans to let other companies export their vehicles using BYD’s ships, it says.

For its maiden voyage, the ship is carrying over 5,000 BYD vehicles and heading toward the ports of Vlissingen in the Netherlands and Bremerhaven in Germany, according to Chinese state media outlet Xinhua.

BYD is not the only Chinese automaker making this move. SAIC Motor, a Chinese state-owned company, sold 1.2 million vehicles overseas in 2023, 24% of which were EVs. It formed a RORO shipping subsidiary in 2021, and its newest RORO vessel, the largest of its kind and able to carry 7,600 cars, also set sail for the first time in January. Like BYD Explorer No.1, it’s going to Europe.

While BYD has announced that it will add energy-storing battery tech to its vessels, the RORO ships it’s chartering today are not electric yet. Most of the newer ships can be powered by either traditional fuel or liquefied natural gas, which is a cleaner energy source.

From carrying wood pulp to cars

It will be some time before these Chinese companies finish assembling their sea freight empires, as these massive new ships take years to build. In the meantime, some have turned to creative fixes for the supply shortage: repurposing ships that were designed for other types of cargo.

Particularly, they have their eyes on gigantic ships typically used to import thousands of tons of wood pulp from South America to China, where it’s made into everyday products like tissue, paper, and books. These wood-pulp carriers often end up empty or barely loaded on the way back, because China doesn’t have similar products to export. 

However, in recent years Chinese car companies have started to sell their vehicles to the South American continent, and shipping companies saw an opportunity there. China Ocean Shipping Company (COSCO), one of the largest shipping companies in the world, designed a foldable rack that can load cars and stack them up into a wood-pulp carrier. In July last year, COSCO loaded such a ship with over 2,700 cars and sent them to Brazil.

With makeshift arrangements like this and new RORO vessels being built, shipping bottlenecks for Chinese automakers could be significantly reduced in the next couple of years. Having their own fleets or chartering ships from domestic shipping companies could also further drive down costs, making Chinese cars even more competitive abroad. 

And just as the auto industry in Japan and South Korea has pushed these two countries to become global leaders in shipping, EVs could make China a major player in the ocean too.

Three ways we can fight deepfake porn

Last week, sexually explicit images of Taylor Swift, one of the world’s biggest pop stars, went viral online. Millions of people viewed nonconsensual deepfake porn of Swift on the social media platform X, which has since taken the drastic step of blocking all searches for Taylor Swift to try to get the problem under control.

This is not a new phenomenon: deepfakes have been around for years. However, the rise of generative AI has made it easier than ever to create deepfake pornography and sexually harass people using AI-generated images and videos.

Thankfully, there is some hope. Our senior AI writer Melissa Heikkilä has set out three ways we can combat nonconsensual deepfake porn. Read the full story.

Read Melissa’s open letter to Taylor Swift in the latest edition of The Algorithm, our weekly AI newsletter. While the reality is that there is no neat technical fix for this grim problem, Swift’s stature means that she has the rare opportunity—and momentum—to push through real, actionable change. Sign up to receive it in your inbox every Monday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Neuralink has implanted its first device in a human brain, says Musk
He also said the patient is recovering well from the procedure. (WSJ $)
+ The company is yet to share any more concrete details, though. (Wired $)
+ Elon Musk wants more bandwidth between people and machines. Do we need it? (MIT Technology Review)

2 Microsoft has made changes to the AI tool used to create Taylor Swift deepfakes
It closed spelling loopholes in its Designer tool that circumvented its ban on generating nude images. (404 Media)
+ X has lifted its temporary ban on searches for the pop superstar. (WSJ $)
+ The amount of deepfake porn online is likely to skyrocket. (Slate $)

3 Drone warfare is becoming accessible to all
As the attack on a US base in Jordan at the weekend shows, the US no longer has a monopoly on these sorts of strikes. (Vox)
+ Mass-market military drones have changed the way wars are fought. (MIT Technology Review)

4 Amazon has giving up on trying to acquire iRobot
Which is music to regulators’ ears. (WP $)
+ A Roomba recorded a woman on the toilet. How did screenshots end up on Facebook? (MIT Technology Review)

5 Scientists have found the first evidence of transmitted Alzheimer’s cases
A now-banned hormone treatment introduced infectious proteins to patients’ brains. (FT $)

6 We can’t have more electric trucks without installing more chargers
So the biggest truck makers are uniting to pressure the US government to build more. (NYT $)
+ Why getting more EVs on the road is all about charging. (MIT Technology Review)

