Everything you need to know about the wild world of alternative jet fuels

Tech Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more here.

The future of flying might depend on french fries, trash, and sunlight.

Aviation accounts for about 2% of global carbon dioxide emissions, and once you add in other polluting gases, the industry is responsible for about 3% of all human-caused global warming.

One way the aviation industry hopes to cut down on its climate impacts is by using new fuels. These alternatives, often called sustainable aviation fuels (SAFs), are made from a wide range of sources and can largely be used by existing planes. They could be the key to helping this sector meet its climate target: net-zero carbon dioxide emissions by 2050.

New policies in both the European Union and the US are boosting these new fuels, and airlines are pushing ad campaigns that feature their efforts to switch fuel sources.

But while alternative fuels could be a climate solution for aviation, their actual impact will depend on a lot of factors. Here’s everything you need to know about the future of jet fuel and the climate.

What are SAFs?

Planes today mostly burn jet fuel, also called kerosene—a fossil fuel with a mix of carbon-containing molecules. The mix of those molecules can vary, but the primary ingredient is simple chains of carbon and hydrogen that are packed with energy. Alternative fuels have the same basic chemical makeup as fossil fuels; the difference is that SAFs are derived from renewable sources.

These fuels fall into two main categories: biofuels and synthetic electrofuels.

Biofuels come from a range of biological sources; some are derived from waste like used cooking oils, agricultural residues, or landfill trash, while others can be made from crops grown specifically for fuel, from corn to palm trees to switchgrass. 

Making fuel from biological sources requires chopping up the complicated chemical structures that plants make to store energy. Fats and carbohydrates can be broken apart into smaller pieces and purified, sometimes using existing refineries, to make the simple chains of carbon-rich molecules that are jet fuel’s primary ingredient. 

Electrofuels (also called e-fuels), on the other hand, don’t start with plants. Instead, they start with two main building blocks: hydrogen and carbon dioxide. 

While both can come from a variety of sources, the most climate-friendly way to make e-fuels starts with hydrogen that’s been generated by splitting water into its constituent elements using renewable electricity, plus carbon dioxide that’s been pulled out of the atmosphere through direct air capture. These are then combined and transformed in chemical reactions powered by electricity. 

Making e-fuels is expensive today, because the process is inefficient and still isn’t done widely at commercial scale. But experts say that to reach its 2050 target, aviation will largely need to rely on them. That’s because they’re the most effective at cutting carbon dioxide emissions, and they won’t be limited by supply or collection logistics like fuels made from plants or waste. 

So how do SAFs help climate progress?

Like conventional jet fuel, alternative fuels produce carbon dioxide and other emissions when they’re burned for energy in planes. 

The difference is that SAFs can offset their carbon dioxide emissions, depending on how they’re made. In an ideal world, the process of making the alternative fuels would suck down so much carbon that when the fuel is burned, the carbon dioxide emissions would be essentially canceled out. 

However, that’s often far from the reality. Today, the process of making alternative fuels can be linked to carbon dioxide emissions itself, either because of the energy required to make them or because they affect ecosystems in ways that emit carbon.

“Not all SAFs are created equal,” says Matteo Mirolo, aviation policy manager at the nonprofit group Transport & Environment.

Alternative fuels fall on a spectrum in terms of how much they reduce carbon dioxide emissions, says Nikita Pavlenko, head of the fuels program at the International Council on Clean Transportation. On one end, synthetic fuels that are made with carbon sucked out of the air via direct air capture and whose manufacturing facilities are powered entirely by renewable electricity will reduce emissions by nearly 100% compared with fossil fuels.

On the other end of the spectrum, some crop-based biofuels can actually produce more carbon dioxide emissions overall than fossil fuels, Pavlenko says. That’s frequently the case for biofuels made from palm oil, since growing that crop can decimate rainforests. Even synthetic e-fuels can approach the impact of jet fuel if they’re produced using electricity from fossil fuels.

Today, most commercially available alternative jet fuels are made from fats, oils, and greases. If they’re derived from waste sources like used cooking oils, these fuels reduce carbon dioxide emissions by roughly 70% to 80% compared with fossil fuels.

It’s worth noting that while SAFs can approach net-zero carbon dioxide emissions, burning the fuels still produces other types of pollution, including other greenhouse gases and particulate matter. The fuels can also contribute to formation of contrails, which trap heat in the atmosphere. 

What’s next for SAFs?

There are a few other technologies on the table for cutting climate impacts in aviation, including hydrogen– and battery-powered planes. However, without further technical progress, these options may be limited to smaller planes flying shorter routes, and most global carbon dioxide emissions today come from flights over about 900 miles (1,500 kilometers). That’s where SAFs could help. Alternative fuels are attractive for the aviation industry because they’re a drop-in solution, requiring little adjustment of aircraft and airport infrastructure. (Planes might need small adjustments to run on 100% SAFs in the future, depending on the mix of chemicals in the fuel.)

Many aviation net-zero plans, like the one published by the International Air Transport Association, assume that SAFs will make up the majority of the industry’s climate progress in the coming decades. Over the past year, several test flights powered by 100% SAFs have taken off. However, alternative fuels made up less than 0.2% of the global jet fuel supply in 2022. So there’s a lot of progress needed to supply alternative fuels that are actually helpful for the climate.

One of the main challenges to getting SAFs into the skies is expanding the supply. While fats, oils, and greases are the basis of most commercially available SAFs today, the world doesn’t eat enough french fries for used cooking oils to meet global jet fuel demand alone. In fact, even with increased collection, waste fats, oils, and greases probably won’t provide more than 5% of global jet fuel supply, Pavlenko says.

Some new biofuels, like those made from agricultural residue, municipal solid waste, and hardy crops like switchgrass, are starting to enter the market; a few facilities are under construction or producing jet fuel from these sources worldwide, and the carbon dioxide emission savings they achieve can range from 50% to 90%.

Recent policy moves in both the US and the European Union are aimed at boosting the market for alternative fuels. RefuelEU Aviation, a deal finalized in April, requires that fuel supply at EU airports include 2% SAFs by 2025 and 70% by 2050. The EU rule will only count SAFs from waste sources, advanced biofuels, and e-fuels, not crop-derived fuels. It also has a specific target for e-fuels that’s aimed at boosting their production.

The US, on the other hand, recently passed new tax credits for alternative fuels, aimed at helping expensive options reach price parity with fossil fuels. The tax credits last until 2027 and apply to any fuel that reduces carbon dioxide emissions by at least 50% compared with fossil fuels, though the details on how reductions are calculated haven’t been released yet.

Ultimately, alternative fuels present one of the most straightforward pathways to cutting the climate impacts from aviation, but only certain types will end up benefiting the climate. “SAFs are a solution, but they need to be very properly done,” Mirolo says. Otherwise, they risk becoming “a cure that’s worse than the disease.”  

Our quick guide to the 6 ways we can regulate AI

Tech Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more here.

AI regulation is hot. Ever since the success of OpenAI’s chatbot ChatGPT, the public’s attention has been grabbed by wonder and worry about what these powerful AI tools can do. Generative AI has been touted as a potential game-changer for productivity tools and creative assistants. But they are already showing the ways they can cause harm. Generative models have been used to generate misinformation, and they could be weaponized as spamming and scamming tools

Everyone from tech company CEOs to US senators and leaders at the G7 meeting has in recent weeks called for international standards and stronger guardrails for AI technology. The good news? Policymakers don’t have to start from scratch.  

We’ve analyzed six different international attempts to regulate artificial intelligence, set out the pros and cons of each, and given them a rough score indicating how influential we think they are.

A legally binding AI treaty

The Council of Europe, a human rights organization that counts 46 countries as its members, is finalizing a legally binding treaty for artificial intelligence. The treaty requires signatories to take steps to ensure that AI is designed, developed, and applied in a way that protects human rights, democracy, and the rule of law. The treaty could potentially include moratoriums on technologies that pose a risk to human rights, such as facial recognition

If all goes according to plan, the organization could finish drafting the text by November, says Nathalie Smuha, a legal scholar and philosopher at the KU Leuven Faculty of Law who advises the council. 

