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Boston’s dense health-sciences networks help the city to maintain its lead
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An analytical chemist works in the lab of biotech company Arcaea, which is based in Boston, Massachusetts.Credit: Boston Globe/Getty
When a delegation of scientists from Japan recently visited Harvard University in Cambridge, Massachusetts, they asked their hosts a familiar question: what are the secret factors that make the Boston area, which includes Cambridge, such a hotbed for health-sciences research and innovation? In response, George Daley, dean of the Faculty of Medicine at Harvard Medical School, gave the half-joking answer he normally uses when asked similar questions: “Just incubate two of the most important educational institutions on the planet, support them for 200 years, and watch the magic happen.”
The Boston area is home to a critical mass of leading universities, hospitals, biotechnology and pharmaceutical companies, and independent research institutions that all interact synergistically, says Dan Barouch, an immunologist at Harvard Medical School and director of the Center for Virology and Vaccine Research at Beth Israel Deaconess Medical Center in Boston. “The quality, depth and sheer breadth and scope of research in Boston is just astounding.”
Nature Index 2024 Science cities
It’s no surprise, then, that the Boston metropolitan area leads the Nature Index Science Cities rankings in health sciences, based on 2023 research output in journals tracked by the database. According to the findings, the New York City metropolitan area ranks second after Boston, followed by the urban area formed by Baltimore and Washington DC; London; the San Francisco Bay Area; Beijing and Shanghai.
Science cities is tracking health sciences for the first time this year after data from journals in the subject were added to the Nature Index in 2022, but already, the data reveal some new trends. For one, US cities and London take the top five positions, whereas for most other tracked disciplines — including chemistry, physical sciences and Earth and environmental sciences — China now dominates the top positions.
Science cities rankings are not adjusted for population size, which means large cities such as Beijing and Shanghai — with populations of 21.5 and 26.3 million, respectively — have strong advantages for research output. But this also highlights the oversized contribution to health-sciences research by smaller leading cities such as Boston, whose greater metropolitan population is just 4.9 million. Boston is clearly “still very dominant in this area”, says Yiming Dong, a Chinese studies researcher at King’s College London. But this could change soon, with Dong emphasizing that China is moving quite quickly in the subject.
A tremendous anthill
Lots of cities around the world have good universities, smart people and some industry and capital for research, but few possess “this alchemy that creates, effectively, gold out of these regular materials”, says Paul Sagan, a senior adviser at General Catalyst, a venture-capital firm founded in Cambridge, Masachusetts. Scale, in terms of a concentration of elite scientific research institutions, and repetition, in terms of spinning out a continuous stream of new ideas — some of which succeed and spawn new biotech companies, are key to transforming a city into a true hub of excellence for science and innovation, Sagan continues. Among such hubs for health sciences and biotechnology, he adds, it’s clear “that Boston has sped ahead of everyone”. There are several probable reasons for this, he continues, including the presence of elite research institutions, start-ups and international companies with headquarters there, and a number of government initiatives over the years that have promoted and supported biotech research.
The Boston metropolitan area contains a familiar list of the leading institutions in the health sciences. Harvard University ranks first in the world in the Nature Index for the subject by a large distance and the leading two health-care facilities — Brigham and Women’s Hospital and Massachusetts General Hospital — are located nearby. Boston’s biotechnology sector is also growing quickly, Daley says, and most of the top pharmaceutical companies have established major research centres there.
A large and growing pot of venture capital also fuels health-sciences innovation in Boston. “Because drug development is so expensive, public research funding will never carry all the costs,” says Andrea Braun Střelcová, who studies science policy and research collaboration, with an emphasis on China, at the Max Planck Institute for the History of Science in Berlin. “So, the role of the market is really important.”
Although California has a strong venture-capital presence, too, “the big difference” for the Boston area is the presence of leading pharmaceutical companies — many of which are just a walk from the Massachusetts Institute of Technology (MIT) and Harvard, says Nobel laureate Phillip Sharp, who holds an emeritus position at MIT’s Koch Institute for Integrative Cancer Research.
