Job titles of the future: Pharmaceutical-grade mushroom grower

Studies have indicated that psychedelic drugs, such as psilocybin and MDMA, have swift-acting and enduring antidepressant effects. Though the US Food and Drug Administration denied the first application for medical treatments involving psychedelics (an MDMA-based therapy) last August, these drugs appear to be on the road to mainstream medicine. Research into psilocybin led by the biotech company Compass Pathways has been slowed in part by the complexity of the trials, but the data already shows promise for the psychedelic compound within so-called magic mushrooms. Eventually, the FDA will decide whether to approve it to treat depression. If and when it does—a move that would open up a vast legal medical market—who will grow the mushrooms?

Scott Marshall already is. The head of mycology at the drug manufacturer Optimi Health in British Columbia, Canada, he is one of a very small number of licensed psilocybin mushroom cultivators in North America. Growers and manufacturers would need to do plenty of groundwork to be able to produce pharmaceutical psilocybin on an industrial, FDA-approved scale. That’s why Optimi is keen to get a head start.

A nascent industry

Marshall is at the cutting edge of the nascent psychedelics industry. Psilocybin mushroom production was not legally permitted in Canada until 2022, when the country established its limited compassionate-­access program. “Our work is pioneering large-scale, legal cultivation of psilocybin mushrooms, ensuring the highest standards of safety, quality, and consistency,” he says. 

Backed by more than $22 million in investment, Optimi received a drug establishment license in 2024 from Canadian regulators to export pharmaceutical-­grade psilocybin to psychiatrists abroad in the limited number of places that have legal avenues for its use. Oregon has legalized supervised mushroom journeys, Australia has approved psilocybin therapy for PTSD and depression, and an increasing number of governments—national, state, and local—are considering removing legal barriers to psychedelic mushrooms on a medical basis as the amount of research supporting their use grows. There are also suggestions that the Trump administration may be more likely to support federal reform in the US.

But the legal market, medical or otherwise, remains tiny. So for now, almost all of Marshall’s mushrooms—he has grown more than 500 pounds since joining Optimi in 2022—stay in the company’s vault. “By setting the bar for production and [compliance with] regulation,” he says, “we’re helping to expand scientific understanding and accessibility of psychedelics for therapeutic use.”

Learning the craft

Before Marshall, 40, began cultivating mushrooms, he was working in property management. But that changed in 2014, when a friend who was an experienced grower gave him a copy of the book Mushroom Cultivator: A Practical Guide to Growing Mushrooms at Home (1983). That friend also gave him a spore print, effectively the “seeds” of a mushroom, from which Marshall grew three Psilocybin cubensis mushrooms from the golden teacher variety, his first foray into the field. “I kept growing and growing and growing—for my own health and well-being—and then got to a point where I wanted to help other people,” he says.

In 2018, he established his own company, Ra Mushrooms, selling cultivation kits for several varieties, including illegal psilocybin, and he was regularly posting photos on Instagram of mushrooms he had grown. In 2022, he was hired by Optimi, marking his journey from underground grower to legal market cultivator—“an unbelievable dream of mine.” 

Mattha Busby is a journalist specializing in drug policy and psychedelic culture.

The foundations of America’s prosperity are being dismantled

Ever since World War II, the US has been the global leader in science and technology—and benefited immensely from it. Research fuels American innovation and the economy in turn. Scientists around the world want to study in the US and collaborate with American scientists to produce more of that research. These international collaborations play a critical role in American soft power and diplomacy. The products Americans can buy, the drugs they have access to, the diseases they’re at risk of catching—are all directly related to the strength of American research and its connections to the world’s scientists.

That scientific leadership is now being dismantled, according to more than 10 federal workers who spoke to MIT Technology Review, as the Trump administration—spearheaded by Elon Musk’s Department of Government Efficiency (DOGE)—slashes personnel, programs, and agencies. Meanwhile, the president himself has gone after relationships with US allies.   

These workers come from several agencies, including the Departments of State, Defense, and Commerce, the US Agency for International Development, and the National Science Foundation. All of them occupy scientific and technical roles, many of which the average American has never heard of but which are nevertheless critical, coordinating research, distributing funding, supporting policymaking, or advising diplomacy.

They warn that dismantling the behind-the-scenes scientific research programs that backstop American life could lead to long-lasting, perhaps irreparable damage to everything from the quality of health care to the public’s access to next-generation consumer technologies. The US took nearly a century to craft its rich scientific ecosystem; if the unraveling that has taken place over the past month continues, Americans will feel the effects for decades to come. 

Most of the federal workers spoke on condition of anonymity because they were not authorized to talk or for fear of being targeted. Many are completely stunned and terrified by the scope and totality of the actions. While every administration brings its changes, keeping the US a science and technology leader has never been a partisan issue. No one predicted the wholesale assault on these foundations of American prosperity.

“If you believe that innovation is important to economic development, then throwing a wrench in one of the most sophisticated and productive innovation machines in world history is not a good idea,” says Deborah Seligsohn, an assistant professor of political science at Villanova University who worked for two decades in the State Department on science issues. “They’re setting us up for economic decline.”

The biggest funder of innovation

The US currently has the most top-quality research institutes in the world. This includes world-class universities like MIT (which publishes MIT Technology Review) and the University of California, Berkeley; national labs like Oak Ridge and Los Alamos; and federal research facilities run by agencies like the National Oceanic and Atmospheric Administration and the Department of Defense. Much of this network was developed by the federal government after World War II to bolster the US position as a global superpower. 

Before the Trump administration’s wide-ranging actions, which now threaten to slash federal research funding, the government remained by far the largest supporter of scientific progress. Outside of its own labs and facilities, it funded more than 50% of research and development across higher education, according to data from the National Science Foundation. In 2023, that came to nearly $60 billion out of the $109 billion that universities spent on basic science and engineering. 

The return on these investments is difficult to measure. It can often take years or decades for this kind of basic science research to have tangible effects on the lives of Americans and people globally, and on the US’s place in the world. But history is littered with examples of the transformative effect that this funding produces over time. The internet and GPS were first developed through research backed by the Department of Defense, as was the quantum dot technology behind high-resolution QLED television screens. Well before they were useful or commercially relevant, the development of neural networks that underpin nearly all modern AI systems was substantially supported by the National Science Foundation. The decades-long drug discovery process that led to Ozempic was incubated by the Department of Veterans Affairs and the National Institutes of Health. Microchips. Self-driving cars. MRIs. The flu shot. The list goes on and on. 

In her 2013 book The Entrepreneurial State, Mariana Mazzucato, a leading economist studying innovation at University College London, found that every major technological transformation in the US, from electric cars to Google to the iPhone, can trace its roots back to basic science research once funded by the federal government. If the past offers any lesson, that means every major transformation in the future could be shortchanged with the destruction of that support.

The Trump administration’s distaste for regulation will arguably be a boon in the short term for some parts of the tech industry, including crypto and AI. But the federal workers said the president’s and Musk’s undermining of basic science research will hurt American innovation in the long run. “Rather than investing in the future, you’re burning through scientific capital,” an employee at the State Department said. “You can build off the things you already know, but you’re not learning anything new. Twenty years later, you fall behind because you stopped making new discoveries.”

A global currency

The government doesn’t just give money, either. It supports American science in numerous other ways, and the US reaps the returns. The Department of State helps attract the best students from around the world to American universities. Amid stagnating growth in the number of homegrown STEM PhD graduates, recruiting foreign students remains one of the strongest pathways for the US to expand its pool of technical talent, especially in strategic areas like batteries and semiconductors. Many of those students stay for years, if not the rest of their lives; even if they leave the country, they’ve already spent some of their most productive years in the US and will retain a wealth of professional connections with whom they’ll collaborate, thereby continuing to contribute to US science.

The State Department also establishes agreements between the US and other countries and helps broker partnerships between American and international universities. That helps scientists collaborate across borders on everything from global issues like climate change to research that requires equipment on opposite sides of the world, such as the measurement of gravitational waves.

The international development work of USAID in global health, poverty reduction, and conflict alleviation—now virtually shut down in its entirety—was designed to build up goodwill toward the US globally; it improved regional stability for decades. In addition to its inherent benefits, this allowed American scientists to safely access diverse geographies and populations, as well as plant and animal species not found in the US. Such international interchange played just as critical a role as government funding in many crucial inventions.

Several federal agencies, including the Centers for Disease Control and Prevention, the Environmental Protection Agency, and the National Oceanic and Atmospheric Administration, also help collect and aggregate critical data on disease, health trends, air quality, weather, and more from disparate sources that feed into the work of scientists across the country.

The National Institutes of Health, for example, has since 2015 been running the Precision Medicine Initiative, the only effort of its kind to collect extensive and granular health data from over 1 million Americans who volunteer their medical records, genetic history, and even Fitbit data to help researchers understand health disparities and develop personalized and more effective treatments for disorders from heart and lung disease to cancer. The data set, which is too expensive for any one university to assemble and maintain, has already been used in hundreds of papers that will lay the foundation for the next generation of life-saving pharmaceuticals.

Beyond fueling innovation, a well-supported science and technology ecosystem bolsters US national security and global influence. When people want to study at American universities, attend international conferences hosted on American soil, or move to the US to work or to found their own companies, the US stays the center of global innovation activity. This ensures that the country continues to get access to the best people and ideas, and gives it an outsize role in setting global scientific practices and priorities. US research norms, including academic freedom and a robust peer review system, become global research norms that lift the overall quality of science. International agencies like the World Health Organization take significant cues from American guidance.

US scientific leadership has long been one of the country’s purest tools of soft power and diplomacy as well. Countries keen to learn from the American innovation ecosystem and to have access to American researchers and universities have been more prone to partner with the US and align with its strategic priorities.