7 Goodbye chip transistors, hello memcapacitors
The new form of chips would rely on electrical fields, not currents, to perform calculations. (TechCrunch)

8 How the world’s largest music company is experimenting with AI
Universal boss Lucien Grange refuses to run scared. Can he bend AI to his will? (New Yorker $)
+ Sony’s AI ethicist is all about consent. (IEEE Spectrum)
+ These impossible instruments could change the future of music. (MIT Technology Review)

9 TikTok is tinkering with making all posts shoppable
Is there a product in your clip? Tap here to buy it. (Bloomberg $)
+ It looks like its AI identifying tools need a fair bit of work, though. (The Verge)

10 A new hipster social network is on the horizon
Perfectly Imperfect wants to capture the naive promise of the early web. (The Verge)

Quote of the day

“Imagine if Stephen Hawking could communicate faster than a speed typist or auctioneer. That is the goal.”

—Elon Musk describes his ultimate vision for his first Neuralink brain implant product, which he says is called Telepathy.

The big story

Inside the messy ethics of making war with machines

August 2023

In recent years, intelligent autonomous weapons have become a matter of serious concern. Giving an AI system the power to decide matters of life and death would radically change warfare forever.

But weapons that fully displace human decision-making have (likely) yet to see real-world use. Even the “autonomous” drones and ships fielded by the US and other powers are used under close human supervision. 

However, these systems have become sophisticated enough to raise novel questions—ones that are trickier to answer than the well-­covered wrangles over killer robots. What does it mean when a decision is only part human and part machine? And when, if ever, is it ethical for that decision to be a decision to kill? Read the full story.

—Arthur Holland Michel

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ How one man shook his addiction to laverbread seaweed, aka Welshman’s caviar.
+ Toddlers aren’t known for their discerning taste, but some of their books are better than others.
+ Malaysia’s interpretation of Middle Earth’s Shire is quite something.
+ Netflix’s new dystopian film The Kitchen sounds great.
+ Happy 73rd birthday to Phil Collins—one of the best to ever do it.

Hi, Taylor.

I can only imagine how you must be feeling after sexually explicit deepfake videos of you went viral on X. Disgusted. Distressed, perhaps. Humiliated, even. 

I’m really sorry this is happening to you. Nobody deserves to have their image exploited like that. But if you aren’t already, I’m asking you to be furious. 

Furious that this is happening to you and so many other women and marginalized people around the world. Furious that our current laws are woefully inept at protecting us from violations like this. Furious that men (because let’s face it, it’s mostly men doing this) can violate us in such an intimate way and walk away unscathed and unidentified. Furious that the companies that enable this material to be created and shared widely face no consequences either, and can profit off such a horrendous use of their technology. 

Deepfake porn has been around for years, but its latest incarnation is its worst one yet. Generative AI has made it ridiculously easy and cheap to create realistic deepfakes. And nearly all deepfakes are made for porn. Only one image plucked off social media is enough to generate something passable. Anyone who has ever posted or had a photo published of them online is a sitting duck. 

First, the bad news. At the moment, we have no good ways to fight this. I just published a story looking at three ways we can combat nonconsensual deepfake porn, which include watermarks and data-poisoning tools. But the reality is that there is no neat technical fix for this problem. The fixes we do have are still experimental and haven’t been adopted widely by the tech sector, which limits their power. 

The tech sector has thus far been unwilling or unmotivated to make changes that would prevent such material from being created with their tools or shared on their platforms. That is why we need regulation. 

People with power, like yourself, can fight with money and lawyers. But low-income women, women of color, women fleeing abusive partners, women journalists, and even children are all seeing their likeness stolen and pornified, with no way to seek justice or support. Any one of your fans could be hurt by this development. 

The good news is that the fact that this happened to you means politicians in the US are listening. You have a rare opportunity, and momentum, to push through real, actionable change. 

I know you fight for what is right and aren’t afraid to speak up when you see injustice. There will be intense lobbying against any rules that would affect tech companies. But you have a platform and the power to convince lawmakers across the board that rules to combat these sorts of deepfakes are a necessity. Tech companies and politicians need to know that the days of dithering are over. The people creating these deepfakes need to be held accountable. 

You once caused an actual earthquake. Winning the fight against nonconsensual deepfakes would have an even more earth-shaking impact.

This is not a new phenomenon: deepfakes have been around for years. However, the rise of generative AI has made it easier than ever to create deepfake pornography and sexually harass people using AI-generated images and videos. 