The size of Boston’s talent pool is also notable, Daley says. Harvard’s full-time medical faculty alone numbers 10,000-plus — more than three times the size of other large medical schools in the United States. Considering all the other Boston-area health-sciences institutions, “you’ve got tens of thousands of clinicians and scientists working towards common goals in confronting disease and solving fundamental biomedical questions”, Daley says. “That’s just a tremendous anthill of activity all within a very small radius.”
Entrepreneurial and cool
Other top cities for health-sciences research possess the same features that make Boston stand out —only on a smaller scale. The New York City metropolitan area, for example, has Memorial Sloan Kettering Cancer Center, ranked sixth in the world among health-care institutions in the Nature Index for health sciences, and the Mount Sinai Health System, ranked eighth. Experts at many top-ranked institutions collaborate, too, which amplifies their impact and output. In the health sciences, collaborations between Harvard, MIT, Johns Hopkins University in Baltimore and the University of California, San Francisco, are among the most productive in the world, according to Nature Index data.
Like its US counterparts, London also has top-notch universities and strong biotechnology and pharmaceutical industries, says Rebecca Shipley, director of the Academic Health Science Centre at UCLPartners in London — an organization that brings together universities and health-care providers to accelerate the translation of research into improved outcomes. Unlike in the United States, researchers in London can benefit from the United Kingdom’s National Health Service, which operates across the country and makes it easier to obtain patient data and run clinical trials. Shipley predicts that London will continue to hold its spot among the leading five science cities in health sciences and has the potential to rise even higher. For example, the UK National Institute for Health and Care Research, which is the major funder of research to improve the population’s health, has awarded nearly £800 million (US$1 billion) in funding over 5 years to 20 university-hospital research centres around the United Kingdom — seven of which are in London — to translate basic discoveries into real-world patient care. There is also an increasing investment in London and nationally to build infrastructure to make patient data better available for research and innovation, Shipley says. This includes secure access for researchers to NHS patient data on a national level through a specialized platform, as well as a London-specific information-sharing hub called OneLondon that connects health and care staff to patient records, among other things. “There’s a real appetite in London to be innovative and build on this momentum,” Shipley says.
Visitors view a medicine and health exhibition at the 2024 Beijing Science and Technology Week, held in Beijing, China.Credit: NurPhoto/Getty
Indeed, for any sort of innovation hub to take off, there has to be a culture of entrepreneurialism and a mindset of “not being afraid to fail”, Sagan says. To attract and retain talent, the hub itself also must be somewhere that people want to live. “There are great research universities that might have some innovation, like the University of Illinois Urbana-Champaign, but by and large, that’s not a place where people aspire to live because it’s a small town, and small towns are limited, by definition,” Sagan says. “Not to demean small towns, but most ambitious entrepreneurs and researchers want to go to top-tier cities like New York City, Boston, or Silicon Valley because they are places where their partners can also get good jobs, their kids can go to great schools and their community offers great cultural diversity — and it’s just cool to be there.”
Surprising slips
The United States is showing some puzzling trends for health-sciences research output, however. Unlike the Boston metropolitan area, which increased its adjusted Share in the Nature Index by 6.6% from 2022 to 2023, the other leading four US cities lost ground. The San Francisco Bay Area experienced the steepest decline of 13.2%.
One explanation is likely to be that the Nature Index represents a relatively fixed set of research articles. If cities in one part of the world, such as China, are rapidly increasing their Share then others must fall to compensate. This makes Boston’s performance even more remarkable.
Stacie Bloom, the vice-provost for research and chief research officer at New York University, says she is surprised by New York’s results and that “all the messaging we get indicates that things are going in a more positive direction”. Daley also says that his perspective is that the US cities experiencing a drop in adjusted Share remain strong. “New York City has been on fire, and the Baltimore–Washington DC corridor is a hotbed of innovation,” he says. The San Francisco Bay Area also remains Boston’s “main competition” for cutting-edge biotechnology.