Pros: The Council of Europe includes many non-European countries, including the UK and Ukraine, and has invited others such as the US, Canada, Israel, Mexico, and Japan to the negotiating table. “It’s a strong signal,” says Smuha. 

Cons: Each country has to individually ratify the treaty and then implement it in national law, which could take years. There’s also a possibility that countries will be able to opt out of certain elements that they don’t like, such as stringent rules or moratoriums. The negotiating team is trying to find a balance between strengthening protection and getting as many countries as possible to sign, says Smuha. 

Influence rating: 3/5

The OECD AI principles 

In 2019, countries that belong to the Organisation for Economic Co-operation and Development (OECD) agreed to adopt a set of nonbinding principles laying out some values that should underpin AI development. Under these principles, AI systems should be transparent and explainable; should function in a robust, secure, and safe way; should have accountability mechanisms; and should be designed in a way that respects the rule of law, human rights, democratic values, and diversity. The principles also state that AI should contribute to economic growth. 

Pros: These principles, which form a sort of  constitution for Western AI policy, have shaped AI policy initiatives around the world since. The OECD’s legal definition of AI will likely be adopted in the EU’s AI Act, for example. The OECD also tracks and monitors national AI regulations and does research on AI’s economic impact. It has an active network of global AI experts doing research and sharing best practices.

Cons: The OECD’s mandate as an international organization is not to come up with regulation but to stimulate economic growth, says Smuha. And translating the high-level principles into workable policies requires a lot of work on the part of individual countries, says Phil Dawson, head of policy at the responsible AI platform Armilla. 

Influence rating:  4/5

The Global Partnership on AI

The brainchild of Canadian prime minister Justin Trudeau and French president Emmanuel Macron, the Global Partnership on AI (GPAI) was founded in 2020 as an international body that could share research and information on AI, foster international research collaboration around responsible AI, and inform AI policies around the world. The organization includes 29 countries, some in Africa, South America, and Asia. 

Pros: The value of GPAI is its potential to encourage international research and cooperation, says Smuha. 

Cons: Some AI experts have called for an international body similar to the UN’s Intergovernmental Panel on Climate Change to share knowledge and research about AI, and GPAI had potential to fit the bill. But after launching with pomp and circumstance, the organization has been keeping a low profile, and it hasn’t published any work in 2023. 

Influence rating: 1/5 

The EU’s AI Act

The European Union is finalizing the AI Act, a sweeping regulation that aims to regulate the most “high-risk” usages of AI systems. First proposed in 2021, the bill would regulate AI in sectors such as health care and education.  

Pros: The bill could hold bad actors accountable and prevent the worst excesses of harmful AI by issuing huge fines and preventing the sale and use of noncomplying AI technology in the EU. The bill will also regulate generative AI and impose some restrictions on AI systems that are deemed to create “unacceptable” risk, such as facial recognition. Since it’s the only comprehensive AI regulation out there, the EU has a first-mover advantage. There is a high chance the EU’s regime will end up being the world’s de facto AI regulation, because companies in non-EU countries that want to do business in the powerful trading bloc will have to adjust their practices to comply with the law. 

Cons: Many elements of the bill, such as facial recognition bans and approaches to regulating generative AI, are highly controversial, and the EU will face intense lobbying from tech companies to water them down. It will take at least a couple of years before it snakes its way through the EU legislative system and enters into force.

Influence rating: 5/5

Technical industry standards

Technical standards from standard-setting bodies will play an increasingly crucial role in translating regulations into straightforward rules companies can follow, says Dawson. For example, once the EU’s AI Act passes, companies that meet certain technical standards will automatically be in compliance with the law. Many AI standards exist already, and more are on their way. The International Organization for Standardization (ISO) has already developed standards for how companies should go about risk management and impact assessments and manage the development of AI. 

Pros: These standards help companies translate complicated regulations into practical measures. And as countries start writing their own individual laws for AI, standards will help companies build products that work across multiple jurisdictions, Dawson says. 

Cons: Most standards are general and apply across different industries. So companies will have to do a fair bit of translation to make them usable in their specific sector. This could be a big burden for small businesses, says Dawson. One bone of contention is whether technical experts and engineers should be drafting rules around ethical risks. “A lot of people have concerns that policymakers … will simply punt a lot of the difficult questions about best practice to industry standards development,” says Dawson. 

Influence rating: 4/5

The United Nations

The United Nations, which counts 193 countries as its members, wants to be the sort of international organization that could support and facilitate global coordination on AI. In order to do that, the UN set up a new technology envoy in 2021. That year, the UN agency UNESCO and member countries also adopted a voluntary AI ethics framework, in which member countries pledge to, for example, introduce ethical impact assessments for AI, assess the environmental impact of AI, and ensure that AI promotes gender equality and is not used for mass surveillance. 

Pros: The UN is the only meaningful place on the international stage where countries in the Global South have been able to influence AI policy. While the West has committed to OECD principles, the UNESCO AI ethics framework has been hugely influential in developing countries, which are newer to AI ethics. Notably, China and Russia, which have largely been excluded from Western AI ethics debates, have also signed the principles.  

Cons: That raises the question of how sincere countries are in following the voluntary ethical guidelines, as many countries, including China and Russia, have used AI to surveil people. The UN also has a patchy track record when it comes to tech. The organization’s first attempt at global tech coordination was a fiasco: the diplomat chosen as technology envoy was suspended after just five days following a harassment scandal. And the UN’s attempts to come up with rules for lethal autonomous drones (also known as killer robots) haven’t made any progress for years. 

Influence rating: 2/5

Everything you need to know about the wild world of heat pumps

Tech Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more here.

We’re entering the era of the heat pump.

The concept behind heat pumps is simple: powered by electricity, they move heat around to either cool or heat buildings. It’s not a new idea—they were invented in the 1850s and have been used in homes since the 1960s. But all of a sudden, they’ve become the hottest home appliance, shoved into the spotlight by the potential for cost savings and climate benefits, as well as by recent policy incentives. 

Simple though the basic idea may be, the details of how heat pumps work are fascinating. In the name of controlling your home’s temperature, this device can almost seem to break the laws of physics. Heat pumps are also getting better: new models are more efficient and better able to handle cold weather. 

So let’s dive in and uncover what makes a heat pump tick.  

How does a heat pump work?

At a high level, a heat pump gathers heat from one place and puts it in another place. We’ll mostly talk about heat pumps in the context of heating, but they can also be used for cooling, gathering heat from inside and sending it outside like an air conditioner. Many heat pumps can actually be run in reverse, either heating or cooling depending on what’s needed. 

The hero in a heat pump is the refrigerant: a fluid that moves in a circuit, soaking up and releasing heat as it goes. Electricity powers the system, pushing the refrigerant around the cycle. 

As the refrigerant moves through the heat pump, it’s compressed and expanded, switching between liquid and gas forms to allow it to gather and release heat at different points in the cycle. (If this is enough detail for you, feel free to skip to the next question. Otherwise, join me on a journey inside a heat pump to understand how this all works.)

A diagram showing a heat pump refrigerant cycle

INTERNATIONAL ENERGY AGENCY

Picture this: it’s a chilly winter day, say 25 °F (-5 °C). You’re sitting on the couch in your living room with a good book, and your cat is curled up nearby. You look over at the thermostat, which is set to 68 °F. Sensible, but a little chilly. You walk over and bump it up a bit, to 70 °F. 

Your heat pump has been quietly humming along in the background. Now it kicks things up a notch to raise the temperature: the fan and compressor inside speed up, and the refrigerant starts moving faster to transfer more heat from outside to inside.

It may seem counterintuitive to collect heat from outside when it’s so cold out, so let’s follow the refrigerant for one cycle to see how it works. For most heat pumps, the trip takes just a few minutes.

Heat pump refrigerants have very low boiling points, typically below -15 °F (-25 °C). So at the beginning of our journey, the refrigerant is around that temperature, and in liquid form. Even in the coldest places, a refrigerant in this state is usually significantly colder than the outside air (in our case, more than 40 degrees colder).