Of all types of harm related to generative AI, nonconsensual deepfakes affect the largest number of people, with women making up the vast majority of those targeted, says Henry Ajder, an AI expert who specializes in generative AI and synthetic media.

Thankfully, there is some hope. New tools and laws could make it harder for attackers to weaponize people’s photos, and they could help us hold perpetrators accountable. 

Here are three ways we can combat nonconsensual deepfake porn. 

WATERMARKS

Social media platforms sift through the posts that are uploaded onto their sites and take down content that goes against their policies. But this process is patchy at best and misses a lot of harmful content, as the Swift videos on X show. It is also hard to distinguish between authentic and AI-generated content. 

One technical solution could be watermarks. Watermarks hide an invisible signal in images that helps computers identify if they are AI generated. For example, Google has developed a system called SynthID, which uses neural networks to modify pixels in images and adds a watermark that is invisible to the human eye. That mark is designed to be detected even if the image is edited or screenshotted. In theory, these tools could help companies improve their content moderation and make them faster to spot fake content, including nonconsensual deepfakes.

Pros: Watermarks could be a useful tool that makes it easier and quicker to identify AI-generated content and identify toxic posts that should be taken down. Including watermarks in all images by default would also make it harder for attackers to create nonconsensual deepfakes to begin with, says Sasha Luccioni, a researcher at the AI startup Hugging Face who has studied bias in AI systems.

Cons: These systems are still experimental and not widely used. And a determined attacker can still tamper with them. Companies are also not applying the technology to all images across the board. Users of Google’s Imagen AI image generator can choose whether they want their AI-generated images to have the watermark, for example. All these factors limit their usefulness in fighting deepfake porn. 

PROTECTIVE SHIELDS

At the moment, all the images we post online are free game for anyone to use to create a deepfake. And because the latest image-making AI systems are so sophisticated, it is growing harder to prove that AI-generated content is fake. 

But a slew of new defensive tools allow people to protect their images from AI-powered exploitation by making them look warped or distorted in AI systems. 

One such tool, called PhotoGuard, was developed by researchers at MIT. It works like a protective shield by altering the pixels in photos in ways that are invisible to the human eye. When someone uses an AI app like the image generator Stable Diffusion to manipulate an image that has been treated with PhotoGuard, the result will look unrealistic. Fawkes, a similar tool developed by researchers at the University of Chicago, cloaks images with hidden signals that make it harder for facial recognition software to recognize faces. 

Another new tool, called Nightshade, could help people fight back against being used in AI systems. The tool, developed by researchers at the University of Chicago, applies an invisible layer of “poison” to images. The tool was developed to protect artists from having their copyrighted images scraped by tech companies without their consent. However, in theory, it could be used on any image its owner doesn’t want to end up being scraped by AI systems. When tech companies grab training material online without consent, these poisoned images will break the AI model. Images of cats could become dogs, and images of Taylor Swift could also become dogs. 

Pros: These tools make it harder for attackers to use our images to create harmful content. They show some promise in providing private individuals with protection against AI image abuse, especially if dating apps and social media companies apply them by default, says Ajder. 

“We should all be using Nightshade for every image we post on the internet,” says Luccioni. 

Cons: These defensive shields work on the latest generation of AI models. But there is no guarantee future versions won’t be able to override these protective mechanisms. They also don’t work on images that are already online, and they are harder to apply to images of celebrities, as famous people don’t control which photos of them are uploaded online. 

“It’s going to be this giant game of cat and mouse,” says Rumman Chowdhury, who runs the ethical AI consulting and auditing company Parity Consulting. 

REGULATION

Technical fixes go only so far. The only thing that will lead to lasting change is stricter regulation, says Luccioni. 

Taylor Swift’s viral deepfakes have put new momentum behind efforts to clamp down on deepfake porn. The White House said the incident was “alarming” and urged Congress to take legislative action. Thus far, the US has had a piecemeal, state-by-state approach to regulating the technology. For example, California and Virginia have banned the creation of pornographic deepfakes made without consent. New York and Virginia also ban the distribution of this sort of content. 

However, we could finally see action on a federal level. A new bipartisan bill that would make sharing fake nude images a federal crime was recently reintroduced in the US Congress. A deepfake porn scandal at a New Jersey high school has also pushed lawmakers to respond with a bill called the Preventing Deepfakes of Intimate Images Act. The attention Swift’s case has brought to the problem might drum up more bipartisan support. 

Lawmakers around the world are also pushing stricter laws for the technology. The UK’s Online Safety Act, passed last year, outlaws the sharing of deepfake porn material, but not its creation. Perpetrators could face up to six months of jail time. 