Daley adds that another explanation is health-sciences research from 2022 to 2023 was probably still affected by problems linked to the COVID-19 pandemic. The pandemic caused significant supply-chain issues for biomedical materials, he says, and across many industries, including in science, some people changed careers or took a while to return to work. Boston was probably more insulated from these impacts than other US cities, he adds, because of its higher density of people and institutions.
Daley expects that any decline in top US cities’ health-sciences research output will be “a momentary blip”, and that those hubs of innovation will “return to productivity and growth very soon”.
China rising
For now, cities in the United States, alongside London, still lead in health sciences, but experts predict that China will continue to gain ground. Logistically, this makes sense, says Yu-Xuan Lyu, a scientist at the Southern University of Science and Technology in Shenzhen, who studies ageing. It’s only in the past 10 to 15 years that China rapidly expanded its international research presence and rose to the top in natural-science subjects such as chemistry, which don’t require a close collaboration between universities, hospitals and industry. It has taken a bit more time for China to lay the structural groundwork to conduct world-class health-sciences research, but now that that is beginning to take shape, “the conditions are really good for China to start performing even better”, Střelcová says.
Beijing increased its health-sciences research output in the Nature Index by 17.6% between 2022 and 2023, while Shanghai’s contribution rose by nearly 4%. The southern city of Guangzhou, which is currently ranked 12th in the world for health-sciences research, is also growing quickly, with a 32.4% increase in the year to 2023. This growth is largely because health care and health-sciences research are priorities for the Chinese government, Dong says. “They’re spending a huge amount of money on this.” Health-sciences research accounted for 36%, or 97.6 billion yuan (US$13.8 billion), of the 2024 budget for the National Health Commission — an executive department under the State Council that’s responsible for health policies and health-related emergency management in mainland China.
Scientific advancement in health research is a key pillar of the Healthy China 2030 plan, a set of strategic public health goals first published in 2016. The country’s 14th five-year plan — which outlines overall objectives for long-term domestic economic development and innovation — also includes health-sciences goals, including specific plans to address China’s ageing population and improve health care. China’s National Health Commission’s science strategy also highlights similar goals, and the government is additionally investing in studying and developing traditional Chinese medicine. Some of the largest research grants in the health-sciences field in China are currently being given by the Ministry of Science and Technology and other public funders to university–hospital collaborations for translational research in service of these goals, Lyu says.
In 2022, construction also began in Shanghai on the first of a nationwide network of hospitals that are intended to act as comprehensive national medical centres. Some of the people who work there are likely to be expat Chinese scientists who are being attracted back from the United States or other Western countries, Dong says, through more than 100 talent-recruitment programmes operating at the national, provincial and city level, and also by high salaries offered by Chinese universities and research institutions. Many of these experts have left corporate positions abroad or vacated tenured roles at top-tier American universities, Dong says, including Harvard and MIT.
China’s provinces and cities can also introduce their own targeted priorities, and in both Beijing and Shanghai, that includes biosciences, says Glen Noble, the founder and director of Noble Endeavours, a London-based consultancy focused on research and academia in the United Kingdom, European Union and China. Both cities have “huge amounts of leeway and resources” to implement things such as tax breaks, subsidies, talent-recruiting programmes, science parks and research funding, Noble says. This allows health-science researchers to tap into support from multiple initiatives and levels of government.
Collaborations in China between academia and industry have also started “booming” over the past year or so, Lyu says, and grants are specifically set up to encourage and enable these partnerships. China still has issues regarding intellectual property (IP) protections that draw criticism from the United States and the West, Střelcová adds, including concerns over IP theft and economic espionage. On the other hand, she continues, over the past decade or so, China has “improved and professionalized” the IP protection landscape compared with the past, especially through its regulatory framework and enforcement. “The caveat is that the intent is not confined to intellectual-property rights protection itself, but rather to the overall desire to strengthen national security and increase the country’s competitiveness,” Střelcová says. Regardless of the intent, though, this is a boon for innovators, Dong says, because of the size of China’s market.