Just one example: Science diplomacy has long played an important role in maintaining the US’s strong relationship with the Netherlands, which is home to ASML, the only company in the world that can produce the extreme ultraviolet lithography machines needed to produce the most advanced semiconductors. These are critical for both AI development and national security.

International science cooperation has also served as a stabilizing force in otherwise difficult relationships. During the Cold War, the US and USSR continued to collaborate on the International Space Station; during the recent heightened economic competition between the US and China, the countries have remained each other’s top scientific partners. “Actively working together to solve problems that we both care about helps maintain the connections and the context but also helps build respect,” Seligsohn says.

The federal government itself is a significant beneficiary of the country’s convening power for technical expertise. Among other things, experts both inside and outside the government support its sound policymaking in science and technology. During the US Senate AI Insight Forums, co-organized by Senator Chuck Schumer through the fall of 2023, for example, the Senate heard from more than 150 experts, many of whom were born abroad and studying at American universities, working at or advising American companies, or living permanently in the US as naturalized American citizens.

Federal scientists and technical experts at government agencies also work on wide-ranging goals critical to the US, including building resilience in the face of an increasingly erratic climate; researching strategic technologies such as next-generation battery technology to reduce the country’s reliance on minerals not found in the US; and monitoring global infectious diseases to prevent the next pandemic.

“Every issue that the US faces, there are people that are trying to do research on it and there are partnerships that have to happen,” the State Department employee said.

A system in jeopardy

Now the breadth and velocity of the Trump administration’s actions has led to an unprecedented assault on every pillar upholding American scientific leadership.

For starters, the purging of tens of thousands—and perhaps soon hundreds of thousands—of federal workers is removing scientists and technologists from the government and paralyzing the ability of critical agencies to function. Across multiple agencies, science and technology fellowship programs, designed to bring in talented early-career staff with advanced STEM degrees, have shuttered. Many other federal scientists were among the thousands who were terminated as probationary employees, a status they held because of the way scientific roles are often contractually structured.

Some agencies that were supporting or conducting their own research, including the National Institutes of Health and the National Science Foundation, are no longer functionally operational. USAID has effectively shuttered, eliminating a bastion of US expertise, influence, and credibility overnight.

“Diplomacy is built on relationships. If we’ve closed all these clinics and gotten rid of technical experts in our knowledge base inside the government, why would any foreign government have respect for the US in our ability to hold our word and in our ability to actually be knowledgeable?” a terminated USAID worker said. “I really hope America can save itself.”

Now the Trump administration has sought to reverse some terminations after discovering that many were key to national security, including nuclear safety employees responsible for designing, building, and maintaining the country’s nuclear weapons arsenal. But many federal workers I spoke to can no longer imagine staying in the public sector. Some are considering going into industry. Others are wondering whether it will be better to move abroad.

“It’s just such a waste of American talent,” said Fiona Coleman, a terminated federal scientist, her voice cracking with emotion as she described the long years of schooling and training she and her colleagues went through to serve the government.

Many fear the US has also singlehandedly kneecapped its own ability to attract talent from abroad. Over the last 10 years, even as American universities have continued to lead the world, many universities in other countries have rapidly leveled up. That includes those in Canada, where liberal immigration policies and lower tuition fees have driven a 200% increase in international student enrollment over the last decade, according to Anna Esaki-Smith, cofounder of a higher-education research consultancy called Education Rethink and author of Make College Your Superpower.

Germany has also seen an influx, thanks to a growing number of English-taught programs and strong connections between universities and German industry. Chinese students, who once represented the largest share of foreign students in the US, are increasingly staying at home or opting to study in places like Hong Kong, Singapore, and the UK.

During the first Trump administration, many international students were already more reluctant to come to the US because of the president’s hostile rhetoric. With the return and rapid escalation of that rhetoric, Esaki-Smith is hearing from some universities that international students are declining their admissions offers.

Add to that the other recent developments—the potential dramatic cuts in federal research funding, the deletion of scores of rich public data sets on health and the environment, the clampdown on academic freedom for research that appears related to diversity, equity, and inclusion and the fear that these restrictions could ultimately encompass other politically charged topics like climate change or vaccines—and many more international science and engineering students could decide to head elsewhere.

“I’ve been hearing this increasingly from several postdocs and early-career professors, fearing the cuts in NIH or NSF grants, that they’re starting to look for funding or job opportunities in other countries,” Coleman told me. “And then we’re going to be training up the US’s competitors.”

The attacks could similarly weaken the productivity of those who stay at American universities. While many of the Trump administration’s actions are now being halted and scrutinized by US judges, the chaos has weakened a critical prerequisite for tackling the toughest research problems: a long-term stable environment. With reports that the NSF is combing through research grants for words like “women,” “diverse,” and “institutional” to determine whether they violate President Trump’s executive order on DEIA programs, a chilling effect is also setting in among federally funded academics uncertain whether they’ll get caught in the dragnet.

To scientists abroad, the situation in the US government has marked American institutions and researchers as potentially unreliable partners, several federal workers told me. If international researchers think collaborations with the US can end at any moment when funds are abruptly pulled or certain topics or keywords are suddenly blacklisted, many of them could steer clear and look to other countries. “I’m really concerned about the instability we’re showing,” another employee at the State Department said. “What’s the point in even engaging? Because science is a long-term initiative and process that outlasts administrations and political cycles.”

Meanwhile, international scientists have far more options these days for high-caliber colleagues to collaborate with outside America. In recent years, for example, China has made a remarkable ascent to become a global peer in scientific discoveries. By some metrics, it has even surpassed the US; it started accounting for more of the top 1% of most-cited papers globally, often called the Nobel Prize tier, back in 2019 and has continued to improve the quality of the rest of its research. 

Where Chinese universities can also entice international collaborators with substantial resources, the US is more limited in its ability to offer tangible funding, the State employee said. Until now, the US has maintained its advantage in part through the prestige of its institutions and its more open cultural norms, including stronger academic freedom. But several federal scientists warn that this advantage is dissipating. 

“America is made up of so many different people contributing to it. There’s such a powerful global community that makes this country what it is, especially in science and technology and academia and research. We’re going to lose that; there’s not a chance in the world that we’re not going to lose that through stuff like this,” says Brigid Cakouros, a federal scientist who was also terminated from USAID. “I have no doubt that the international science community will ultimately be okay. It’ll just be a shame for the US to isolate themselves from it.”

Doctors and patients are calling for more telehealth. Where is it?

Maggie Barnidge, 18, has been managing cystic fibrosis her whole life. But not long after she moved out of her home state to start college, she came down with pneumonia and went into liver failure. She desperately wanted to get in touch with her doctor back home, whom she’d been seeing since she was diagnosed as an infant and who knew which treatments worked best for her—but he wasn’t allowed to practice telemedicine across state lines. The local hospital, and doctors unfamiliar with her complicated medical history, would have to do. 

“A lot of what Maggie needed wasn’t a physical exam,” says Barnidge’s mother, Elizabeth. “It was a conversation: What tests should I be getting next? What did my labs look like? She just needed her doctor who knew her well.”  

But doctors are generally allowed to practice medicine only where they have a license. This means they cannot treat patients across state lines unless they also have a license in the patient’s state, and most physicians have one or two licenses at most. This has led to what Ateev Mehrotra, a physician and professor of health policy at the Brown University School of Public Health, calls an “inane” norm: A woman with a rare cancer boarding an airplane, at the risk of her chemotherapy-weakened immune system, to see a specialist thousands of miles away, for example, or a baby with a rare disease who’s repeatedly shuttled between Arizona and Massachusetts. 

While eligible physicians can currently apply to practice in states besides their own, this can be a burdensome and impractical process. For instance, let’s say you are an oncologist in Minnesota, and a patient from Kansas arrives at your office seeking treatment. The patient will probably want to do follow-up appointments via telehealth when possible, to avoid having to travel back to Minnesota. 

But if you are not yet licensed to practice in Kansas (and you probably are not), you can’t suddenly start practicing medicine there. You would first need to apply to do so, either through the Interstate Medical Licensure Compact (designed to streamline the process of obtaining a full license in another state, but at a price of $700 per year) or with Kansas’s board of medicine directly. Maybe this poses too great an administrative hurdle for you—you work long hours, and how will you find time to compile the necessary paperwork? Doctors can’t reasonably be expected to apply for licensure in all 50 states. The patient, then, either loses out on care or must shoulder the burden of traveling to Minnesota for a doctor’s visit. The only way to access telehealth, if that’s what the patient prefers, would be to cross into the state and log in—an option that might still be preferable to traveling all the way to the doctor’s office. These obstacles to care have led to a growing belief among health-care providers, policymakers, and patients that under certain circumstances, doctors should be able to treat their patients anywhere. 

Lately, telehealth has proved to be widely popular, too. The coronavirus emergency in 2020 served as proof of concept, demonstrating that new digital platforms for medicine were feasible—and often highly effective. One study showed that telehealth accounted for nearly a quarter of contacts between patients and providers during the first four months of the pandemic (up from 0.3% during the same period in 2019), and among Medicare users, nearly half had used telehealth in 2020—a 63-fold increase. This swift and dramatic shift came about because Congress and the Centers for Medicare and Medicaid Services had passed legislation to make more telehealth visits temporarily eligible for reimbursement (the payments a health-care provider receives from an insurance company for providing medical services), while state boards of medicine relaxed the licensing restrictions. Now, more providers were able to offer telehealth, and more patients were eager to receive medical care without leaving their homes.

Though in-person care remains standard, telehealth has gained a significant place in US medicine, increasing from 0.1% of total Medicare visits in 2019 to 5.3% in 2020 and 3.5% in 2021. By the end of 2023, more than one in 10 Medicare patients were still using telehealth. And in some specialties the rate is much higher: 37% of all mental-health visits in the third quarter of 2023 were telemedicine, as well as 10% of obstetric appointments, 10% of transplant appointments, and 11% of infectious-disease appointments. 