In the first stage of its trek, the refrigerant flows through a heat exchanger, past that outside air and warms up enough to start boiling, changing from a liquid to a gas.

The second phase of its journey is a trip through the compressor. The compressor squeezes the refrigerant into a smaller volume, increasing its pressure and boiling point (this will become important in a minute). This also warms it further, so by the time the refrigerant is past the compressor, it’s warmer than the room indoors.  

The third leg of the refrigerant’s journey takes it through another heat exchanger. But by now, the refrigerant is a warm gas, above 100 °F, and it’s flowing past a relatively colder room. As it transfers some of that heat into the room with the help of a fan, it starts turning back into a liquid.

Finally, in the fourth stage, the liquid refrigerant will go through an expansion valve, releasing the pressure. Just as squeezing a material heats it up, expanding it allows it to cool down again, so now the liquid is back to a low temperature and ready to absorb more heat to bring inside.

Do heat pumps work in the cold?

The claim that heat pumps don’t work well in really cold weather is often repeated by fossil-fuel companies, which have a competing product to sell.

There’s a kernel of truth here—heat pumps can be less efficient in extreme cold. As the temperature difference between inside and outside increases, a heat pump will have to work harder to gather heat from that outside air and disperse it into the room, so efficiencies drop.

But even if heat pumps aren’t running at peak efficiency in colder climates, “they work everywhere,” says Sam Calisch, head of special projects at Rewiring America, a nonprofit group focused on electrification.

There are heat pumps running everywhere from Alaska to Maine in the US. And about 60% of buildings in Norway are heated with heat pumps, along with 40% in Sweden and Finland.

Heat pumps can work efficiently even in the coldest places. Still, choosing the right heat pump is key to making sure it works well when temperatures drop, says Andy Meyer, senior program manager at Efficiency Maine, an agency that runs energy efficiency programs in the state.

Some heat pumps won’t be equipped to warm a room when it’s below zero, but there are models that will work efficiently in colder temperatures, Meyer says. Small space heaters can help provide backup for cold snaps, but if you choose a well-sized system, you shouldn’t need them, he adds.

So what’s new with heat pump technology?

Improvements in several of their main components have helped boost the efficiency and performance of heat pumps, especially in the cold, Meyer says.

One major improvement is in the refrigerants. Freon, also called R-22, used to dominate the market, but it has been phased out in the US and other major markets for its ozone-depleting effects.

Today, a mixture of chemicals referred to as R-410A is one of the most widely used refrigerants in heat pumps. In addition to being slightly less harmful for the ozone layer, R-410A has a lower boiling point than R-22, meaning it can absorb more heat at lower temperatures, boosting efficiency in the cold.

Other components have improved as well. New compressors used in heat pumps today can get refrigerants to higher pressures using less power. There are also new so-called variable-speed compressors that allow heat pumps to ramp their power up and down. Finally, the heat exchangers that transfer heat between the air and the refrigerant are getting bigger and better, so they can move heat around more effectively.  

There’s already a wide range of heat pumps available today. About 85% of those installed are air-source heat pumps like the one I’ve described. These come in a wide range of shapes and sizes. But other models—so-called ground-source or geothermal heat pumps—gather heat from underground instead of collecting it from the air. 

How do heat pumps help with climate change?

Heating buildings frequently relies on natural gas or heating oil, which is why the sector accounts for about 10% of global emissions today. Heat pumps will be the central technology used to cut heating’s climate impact, predicts Yannick Monschauer, an energy analyst at the International Energy Agency.

Heat pumps run using electricity from the grid. While fossil-fuel plants still help power grids around the world, renewables and low-carbon power sources also contribute. So with the current energy mix in all major markets, heat pumps are better for the climate than directly fossil-fuel-powered heating, Monschauer says. 

Heat pumps’ real climate superpower is their efficiency. Heat pumps today can reach 300% to 400% efficiency or even higher, meaning they’re putting out three to four times as much energy in the form of heat as they’re using in electricity. For a space heater, the theoretical maximum would be 100% efficiency, and the best models today reach around 95% efficiency.

The gulf in efficiency between heat pumps and heaters comes down to how they work. Space heaters work by transforming energy from the form of electricity into another form, heat. 

Heat pumps, on the other hand, aren’t turning electricity into heat—they’re using electricity to gather heat and move it around. It’s a subtle difference, but it basically means that a heat pump can return significantly more heat using the same amount of electricity.

A heat pump’s maximum efficiency will depend on the refrigerant and the system that’s installed, as well as the temperature difference between the room it’s heating and the outside.

What else should I know if I’m considering a heat pump? 

Up-front costs for heat pumps are a major barrier to adoption: purchasing and installing one today can cost between $3,000 and $6,000 or even more, depending on the system.

But over their lifetime of about 15 years, heat pumps are already cheaper to buy and operate than other systems for some consumers, especially if they’re used to both heat and cool a home during different parts of the year, Monschauer says. 

And over 30 countries around the world have incentive programs for heat pumps, often with bonuses for low-income households or those purchasing high-efficiency equipment. Italy has especially generous subsidies for heat pumps that are installed when retrofitting buildings for energy efficiency, with customers getting up to 110% of the purchase price back as a tax credit. 

In the US, the Inflation Reduction Act offers a 30% tax credit on the purchase price of a heat pump, with additional rebates for low- and moderate-income households. For some households, the funding could cover 100% of the cost. Rewiring America has a calculator to help people determine what IRA subsidies they qualify for.

What’s next for heat pumps? 

While heat pumps are significantly better than they were a decade ago, there’s still plenty of potential growth ahead for the technology. 

New designs, like self-contained window units from startup Gradient, could cut down on installation costs. Other companies, like Midea and LG, have also started offering small, portable units. These new options could allow heat pumps to break into new spaces, like older apartment buildings where installation might otherwise be expensive or impossible. 

One ripe area for further progress is in refrigerants. While today’s refrigerants are an improvement over older options, even the newer ones are powerful greenhouse gases. Careful handling and precise manufacturing are required to avoid leaks. The climate benefits from heat pumps outweigh the warming potential of leaking refrigerants, but alternatives could help cut this risk further. 

Gradient, for example, uses a refrigerant called R-32, which has a lower global warming potential than R-410A. Other classes of refrigerants, like the hydrocarbons propane and butane, pose even less climate risk. However, some of these more climate-friendly refrigerants tend to be extremely flammable, so safety systems are required. 

New technological advances will help expand the already massive array of heat pumps on the market. And costs should come down over time as the technology becomes more common.

Global heat pump sales grew by 15% in 2021. Europe has seen some of the quickest growth, with 35% sales growth in 2021, a trend that’s likely to continue because of the energy crisis. North America still has the largest number of homes with heat pumps installed today, but China takes the prize for the most new sales. 

Wherever you look, the era of the heat pump has officially begun. 

ChatGPT is everywhere. Here’s where it came from

We’ve reached peak ChatGPT. Released in December as a web app by the San Francisco–based firm OpenAI, the chatbot exploded into the mainstream almost overnight. According to some estimates, it is the fastest-growing internet service ever, reaching 100 million users in January, just two months after launch. Through OpenAI’s $10 billion deal with Microsoft, the tech is now being built into Office software and the Bing search engine. Stung into action by its newly awakened onetime rival in the battle for search, Google is fast-tracking the rollout of its own chatbot, LaMDA. Even my family WhatsApp is filled with ChatGPT chat.

But OpenAI’s breakout hit did not come out of nowhere. The chatbot is the most polished iteration to date in a line of large language models going back years. This is how we got here.

1980s–’90s: Recurrent Neural Networks

ChatGPT is a version of GPT-3, a large language model also developed by OpenAI.  Language models are a type of neural network that has been trained on lots and lots of text. (Neural networks are software inspired by the way neurons in animal brains signal one another.) Because text is made up of sequences of letters and words of varying lengths, language models require a type of neural network that can make sense of that kind of data. Recurrent neural networks, invented in the 1980s, can handle sequences of words, but they are slow to train and can forget previous words in a sequence.