Regardless of whether Chinese cities do overtake locations in the United States and other Western cities such as London in health-sciences research, Noble hopes that researchers around the world will be able to maintain strong international collaborations despite political tensions. Currently, however, policies around research security in the West “are primarily calibrated around preventing China accessing Western technology — as if China wasn’t already a scientific power in its own right, across many disciplines”, he says. “Increasingly, we need the science happening in China to be disseminated back to us in the West.”
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How ‘Made in China 2025’ helped supercharge scientific development in China’s cities
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A worker tests a charging pile at a workshop for a new energy company in Hefei, China.Credit: NurPhoto/Getty
One of the fastest growing cities in China, Hefei is catching up to Beijing and Shanghai as a buzzing centre of innovation. In just a few years, the city has replaced vast swathes of farmland with sprawling technology parks and scientific facilities, and much of its high-tech industry has moved away from sourcing equipment and components from overseas to producing them in-house. In the past decade alone, Hefei has managed to double its economic output to around US$140 billion.
Key to Hefei’s success is Made in China (MIC2025), a national policy launched in 2015 and due to end next year. The overarching goal of MIC2025 is to move China away from being the ‘world’s factory’ for cheap, low-value products and transform it into a manufacturer of high-tech, innovative goods and services in areas such as information technology, ocean engineering and aerospace equipment. As part of this initiative, China set itself the goal of becoming 70% self-sufficient across key industries. Official numbers on MIC2025’s progress are scarce, but there are hints that many of its targets have been met, particularly in renewable energy and biopharmaceuticals, says Julian Mueller, a researcher who focuses on supply-chain management at the University of Erlangen-Nuremberg in Germany. “I would say China has succeeded,” he says.
Nature Index 2024 Science cities
The engines driving China’s success are its cities, many of which have become specialists in strategic areas. Hefei, for example, has become the country’s electric-vehicle capital, Shanghai is a hotspot for biopharmaceuticals, and Urumqi is home to the world’s biggest solar farm. But despite China’s rapid progress towards achieving its MIC2025 goals, many hurdles remain.
The policy’s focus on self-reliance and elevating China to a more competitive position in the global technology market has triggered a backlash from other countries, most notably the United States, which in 2018 launched a trade war against China in the form of increased tariffs, sanctions and more recently, an artificial intelligence (AI) chip ban. Such restrictions could make it difficult for China to meet its MIC2025 targets in areas of relative weakness, including semiconductors, high-precision machinery and new materials, says Marina Zhang, an innovation researcher who specializes in China at the University of Technology Sydney, Australia. Some researchers also worry that China’s focus on areas that align with the government’s priorities might stifle creativity among scientists.
A sustainable future
China’s universities have been fundamental to achieving its MIC2025 goals, because they supply the talent and expertise that its high-tech industries need, says Zhang. Government initiatives to attract foreign researchers and entice Chinese researchers to return home are helping to boost China’s performance in innovation areas, as are incentives for universities and research institutes to apply for patents and establish more industry collaborations. Today, China leads the world in patent application numbers, picking up four times more AI-related patents than the United States in 2022.
China’s growth in new energy vehicle (NEV) production — a key goal of MIC2025 — shows how rapidly the country can dominate a market. By next year, China aims to have domestically produced NEVs (a category that includes any electrified vehicle, including hybrid, battery-electric and hydrogen fuel-cell vehicles) account for more than 80% of the domestic market. It’s also pushing for NEV manufacturers to develop and manufacture all of their components in-house. Few cities have responded to this challenge quite like Hefei. The city’s government has established innovation platforms and incubators, such as the Hefei Innovation Industrial Park and the Hefei NEV Innovation Center, which provide funding support to start-ups companies to help them break into the market. The government’s policies also encourage collaboration between enterprises and universities or research institutes. Such partnerships, particularly with the University of Science and Technology of China, one of the city’s leading universities, have played a pivotal role in transforming scientific achievements into technological innovations, says Zhang. “It’s a city-centred, regional-based innovation ecosystem,” she says.