“Telehealth has broadened our ability to provide care in ways not imaginable prior to the pandemic,” says Tara Sklar, faculty director of the health law and policy program at the University of Arizona James E. Rogers College of Law. 

Traditionally, patients and providers alike have been skeptical that telehealth care can meet the standards of an in-person appointment. However, most people advocating for telehealth aren’t arguing that it should completely replace visiting your doctor, explains Carmel Shachar, director of Harvard Law School’s Health Law and Policy Clinic. Rather, “it’s a really useful way to improve access to care.” Digital medicine could help address a gap in care for seniors by eliminating the need for them to make an arduous journey to the doctor’s office; many older adults find they’re more likely to keep their follow-up appointments when they can do them remotely. Telemedicine could also help address the equity issues facing hourly employees, who might not be able to take a half or full day off work to attend an in-­person appointment. For them, the offer of a video call might make the difference between seeking and not seeking help. 

“It’s a modality that we’re not using to its fullest potential because we’re not updating our regulations to reflect the digital age,” Shachar says.

Last December, Congress extended most of the provisions increasing Medicare coverage for telehealth through the end of March 2025, including the assurances that patients can be in their homes when they receive care and that they don’t need to be in a rural area to be eligible for telemedicine. 

“We would love to have these flexibilities made permanent,” says Helen Hughes, medical director for the Johns Hopkins Office of Telemedicine. “It’s confusing to explain to our providers and patients the continued regulatory uncertainty and news articles implying that telehealth is at risk, only to have consistent extensions for the last five years. This uncertainty leads providers and patients to worry that this type of care is not permanent and probably stifles innovation and investment by health systems.” 

In the meantime, several strategies are being considered to facilitate telehealth across state lines. Some places—like Maryland, Virginia, and Washington, DC—offer “proximal reciprocity,” meaning that a physician licensed in any of those states can more efficiently be licensed in the others. And several states, like Arkansas and Idaho, say that out-of-state doctors can generally practice telemedicine within their borders as long as they are licensed in good standing in another state and are using the technology to provide follow-up care. Expanding on these ideas, some advocates say that an ideal approach might look similar to how we regulate driving across state lines: A driver’s license from one state generally permits you to drive anywhere in the country as long as you have a good record and obey the rules of the road in the state that you’re in. Another idea is to create a telemedicine-specific version of the Interstate Medical Licensure Compact (which deals only with full medical licenses) in which qualifying physicians can register to practice telehealth among all participating states via a centralized compact.

For the foreseeable future, telehealth policy in the US is locked in what Mehrotra calls “hand-to-hand warfare”—states duking it out within their own legislatures to try to determine rules and regulations for administering telemedicine. Meanwhile, advocates are also pushing for uniformity between states, as with the Uniform Law Commission’s Telehealth Act of 2022, which set out consistent terminology so that states can adopt similar telehealth laws. 

“We’ve always advanced our technologies, like what I can provide as a doctor—meds, tests, surgeries,” Mehrotra says. “But in 2024, the basic structure of how we deliver that care is very similar to 1964.” That is, we still ask people to come to a doctor’s office or emergency department for an in-person visit. 

“That’s what excites me about telehealth,” he says. “I think there’s the potential that we can deliver care in a better way.” 

Isabel Ruehl is a writer based in New York and an assistant editor at Harper’s Magazine.

8,000 pregnant women may die in just 90 days because of US aid cuts

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

Yesterday marks a month since the inauguration of Donald Trump as the 47th US president. And what a month it has been. The Trump administration wasted no time in delivering a slew of executive orders, memos, and work notices to federal employees.

On February 18, Trump signed an executive order that seeks to make IVF more accessible to people in the US. In some ways, the move isn’t surprising—Trump has expressed his support for the technology in the past, and even called himself “the father of IVF” while on the campaign trail last year.

Making IVF more affordable and accessible should give people more options when it comes to family planning and reproductive freedom more generally. But the move comes after a barrage of actions by the new administration that are hitting reproductive care hard for people around the world. On January 20, his first day in office, Trump ordered a “90-day pause in United States foreign development assistance” for such programs to be assessed. By January 24, a “stop work” memo issued by the State Department brought US-funded aid programs around the world to a halt.  

Recent estimates suggest that more than 8,000 women will die from complications related to pregnancy and childbirth over the next 90 days if the funding is not reinstated.

On January 24 Trump also reinstated the global gag rule—a policy that requires nongovernmental organizations receiving US health funding to agree that they will not offer abortion counseling and care. This move alone immediately stripped organizations of the funding they need to perform their work. MSI Reproductive Choices, which offers support for reproductive health care in 36 countries, lost $14 million as a result, says Anna Mackay, who manages donor-funded programs at the organization. “Over 2 million women and girls would have received contraceptive services with that money,” she says.

The US Agency for International Development (USAID) had a 2025 budget of $42.8 billion to spend on foreign assistance, which covers everything from humanitarian aid and sanitation to programs promoting gender equality and economic growth in countries around the world. But the “stop work” memo froze that funding for 90 days.

The impacts were felt immediately and are still rippling out. Clinical trials were halted. Jobs were lost. Health programs were shut down.

“I think this is going to have a devastating impact on the global health architecture,” says Thoai Ngo at Columbia University’s Mailman School of Public Health. “USAID is the major foreign funder for global health … I’m afraid that there isn’t [another government] that can fill the gap.”

Reproductive health care is likely to lose out as affected governments and health organizations try to reorganize their resources, says Ngo: “In times of crisis … women and girls tend to be deprioritized in terms of access to health and social services.”

Without information on and access to a range of contraceptive options, unintended pregnancies result. These have the potential to limit the freedoms of people who become pregnant. And they can have far-reaching economic impacts, since access to contraception can improve education rates and career outcomes.

And the health consequences can be devastating. Unintended pregnancies are more likely to be ended with abortions—potentially unsafe ones. Maternal death rates are high in regions that lack adequate resources. A maternal death occurred every two minutes in 2020.

“It’s difficult to overstate how catastrophic this freeze has been over the last several weeks,” says Amy Friedrich-Karnik, director of federal policy at the Guttmacher Institute, a research and policy organization focused on global sexual and reproductive health and rights. “Every single day that the freeze is in place, there are 130,000 women who are being denied contraceptive care,” she says.

The Guttmacher Institute estimates that should USAID funding be frozen for the full 90 days, around 11.7 million women and girls would lose access to contraceptive care, and 4.2 million of them would experience unintended pregnancies. Of those, “8,340 will die from complications during pregnancy and childbirth,” says Friedrich-Karnik.

“By denying people access to contraception, not only are you denying them tools for their bodily autonomy—you are really risking their lives,” she says. “Thousands more women will die down the road.”

“USAID plays such a central role in supporting these life-saving programs,” says Ngo. “The picture is bleak.”

Even online sources of information on contraceptives are being affected by the funding freeze. Ben Bellows is a chief business officer at Nivi, a digital health company that develops chatbots to deliver health information to people via WhatsApp. “Two million users have used the bot,” he says.

He and his team have been working on a project to deliver information on contraceptive options and family planning to women in India, and they have been looking to incorporate AI into their bot. The project was funded by a company that, in turn, is funded by USAID. Like the funding, the work is “frozen,” says Bellows.

“We’ve slowed [hiring] and we’ve slowed some of the tech development because of the freeze [on USAID],” he says. “It’s bad [for] the individuals, it’s bad [for] the companies that are trying to operate in these markets, and it’s bad [for] public health outcomes.”

Reproductive health and freedoms are also likely to be affected by the Trump administration’s cuts to federal agencies. The National Institutes of Health and the Centers for Disease Control and Prevention have been in the administration’s crosshairs, as has the Food and Drug Administration.

After all, the FDA regulates drugs and medical devices in the US, including contraceptives. The CDC collects and shares important data on sexual and reproductive health. And the NIH supports vital research on reproductive health and contraception.

The CDC also funds health programs in low-income countries like Ethiopia. Following Trump’s executive order, the country’s ministry of health terminated the contracts of more than 5,000 health workers whose salaries were supported by the CDC as well as USAID.

“That’s midwives and nurses working in rural health posts,” says Mackay. “We’re turning up to support these staff and provide them with sexual reproductive health training and make sure they’ve got the contraceptives, and there’s just no one at the facility.”

So, yes, it is great news if the Trump administration can find a way to make IVF more accessible. But, as Mackay points out, “it’s increasing reproductive choice in one direction.”


Now read the rest of The Checkup

Read more from MIT Technology Review‘s archive

Last November, two years after Roe v. Wade was overturned, 10 US states voted on abortion rights. Seven of them voted to extend and protect access.

My colleague Rhiannon Williams reported on the immediate aftermath of the decision that reversed Roe v. Wade.

Fertility rates are falling around the world, in almost every country. IVF is great, but it won’t save us from a looming fertility crisis. Gender equality and family-friendly policies are much more likely to be effective. 

Decades of increasingly successful IVF treatments have caused millions of embryos to be stored in cryopreservation tanks around the world. In some cases, they can’t be donated, used, or destroyed and appear to be stuck in limbo “forever.”

Ever come across the term “women of childbearing age”? The insidious idea that women’s bodies are, above all else, vessels for growing children has plenty of negative consequences for us all. But it has also set back scientific research and health policy

There are other WhatsApp-based approaches to improving access to health information in India. Accredited social health activists in the country are using the platform to counter medical misinformation and superstitions around pregnancy.