In 1997, computer scientists Sepp Hochreiter and Jürgen Schmidhuber fixed this by inventing LTSM (Long Short-Term Memory) networks, recurrent neural networks with special components that allowed past data in an input sequence to be retained for longer. LTSMs could handle strings of text several hundred words long, but their language skills were limited.  

2017: Transformers

The breakthrough behind today’s generation of large language models came when a team of Google researchers invented transformers, a kind of neural network that can track where each word or phrase appears in a sequence. The meaning of words often depends on the meaning of other words that come before or after. By tracking this contextual information, transformers can handle longer strings of text and capture the meanings of words more accurately. For example, “hot dog” means very different things in the sentences “Hot dogs should be given plenty of water” and “Hot dogs should be eaten with mustard.”

2018–2019: GPT and GPT-2

OpenAI’s first two large language models came just a few months apart. The company wants to develop multi-skilled, general-purpose AI and believes that large language models are a key step toward that goal. GPT (short for Generative Pre-trained Transformer) planted a flag, beating state-of-the-art benchmarks for natural-language processing at the time. 

GPT combined transformers with unsupervised learning, a way to train machine-learning models on data (in this case, lots and lots of text) that hasn’t been annotated beforehand. This lets the software figure out patterns in the data by itself, without having to be told what it’s looking at. Many previous successes in machine-learning had relied on supervised learning and annotated data, but labeling data by hand is slow work and thus limits the size of the data sets available for training.  

But it was GPT-2 that created the bigger buzz. OpenAI claimed to be so concerned people would use GPT-2 “to generate deceptive, biased, or abusive language” that it would not be releasing the full model. How times change.

2020: GPT-3

GPT-2 was impressive, but OpenAI’s follow-up, GPT-3, made jaws drop. Its ability to generate human-like text was a big leap forward. GPT-3 can answer questions, summarize documents, generate stories in different styles, translate between English, French, Spanish, and Japanese, and more. Its mimicry is uncanny.

One of the most remarkable takeaways is that GPT-3’s gains came from supersizing existing techniques rather than inventing new ones. GPT-3 has 175 billion parameters (the values in a network that get adjusted during training), compared with GPT-2’s 1.5 billion. It was also trained on a lot more data. 

But training on text taken from the internet brings new problems. GPT-3 soaked up much of the disinformation and prejudice it found online and reproduced it on demand. As OpenAI acknowledged: “Internet-trained models have internet-scale biases.”

December 2020: Toxic text and other problems

While OpenAI was wrestling with GPT-3’s biases, the rest of the tech world was facing a high-profile reckoning over the failure to curb toxic tendencies in AI. It’s no secret that large language models can spew out false—even hateful—text, but researchers have found that fixing the problem is not on the to-do list of most Big Tech firms. When Timnit Gebru, co-director of Google’s AI ethics team, coauthored a paper that highlighted the potential harms associated with large language models (including high computing costs), it was not welcomed by senior managers inside the company. In December 2020, Gebru was pushed out of her job.  

January 2022: InstructGPT

OpenAI tried to reduce the amount of misinformation and offensive text that GPT-3 produced by using reinforcement learning to train a version of the model on the preferences of human testers. The result, InstructGPT, was better at following the instructions of people using it—known as “alignment” in AI jargon—and produced less offensive language, less misinformation, and fewer mistakes overall. In short, InstructGPT is less of an asshole—unless it’s asked to be one.

May–July 2022: OPT, BLOOM

A common criticism of large language models is that the cost of training them makes it hard for all but the richest labs to build one. This raises concerns that such powerful AI is being built by small corporate teams behind closed doors, without proper scrutiny and without the input of a wider research community. In response, a handful of collaborative projects have developed large language models and released them for free to any researcher who wants to study—and improve—the technology. Meta built and gave away OPT, a reconstruction of GPT-3. And Hugging Face led a consortium of around 1,000 volunteer researchers to build and release BLOOM.      

December 2022: ChatGPT

Even OpenAI is blown away by how ChatGPT has been received. In the company’s first demo, which it gave me the day before ChatGPT was launched online, it was pitched as an incremental update to InstructGPT. Like that model, ChatGPT was trained using reinforcement learning on feedback from human testers who scored its performance as a fluid, accurate, and inoffensive interlocutor. In effect, OpenAI trained GPT-3 to master the game of conversation and invited everyone to come and play. Millions of us have been playing ever since.

What Mexico’s planned geoengineering restrictions mean for the future of the field

Tech Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more here.

An American entrepreneur’s crude solar geoengineering effort in Baja California, first reported by MIT Technology Review in late December, has prompted widespread criticism—and now, the Mexican government plans to ban related experiments. 

Luke Iseman, previously a director of hardware at Y Combinator and the cofounder of a geoengineering startup, says he added a few grams of sulfur dioxide into a pair of weather balloons and launched them from an unspecified site somewhere on the Mexican peninsula last spring. He says he intended for the balloons to reach the stratosphere and burst under pressure there, releasing the particles into the open air. 

Scientists believe that spraying sulfur dioxide or other reflective particles into the stratosphere in sufficient quantities might be able to offset some level of global warming, mimicking the cooling effect from major volcanic eruptions in the past. But it’s a controversial field, given the unknowns about potential side effects, fears that even discussing the possibility could undermine the urgency to address the root causes of climate change, and the difficult questions over how to govern a technology that has the power to tweak the temperature of the planet but could have sharply divergent regional effects. 

Iseman acknowledged to MIT Technology Review, and other outlets that reported on the effort, that he didn’t seek scientific or government approval before moving forward with the balloon launches. He subsequently cofounded the startup, Make Sunsets, to commercialize the concept. The company previously said it had raised around $750,000 in venture capital and planned to sell “cooling credits” for particles released during future balloon launches. 

But on January 13, Mexico’s Ministry of Environment and Natural Resources announced that the government will prohibit and, where appropriate, halt any solar geoengineering experiments within the country. The agency noted that Make Sunset’s launches were done without notice or consent. It said the prohibition was motivated by the risks of geoengineering, the lack of international agreements supervising such efforts, and the need to protect communities and the environment. 

Mexico may be one of the first nations, if not the first, to announce such an explicit  ban on experiments, although many nations have existing environmental regulations and other policies that could restrict certain practices. It’s not clear from the statement that all research in the field would be prohibited, which can also include modeling and lab work. The press release also says Mexico will stop any large-scale solar geoengineering practices, which may mean large experiments or full deployment of the technology.

Representatives from the Ministry of Environment and Natural Resources and the government of Baja California couldn’t be immediately reached for comment.

‘Indefinitely on hold’

Iseman, who didn’t respond to an inquiry from MIT Technology Review, told The Verge that future launches are “indefinitely on hold.” He said to the Wall Street Journal that he was “surprised by the speed and scope of the response” and had “expected and hoped for dialogue.”

But others weren’t surprised. Shuchi Talati, a scholar in residence at American University who is forming a nonprofit focused on governance and justice in solar geoengineering, warned in MIT Technology Review’s original piece that Make Sunsets’s actions could have a chilling effect on the field. She said the unauthorized effort could diminish government support for geoengineering research and amplify demands to restrict experiments.

Indeed, long-standing critics of geoengineering had seized on the news, saying Make Sunset’s efforts demonstrated that research is a slippery slope leading quickly to deployment. The Center for International Environmental Law applauded Mexico’s response and called on “all governments to take steps to ban solar geoengineering outdoor experiments, technology development, and deployment.”

Critics commonly claim that there’s already a moratorium on outdoor geoengineering activities under the UN’s Convention on Biological Diversity, an assertion repeated in the Mexican government’s statement. But geoengineering researchers have long said that this is a misreading. A 2016 paper highlighting “five solar geoengineering tropes that have outstayed their welcome” calls the claim “inaccurate on several counts.”

Geoengineering critics and researchers in the field alike criticized the decision to launch the balloons from Mexico, without approvals. The nation’s response “highlights the reckless way in which this company acted,” Talati said in an email. “To go to another country and conduct something akin to experimentation without consultation or engagement is unacceptable.” 

Iseman previously said he was motivated to launch Make Sunsets to combat the rising dangers of climate change. He had hoped forging ahead would help push forward a scientific field that, amid public criticism, has repeatedly encountered serious challenges to carrying out small-scale field experiments.