In the first half of 2024, Hefei produced more than 500,000 NEVs, a jump of around 67% on the previous year. Many vehicle companies have received generous backing from the Hefei government; in 2020, it poured almost $1 billion of investment funds into Chinese car manufacturer NIO, and in 2021, it took just 23 days to negotiate with BYD, another of the country’s major vehicle companies, over the establishment of an expansive factory in the city.
China accounts for more than half of all new electric cars sold globally, but geopolitical tensions are threatening to undermine its success. This year, the US government imposed a 100% tariff on Chinese electric vehicle imports, which was closely followed by a 37.6% tariff from the European Union, raising concerns that China now has an overcapacity in the space.
Aligning with China’s broader goals of reducing its reliance on fossil fuels, MIC2025 is pushing for renewable energy equipment and energy-storage devices to account for more than 80% of the Chinese market. Rapid progress has been made in photovoltaic solar cell production, in particular. At the time of MIC2025’s launch, China relied on other countries for key materials and essential components of photovoltaic cells. Today, it’s responsible for 80% of the world’s solar cell exports and hosts the 10 leading suppliers of solar-cell manufacturing equipment globally. China is also now home to the world’s largest solar farm, by capacity: the Urumqi Solar Farm, in the northwestern city of Urumqi. With more than 5 million photovoltaic panels spread over an area roughly the size of New York City, the facility can generate enough power to keep a small country running for a year.
A biopharma innovation machine
Biopharmaceuticals and medical devices are another focus area for MIC2025. Goals include boosting the number of China-developed drugs that are registered in other countries and bringing as many as 30 new medications to market by 2025. Helen Chen, who heads life sciences and health care at LEK Consulting, a global strategy and management consulting firm in Shanghai, says MIC2025’s biopharmaceutical targets have been “substantially met”, with many Chinese-developed assets being picked up by international companies and life-science venture-capital firms. “The biopharma sector in China is clearly moving towards innovation,” says Chen.
Robots work on the production line of a factory producing flat glass for solar panels in Urumqi, in northwest China’s Xinjiang Uygur Autonomous Region.Credit: Feature China/Getty
Among the cities, Beijing, Zhejiang and Chengdu are big players in biomedical research, but Shanghai is a standout. A popular destination for both local and international scientists, Shanghai has more than 3,000 life-science companies that employ at least 270,000 people, according to LEK research. One-quarter of China’s life-sciences and medicine researchers work in Shanghai, which in 2022 invested $15 billion in R&D. The ingredients for Shanghai’s success are a mix of infrastructure and financial incentives from the local commerce bureau, says Chen, including free lease of land for companies, tax rebates for international talent and support for equipment purchase. Zhangjiang Science City, an area of Shanghai that covers almost 100 square kilometres, hosts more than 400 biomedicine companies, 100 R&D institutes and 40 contract research organizations and is the site of the regional headquarters of several of the world’s leading pharmaceutical companies, including Pfizer, AstraZeneca and Roche.
In August, the Shanghai government announced that it will offer around $4 billion in subsidies for biomedicine companies that are conducting clinical trials. Soon after, it released a set of guidelines to accelerate Shanghai’s clinical research system and biopharmaceutical industry. The goals include establishing up to four clinical-research platforms by 2025 and forging collaborative links across medical institutions, universities and research institutes. The aim is speed up the translation of fundamental research, particularly in areas such as genomics, synthetic biology and gene editing.
Renewable energy factories
Although MIC2025 has brought certain industries to the forefront of technological innovation, China has bottlenecks in some important areas, such as semiconductors, says Zhang. The semiconductor industry is highly complex and involves an extensive web of collaborations between research institutions and industry, and among various industry sectors, she says. Even before the US-led chip ban came into effect, China lacked a robust local market for homegrown semiconductors, along with the research to support them. Chinese firms and research institutes have intensified their collaborative efforts in semiconductor development since the US export controls, which restricted access to imported technologies and products, but China still lags behind others owing to a talent gap and a lack of access to key materials and tools, says Zhang.