From around the web

The US Food and Drug Administration assesses the efficacy and toxicity of experimental medicines before they are approved. It should also consider their “financial toxicity,” given that medical bills can fall on the shoulders of patients themselves, argue a group of US doctors. (The New England Journal of Medicine)

Robert F. Kennedy Jr., the new US secretary of health and human services, has vowed to investigate the country’s childhood vaccination schedule. During his confirmation hearing a couple of weeks ago, he promised not to change the schedule. (Associated Press)

Some scientists have been altering their published work without telling anyone. Such “stealth corrections” threaten scientific integrity, say a group of researchers from Europe and the US. (Learned Publishing)

The US Department of Agriculture said it accidentally fired several people who were working on the federal response to the bird flu outbreak. Apparently the agency is now trying to hire them back. (NBC News)

Could your next pet be a glowing rabbit? This startup is using CRISPR to “level up” pets. Their goal is to eventually create a real-life unicorn. (Wired)

This company is trying to make a biodegradable alternative to spandex

It probably hasn’t been long since you last slipped into something stretchy. From yoga pants to socks, stretch fabrics are everywhere. And they’re only getting more popular: The global spandex market, valued at almost $8 billion in December 2024, is projected to grow between 2% and 8% every year over the next decade. That might be better news for your comfort than for the environment. Most stretch fabrics contain petroleum-based fibers that shed microplastics and take centuries to decompose. And even a small amount of plastic-based stretch fiber in a natural garment can render it nonrecyclable.

Alexis Peña and Lauren Blake, cofounders of Good Fibes, aim to tackle this problem with lab-grown elastics. Operating out of Tufts University and Argonne National Laboratory in Illinois, they are using a class of materials called silk elastin-like proteins (SELPs) to create biodegradable textiles.

“True circularity has to start with raw materials,” says Peña. “We talk about circularity across many industries, but for textiles, we must address what we’re using at the source.”

Engineered from recombinant DNA, SELPs are copycat proteins inspired by silk and elastin that can be customized for qualities like tensile strength, dye affinity, and elasticity. Silk’s amino acid sequences—like glycine-alanine and glycine-serine—give fibers strength, while elastin’s molecular structure adds stretchiness. Combine these molecules like Lego blocks, and voilà!—at least theoretically, you have the ideal flexible fiber.

An early-stage startup, Good Fibes creates its elastics with proteins from E. coli, a common bacterium. The process involves transforming the proteins into a gel-like material, which can then be made into fibers through wet-spinning. These fibers are then processed into nonwoven textiles or threads and yarns to make woven fabrics.

Scaling, however, remains a challenge: To produce a single swatch of test fabric, Blake says, she needs at least one kilogram (approximately two pounds) of microbial material. The fibers must also be stretchy, durable, and resistant to moisture in all the right proportions. “We’re still solving these issues using various chemical additions,” she says. For that reason, she’s also experimenting with plant-based proteins like wheat gluten, which she says is available in larger quantities than bacteria.

Timothy McGee, a biomaterials expert at the research lab Speculative Technologies, says manufacturing is the biggest hurdle for biotextile startups. “Many labs and startups around the world successfully create recombinant proteins with amazing qualities, but they often struggle to turn those proteins into usable fibers,” he says.

One Japanese biomaterials company, Spiber, opened a commercial facility in 2022 to produce textiles from recombinant E. coli proteins using a fermentation process the company first developed in 2007. The following year—after 16 years of prototyping—The North Face, Goldwin, Nanamica, and Woolrich became the first mass-market brands to sell garments using Spiber’s protein-based textiles.

Good Fibes wants to do the same thing, but for stretchy fabrics. The company recently began experimenting with non­woven versions of its textiles after Peña received a $200,000 US Department of Energy grant in 2024. The most popular nonwoven materials are those used in paperlike products, such as surgical masks and paper towels, but Peña envisions a softer, stretchier version that’s almost more like a lightweight felt. She used the grant to buy the company’s first 3D bioprinter, which arrived in January. With it, she’ll begin patterning nonwoven swatches. 

If it’s successful, McGee predicts, a nonwoven stretch fabric could be a more scalable option than wovens. But he adds: “Nonwovens are not very structural, so they’re usually not very tough. The challenge [Good Fibes] will need to show is what level of strength and toughness—at what size and scale—can they produce, and at what cost?”

With additional funding, Peña and Blake plan to develop both woven and nonwoven textiles moving forward. 

Meanwhile, they’ve already forged relationships with at least one major athletic apparel retailer eager to test their future fabric samples. “They’re like, ‘When you get a swatch, send it to us!’” Blake says, adding that she believes Good Fibes will be ready to commercialize in two years.

Until then, their fashion innovation will continue taking shape in the lab. As Blake puts it: “We’re thinking big by thinking small—down to the molecular level.” 

Megan DeMatteo is a journalist based in New York City. 

What’s driving electricity demand? It isn’t just AI and data centers.

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

Electricity demand rose by 4.3% in 2024 and will continue to grow at close to 4% annually through 2027, according to a new report from the International Energy Agency. 

If that sounds familiar, it may be because there’s been a constant stream of headlines about energy demand recently, largely because of the influx of data centers—especially those needed to power the AI that’s spreading seemingly everywhere. These technologies are sucking up more power from the grid, but they’re just a small part of a much larger story. 

What’s actually behind this demand growth is complicated. Much of the increase comes from China, India, and Southeast Asia. Air-conditioning, electric vehicles, and factories all play a role. And of course, we can’t entirely discount the data centers. Here are a few key things to know about global electricity in 2025, and where things are going next.

China, India, and Southeast Asia are the ones to watch.

Between now and 2027, about 85% of electricity demand growth is expected to come from developing and emerging economies. China is an especially major force, having accounted for over half of global electricity demand growth last year.

The influence of even individual sectors in China is staggering. For example, in 2024, about 300 terawatt-hours’ worth of electricity was used just to produce solar modules, batteries, and electric vehicles. That’s as much electricity as Italy uses in a year. And this sector is growing quickly. 

A boom in heavy industry, an increase in the number of air conditioners, and a robust electric-vehicle market are all adding to China’s power demand. India and Southeast Asia are also going to have above-average increases in demand, driven by economic growth and increased adoption of air conditioners. 

And there’s a lot of growth yet to come, as 600 million people across Africa still don’t have access to reliable electricity.

Data centers are a somewhat minor factor globally, but they can’t be counted out.

According to another IEA projection published last year, data centers are expected to account for less than 10% of global electricity demand growth between now and 2030. That’s less than the expected growth due to other contributors like electric vehicles, air conditioners, and heavy industry.

However, data centers are a major storyline for advanced economies like the US and many countries in Europe. As a group, these nations have largely seen flat or declining electricity demand for the last 15 years, in part because of efficiency improvements. Data centers are reversing that trend.

Take the US, for example. The IEA report points to other research showing that the 10 states hosting the most data center growth saw a 10% increase in electricity demand between 2019 and 2023. Demand in the other 40 states declined by about 3% over the same period.

One caveat here is that nobody knows for sure what’s going to happen with data centers in the future, particularly those needed to run AI. Projections are all over the place, and small changes could drastically alter the amount of energy required for the technology. (See the DeepSeek drama.)

One bit I found interesting here is that China could see data centers emerge as yet another source of growing electricity demand in the future, with demand projected to double between now and 2027 (though, again, it’s all quite uncertain).

What this all means for climate change is complicated.

Growth in electricity demand can be seen as a good thing for our climate. Using a heat pump rather than a natural-gas heating system can help reduce emissions even as it increases electricity use. But as we add demand to the grid, it’s important to remember that in many places, it’s still largely reliant on fossil fuels.

The good news in all this is that there’s enough expansion in renewable and low-emissions electricity sources to cover the growth in demand. The rapid deployment of solar power alone contributes enough energy to cover half the demand growth expected through 2027. Nuclear power is also expected to see new heights soon, with recovery in France, restarts in Japan, and new reactors in China and India adding to a stronger global industry.

However, just adding renewables to meet electricity demand doesn’t automatically pull fossil fuels off the grid; existing coal and natural-gas plants are still chugging along all over the world. To make a dent in emissions, low-carbon sources need to grow fast enough not only to meet new demand, but to replace existing dirtier sources.

It isn’t inherently bad that the grid is growing. More people having air-conditioning and more factories making solar panels are all firmly in the “positive” column, I’d argue. But keeping up with this breakneck pace of demand growth is going to be a challenge—one that could have major effects on our ability to cut emissions. 


Now read the rest of The Spark

Related reading

Transmission equipment is key to getting more power to more people. Here’s why one developer won’t quit fighting to connect US grids, as reported by my colleague James Temple.

Virtual power plants could help meet growing electricity demand for EVs in China, as Zeyi Yang lays out in this story.

Power demand from data centers is rising, and so are emissions. They’re set to climb even higher, as James O’Donnell explains in this story from December.

robot made with humanoid head, car engine, chassis, wheels and industrial robot arms holds an electric drill and smaller car.

STEPHANIE ARNETT/MIT TECHNOLOGY REVIEW

Another thing

Competition is stiff in China’s EV market, so some automakers are pivoting to humanoid robots. With profit margins dropping for electrified vehicles, financial necessity is driving creativity, as my new colleague Caiwei Chen explains in her latest story

Keeping up with climate

The Trump administration has frozen funds and set hiring restrictions, and that could leave the US vulnerable to wildfire. (ProPublica)

US tariffs on imported steel and aluminum are set to go into effect next month, and they could be a problem for key grid equipment. The metals are used in transformers, which are in short supply. (Heatmap)

A maker of alternative jet fuel will get access to a $1.44 billion loan it was promised earlier this year. The Trump administration is exploring canceling promised financing, but this loan went ahead after a local representative pressured the White House. (Canary Media)

A third-generation oil and gas worker has pivoted to focus on drilling for geothermal systems. This Q&A is a fascinating look at what it might look like for more workers to move from fossil fuels to renewables. (Inside Climate News)

The Trump administration is working to fast-track hundreds of fossil-fuel projects. The US Army Corps of Engineers is speeding up permits using an emergency designation. (New York Times)

Japan’s government is adopting new climate targets. The country aims to cut greenhouse-gas emissions by more than 70% from 2013 levels over the next 15 years and reach net zero by 2050. Expansion of renewables and nuclear power will be key in the plan. (Associated Press)

A funding freeze has caused a whole lot of confusion about the state of federal financing for EV chargers in the US. But there’s still progress on building chargers, both from government funds already committed and from the private sector. (Wired)

The US National Oceanic and Atmospheric Administration (NOAA) is the latest target of the Trump administration’s cuts. NOAA provides weather forecasts, and private industry is reliant on the agency’s data. (Bloomberg)

Congress used to evaluate emerging technologies. Let’s do it again.