But geoengineering researchers are still grappling with what this episode, and the reaction to it, will mean for the field. 

A growing number of nations and universities have established formal research programs. In addition, a handful of scientists are working to move ahead with small-scale, controlled outdoor experiments related to geoengineering, including a Harvard group’s long-running efforts to conduct atmospheric balloon studies. Australian researchers have already carried out and obtained data from the first field experiments in marine cloud brightening, a separate approach that entails spraying salt particles to make coastal clouds more reflective.

As the idea has moved further into the scientific mainstream, it’s also sparked greater concerns. Early last year, dozens of scholars across a variety of fields called for an “International Non-Use Agreement on Solar Geoengineering.” It asks countries to ban outdoor experiments and prohibit national funding agencies from supporting the development of solar geoengineering technologies. 

‘A strong humanitarian case’

But geoengineering researchers stress that they want to explore the potential of the technology because it could save lives—possibly many, many lives as heat waves, famines, wildfires, and other extreme weather events grow more common and severe in the coming decades. 

“Solar geoengineering could substantially offset global temperature rise and potentially offset serious secondary impacts, such as reduction in crop yields and increased frequency and intensity of hurricanes and typhoons,” wrote Holly Buck, the author of After Geoengineering: Climate Tragedy, Repair, and Restoration, in an MIT Technology Review op-ed arguing against the ban last year. “We don’t know everything about what it would do. But there is a strong humanitarian case for learning more.” 

Many also believe it’s inevitable that some nation or actor will carry it out regardless of the risks or the lack of an international consensus, given that it’s relatively cheap and easy to spray materials into the stratosphere. For this reason, some say it’s better to do research that could highlight the safest, most effective means of doing geoengineering or identify serious dangers before someone carries out large-scale releases.

“The need to understand the possibilities, limitations, and potential side effects of climate intervention becomes all the more apparent with the recognition that other countries or the private sector may decide to conduct intervention experiments independently from the U.S. Government,” wrote the authors of a 2017 report in which the US Global Change Research Program, which guides federally supported climate research, recommended geoengineering studies for the first time.

The main fear scientists articulated to MIT Technology Review is that Make Sunsets’s rudimentary balloon launches and attempts at commercialization will distort the perception of the field among the public and policymakers. 

“I think there’s a danger of painting serious scientists and careful experiments with the same brush as some dude that released some weather balloon and tried to make a buck off of it,” says Peter Irvine, a lecturer in climate change and solar geoengineering at University College London. 

“There are many of us who think seriously studying this idea … is worth doing, because it looks like it has the potential to substantially decrease the risk of climate change,” he adds. “We shouldn’t throw the baby out with the bathwater, and that’s the worry.”

However, Irvine adds that he’s not sure there has been or will be a chilling effect, noting that it’s not clear the government of Mexico had supported geoengineering experiments in the first place. He doubts that this incident alone would prompt the US federal government to backtrack on its plans to establish a research program and guidelines, or dissuade scientists from continuing to explore the field.

‘A deep need’

A moratorium on deploying solar geoengineering is appropriate at this stage because we simply don’t know enough about it to move forward on large scales, says Gernot Wagner, a climate economist at Columbia Business School who has closely studied geoengineering issues. But he stresses that that’s also why it’s crucial to allow for research—to enable scientists to attempt to fill in those unknowns.

The consequences of the current controversy may not be all bad for the field.

Some hope the Make Sunsets incident and its aftermath will prompt more nations to establish clear rules guiding research efforts, or spur the development of international oversight agreements, for which there is a “deep need,” Talati says.

In addition, the overwhelmingly negative response to the company’s actions, the likely lack of market demand for its cooling credits, and the forceful response from Mexico may well discourage the formation of other for-profit solar geoengineering startups or unapproved, self-funded launches, other observers add. 

Still, most geoengineering researchers who MIT Technology Review interviewed agreed that a venture-capital-backed startup forging ahead in a foreign country without approval, striving to move fast and disrupt this area of research, was a terrible look. Many fear it could still exact a steep cost for public perceptions of a scientific field where it has already proved incredibly difficult to move forward on even the smallest experiments.

The worst technology of 2022
 

We’re back with our annual list of the worst technologies of the year. Think of these as anti-breakthroughs, the sort of mishaps, misuses, miscues, and bad ideas that lead to technology failure. This year’s disastrous accomplishments range from deadly pharmaceutical chemistry to a large language model that was jeered off the internet.

One theme that emerges from our disaster list is how badly policy—the rules, processes, institutions, and ideals that govern technology’s use—can let us down. In China, a pervasive system of pandemic controls known as “zero covid” came to an abrupt and unexpected end. On Twitter, Elon Musk intentionally destroyed the site’s governing policies, replacing them with a puckish and arbitrary mix of free speech, personal vendettas, and appeals to the right wing of US politics. In the US, policy failures were evident in the highest levels of overdose deaths ever recorded, many of them due to a 60-year-old chemical compound: fentanyl.

The impact of these technologies could be measured in the number of people affected. More than a billion people in China are now being exposed to the virus for the first time; 335 million on Twitter are watching Musk’s antics; and fentanyl killed 70,000 in the US. In each of these messes, there are important lessons about why technology fails. Read on.


The FTX meltdown

Night falls on made-up money

Imagine a world in which you can make up new kinds of money and other people will pay you, well, real money to get some. Let’s call what they’re buying cryptocurrency tokens. But because there are so many types of tokens, and they’re hard to buy and sell, imagine that an entrepreneur creates a private stock market to trade them. Let’s call that a “cryptocurrency exchange.” Because the tokens have no intrinsic value and other exchanges have gone belly-up, you’d make sure yours was ultra-safe and well regulated.

That was the concept behind FTX Trading, a crypto exchange started by Sam Bankman-Fried, a twentysomething who touted sophisticated technology, like a 24/7 “automated risk engine” that would check every 30 seconds to see if depositors had enough real money to cover their crypto gambles. Technology would assure “complete transparency.”

Behind the façade, though, FTX was seemingly just old-fashioned embezzlement. According to US investigators, Bankman-Fried took customers’ money and used it to buy fancy houses, make political donations, and amass huge stakes in illiquid crypto tokens. It all came crashing down in November. John Ray, appointed to oversee the bankrupt company, said that FTX’s technology “was not sophisticated at all.”  Neither was the purported fraud: “This is just taking money from customers and using it for your own purpose.”

Bankman-Fried, an MIT graduate whose parents are both Stanford University law professors, was arrested in the Bahamas in December and faces multiple counts of conspiracy, fraud, and money laundering.

To learn more about cryptocurrency promoters, we recommend if Wolf of Wall Street were about crypto, a satirical video by Joma Tech.


From medicine to murder

How fentanyl became a killer

Back in 1953, the Belgian doctor and chemist Paul Janssen set about creating the strongest painkiller he could. He believed he could improve on morphine, designing a molecule that was 100 times more potent but with a short duration. His discovery, the synthetic opioid fentanyl, would become the painkiller most widely used during surgery.

Today, fentanyl is setting grim records—it’s involved in the accidental death of around 70,000 people a year in the US, or about two-thirds of all fatal drug overdoses. It’s the leading cause of death in American adults under 50, killing more than car accidents, guns, and covid together.

Fentanyl kills by stopping your breathing. Its potency is what makes it deadly. Two milligrams—the weight of a hummingbird feather—can be a fatal dose.

How did we get to nearly 200 deaths a day? Janssen Pharmaceuticals, a division of Johnson & Johnson, played a role. It made false claims about how addictive prescription opioid drugs were, minting money while people got hooked on pills and patches. This year, Janssen agreed to pay a $5 billion settlement without admitting wrongdoing.

Now fentanyl reaches drug users from clandestine labs in Mexico, run by ruthless cartels. It’s used to spike heroin or pressed into counterfeit pain pills. Can things get worse? They can. US states are reporting a rapid uptick in fentanyl deaths in young children who accidentally ingest pills.

For recent reporting on the fentanyl crisis, read “Cartel RX,” a new series in the Washington Post.