Several Chinese universities have answered the call to build the country’s semiconductor capabilities and workforce. In 2021, a dozen universities — including heavyweights Tsinghua University and Peking University in Beijing — established schools dedicated to integrated circuits. But there is still a way to go before these efforts will bear enough fruit to bring China up to speed with other countries, says Erik Baark, a social scientist who studies China’s innovation policies at the Max Planck Institute for the History of Science in Berlin.
“Developing talent in such a sector takes some time, maybe even a decade,” he says.
China is also slower to adopt the use of high-end machine tools, which are key to innovative manufacturing. Although the country’s advanced machine tool industry has made strides over the past decade, the domestic sector still uses less sophisticated equipment, trailing behind other countries by around 15 years, according to a 2020 study produced by the Chinese Academy of Engineering. Another report published in September by the Information Technology and Innovation Foundation, a non-profit policy think tank in Washington DC, noted that China still imports more than 90% of its machine tool components. Foreign companies also make up around 70% of China’s medium-end machine tool industry.
Questions have been raised over MIC2025’s overall effect on innovation. A 2024 study that examined how MIC2025 has impacted Chinese companies that were targeted by the policy found that it has had little effect on their productivity and patents, despite these firms increasing their R&D efforts and receiving more innovation subsidies. China’s top-down approach may also hinder researchers’ ability to innovate because they are more intent on working on government priorities over their own basic research interests, says Baark. “We should respect the need for autonomy and advanced creativity in the work of academics,” he says. “If so, they are likely to be able to contribute even more to China’s future.”
Finding a balance between scientific breakthroughs and innovation with a practical outcome will require restructuring incentives so they encourage both, adds Zhang. This would involve developing more clear-cut definitions for intellectual-property ownership in academic–industry partnerships
The end of MIC2025 is fast-approaching, and China has its sights set on becoming a leading innovative nation by 2035, says Baark. The country’s 15th Five-Year Plan, which will be implemented in 2026, will probably boost China’s momentum towards high-tech goals beyond MIC2025, he adds, but points out that local governments might be less eager to spend big on new initiatives owing to economic challenges, such as stagnating income from the property sector.
Zhang expects that China will continue playing to its strengths in NEVs, renewable energy and biopharmaceuticals, while also pouring more investment into semiconductors and high-precision machinery. “This may involve a greater emphasis on enhancing China’s position in global supply chains and promoting industrial upgrading and technological innovation,” she says.
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China’s regional cities are now major players in world science
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As Chinese research goes from strength to strength, it is natural that the country’s biggest and most economically developed urban areas, such as Beijing and Shanghai, would become superstar science cities; as China gets richer, more educated and more technologically sophisticated, the megacities drive further progress. What might be more surprising is that some of China’s smaller provincial capitals are becoming globally significant, also ranking among the Nature Index top 20. Nanjing (5th), Wuhan (9th), Hangzhou (13th), Hefei (15th) and Xi’an (20th) are all examples, inhabiting ranking territory similar to major global cities, such as Tokyo (10th), Paris (11th), Seoul (12th), London (14th) and Chicago (17th). Furthermore, the data indicate that these provincial cities — each anchoring regions as large and as wealthy, in relative terms, as a European country — are among those seeing the fastest-rising research output in the Nature Index. These trends reveal that as China’s government places science and innovation at the core of its economic strategy, such cities and regions are playing a key role in cultivating excellence and, as a result, a bid for sustainable, technologically driven growth.