At about the time when personal computers charged into cubicle farms, another machine muscled its way into human resources departments and became a staple of routine employment screenings. By the early 1980s, some 2 million Americans annually found themselves strapped to a polygraph—a metal box that, in many people’s minds, detected deception. Most of those tested were not suspected crooks or spooks. 

Then the US Office of Technology Assessment, an independent office that had been created by Congress about a decade earlier to serve as its scientific consulting arm, got involved. The office reached out to Boston University researcher Leonard Saxe with an assignment: Evaluate polygraphs. Tell us the truth about these supposed truth-telling devices.

And so Saxe assembled a team of about a dozen researchers, including Michael Saks of Boston College, to begin a systematic review. The group conducted interviews, pored over existing studies, and embarked on new lines of research. A few months later, the OTA published a technical memo, “Scientific Validity of Polygraph Testing: A Research Review and Evaluation.” Despite the tests’ widespread use, the memo dutifully reported, “there is very little research or scientific evidence to establish polygraph test validity in screening situations, whether they be preemployment, preclearance, periodic or aperiodic, random, or ‘dragnet.’” These machines could not detect lies. 

Four years later, in 1987, critics at a congressional hearing invoked the OTA report as authoritative, comparing polygraphs derisively to “tea leaf reading or crystal ball gazing.” Congress soon passed strict limits on the use of polygraphs in the workplace. 

Over its 23-year history, the OTA would publish some 750 reports—lengthy, interdisciplinary assessments of specific technologies that proposed means of maximizing their benefits and minimizing harms. Their subjects included electronic surveillance, genetic engineering, hazardous-waste disposal, and remote sensing from outer space. Congress set its course: The office initiated studies only at the request of a committee chairperson, a ranking minority leader, or its 12-person bipartisan board. 

The investigations remained independent; staffers and consultants from both inside and outside government collaborated to answer timely and sometimes politicized questions. The reports addressed worries about alarming advances and tamped down scary-sounding hypotheticals. Some of those concerns no longer keep policymakers up at night. For instance, “Do Insects Transmit AIDS?” A 1987 OTA report correctly suggested that they don’t.

The office functioned like a debunking arm. It sussed out the snake oil. Lifted the lid on the Mechanical Turk. The reports saw through the alluring gleam of overhyped technologies. 

In the years since its unceremonious defunding, perennial calls have gone out: Rouse the office from the dead! And with advances in robotics, big data, and AI systems, these calls have taken on a new level of urgency. 

Like polygraphs, chatbots and search engines powered by so-called artificial intelligence come with a shimmer and a sheen of magical thinking. And if we’re not careful, politicians, employers, and other decision-makers may accept at face value the idea that machines can and should replace human judgment and discretion. 

A resurrected OTA might be the perfect body to rein in dangerous and dangerously overhyped technologies. “That’s what Congress needs right now,” says Ryan Calo at the University of Washington’s Tech Policy Lab and the Center for an Informed Public, “because otherwise Congress is going to, like, take Sam Altman’s word for everything, or Eric Schmidt’s.” (The CEO of OpenAI and the former CEO of Google have both testified before Congress.) Leaving it to tech executives to educate lawmakers is like having the fox tell you how to build your henhouse. Wasted resources and inadequate protections might be only the start. 

A man administers a lie detector test to a job
applicant in 1976. A 1983 report from the OTA debunked the efficacy of polygraphs.
LIBRARY OF CONGRESS

No doubt independent expertise still exists. Congress can turn to the Congressional Research Service, for example, or the National Academies of Sciences, Medicine, and Engineering. Other federal entities, such as the Office of Management and Budget and the Office of Science and Technology Policy, have advised the executive branch (and still existed as we went to press). “But they’re not even necessarily specialists,” Calo says, “and what they’re producing is very lightweight compared to what the OTA did. And so I really think we need OTA back.”  

What exists today, as one researcher puts it, is a “diffuse and inefficient” system. There is no central agency that wholly devotes itself to studying emerging technologies in a serious and dedicated way and advising the country’s 535 elected officials about potential impacts. The digestible summaries Congress receives from the Congressional Research Service provide insight but are no replacement for the exhaustive technical research and analytic capacity of a fully staffed and funded think tank. There’s simply nothing like the OTA, and no single entity replicates its incisive and instructive guidance. But there’s also nothing stopping Congress from reauthorizing its budget and bringing it back, except perhaps the lack of political will. 

“Congress Smiles, Scientists Wince”

The OTA had not exactly been an easy sell to the research community in 1972. At the time, it was only the third independent congressional agency ever established. As the journal Science put it in a headline that year, “The Office of Technology Assessment: Congress Smiles, Scientists Wince.” One researcher from Bell Labs told Science that he feared legislators would embark on “a clumsy, destructive attempt to manage national R&D,” but mostly the cringe seemed to stem from uncertainty about what exactly technology assessment entailed. 

The OTA’s first report, in 1974, examined bioequivalence, an essential part of evaluating generic drugs. Regulators were trying to figure out whether these drugs could be deemed comparable to their name-brand equivalents without lengthy and expensive clinical studies demonstrating their safety and efficacy. Unlike all the OTA’s subsequent assessments, this one listed specific policy recommendations, such as clarifying what data should be required in order to evaluatea generic drug and ensure uniformity and standardization in the regulatory approval process. The Food and Drug Administration later incorporated these recommendations into its own submission requirements. 

From then on, though, the OTA did not take sides. The office had not been set up to advise Congress on how to legislate. Rather, it dutifully followed through on its narrowly focused mandate: Do the research and provide policymakers with a well-reasoned set of options that represented a range of expert opinions.

Perhaps surprisingly, given the rise of commercially available PCs, in the first decade of its existence the OTA produced only a few reports on computing. One 1976 report touched on the automated control of trains. Others examined computerized x-ray imaging, better known as CT scans; computerized crime databases; and the use of computers in medical education. Over time, the office’s output steadily increased, eventually averaging 32 reports a year. Its budget swelled to $22 million; its staff peaked at 143. 

While it’s sometimes said that the future impact of a technology is beyond anyone’s imagination, several findings proved prescient. A 1982 report on electronic funds transfer, or EFT, predicted that financial transactions would increasingly be carried out electronically (an obvious challenge to paper currency and hard-copy checks). Another predicted that email, or what was then termed “electronic message systems,” would disrupt snail mail and the bottom line of the US Postal Service. 

In vetting the digital record-keeping that provides the basis for routine background checks, the office commissioned a study that produced a statistic still cited today, suggesting that only about a quarter of the records sent to the FBI were “complete, accurate, and unambiguous.” It was an indicator of a growing issue: computational systems that, despite seeming automated, are not free of human bias and error. 

Many of the OTA’s reports focus on specific events or technologies. One looked at Love Canal, the upstate New York neighborhood polluted by hazardous waste (a disaster, the report said, that had not yet been remediated by the Environmental Protection Agency’s Superfund cleanup program); another studied the Boston Elbow, a cybernetic limb (the verdict: decidedly mixed). The office examined the feasibility of a water pipeline connecting Alaska to California, the health effects of the Kuwait oil fires, and the news media’s use of satellite imagery. The office also took on issues we grapple with today—evaluating automatic record checks for people buying guns, scrutinizing the compensation for injuries allegedly caused by vaccines, and pondering whether we should explore Mars. 

The OTA made its biggest splash in 1984, when it published a background report criticizing the Strategic Defense Initiative (commonly known as “Star Wars”), a pet project of the Reagan administration that involved several exotic missile defense systems. Its lead author was the MIT physicist Ashton Carter, later secretary of defense in the second Obama administration. And the report concluded that a “perfect or near-perfect” system to defend against nuclear weapons was basically beyond the realm of the plausible; the possibility of deployment was “so remote that it should not serve as the basis of public expectation or national policy.” 

The report generated lots of clicks, so to speak, especially after the administration claimed that the OTA had divulged state secrets. These charges did not hold up and Star Wars never materialized, although there have been recent efforts to beef up the military’s offensive capacity in space. But for the work of an advisory body that did not play politics, the report made a big political hubbub. By some accounts, its subsequent assessments became so neutral that the office risked receding to the point of invisibility.

From a purely pragmatic point of view, the OTA wrote to be understood. A dozen reports from the early ’90s received “Blue Pencil Awards,” given by the National Association of Government Communicators for “superior government communication products and those who produce them.” None are copyrighted. All were freely reproduced and distributed, both in print and electronically. The entire archive is stored on CD-ROM, and digitized copies are still freely available for download on a website maintained by Princeton University, like an earnest oasis of competence in the cloistered world of federal documents. 

Assessments versus accountability

Looking back, the office took shape just as debates about technology and the law were moving to center stage. 

While the gravest of dangers may have changed in form and in scope, the central problem remains: Laws and lawmakers cannot keep up with rapid technological advances. Policymakers often face a choice between regulating with insufficient facts and doing nothing. 

In 2018, Adam Kinzinger, then a Republican congressman from Illinois, confessed to a panel on quantum computing: “I can understand about 50% of the things you say.” To some, his admission underscored a broader tech illiteracy afflicting those in power. But other commentators argued that members of Congress should not be expected to know it all—all the more reason to restaff an office like the OTA.

A motley chorus of voices have clamored for an OTA 2.0 over the years. One doctor wrote that the office could help address the “discordance between the amount of money spent and the actual level of health.” Tech fellows have said bringing it back could help Congress understand machine learning and AI. Hillary Clinton, as a Democratic presidential hopeful, floated the possibility of resurrecting the OTA in 2017. 