In the European Union, a bunch of new bills tackle the problem from different angles. The sweeping AI Act requires deepfake creators to clearly disclose that the material was created by AI, and the Digital Services Act will require tech companies to remove harmful content much more quickly. 

China’s deepfake law, which entered into force in 2023, goes the furthest. In China, deepfake creators need to take steps to prevent the use of their services for illegal or harmful purposes, ask for consent from users before making their images into deepfakes, authenticate people’s identities, and label AI-generated content. 

Pros: Regulation will offer victims recourse, hold creators of nonconsensual deepfake pornography accountable, and create a powerful deterrent. It also sends a clear message that creating nonconsensual deepfakes is not acceptable. Laws and public awareness campaigns making it clear that people who create this sort of deepfake porn are sex offenders could have a real impact, says Ajder. “That would change the slightly blasé attitude that some people have toward this kind of content as not harmful or not a real form of sexual abuse,” he says. 

Cons: It will be difficult to enforce these sorts of laws, says Ajder. With current techniques, it will be hard for victims to identify who has assaulted them and build a case against that person. The person creating the deepfakes might also be in a different jurisdiction, which makes prosecution more difficult. 

However, tapping into procurement’s potential for generating value requires mastering the diverse needs of today’s global and hybrid businesses, navigating an increasingly complex supplier ecosystem, and wrangling the vast volumes of data generated by a rapidly digitalizing supply chain. Advanced procurement tools and technologies can support all three.

Purchasing the products and services a company needs to support its daily operations aggregates thousands of individual decisions, from a remote worker selecting a computer keyboard to a materials expert contracting with suppliers. Keeping the business running requires procurement processes and policies set by a chief procurement officer (CPO) and team who “align their decisions with company goals, react to changes with speed, and are agile enough to ensure a company has the right products at the right time,” says Rajiv Bhatnagar, director of product and technology at Amazon Business.

At the same time, he says, the digitalization of the supply chain has created “a jungle of data,” challenging procurement to “glean insights, identify trends, and detect anomalies” with record speed. The good news is advanced analytics tools can tackle these obstacles, and establish a data-driven, streamlined approach to procurement. Aggregating the copious data produced by enterprise procurement—and empowering procurement teams to recognize and act on patterns in that data—enables speed, agility, and smarter decision-making.

Today’s executives increasingly look to data and analytics to enable better decision-making in a challenging and fast-changing business climate. Procurement teams are no exception. In fact, 65% of procurement professionals report having an initiative aimed at improving data and analytics, according to The Hackett Group’s 2023 CPO Agenda report.

And for good reason—analytics can significantly enhance supply chain visibility, improve buying behavior, strengthen supply chain partnerships, and drive productivity and sustainability. Here’s how.

Gaining full visibility into purchasing activity

Just getting the full view of a large organization’s procurement is a challenge. “People involved in the procurement process at different levels with different goals need insight into the entire process,” says Bhatnagar. But that’s not easy given the layers upon layers of data being managed by procurement teams, from individual invoice details to fluctuating supplier pricing. Complicating matters further is the fact that this data exists both within and outside of the procurement organization.

Fortunately, analytics tools deliver greater visibility into procurement by consolidating data from myriad sources. This allows procurement teams to mine the most comprehensive set of procurement information for “opportunities for optimization,” says Bhatnagar. For instance, procurement teams with a clear view of their organization’s data may discover an opportunity to reduce complexity by consolidating suppliers or shifting from making repeated small orders to more cost-efficient bulk purchasing.

Identifying patterns—and responding quickly

When carefully integrated and analyzed over time, procurement data can reveal meaningful patterns—indications of evolving buying behaviors and emerging trends. These patterns can help to identify categories of products with higher-than-normal spending, missed targets for meeting supplier commitments, or a pattern of delays for an essential business supply. The result, says Bhatnagar, is information that can improve budget management by allowing procurement professionals to “control rogue spend” and modify a company’s buying behavior.

In addition to highlighting unwieldy spending, procurement data can provide a glimpse into the future. These days, the world moves at a rapid clip, requiring organizations to react quickly to changing business circumstances. Yet only 25% of firms say they are able to identify and predict supply disruptions in a timely manner “to a large extent,” according to Deloitte’s 2023 Global CPO survey.

“Machine learning-based analytics can look for patterns much faster,” says Bhatnagar. “Once you have detected a pattern, you can take action.” By detecting patterns in procurement data that could indicate supply chain interruptions, looming price increases, or new cost drivers, procurement teams can proactively account for market changes. For example, a team might enable automatic reordering of an essential product that is likely to be impacted by a supply chain bottleneck.