A pig heart with a virus in it

Unanswered questions about that historic transplant

Here’s a technology that’s a bona fide breakthrough and a big-time screwup. Last January, surgeons in Maryland transplanted a pig heart into a dying man with heart failure. The organ was genetically engineered to resist rejection by the human immune system. The patient, David Bennett Sr., died two months after the transplant.

No human had ever survived even temporarily with a pig heart before. That part was a massive success. The problem is that the heart harbored a pig virus, one that might have contributed to the patient’s death. It looks as if the company that designed and bred the engineered pigs, United Therapeutics, didn’t test well enough to detect the virus. It’s hard to know for sure, because United swept a veil of secrecy around what happened.

The risk of spreading pig viruses into humans has always been the gravest question about this technology. Martine Rothblatt, the founder of United, even wrote an entire book on the subject. “Every right to make a technology is coupled to an obligation,” she told the podcaster Tim Ferriss in 2020. With pig organ transplants, that obligation is “no risk—not some risk, but no risk” of any kind of animal virus seeping into the human population.

This particular virus, known as porcine cytomegalovirus, isn’t believed to be able to infect human cells. It won’t spawn a deadly pandemic. You might say, “No harm, no foul.” But what about the next time? We need to know how and why the virus slipped through and whether it was part of what killed David Bennett. And so far, no one has offered an explanation.

Read our scoop about the virus in MIT Technology Review: The gene-edited pig heart given to a dying patient was infected with a pig virus.


The collapse of “zero covid”

China suspends virus controls

For two and a half years, China kept the coronavirus in check through a system of quarantine hotels, constant testing, and phone QR codes. A green code meant freedom. A red code meant you’d been near someone with the virus—turning you into an instant pariah, unable to eat in a restaurant or board a plane. China’s leader, Xi Jinping, styled himself the leader of a “people’s war” against the germ.

The system was oppressive—and it worked. China had incredibly few cases of covid. But in December, the government abruptly disbanded the program. Now analysts predict 1 million deaths.

Some observers have linked the reversal to widening dissent over the suffocating policies. In October a bold protester hung a banner from a Beijing bridge. “No to covid tests!” it read. “No to great leader, yes to vote.” Soon lockdown demonstrators around the country had taken up the slogan. Unruly scenes of students and workers demanding change began to spread on social networks.

But the real story may be that China’s suite of anti-covid measures and technologies—once so effective—had finally failed. Mike Ryan, a senior official at the World Health Organization, believes China was tracking widening outbreaks of the easily transmitted omicron variant “long before there was any change in the policy.”

“The disease was spreading intensively because, I believe, the control measures in themselves were not stopping the disease,” says Ryan.

To learn more about daily life under the zero-covid policy, read the travelogue of a scholar visiting China that was published by the Center for Strategic and International Studies.


Elon Musk’s Twitter rules

An absolute monarch tests his powers

When the world’s richest man (at the time) bought Twitter, he promised above all to restore “free speech” to the platform.

Musk fired most of Twitter’s staff and released the “Twitter files”—Slack messages exchanged by former executives as they decided whether to ban Donald Trump or block news about Hunter Biden’s laptop. He insinuated that Twitter’s former head of trust and safety was a secret pedophile. He let controversial figures back on and announced new rules as he went, seemingly on the fly: No parodies. No Instagram links. No posting of public data showing the location of billionaires’ private jets.

Some predicted Twitter’s technology would break under the stress. But what Musk was breaking—violently and suddenly—were the rules of interaction on the site and, therefore, the product itself. “The essential truth of every social network is that the product is content moderation,” wrote the journalist Nilay Patel. “Content moderation is what Twitter makes—it is the thing that defines the user experience.”

The site’s users must now decide whether the new, changed Twitter is one they want. They will deliver the real verdict on Musk’s manic one-man rule as moderator in chief. Six weeks after taking control of the company, Musk, perhaps tiring of the job, put his reign to a vote. “Should I step down as head of Twitter? I will abide by the results of this poll,” he tweeted on December 18.

The result: 57.5% said he should leave, and 42.5% asked him to stay on.

The people have spoken. But will Musk listen?

Read more: We’re witnessing the brain death of Twitter, at MIT Technology Review.


Ticketmaster

Angry “Swifties” have antitrust questions

You had one job, Ticketmaster.

In 2022 there should be a way to sell concert tickets smoothly and transparently, even for large events like the hotly anticipated tour by Taylor Swift. But the world’s largest ticket seller couldn’t get it straight. It bobbled sales for the tour when its system crashed, leaving passionate “Swifties” furious. Then, in Mexico City, more than a thousand Bad Bunny fans had their tickets rejected as fakes—even as the reggaeton star played to a partly empty venue.

Mexico’s consumer protection bureau says it may file a lawsuit. Swift fans in Los Angeles already have, alleging that the “ticket sale disaster” was due to Ticketmaster’s “anticompetitive” practices. Ticketmaster and its parent company, Live Nation, control more than 80% of concert sales in the US, and the company has long been scrutinized by antitrust regulators.

It’s not just that tickets are expensive (buying a so-so seat for Taylor Swift’s tour costs $1,000). According to Yale economist Florian Elderer, lack of competition could account for the ticketing mistakes. “The allegations against Ticketmaster are that it abused its dominant market position by underinvesting in site stability and customer service,” Elderer says. “Thus, rather than causing harm to consumers by charging exorbitant prices, Ticketmaster is alleged to have caused harm by providing inferior quality—which it could not have done had it faced credible competitors.”

Read more: Did Ticketmaster’s Market Dominance Fuel the Chaos for Swifties? from Yale School of Management.


The sinking of the flagship Moskva

“Russian warship, go f—ck yourself”

Nothing symbolizes Ukraine’s surprising resistance to the Russian invasion better than the sinking of the Moskva, Russia’s Black Sea flagship, in April. The cruiser, bristling with missile tubes, was a floating air-defense system. But on the 13th of April, the ship was hit and sunk by two missiles launched from the shore.

Analysts have pored over the event. The Moskva ought to have been able to see and shoot down the missiles. But there are signs the ship wasn’t ready for a shooting war. It may have been having problems with its aging radars and guns. Half its crew were recent conscripts who officially weren’t even supposed to be fighting. Russia has denied that the ship was even attacked: it says the Moskva sank in bad weather after some ammunition exploded.

To commemorate its resistance, Ukraine’s government printed a memorial stamp, featuring a soldier holding up a middle finger at the warship.

Read more: Prized Russian Ship Was Hit by Missiles, US Officials Say, in the New York Times.


Meta’s Galactica

A generative AI gets booed off the stage

This fall, two large language models—AIs that can respond to questions in fluent, human-like text—were released online for the public to experiment with. Although the two systems were similar, their public reception was anything but.

The model from Meta, called Galactica, survived only three days before furious criticism caused the company to pull the plug. We decided to prompt the surviving model, OpenAI’s ChatGPT (which is getting rave reviews), to tell a story about what happened. Below is our prompt and the model’s response. It took ChatGPT about 25 seconds to compose its answer.

screenshot for interaction with ChatGPT

To learn what actually happened, which is not so different, read Why Meta’s latest large language model survived only three days online in MIT Technology Review.

China just announced a new social credit law. Here’s what it means.

It’s easier to talk about what China’s social credit system isn’t than what it is. Ever since 2014, when China announced a six-year plan to build a system to reward actions that build trust in society and penalize the opposite, it has been one of the most misunderstood things about China in Western discourse. Now, with new documents released in mid-November, there’s an opportunity to correct the record.

For most people outside China, the words “social credit system” conjure up an instant image: a Black Mirror–esque web of technologies that automatically score all Chinese citizens according to what they did right and wrong. But the reality is, that terrifying system doesn’t exist, and the central government doesn’t seem to have much appetite to build it, either. 

Instead, the system that the central government has been slowly working on is a mix of attempts to regulate the financial credit industry, enable government agencies to share data with each other, and promote state-sanctioned moral values—however vague that last goal in particular sounds. There’s no evidence yet that this system has been abused for widespread social control (though it remains possible that it could be wielded to restrict individual rights). 