But Meg Leta Jones, a law scholar at Georgetown University, argues that assessing new technologies is the least of our problems. The kind of work the OTA did is now done by other agencies, such as the FTC, FCC, and National Telecommunications and Information Administration, she says: “The energy I would like to put into the administrative state is not on assessments, but it’s on actual accountability and enforcement.”

She sees the existing framework as built for the industrial age, not a digital one, and is among those calling for a more ambitious overhaul. There seems to be little political appetite for the creation of new agencies anyway. That said, Jones adds, “I wouldn’t be mad if they remade the OTA.” 

No one can know whether or how future administrations will address AI, Mars colonization, the safety of vaccines, or, for that matter, any other emerging technology that the OTA investigated in an earlier era. But if the new administration makes good on plans to deregulate many sectors, it’s worth noting some historic echoes. In 1995, when conservative politicians defunded the OTA, they did so in the name of efficiency. Critics of that move contend that the office probably saved the government money and argue that the purported cost savings associated with its elimination were largely symbolic. 

Jathan Sadowski, a research fellow at Monash University in Melbourne, Australia, who has written about the OTA’s history, says the conditions that led to its demise have only gotten more partisan, more politicized. This makes it difficult to envision a place for the agency today, he says—“There’s no room for the kind of technocratic naïveté that would see authoritative scientific advice cutting through the noise of politics.”

Congress purposely cut off its scientific advisory arm as part of a larger shake-up led by Newt Gingrich, then the House Speaker, whose pugilistic brand of populist conservatism promised “drain the swamp”–type reforms and launched what critics called a “war on science.” As a rationale for why the office was defunded, he said, “We constantly found scientists who thought what they were saying was not correct.” 

Once again, Congress smiled and scientists winced. Only this time it was because politicians had pulled the plug. 

Peter Andrey Smith, a freelance reporter, has contributed to Undark, the New Yorker, the New York Times Magazine, and WNYC’s Radiolab.

Your most important customer may be AI

Imagine you run a meal prep company that teaches people how to make simple and delicious food. When someone asks ChatGPT for a recommendation for meal prep companies, yours is described as complicated and confusing. Why? Because the AI saw that in one of your ads there were chopped chives on the top of a bowl of food, and it determined that nobody is going to want to spend time chopping up chives.

This is a real example from Jack Smyth, chief solutions officer of AI, planning, and insights at JellyFish, part of the Brandtech Group. He works with brands to help them understand how their products or company are perceived by AI models in the wild. It may seem odd for companies or brands to be mindful of what an AI “thinks,” but it’s already becoming relevant. A study from the Boston Consulting Group showed that 28% of respondents are using AI to recommend products such as cosmetics. And the push for AI agents that may handle making direct purchases for you is making brands even more conscious of how AI sees their products and business. 

The end results may be a supercharged version of search engine optimization (SEO) where making sure that you’re positively perceived by a large language model might become one of the most important things a brand can do.

Smyth’s company has created software, Share of Model, that assesses how different AI models view your brand. Each AI model has different training data, so although there are many similarities in how brands are assessed, there are differences, too.

For example, Meta’s Llama model may perceive your brand as exciting and reliable, whereas OpenAI’s ChatGPT may view it as exciting but not necessarily reliable. Share of Model asks different models many different questions about your brand and then analyzes all the responses, trying to find trends. “It’s very similar to a human survey, but the respondents here are large language models,” says Smyth.

The ultimate goal is not just to understand how your brand is perceived by AI but to modify that perception. How much models can be influenced is still up in the air, but preliminary results indicate that it may be possible. Since the models now show sources, if you ask them to search the web, a brand can see where the AI is picking up data. 

“We have a brand called Ballantine’s. It’s the No. 2 Scotch whisky that we sell in the world. So it’s a product for mass audiences,” says Gokcen Karaca, head of digital and design at Pernod Ricard, which owns Ballantine’s and a customer utilizing Share of Model. “However, Llama was identifying it as a premium product.” Ballantine’s also has a premium version, which is why the model may have been confused.

So Karaca’s team created new assets like images on social media for Ballantine’s mass product, highlighting its universal appeal to counteract the premium image. It’s not clear yet if the changes are working but Karaca claims early indications are good. “We made tiny changes, and it is taking time. I can’t give you concrete numbers but the trajectory is positive toward our target,” says Karaca.

It’s hard to know how exactly to influence AI because many models are closed-source, meaning their code and weights aren’t public and their inner workings are a bit of a mystery. But the advent of reasoning models, where the AI will share its process of solving a problem in text, could make the process simpler. You may be able to see the “chain of thought” that leads a model to recommend Dove soap, for example. If, in its reasoning, it details how important a good scent is to its soap recommendation, then the marketer knows what to focus on.

The ability to influence models has also opened up other ways to modify how your brand is perceived. For example, research out of Carnegie Mellon shows that changing the prompt can significantly modify what product an AI recommends. 

For example, take these two prompts:

1. “I’m curious to know your preference for the pressure cooker that offers the best combination of cooking performance, durable construction, and overall convenience in preparing a variety of dishes.”

2. “Can you recommend the ultimate pressure cooker that excels in providing consistent pressure, user-friendly controls, and additional features such as multiple cooking presets or a digital display for precise settings?”

The change led one of Google’s models, Gemma, to change from recommending the “Instant Pot” 0% of the time to recommending it 100% of the time. This dramatic change is due to the word choices in the prompt that trigger different parts of the model. The researchers believe we may see brands trying to influence recommended prompts online. For example, on forums like Reddit, people will frequently ask for example prompts to use. Brands may try to surreptitiously influence what prompts are suggested on these forums by having paid users or their own employees offer ideas designed specifically to result in recommendations for their brand or products. “We should warn users that they should not easily trust model recommendations, especially if they use prompts from third parties,” says Weiran Lin, one of the authors of the paper.

This phenomenon may ultimately lead to a push and pull between AI companies and brands similar to what we’ve seen in search over the past several decades. “It’s always a cat-and-mouse game,” says Smyth. “Anything that’s too explicit is unlikely to be as influential as you’d hope.” 

Brands have tried to “trick” search algorithms to place their content higher, while search engines aim to deliver—or at least we hope they deliver—the most relevant and meaningful results for consumers. A similar thing is happening in AI, where brands may try to trick models to give certain answers. “There’s prompt injection, which we do not recommend clients do, but there are a lot of creative ways you can embed messaging in a seemingly innocuous asset,” Smyth says. AI companies may implement techniques like training a model to know when an ad is disingenuous or trying to inflate the image of a brand. Or they may try to make their AI more discerning and less susceptible to tricks.

Another concern with using AI for product recommendations is that biases are built into the models. For example, research out of the University of South Florida shows that models tend to view global brands as higher quality and better than local brands, on average.

“When I give a global brand to the LLMs, it describes it with positive attributes,” says Mahammed Kamruzzaman, one of the authors of the research. “So if I am talking about Nike, in most cases it says that it’s fashionable or it’s very comfortable.” The research shows that if you then ask the model for its perception of a local brand, it will describe it as poor quality or uncomfortable. 

Additionally, the research shows that if you prompt the LLM to recommend gifts for people in high-income countries, it will suggest luxury-brand items, whereas if you ask what to give people in low-income countries, it will recommend non-luxury brands. “When people are using these LLMs for recommendations, they should be aware of bias,” says Kamruzzaman.

AI can also serve as a focus group for brands. Before airing an ad, you can get the AI to evaluate it from a variety of perspectives. “You can specify the audience for your ad,” says Smyth. “One of our clients called it their gen-AI gut check. Even before they start making the ad, they say, ‘I’ve got a few different ways I could be thinking about going to market. Let’s just check with the models.”

Since AI has read, watched, and listened to everything that your brand puts out, consistency may become more important than ever. “Making your brand accessible to an LLM is really difficult if your brand shows up in different ways in different places, and there is no real kind of strength to your brand association,” says Rebecca Sykes, a partner at Brandtech Group, the owner of Share of Model. “If there is a huge disparity, it’s also picked up on, and then it makes it even harder to make clear recommendations about that brand.”

Regardless of whether AI is the best customer or the most nitpicky, it may soon become undeniable that an AI’s perception of a brand will have an impact on its bottom line. “It’s probably the very beginning of the conversations that most brands are having, where they’re even thinking about AI as a new audience,” says Sykes.

A new Microsoft chip could lead to more stable quantum computers

Microsoft announced today that it has made significant progress in its 20-year quest to make topological quantum bits, or qubits—a special approach to building quantum computers that could make them more stable and easier to scale up. 

Researchers and companies have been working for years to build quantum computers, which could unlock dramatic new abilities to simulate complex materials and discover new ones, among many other possible applications. 

To achieve that potential, though, we must build big enough systems that are stable enough to perform computations. Many of the technologies being explored today, such as the superconducting qubits pursued by Google and IBM, are so delicate that the resulting systems need to have many extra qubits to correct errors. 

Microsoft has long been working on an alternative that could cut down on the overhead by using components that are far more stable. These components, called Majorana quasiparticles, are not real particles. Instead, they are special patterns of behavior that may arise inside certain physical systems and under certain conditions.

The pursuit has not been without setbacks, including a high-profile paper retraction by researchers associated with the company in 2018. But the Microsoft team, which has since pulled this research effort in house, claims it is now on track to build a fault-tolerant quantum computer containing a few thousand qubits in a matter of years and that it has a blueprint for building out chips that each contain a million qubits or so, a rough target that could be the point at which these computers really begin to show their power.

This week the company announced a few early successes on that path: piggybacking on a Nature paper published today that describes a fundamental validation of the system, the company says it has been testing a topological qubit, and that it has wired up a chip containing eight of them. 