Sharing across the partner ecosystem

Data analysis allows procurement teams to “see some of the challenges and react to them in real-time,” says Bhatnagar. But in an era of interconnectedness, no one organization acts alone. Instead, today’s supplier ecosystems are deeply interconnected networks of supply-chain partners with complex interdependencies.

For this reason, sharing data-driven insights with suppliers helps organizations better pinpoint causes for delays or inaccurate orders and work collaboratively to overcome obstacles. Such “discipline and control” over data, says Bhatnagar, not only creates a single source of truth for all supply-chain partners, but helps eliminate finger-pointing while also empowering procurement teams to negotiate mutually beneficial terms with suppliers.

Improving employee productivity and satisfaction

Searching for savings opportunities, negotiating with suppliers, and responding to supply-chain disruptions—these time-consuming activities can negatively impact a procurement team’s productivity. However, by relying on analytics to discover and share meaningful patterns in data, procurement teams can shift focus from low-value tasks to business-critical decision-making.

Shifting procurement teams to higher-impact work results in a better overall employee experience. “Using analytics, employees feel more productive and know that they’re bringing more value to their job,” says Bhatnagar.

Another upside of heightening employee morale is improved talent retention. After all, workers with a sense of value and purpose are likelier to stay with an employer. This is a huge benefit in a time when nearly half (46%) of CPOs cite the loss of critical talent as a high or moderate risk, according to Deloitte’s 2023 Global CPO survey.

Meeting compliance metrics and organizational goals

Procurement analytics can also deliver on a broader commitment to changing how products and services are purchased.

According to a McKinsey Global Survey on environmental, social, and governance (ESG) issues, more than nine in ten organizations say ESG is on their agenda. Yet 40% of CPOs in the Deloitte survey report their procurement organizations need to define or measure their own set of relevant ESG factors.

Procurement tools can bridge this gap by allowing procurement teams to search for vendor or product certifications and generate credentials reports to help them shape their organization’s purchases toward financial, policy, or ESG goals. They can develop flexible yet robust spending approval workflows, designate restricted and out-of-policy purchases, and encourage the selection of sustainable products or preference for local or minority-owned suppliers.

“A credentials report can really allow organizations to improve their visibility into sustainability [initiatives] when they’re looking for seller credentials or compliant credentials,” says Bhatnagar. “They can track all of their spending from diverse sellers or small sellers—whatever their goals are for the organization.”

Delivering the procurement of tomorrow

Advanced analytics can free procurement teams to glean meaningful insights from their data—information that can drive tangible business results, including a more robust supplier ecosystem, improved employee productivity, and a greener planet.

As supply chains become increasingly complex and the ecosystem increasingly digital, data-driven procurement will become critical. In the face of growing economic instability, talent shortages, and technological disruption, advanced analytics capabilities will enable the next generation of procurement.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

Learn how Amazon Business is leveraging AI/ML to offer procurement professionals more efficient processes, a greater understanding of smart business buying habits and, ultimately, reduced prices.

People are worried that AI will take everyone’s jobs. We’ve been here before.

It was 1938, and the pain of the Great Depression was still very real. Unemployment in the US was around 20%. New machinery was transforming factories and farms, and everyone was worried about jobs.

Were the impressive technological achievements that were making life easier for many also destroying jobs and wreaking havoc on the economy? To make sense of it all, Karl T. Compton, the president of MIT from 1930 to 1948 and one of the leading scientists of the day, wrote in the December 1938 issue of this publication about the “Bogey of Technological Unemployment.”

His essay concisely framed the debate over jobs and technical progress in a way that remains relevant, especially given today’s fears over the impact of artificial intelligence. It’s a worthwhile reminder that worries over the future of jobs are not new and are best addressed by applying an understanding of economics, rather than conjuring up genies and monsters. Read the full story.

—David Rotman

This high-tech mouthguard might help prevent concussions

When athletes or soldiers have a concussion, the most beneficial course of action is to simply get them off the playing field or out of the action so they can recover. Yet much about head injuries remains a mystery, including the reasons why some impacts result in concussion while others don’t.

New measuring devices, such as the Impact Monitoring Mouthguard, are being developed that could help deliver a wealth of information about head impacts. By giving an immediate warning that a person needs to be removed from action or play, they could help protect soldiers and athletes alike from brain damage. Read the full story.