While local governments have been much more ambitious with their innovative regulations, causing more controversies and public pushback, the countrywide social credit system will still take a long time to materialize. And China is now closer than ever to defining what that system will look like. On November 14, several top government agencies collectively released a draft law on the Establishment of the Social Credit System, the first attempt to systematically codify past experiments on social credit and, theoretically, guide future implementation. 

Yet the draft law still left observers with more questions than answers. 

“This draft doesn’t reflect a major sea change at all,” says Jeremy Daum, a senior fellow of the Yale Law School Paul Tsai China Center who has been tracking China’s social credit experiment for years. It’s not a meaningful shift in strategy or objective, he says. 

Rather, the law stays close to local rules that Chinese cities like Shanghai have released and enforced in recent years on things like data collection and punishment methods—just giving them a stamp of central approval. It also doesn’t answer lingering questions that scholars have about the limitations of local rules. “This is largely incorporating what has been out there, to the point where it doesn’t really add a whole lot of value,” Daum adds. 

So what is China’s current system actually like? Do people really have social credit scores? Is there any truth to the image of artificial-intelligence-powered social control that dominates Western imagination? 

First of all, what is “social credit”?

When the Chinese government talks about social credit, the term covers two different things: traditional financial creditworthiness and “social creditworthiness,” which draws data from a larger variety of sectors.

The former is a familiar concept in the West: it documents individuals’ or businesses’ financial history and predicts their ability to pay back future loans. Because the market economy in modern China is much younger, the country lacks a reliable system to look up other people’s and companies’ financial records. Building such a system, aimed to help banks and other market players make business decisions, is an essential and not very controversial mission. Most Chinese policy documents refer to this type of credit with a specific word: “征信” (zhengxin, which some scholars have translated to “credit reporting”).

The latter—“social creditworthiness”—is what raises more eyebrows. Basically, the Chinese government is saying there needs to be a higher level of trust in society, and to nurture that trust, the government is fighting corruption, telecom scams, tax evasion, false advertising, academic plagiarism, product counterfeiting, pollution …almost everything. And not only will individuals and companies be held accountable, but legal institutions and government agencies will as well.

This is where things start to get confusing. The government seems to believe that all these problems are loosely tied to a lack of trust, and that building trust requires a one-size-fits-all solution. So just as financial credit scoring helps assess a person’s creditworthiness, it thinks, some form of “social credit” can help people assess others’ trustworthiness in other respects. 

As a result, so-called “social” credit scoring is often lumped together with financial credit scoring in policy discussions, even though it’s a much younger field with little precedent in other societies. 

What makes it extra confusing is that in practice, local governments have sometimes mixed up these two. So you may see a regulation talking about how non-financial activities will hurt your financial credit, or vice versa. (In just one example, the province of Liaoning said in August that it’s exploring how to reward blood donation in the financial credit system.) 

But on a national level, the country seems to want to keep the two mostly separate, and in fact, the new draft law addresses them with two different sets of rules.

Has the government built a system that is actively regulating these two types of credit?

The short answer is no. Initially, back in 2014, the plan was to have a national system tracking all “social credit” ready by 2020. Now it’s almost 2023, and the long-anticipated legal framework for the system was just released in the November 2022 draft law. 

That said, the government has mostly figured out the financial part. The zhengxin system—first released to the public in 2006 and significantly updated in 2020—is essentially the Chinese equivalent of American credit bureaus’ scoring and is maintained by the country’s central bank. It records the financial history of 1.14 billion Chinese individuals (and gives them credit scores), as well as almost 100 million companies (though it doesn’t give them scores). 

On the social side, however, regulations have been patchy and vague. To date, the national government has built only a system focused on companies, not individuals, which aggregates data on corporate regulation compliance from different government agencies. Kendra Schaefer, head of tech policy research at the Beijing-based consultancy Trivium China, has described it in a report for the US government’s US-China Economic and Security Review Commission as “roughly equivalent to the IRS, FBI, EPA, USDA, FDA, HHS, HUD, Department of Energy, Department of Education, and every courthouse, police station, and major utility company in the US sharing regulatory records across a single platform.” The result is openly searchable by any Chinese citizen on a recently built website called Credit China.

But there is some data on people and other types of organizations there, too. The same website also serves as a central portal for over three dozen (sometimes very specific) databases, including lists of individuals who have defaulted on a court judgment, Chinese universities that are legitimate, companies that are approved to build robots, and hospitals found to have conducted insurance fraud. Nevertheless, the curation seems so random that it’s hard to see how people could use the portal as a consistent or comprehensive source of data.

How will a social credit system affect Chinese people’s everyday lives?

The idea is to be both a carrot and a stick. So an individual or company with a good credit record in all regulatory areas should receive preferential treatment when dealing with the government—like being put on a priority list for subsidies. At the same time, individuals or companies with bad credit records will be punished by having their information publicly displayed, and they will be banned from participating in government procurement bids, consuming luxury goods, and leaving the country.

The government published a comprehensive list detailing the permissible punishment measures last year. Some measures are more controversial; for example, individuals who have failed to pay compensation decided by the court are restricted from traveling by plane or sending their children to costly private schools, on the grounds that these constitute luxury consumption. The new draft law upholds a commitment that this list will be updated regularly. 

So is there a centralized social credit score computed for every Chinese citizen?

No. Contrary to popular belief, there’s no central social credit score for individuals. And frankly, the Chinese central government has never talked about wanting one. 

So why do people, particularly in the West, think there is? 

Well, since the central government has given little guidance on how to build a social credit system that works in non-financial areas, even in the latest draft law, it has opened the door for cities and even small towns to experiment with their own solutions. 

As a result, many local governments are introducing pilot programs that seek to define what social credit regulation looks like, and some have become very contentious.

The best example is Rongcheng, a small city with only half a million in population that has implemented probably the most famous social credit scoring system in the world. In 2013, the city started giving every resident a base personal credit score of 1,000 that can be influenced by their good and bad deeds. For example, in a 2016 rule that has since been overhauled, the city decided that “spreading harmful information on WeChat, forums, and blogs” meant subtracting 50 points, while “winning a national-level sports or cultural competition” meant adding 40 points. In one extreme case, one resident lost 950 points in the span of three weeks for repeatedly distributing letters online about a medical dispute.

Such scoring systems have had very limited impact in China, since they have never been elevated to provincial or national levels. But when news of pilot programs like Rongcheng’s spread to the West, it understandably rang an alarm for activist groups and media outlets—some of which mistook it as applicable to the whole population. Prominent figures like George Soros and Mike Pence further amplified that false idea. 

How do we know those pilot programs won’t become official rules for the whole country?

No one can be 100% sure of that, but it’s worth remembering that the Chinese central government has actually been pushing back on local governments’ rogue actions when it comes to social credit regulations. 

In December 2020, China’s state council published a policy guidance responding to reports that local governments were using the social credit system as justification for punishing even trivial actions like jaywalking, recycling incorrectly, and not wearing masks. The guidance asks local governments to punish only behaviors that are already illegal under China’s current legislative system and not expand beyond that. 

“When [many local governments] encountered issues that are hard to regulate through business regulations, they hoped to draw support from solutions involving credits,” said Lian Weiliang, an official at China’s top economic planning authority, at a press conference on December 25, 2020. “These measures are not only incompatible with the rule of law, but also incompatible with the need of building creditworthiness in the long run.” 

And the central government’s pushback seems to have worked. In Rongcheng’s case, the city updated its local regulation on social credit scores and allowed residents to opt out of the scoring program; it also removed some controversial criteria for score changes. 

Is there any advanced technology, like artificial intelligence, involved in the system?

For the most part, no. This is another common myth about China’s social credit system: people imagine that to keep track of over a billion people’s social behaviors, there must be a mighty central algorithm that can collect and process the data.

But that’s not true. Since there is no central system scoring everyone, there’s not even a need for that kind of powerful algorithm. Experts on China’s social credit system say that the entire infrastructure is surprisingly low-tech. While Chinese officials sometimes name-drop technologies like blockchain and artificial intelligence when talking about the system, they never talk in detail about how these technologies might be utilized. If you check out the Credit China website, it’s no more than a digitized library of separate databases. 