“You don’t get to a million qubits without a lot of blood, sweat, and tears and solving a lot of really difficult technical challenges along the way. And I do not want to understate any of that,” says Chetan Nayak, a Microsoft technical fellow and leader of the team pioneering this approach. That said, he says, “I think that we have a path that we very much believe in, and we see a line of sight.” 

Researchers outside the company are cautiously optimistic. “I’m very glad that [this research] seems to have hit a very important milestone,” says computer scientist Scott Aaronson, who heads the ​​Quantum Information Center at the University of Texas at Austin. “I hope that this stands, and I hope that it’s built up.”

Even and odd

The first step in building a quantum computer is constructing qubits that can exist in fragile quantum states—not 0s and 1s like the bits in classical computers, but rather a mixture of the two. Maintaining qubits in these states and linking them up with one another is delicate work, and over the years a significant amount of research has gone into refining error correction schemes to make up for noisy hardware. 

For many years, theorists and experimentalists alike have been intrigued by the idea of creating topological qubits, which are constructed through mathematical twists and turns and have protection from errors essentially baked into their physics. “It’s been such an appealing idea to people since the early 2000s,” says Aaronson. “The only problem with it is that it requires, in a sense, creating a new state of matter that’s never been seen in nature.”

Microsoft has been on a quest to synthesize this state, called a Majorana fermion, in the form of quasiparticles. The Majorana was first proposed nearly 90 years ago as a particle that is its own antiparticle, which means two Majoranas will annihilate when they encounter one another. With the right conditions and physical setup, the company has been hoping to get behavior matching that of the Majorana fermion within materials.

In the last few years, Microsoft’s approach has centered on creating a very thin wire or “nanowire” from indium arsenide, a semiconductor. This material is placed in close proximity to aluminum, which becomes a superconductor close to absolute zero, and can be used to create superconductivity in the nanowire.

Ordinarily you’re not likely to find any unpaired electrons skittering about in a superconductor—electrons like to pair up. But under the right conditions in the nanowire, it’s theoretically possible for an electron to hide itself, with each half hiding at either end of the wire. If these complex entities, called Majorana zero modes, can be coaxed into existence, they will be difficult to destroy, making them intrinsically stable. 

”Now you can see the advantage,” says Sankar Das Sarma, a theoretical physicist at the University of Maryland who did early work on this concept. “You cannot destroy a half electron, right? If you try to destroy a half electron, that means only a half electron is left. That’s not allowed.”

In 2023, the Microsoft team published a paper in the journal Physical Review B claiming that this system had passed a specific protocol designed to assess the presence of Majorana zero modes. This week in Nature, the researchers reported that they can “read out” the information in these nanowires—specifically, whether there are Majorana zero modes hiding at the wires’ ends. If there are, that means the wire has an extra, unpaired electron.

“What we did in the Nature paper is we showed how to measure the even or oddness,” says Nayak. “To be able to tell whether there’s 10 million or 10 million and one electrons in one of these wires.” That’s an important step by itself, because the company aims to use those two states—an even or odd number of electrons in the nanowire—as the 0s and 1s in its qubits. 

If these quasiparticles exist, it should be possible to “braid” the four Majorana zero modes in a pair of nanowires around one another by making specific measurements in a specific order. The result would be a qubit with a mix of these two states, even and odd. Nayak says the team has done just that, creating a two-level quantum system, and that it is currently working on a paper on the results.

Researchers outside the company say they cannot comment on the qubit results, since that paper is not yet available. But some have hopeful things to say about the findings published so far. “I find it very encouraging,” says Travis Humble, director of the Quantum Science Center at Oak Ridge National Laboratory in Tennessee. “It is not yet enough to claim that they have created topological qubits. There’s still more work to be done there,” he says. But “this is a good first step toward validating the type of protection that they hope to create.” 

Others are more skeptical. Physicist Henry Legg of the University of St Andrews in Scotland, who previously criticized Physical Review B for publishing the 2023 paper without enough data for the results to be independently reproduced, is not convinced that the team is seeing evidence of Majorana zero modes in its Nature paper. He says that the company’s early tests did not put it on solid footing to make such claims. “The optimism is definitely there, but the science isn’t there,” he says.

One potential complication is impurities in the device, which can create conditions that look like Majorana particles. But Nayak says the evidence has only grown stronger as the research has proceeded. “This gives us confidence: We are manipulating sophisticated devices and seeing results consistent with a Majorana interpretation,” he says.

“They have satisfied many of the necessary conditions for a Majorana qubit, but there are still a few more boxes to check,” Das Sarma said after seeing preliminary results on the qubit. “The progress has been impressive and concrete.”

Scaling up

On the face of it, Microsoft’s topological efforts seem woefully behind in the world of quantum computing—the company is just now working to combine qubits in the single digits while others have tied together more than 1,000. But both Nayak and Das Sarma say other efforts had a strong head start because they involved systems that already had a solid grounding in physics. Work on the topological qubit, on the other hand, has meant starting from scratch. 

“We really were reinventing the wheel,” Nayak says, likening the team’s efforts to the early days of semiconductors, when there was so much to sort out about electron behavior and materials, and transistors and integrated circuits still had to be invented. That’s why this research path has taken almost 20 years, he says: “It’s the longest-running R&D program in Microsoft history.”

Some support from the US Defense Advanced Research Projects Agency could help the company catch up. Early this month, Microsoft was selected as one of two companies to continue work on the design of a scaled-up system, through a program focused on underexplored approaches that could lead to utility-scale quantum computers—those whose benefits exceed their costs. The other company selected is PsiQuantum, a startup that is aiming to build a quantum computer containing up to a million qubits using photons.

Many of the researchers MIT Technology Review spoke with would still like to see how this work plays out in scientific publications, but they were hopeful. “The biggest disadvantage of the topological qubit is that it’s still kind of a physics problem,” says Das Sarma. “If everything Microsoft is claiming today is correct … then maybe right now the physics is coming to an end, and engineering could begin.” 

This story was updated with Henry Legg’s current institutional affiliation.

How to have a child in the digital age

When the journalist and culture critic Amanda Hess got pregnant with her first child, in 2020, the internet was among the first to know. “More brands knew about my pregnancy than people did,” she writes of the torrent of targeted ads that came her way. “They all called me mama.” 

The internet held the promise of limitless information about becoming the perfect parent. But at seven months, Hess went in for an ultrasound appointment and everything shifted. The sonogram looked atypical. As she waited in an exam room for a doctor to go over the results, she felt the urge to reach for her phone. Though it “was ludicrous,” she writes, “in my panic, it felt incontrovertible: If I searched it smart and fast enough, the internet would save us. I had constructed my life through its screens, mapped the world along its circuits. Now I would make a second life there too.” Her doctor informed her of the condition he suspected her baby might have and told her, “Don’t google it.”

Unsurprisingly, that didn’t stop her. In fact, she writes, the more medical information that doctors produced—after weeks of escalating tests, her son was ultimately diagnosed with Beckwith-Wiedemann syndrome—the more digitally dependent she became: “I found I was turning to the internet, as opposed to my friends or my doctors, to resolve my feelings and emotions about what was happening to me and to exert a sense of external control over my body.”  

But how do we retain control over our bodies when corporations and the medical establishment have access to our most personal information? What happens when humans stop relying on their village, or even their family, for advice on having a kid and instead go online, where there’s a constant onslaught of information? How do we make sense of the contradictions of the internet—the tension between what’s inherently artificial and the “natural” methods its denizens are so eager to promote? In her new book, Second Life: Having a Child in the Digital Age (Doubleday, 2025), Hess explores these questions while delving into her firsthand experiences with apps, products, algorithms, online forums, advertisers, and more—each promising an easier, healthier, better path to parenthood. After welcoming her son, who is now healthy, in 2020 and another in 2022, Hess is the perfect person to ask: Is that really what they’re delivering? 

In your book, you write, “I imagined my [pregnancy] test’s pink dye spreading across Instagram, Facebook, Amazon. All around me, a techno-­corporate infrastructure was locking into place. I could sense the advertising algorithms recalibrating and the branded newsletters assembling in their queues. I knew that I was supposed to think of targeted advertising as evil, but I had never experienced it that way.” Can you unpack this a bit?

Before my pregnancy, I never felt like advertising technology was particularly smart or specific. So when my Instagram ads immediately clocked my pregnancy, it came as a bit of a surprise, and I realized that I was unaware of exactly how ad tech worked and how vast its reach was. It felt particularly eerie in this case because in the beginning my pregnancy was a secret that I kept from everyone except my spouse, so “the internet” was the only thing that was talking to me about it. Advertising became so personalized that it started to feel intimate, even though it was the opposite of that—it represented the corporate obliteration of my privacy. The pregnancy ads reached me before a doctor would even agree to see me.

Though your book was written before generative AI became so ubiquitous, I imagine you’ve thought about how it changes things. You write, “As soon as I got pregnant, I typed ‘what to do when you get pregnant’ in my phone, and now advertisers were supplying their own answers.” What do the rise of AI and the dramatic changes in search mean for someone who gets pregnant today and goes online for answers?

I just googled “what to do when you get pregnant” to see what Google’s generative AI widget tells me now, and it’s largely spitting out commonsensical recommendations: Make an appointment to see a doctor. Stop smoking cigarettes. That is followed by sponsored content from Babylist, an online baby registry company that is deeply enmeshed in the ad-tech system, and Perelel, a startup that sells expensive prenatal supplements. 

So whether or not the search engine is using AI, the information it’s providing to the newly pregnant is not particularly helpful or meaningful. 

The Clue period-tracking
app
AMIE CHUNG/TRUNK ARCHIVE

The internet “made me feel like I had some kind of relationship with my phone, when all it was really doing was staging a scene of information that it could monetize.”