—David Hambling

Join us to discuss critical AI issues in Europe and beyond

Artificial intelligence took the world by storm in 2023. Its future—and ours—will be shaped by what we do next. Register now to join MIT Technology Review journalists for a free LinkedIn Live discussion tomorrow at 11am ET as they explore what’s next for AI in Europe, the US, and beyond.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 X has blocked all searches for Taylor Swift 
It’s a heavy-handed attempt to stop the circulation of AI-generated explicit images of her. (FT $)
+ X is reportedly working on a new content moderation HQ in Texas. (Bloomberg $)
+ The viral AI avatar app Lensa undressed me—without my consent. (MIT Technology Review)

2 Big Tech is desperate to sever its dependence on Nvidia’s chips
Unfortunately for them, it’s not as easy as simply building their own semiconductors. (NYT $)
+ Japan is investing heavily in its own chip production lines. (FT $)
+ Huawei’s 5G chip breakthrough needs a reality check. (MIT Technology Review)

3 China has approved dozens of AI models for public use
Regulators approved 14 in the past week alone. (Reuters)
+ The US is spooked, and wants cloud firms to flag foreign clients. (Bloomberg $)
+ Four things to know about China’s new AI rules in 2024. (MIT Technology Review)

4 Meta is optimistic about going head-to-head with Apple
The war of the mixed reality headsets is starting to heat up. (WSJ $)
+ 2024 hasn’t been plain sailing for Apple so far. (Economist $)
+ These minuscule pixels are poised to take augmented reality by storm. (MIT Technology Review)

5 A George Carlin “AI comedy special” was, in fact, written by a human
Faced with a lawsuit, the video’s creators admitted an algorithm had not generated the material. (NYT $)

6 US spies are sifting through vast amounts of public data
They’re finally tapping into OSINT data. (Bloomberg $)
+ Leaked datasets are a trove of information, if you know what you’re looking for. (Motherboard)

7 Decarbonizing the economy is easier said than done
The legal obstacles are even tougher to navigate than the high costs. (The Atlantic $)
+ That doesn’t mean it’s not worth pursuing, though. (MIT Technology Review)

8 Instacart is using gross AI-generated food photographs
Which makes the entire platform look spammy. (Insider $)

9 BeReal is courting celebrities now
The problem is, they aren’t exactly known for their authenticity. (Wired $)

10 What it takes to grow food in space
Mmm, tasty 3D-printed meals! (The Guardian)
+ Future space food could be made from astronaut breath. (MIT Technology Review)

Quote of the day

“Organizations want to say, ‘Yeah, we have a chief AI officer,’ because that makes them look good.”

—Consultant Randy Bean suggests that companies’ rush to capitalize on the AI boom is mostly a form of corporate bragging, he tells the New York Times.

The big story

How existential risk became the biggest meme in AI

June 2023 

Who’s afraid of the big bad bots? A lot of people, it seems. Hundreds of scientists, business leaders, and policymakers have recently made public pronouncements or signed open letters warning of the catastrophic dangers of artificial intelligence, from deep learning pioneer Geoffrey Hinton to California congressman Ted Lieu.

We’ve been here before: AI doom follows AI hype. But this time feels different. What were once extreme views are now mainstream talking points, grabbing not only headlines but the attention of world leaders.

Has AI really become (more) dangerous? And why are the people who ushered in this tech now the ones raising the alarm? Or is the looming specter of regulation to blame? Read the full story.

—Will Douglas Heaven

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Patrick Swayze classic Road House has had a 2024 makeover.
+ I don’t know if you’ve noticed, but taprooms are pretty fancy these days.
+ The champagne bottles onboard the fateful Titanic are still intact. How?
+ Happy 57th anniversary to the Mantra-Rock Dance, the apex of San Francisco’s hippie era.
+ A Buffy the Vampire Slayer reboot is in the pipeline, according to, err, Dolly Parton.

It was 1938, and the pain of the Great Depression was still very real. Unemployment in the US was around 20%. Everyone was worried about jobs.

In 1930, the prominent British economist John Maynard Keynes had warned that we were “being afflicted with a new disease” called technological unemployment. Labor-saving advances, he wrote, were “outrunning the pace at which we can find new uses for labour.” There seemed to be examples everywhere. New machinery was transforming factories and farms. Mechanical switching being adopted by the nation’s telephone network was wiping out the need for local phone operators, one of the most common jobs for young American women in the early 20th century.

Were the impressive technological achievements that were making life easier for many also destroying jobs and wreaking havoc on the economy? To make sense of it all, Karl T. Compton, the president of MIT from 1930 to 1948 and one of the leading scientists of the day, wrote in the December 1938 issue of this publication about the “Bogey of Technological Unemployment.”