Economic imperative
China’s emphasis on scientific progress over the past decade is not just motivated by the intrinsic value of science; rather, research and innovation are seen as upstream of economic growth, more broadly. Science mega-structures, such as the Five-hundred-meter Aperture Spherical Radio Telescope (FAST) in Guizhou province, or the Kunming Institute of Botany, housing Asia’s largest seed bank, in Yunnan, are constructed with both economic growth and scientific excellence in mind. The hope is that nationally funded institutes and research labs in faraway places can spark new industries, ideas and innovations that are then embedded in those regions. Huge regional investments based on emerging technologies, such as a 3.5-gigawatt solar panel field in Xinjiang, should be seen as part of the same process.
Nature Index 2024 Science cities
This approach of sparking economic growth through regional investment can be especially important at times of instability. As the global financial crisis hit China around 2008, the country invested heavily in infrastructure such as the high-speed rail network that now crisscrosses the country. As China experiences another bout of economic indigestion — by trying to move away from an economy driven by the value of real estate towards one driven by sustainable growth — the country’s leadership has decided that investing in science and technology is central to creating new forms of urban development. Indeed, as China faces an unequal, two-tier economy, with coastal provinces having incomes much higher than interior provinces, it has become politically essential to balance the country’s wealth, lest they experience some Chinese version of the populism that is gripping many Western societies. China’s leaders are well aware of the political problems that can be caused by regional and class inequality, and by assigning key industries of the future, such as green energy or electric cars, to different cities and provinces, science funding becomes a tool of much broader objectives of social equality and stability and the upskilling of a society.
Star student
When China’s president, Xi Jinping, pointed earlier this year to the importance of new technologies to upgrade industry in the country and promote green transformation, he might have been thinking about places such as Hefei. The capital of Anhui province, it scores higher for natural sciences in the Nature Index Science Cities list than London, Los Angeles or Chicago, and is home to the University of Science and Technology of China (USTC), the 5th ranked institution globally in the Nature Index in 2023. Hefei is the star student of China’s regional growth strategy; its rich network of scientific institutions and science graduates gave it the fertile soil for a world-beating industry — electric vehicles (EVs) — to grow. Breakthroughs in EV technology — such as a low-cost solid-state battery developed at USTC that might be a game-changer for the EV market — are part of an extended supply chain that stretches from scientific institutes on one end, through a sophisticated realm of factories and workshops, en route to a huge consumer market. Taken collectively, this makes for a new vision of China’s economy, one with scientific research at its genesis. There will be no shortage of cheerleaders for such a model in the national government, either. Zheng Shanjie, a former party secretary in Anhui province, is now head of the National Development and Reform Commission, China’s main economic planning body.
As other provincial leaders try to make their own cities the next success story, they don’t necessarily need to follow Hefei’s model; there are various ways to connect science with economic growth. Often, the local branch of the Chinese Academy of Sciences (CAS) — the Beijing-headquartered mega-institute that is the global leader in the Nature Index — is a good place to start. CAS has dozens of regional centres throughout the country, such as the Institute of Botany in Kunming. These offshoot institutes sometimes respond to scientific practicalities: Kunming is located in a semi-tropical and extremely biodiverse region, for example. Second, leaders might attempt to establish some of the tie-ins with international investors and multinational corporations that have helped Shanghai’s biotech industry grow; the city hosts large research labs for pharmaceutical giants such as GSK and Pfizer, and a district for start-up businesses in Zhangjiang, where young innovators can get land, office space and tax breaks. Finally, they can coordinate so that each province specializes in targeting a different area of China’s domestic consumer market, in the way Shenzhen’s homegrown tech companies such as Huawei and DJI have done, for instance.
Between these powers of the state, international investment and the vast base of consumers that China has to offer, scientific breakthroughs can be rapidly herded from the laboratory to market to have maximum economic impact. So, in the years to come, it will be no surprise to see other Chinese cities that are relatively unheard of in the West leap up the Nature Index Science Cities rankings. The more unlikely the place, the more China’s leadership will see a need to put it on the map; and in today’s China, science is the royal road to economic and political importance.