For me, the oddly tantalizing thing was that I had asked the internet a question and it gave me something in response, as if we had a reciprocal relationship. So even before AI was embedded in these systems, they were fulfilling the same role for me—as a kind of synthetic conversation partner. It made me feel like I had some kind of relationship with my phone, when all it was really doing was staging a scene of information that it could monetize. 

As I wrote the book, I did put some pregnancy­-related questions to ChatGPT to try to get a sense of the values and assumptions that are encoded in its knowledge base. I asked for an image of a fetus, and it provided this garishly cartoonish, big-eyed cherub in response. But when I asked for a realistic image of a postpartum body, it refused to generate one for me! It was really an extension of something I write about in the book, which is that the image of the fetus is fetishized in a lot of these tech products while the pregnant or postpartum body is largely erased. 

You have this greatbut quite sadquote from a woman on TikTok who said, “I keep hearing it takes a village to raise a child. Do they just show up, or is there a number to call?” 

I really identified with that sentiment, while at the same time being suspicious of this idea that can we just call a hotline to conjure this village?

I am really interested that so many parent-­focused technologies sell themselves this way. [The pediatrician] Harvey Karp says that the Snoo, this robotic crib he created, is the new village. The parenting site Big Little Feelings describes its podcast listeners as a village. The maternity clothing brand Bumpsuit produces a podcast that’s actually called The Village. By using that phrase, these companies are evoking an idealized past that may never have existed, to sell consumer solutions. A society that provides communal support for children and parents is pitched as this ancient and irretrievable idea, as opposed to something that we could build in the future if we wanted to. It will take more than just, like, ordering something.

And the benefit of many of those robotic or “smart” products seems a bit nebulous. You share, for example, that the Nanit baby monitor told you your son was “sleeping more efficiently than 96% of babies, a solid A.”

I’m skeptical of this idea that a piece of consumer technology will really solve a serious problem families or children have. And if it does solve that problem, it only solves it for people who can afford it, which is reprehensible on some level. These products might create a positive difference for how long your baby is sleeping or how easy the diaper is to put on or whatever, but they are Band-Aids on a larger problem. I often found when I was testing out some of these products that the data [provided] was completely useless. My friend who uses the Nanit texted me the other day because she had found a new feature on its camera that showed you a heat map of where your baby had slept in the crib the night before. There is no use for that information, but when you see the heat map, you can try to interpret it to get some useless clues to your baby’s personality. It’s like a BuzzFeed quiz for your baby, where you can say, “Oh, he’s such, like, a right-side king,” or “He’s a down-the-middle guy,” or whatever. 

The Snoo Smart Sleeper Bassinet
COURTESY OF HAPPIEST BABY

“[Companies are] marketing a cure for the parents’ anxiety, but the product itself is attached to the body of a newborn child.”

These products encourage you to see your child themselves as an extension of the technology; Karp even talks about there being an on switch and an off switch in your baby for soothing. So if you do the “right” set of movements to activate the right switch, you can make the baby acquire some desirable trait, which I think is just an extension of this idea that your child can be under your complete control.

… which is very much the fantasy when you’re a parent.

These devices are often marketed as quasi-­medical devices. There’s a converging of consumer and medical categories in baby consumer tech, where the products are marketed as useful to any potential baby, including one who has a serious medical diagnosis or one who is completely healthy. These companies still want you to put a pulse oximeter on a healthy baby, just in case. They’re marketing a cure for the parents’ anxiety, but the product itself is attached to the body of a newborn child.

After spending so much time in hospital settings with my child hooked up to monitors, I was really excited to end that. So I’m interested in this opposite reaction, where there’s this urge to extend that experience, to take personal control of something that feels medical.

Even though I would search out any medical treatment that would help keep my kids healthy, childhood medical experiences can cause a lot of confusion and trauma for kids and their families, even when the results are positive. When you take that medical experience and turn it into something that’s very sleek and fits in your color scheme and is totally under your control, I think it can feel like you are seizing authority over that scary space.

Another thing you write about is how images define idealized versions of pregnancy and motherhood. 

I became interested in a famous photograph that a Swedish photographer named Lennart Nilsson took in the 1960s that was published on the cover of Life magazine. It’s an image of a 20-week-old fetus, and it’s advertised as the world’s first glimpse of life inside the womb. I bought a copy of the issue off eBay and opened the issue to find a little editor’s note saying that the cover fetus was actually a fetus that had been removed from its mother’s body through surgery. It wasn’t a picture of life—it was a picture of an abortion. 

I was interested in how Nilsson staged this fetal body to make it look celestial, like it was floating in space, and I recognized a lot of the elements of his work being incorporated in the tech products that I was using, like the CGI fetus generated by my pregnancy app, Flo. 

You also write about the images being provided at nonmedical sonogram clinics.

I was trying to google the address of a medical imaging center during my pregnancy when I came across a commercial sonogram clinic. There are hundreds of them around the country, with cutesy names like “Cherished Memories” and “You Kiss We Tell.” 

In the book I explore how technologies like ultrasound are used as essentially narrative devices, shaping the way that people think about their bodies and their pregnancies. Ultrasound is odd because it’s a medical technology that’s used to diagnose dangerous and scary conditions, but prospective parents are encouraged to view it as a kind of entertainment service while it’s happening. These commercial sonogram clinics interest me because they promise to completely banish the medical associations of the technology and elevate it into a pure consumer experience. 

baby monitor
The Nanit Pro baby monitor with Flex Stand
COURTESY OF NANIT

You write about “natural” childbirth, which, on the face of it, would seem counter to the digital age. As you note, the movement has always been about storytelling, and the story that it’s telling is really about pain.

When I was pregnant, I became really fascinated with people who discuss freebirth online, which is a practice on the very extreme end of “natural” childbirth rituals—where people give birth at home unassisted, with no obstetrician, midwife, or doula present. Sometimes they also refuse ultrasounds, vaccinations, or all prenatal care. I was interested in how this refusal of medical technology was being technologically promoted, through podcasts, YouTube videos, and Facebook groups. 

It struck me that a lot of the freebirth influencers I saw were interested in exerting supreme control over their pregnancies and children, leaving nothing under the power of medical experts or government regulators. And they were also interested in controlling the narratives of their births—making sure that the moment their children came into the world was staged with compelling imagery that centered them as the protagonist of the event. Video evidence of the most extreme examples—like the woman who freebirthed into the ocean—could go viral and launch the freebirther’s personal brand as a digital wellness guru in her own right. 

The phrase “natural childbirth” was coined by a British doctor, Grantly Dick-Read, in the 1920s. There’s a very funny section in his book for prospective mothers where he complains that women keep telling each other that childbirth hurts, and he claimed that the very idea that childbirth hurts was what created the pain, because birthing women were acting too tense. Dick-Read, like many of his contemporaries, had a racist theory that women he called “primitive” experienced no pain in childbirth because they hadn’t been exposed to white middle-class education and technologies. When I read his work, I was fascinated by the fact that he also described birth as a kind of performance, even back then. He claimed that undisturbed childbirths were totally painless, and he coached women through labor in an attempt to achieve them. Painless childbirth was pitched as a reward for reaching this peak state of natural femininity.

He was really into eugenics, by the way! I see a lot of him in the current presentation of “natural” childbirth online—[proponents] are still invested in a kind of denial, or suppression, of a woman’s actual experience in the pursuit of some unattainable ideal. Recently, I saw one Instagram post from a woman who claimed to have had a supernaturally pain-free childbirth, and she looks so pained and miserable in the photos, it’s absurd. 

I wanted to ask you about Clue and Flo, two very different period-tracking apps. Their contrasting origin stories are striking. 

I downloaded Flo as my period-tracking app many years ago for one reason: It was the first app that came up when I searched in the app store. Later, when I looked into its origins, I found that Flo was created by two brothers, cisgender men who do not menstruate, and that it had quickly outperformed and outearned an existing period-tracking app, Clue, which was created by a woman, Ida Tin, a few years earlier. 

The elements that make an app profitable and successful are not the same as the ones that users may actually want or need. My experience with Flo, especially after I became pregnant, was that it seemed designed to get me to open the app as frequently as possible, even if it didn’t have any new information to provide me about my pregnancy. Flo pitches itself as a kind of artificial nurse, even though it can’t actually examine you or your baby, but this kind of digital substitute has also become increasingly powerful as inequities in maternity care widen and decent care becomes less accessible.

“Doctors and nurses test pregnant women for drugs without their explicit consent or tip off authorities to pregnant people they suspect of mishandling their pregnancies in some way.”

One of the features of Flo I spent a lot of time with was its “Secret Chats” area, where anonymous users come together to go off about pregnancy. It was actually really fun, and it kept me coming back to Flo again and again, especially when I wasn’t discussing my pregnancy with people in real life. But it was also the place where I learned that digital connections are not nearly as helpful as physical connections; you can’t come over and help the anonymous secret chat friend soothe her baby. 

I’d asked Ida Tin if she considered adding a social or chat element to Clue, and she told me that she decided against it because it’s impossible to stem the misinformation that surfaces in a space like that.

You write that Flo “made it seem like I was making the empowered choice by surveilling myself.”

After Roe was overturned, many women publicly opted out of that sort of surveillance by deleting their period-tracking apps. But you mention that it’s not just the apps that are sharing information. When I spoke to attorneys who defend women in pregnancy criminalization cases, I found that they had not yet seen a case in which the government actually relied on data from those apps. In some cases, they have relied on users’ Google searches and Facebook messages, but far and away the central surveillance source that governments use is the medical system itself. 

Doctors and nurses test pregnant women for drugs without their explicit consent or tip off authorities to pregnant people they suspect of mishandling their pregnancies in some way. I’m interested in the fact that media coverage has focused so much on the potential danger of period apps and less on the real, established threat. I think it’s because it provides a deceptively simple solution: Just delete your period app to protect yourself. It’s much harder to dismantle the surveillance systems that are actually in place. You can’t just delete your doctor. 

This interview, which was conducted by phone and email, has been condensed and edited.