How, began Compton, should we think about the debate over technological unemployment—“the loss of work due to obsolescence of an industry or use of machines to replace workmen or increase their per capita production”? He then posed this question: “Are machines the genii which spring from Aladdin’s Lamp of Science to supply every need and desire of man, or are they Frankenstein monsters which will destroy man who created them?” Compton signaled that he’d take a more grounded view: “I shall only try to summarize the situation as I see it.”  

His essay concisely framed the debate over jobs and technical progress in a way that remains relevant, especially given today’s fears over the impact of artificial intelligence. Impressive recent breakthroughs in generative AI, smart robots, and driverless cars are again leading many to worry that advanced technologies will replace human workers and decrease the overall demand for labor. Some leading Silicon Valley techno-optimists even postulate that we’re headed toward a jobless future where everything can be done by AI. 

While today’s technologies certainly look very different from those of the 1930s, Compton’s article is a worthwhile reminder that worries over the future of jobs are not new and are best addressed by applying an understanding of economics, rather than conjuring up genies and monsters.

Uneven impacts

Compton drew a sharp distinction between the consequences of technological progress on “industry as a whole” and the effects, often painful, on individuals. 

For “industry as a whole,” he concluded, “technological unemployment is a myth.” That’s because, he argued, technology “has created so many new industries” and has expanded the market for many items by “lowering the cost of production to make a price within reach of large masses of purchasers.” In short, technological advances had created more jobs overall. The argument—and the question of whether it is still true—remains pertinent in the age of AI.

Then Compton abruptly switched perspectives, acknowledging that for some workers and communities, “technological unemployment may be a very serious social problem, as in a town whose mill has had to shut down, or in a craft which has been superseded by a new art.”

This analysis reconciled the reality all around—millions without jobs—with the promise of progress and the benefits of innovation. Compton, a physicist, was the first chair of a scientific advisory board formed by Franklin D. Roosevelt, and he began his 1938 essay with a quote from the board’s 1935 report to the president: “That our national health, prosperity and pleasure largely depend upon science for their maintenance and their future improvement, no informed person would deny.” 

Compton’s assertion that technical progress had produced a net gain in employment wasn’t without controversy. According to a New York Times article written in 1940 by Louis Stark, a leading labor journalist, Compton “clashed” with Roosevelt after the president told Congress, “We have not yet found a way to employ the surplus of our labor which the efficiency of our industrial processes has created.”

As Stark explained, the issue was whether “technological progress, by increasing the efficiency of our industrial processes, take[s] jobs away faster than it creates them.” Stark reported recently gathered data on the strong productivity gains from new machines and production processes in various sectors, including the cigar, rubber, and textile industries. In theory, as Compton argued, that meant more goods at a lower price, and—again in theory—more demand for these cheaper products, leading to more jobs. But as Stark explained, the worry was: How quickly would the increased productivity lead to those lower prices and greater demand?  

As Stark put it, even those who agreed that jobs will come back in “the long run” were concerned that “displaced wage-earners must eat and care for their families ‘in the short run.’”

World War II soon meant there was no shortage of employment opportunities. But the job worries continued. In fact, while it has waxed and waned over the decades depending on the health of the economy, anxiety over technological unemployment has never gone away. 

Automation and AI

Lessons for our current AI era can be drawn not just from the 1930s but also from the early 1960s. Unemployment was high. Some leading thinkers of the time claimed that automation and rapid productivity growth would outpace the demand for labor. In 1962, MIT Technology Review sought to debunk the panic with an essay by Robert Solow, an MIT economist who received the 1987 Nobel Prize for explaining the role of technology in economic growth and who died late last year at the age of 99. 

In his piece, titled “Problems That Don’t Worry Me,” Solow scoffed at the idea that automation was leading to mass unemployment. Productivity growth between 1947 and 1960, he noted, had been around 3% a year. “That’s nothing to be sneezed at, but neither does it amount to a revolution,” he wrote. No great productivity boom meant there was no evidence of a second Industrial Revolution that “threatens catastrophic unemployment.” But, like Compton, Solow also acknowledged a different type of problem with the rapid technological changes: “certain specific kinds of labor … may become obsolete and command a suddenly lower price in the market … and the human cost can be very great.”