“There is no known instance in which automated data collection leads to the automated application of sanctions without the intervention of human regulators,” wrote Schaefer in the report. Sometimes the human intervention can be particularly primitive, like the “information gatherers” in Rongcheng, who walk around the village and write down fellow villagers’ good deeds by pen.

However, as the national system is being built, it does appear there’s the need for some technological element, mostly to pool data among government agencies. If Beijing wants to enable every government agency to make enforcement decisions based on records collected by other government agencies, that requires building a massive infrastructure for storing, exchanging, and processing the data. 

To this end, the latest draft law talks about the need to use “diverse methods such as statistical methods, modeling, and field certification” to conduct credit assessments and combine data from different government agencies. “It gives only the vaguest hint that it’s a little more tech-y,” says Daum.

How are Chinese tech companies involved in this system?

Because the system is so low-tech, the involvement of Chinese tech companies has been peripheral. “Big tech companies and small tech companies … play very different roles, and they take very different strategies,” says Shazeda Ahmed, a postdoctoral researcher at Princeton University, who spent several years in China studying how tech companies are involved in the social credit system.

Smaller companies, contracted by city or provincial governments, largely built the system’s tech infrastructure, like databases and data centers. On the other hand, large tech companies, particularly social platforms, have helped the system spread its message. Alibaba, for instance, helps the courts deliver judgment decisions through the delivery addresses it collects via its massive e-commerce platform. And Douyin, the Chinese version of TikTok, partnered with a local court in China to publicly shame individuals who defaulted on court judgments. But these tech behemoths aren’t really involved in core functions, like contributing data or compiling credit appraisals.

“They saw it as almost like a civic responsibility or corporate social responsibility: if you broke the law in this way, we will take this data from the Supreme People’s Court, and we will punish you on our platform,” says Ahmed.

There are also Chinese companies, like Alibaba’s fintech arm Ant Group, that have built private financial credit scoring products. But the result, like Alibaba’s Sesame Credit, is more like a loyalty rewards program, according to several scholars. Since the Sesame Credit score is mostly calculated on the basis of users’ purchase history and lending activities on Alibaba’s own platforms, the score is not reliable enough to be used by external financial institutions and has very limited effect on individuals.

Given all this, should we still be concerned about the implications of building a social credit system in China?

Yes. Even if there isn’t a scary algorithm that scores every citizen, the social credit system can still be problematic.

The Chinese government did emphasize that all social-credit-related punishment has to adhere to existing laws, but laws themselves can be unjust in the first place. “Saying that the system is an extension of the law only means that it is no better or worse than the laws it enforces. As China turns its focus increasingly to people’s social and cultural lives, further regulating the content of entertainment, education, and speech, those rules will also become subject to credit enforcement,” Daum wrote in a 2021 article.

Moreover, “this was always about making people honest to the government, and not necessarily to each other,” says Ahmed. When moral issues like honesty are turned into legal issues, the state ends up having the sole authority in deciding who’s trustworthy. One tactic Chinese courts have used in holding “discredited individuals” accountable is encouraging their friends and family to report their assets in exchange for rewards. “Are you making society more trustworthy by ratting out your neighbor? Or are you building distrust in your very local community?” she asks.

But at the end of the day, the social credit system does not (yet) exemplify abuse of advanced technologies like artificial intelligence, and it’s important to evaluate it on the facts. The government is currently seeking public feedback on the November draft document for one month, though there’s no expected date on when it will pass and become law. It could still take years to see the final product of a nationwide social credit system.

When you lose weight, where does it go?

What happens when we lose weight? This is really a question about how our bodies store and use the energy we need to function. 

In general, we store backup energy in fat cells that are distributed around the body, some in the abdomen around the organs (visceral fat) and some under the skin (subcutaneous fat); lesser amounts of fat can also be deposited in muscle tissue. We also have smaller reserves of energy that are stored in the liver, muscles, and brain as glycogen. Glycogen is the stored form of glucose, the sugar that is the body’s main source of energy. 

We use energy all the time, whether we’re running, eating, or sleeping. The energy we use at rest—to pump blood, digest food, regulate temperature, repair cells, breathe, or think—is our baseline metabolism, the minimum energy required to maintain the body’s basic biological functions. So if we’re carrying extra weight, it’s because we’re taking in more energy than we’re using. (The much-cursed thickening around our bellies is a combination of accumulated deep visceral fat and more shallow subcutaneous fat.)

When we expend energy during intense bouts of exercise and other physical activity, the glycogen in our muscles is used first. The liver releases glycogen to help with muscle activity and to regulate blood glucose levels. After about 30 to 60 minutes of aerobic exercise, the body begins to burn fat.

If we take in less energy than the body needs overall to maintain itself—as when dieting—then the body turns more often to fat reserves for energy. As your body metabolizes fat, fatty acid molecules are released into the bloodstream and travel to the heart, lungs, and muscles, which break them apart and use the energy stored in their chemical bonds. The pounds you shed are essentially the byproducts of that process. They are excreted in the form of water—when you sweat and pee—and carbon dioxide, when you exhale. In fact, the lungs are the primary excretory organ for fat.

The body uses energy to carry out the usual basic processes at rest—again, your baseline metabolism—and for the physical activity you do on top of that, which is considered your active metabolism. 

Increasing muscle mass can help you burn more calories, because muscles require more energy to build and maintain than fat does. This can boost your baseline metabolism, and it explains how weightlifting and other types of strength training can meaningfully change your body composition. Note that if you restrict your food intake too drastically, your metabolism will adjust and use fewer calories for basic functions; your body will also start to break down muscle for energy, which in turn will slow down metabolism. Try to find a shortcut to weight loss around the body’s exquisitely balanced chemistry, and you may well find that it backfires on you instead. 

When you lose weight, where does it go?

What happens when we lose weight? This is really a question about how our bodies store and use the energy we need to function. 

In general, we store backup energy in fat cells that are distributed around the body, some in the abdomen around the organs (visceral fat) and some under the skin (subcutaneous fat); lesser amounts of fat can also be deposited in muscle tissue. We also have smaller reserves of energy that are stored in the liver, muscles, and brain as glycogen. Glycogen is the stored form of glucose, the sugar that is the body’s main source of energy. 

We use energy all the time, whether we’re running, eating, or sleeping. The energy we use at rest—to pump blood, digest food, regulate temperature, repair cells, breathe, or think—is our baseline metabolism, the minimum energy required to maintain the body’s basic biological functions. So if we’re carrying extra weight, it’s because we’re taking in more energy than we’re using. (The much-cursed thickening around our bellies is a combination of accumulated deep visceral fat and more shallow subcutaneous fat.)

When we expend energy during intense bouts of exercise and other physical activity, the glycogen in our muscles is used first. The liver releases glycogen to help with muscle activity and to regulate blood glucose levels. After about 30 to 60 minutes of aerobic exercise, the body begins to burn fat.

If we take in less energy than the body needs overall to maintain itself—as when dieting—then the body turns more often to fat reserves for energy. As your body metabolizes fat, fatty acid molecules are released into the bloodstream and travel to the heart, lungs, and muscles, which break them apart and use the energy stored in their chemical bonds. The pounds you shed are essentially the byproducts of that process. They are excreted in the form of water—when you sweat and pee—and carbon dioxide, when you exhale. In fact, the lungs are the primary excretory organ for fat.

The body uses energy to carry out the usual basic processes at rest—again, your baseline metabolism—and for the physical activity you do on top of that, which is considered your active metabolism. 

Increasing muscle mass can help you burn more calories, because muscles require more energy to build and maintain than fat does. This can boost your baseline metabolism, and it explains how weightlifting and other types of strength training can meaningfully change your body composition. Note that if you restrict your food intake too drastically, your metabolism will adjust and use fewer calories for basic functions; your body will also start to break down muscle for energy, which in turn will slow down metabolism. Try to find a shortcut to weight loss around the body’s exquisitely balanced chemistry, and you may well find that it backfires on you instead.