These days, the panic is over artificial intelligence and other advanced digital technologies. Like the 1930s and the early 1960s, the early 2010s were a time of high unemployment, in this case because the economy was struggling to recover from the 2007–’09 financial crisis. It was also a time of impressive new technologies. Smartphones were suddenly everywhere. Social media was taking off. There were glimpses of driverless cars and breakthroughs in AI. Could those advances be related to the lackluster demand for labor? Could they portend a jobless future?

Again, the debate played out in the pages of MIT Technology Review. In a story I wrote titled “How Technology Is Destroying Jobs,” economist Erik Brynjolfsson and his colleague Andrew McAfee argued that technological change was eliminating jobs faster than it was creating them. This wasn’t just about a mill shutting down. Rather, advanced digital technologies were leading to job losses across a broad swath of the economy, raising the specter once again of technological unemployment.

It’s difficult to pinpoint a single cause for something as complex as a dip in total employment—it could be just a result of sluggish economic growth. But it was becoming increasingly obvious, both in the data and in everyday observations, that new technologies were changing the types of jobs in demand—and while that was nothing new, the scope of the transition was troubling, and so was the speed at which it was happening. Industrial robots had killed off many well-paying manufacturing jobs in places like the Rust Belt, and now AI and other digital technologies were coming after clerical and office jobs—and even, it was feared, truck driving.

In his farewell speech before leaving office in January 2017, President Barack Obama spoke about “the relentless pace of automation that makes a lot of good middle-class jobs obsolete.” By that time, it was clear that Compton’s optimism needed to be rethought. Technical progress was not turning out to lead to inevitable job growth, and the pain was not limited to a few specific locations and industries.

Why Musk is wrong

In an interview late last year with the UK prime minister, Rishi Sunak, Elon Musk declared there will come a time when “no job is needed,” thanks to an AI “magic genie that can do everything you want.” Musk added that as a result, “we won’t have universal basic income, we’ll have universal high income”—apparently answering Compton’s rhetorical question about whether machines will be “the genii which … supply every need and desire of man.” 

It might not be possible to prove Musk wrong, since he gave no timeline for his utopian prediction; in any case, how do you argue against the power of a magical genie? But the end-of-work meme is a distraction as we figure out the best way to use AI to expand the economy and create new jobs.

Breakthroughs in generative AI, such as ChatGPT and other large language models, will likely transform the economy and labor markets. But there’s no convincing evidence that we’re on a path to a jobless future. To paraphrase Solow, we should worry about that when there’s a problem to worry about.

Even a bullish estimate about the effects of generative AI by Goldman Sachs puts its impact on productivity growth at around 1.5% a year over the next 10 years. That, as Solow might say, is nothing to sneeze at, but it’s not going to end the need for workers. The Goldman Sachs report calculated that roughly two-thirds of US jobs are “exposed to some degree of automation by AI.” Yet this conclusion is often misinterpreted—it doesn’t mean all those jobs will be replaced. Rather, as the Goldman Sachs report notes, most of these positions are “only partially exposed to automation.” For many of these workers, AI will become part of the workday and won’t necessarily lead to layoffs.

One critical wild card is how many new jobs will be created by AI even as existing ones disappear. Estimating such job creation is notoriously difficult. But MIT’s David Autor and his collaborators recently calculated that 60% of employment in 2018 was in types of jobs that didn’t exist before 1940. One reason innovation has created so many new jobs is that it has increased the productivity of workers, augmenting their capabilities and expanding their potential to do new tasks. The bad news: this job creation is countered by the labor-destroying impact of automation when it’s used to simply replace workers. As Autor and his coauthors conclude, one of the key questions now is whether “automation is accelerating relative to augmentation, as many researchers and policymakers fear.”

In recent decades, companies have often used AI and advanced automation to slash jobs and cut costs. There’s no economic rule that innovation will in fact favor augmentation and job creation over this type of automation. But we have a choice going forward: we can use technology to simply replace workers, or we can use it to expand their skills and capabilities, leading to economic growth and new jobs.

One of the lasting strengths of Compton’s 1938 essay was his argument that companies needed to take responsibility for limiting the pain of any technological transition. His suggestions included “coöperation between industries of a community to synchronize layoffs in one company with new employment in another.” That might sound outdated in today’s global economy. But the underlying sentiment remains relevant: “The fundamental criterion for good management in this matter, as in every other, is that the predominant motive must not be quick profits but best ultimate service of the public.”

At a time when AI companies are gaining unprecedented power and wealth, they also need to take greater responsibility for how the technology is affecting workers. Conjuring up a magical genie to explain an inevitable jobless future doesn’t cut it. We can choose how AI will define the future of work.