This article is part of Nature Index 2024 Science cities, a supplement produced with financial support from the Beijing Municipal Science & Technology Commission, Administrative Commission of Zhongguancun Science Park. Nature maintains full independence in all editorial decisions related to the content. For more information about Nature Index, see the homepage.
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‘Educational’ apps are worth billions. We need to make sure they work
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The past year has seen bans on the use of smartphones in schools in some 60 countries, including the Netherlands, France and the United States. The restrictions come amid spreading worry that social media can harm children’s mental health. It’s a valid concern. But in the heat of the discussion, other technologies used by children — such as educational technology (edtech) — are flying under the radar.
As director of the International Centre for EdTech Impact, I think that’s a mistake. Edtech has the power to improve children’s learning — but it needs scrutiny.
Scientists are building giant ‘evidence banks’ to create policies that actually work
The edtech industry is booming and is projected to be worth a staggering US$600 billion globally by 2027. About 500,000 educational apps are available, ranging from literacy apps to mathematical games. In the United States, each school district used about 2,700 such tools last year. And many philanthropic funds are helping low- and middle-income countries (LMICs) to distribute edtech in schools.
I’ve seen how educational apps have helped children to learn — for instance, they’ve boosted maths and reading skills in Malawi, reducing gender disparities in classrooms. And they are sorely needed. Around 70% of ten-year-olds in LMICs struggle to read and comprehend simple texts. And as many as 70% of nine- and ten-year-olds in low-income areas of the United States cannot read at a basic level.
But, with little regulation and few enforced standards, I worry that governments, schools and families worldwide are collectively spending huge sums of money on ineffective apps that serve only to teach children to play manipulative games. I want researchers, developers and investors to come together to improve the quality of educational tools.
A 2023 report by the United Nations organization UNESCO reveals that there are few robust data on the value of edtech tools (see go.nature.com/4hf8f7d). Apps are seldom vetted or validated by researchers. And companies’ own product analyses often focus on time spent on screens, not on how apps address educational gaps.
Governments should stipulate that apps cannot be sold as ‘educational’ unless rigorous research has demonstrated that they improve children’s learning and well-being. National certification schemes based on independent research and catalogues of recommended resources would help teachers to decide which apps to buy.
The great rewiring: is social media really behind an epidemic of teenage mental illness?
Collaboration is crucial. Simply relying on regulations would empower a few big players who have the financial capabilities to follow the rules. A collaborative approach is more likely to focus on children and to spur innovation among start-up firms and local entrepreneurs.
Superficial, unpaid advisory roles are a thing of the past — companies need committed specialists to design, evaluate and innovate effectively. Policymakers should thus provide funding to encourage partnerships. Finland and some US universities, for instance, are compensating scientists for spending time on researching educational tools through university-based edtech accelerators. A European Union-funded project to bridge edtech academia and industry is exploring how scholars, through secondments and mentoring, can spur innovative studies.
Incentives are also needed to improve data availability. Scientists need raw data about existing apps; companies collect this information but often keep it private. A shared repository to which both scholars and firms can contribute has long been a dream for edtech researchers. The Tools Competition 2025 — an international contest for edtech innovation run by a consortium of organizations — will include a prize pot for technologies that use open data sets. It’s a good first step, but more such initiatives are needed.
Together, researchers and developers must define the educational outcomes that each app aims to support — and determine how to measure them. Around 30 educational apps are launched each month, and some 65 frameworks can be used to assess their effectiveness. Scholars struggle to compare apps that have been evaluated in distinct ways, and teachers and families can find the mass of disparate data and methods confusing.
Ready or not, AI is coming to science education — and students have opinions
Working out how to measure outcomes will be no easy task. Consider a seemingly simple app for reading stories. Such an app will influence language development, reading motivation, critical thinking and more. These aspects of learning will all be experienced differently by native and non-native speakers, people with learning difficulties and so on. Randomized controlled trials — considered by some to be the gold standard for assessing edtech — need to be supplemented with diverse measures of success that take this variability into account. Efforts could involve running focus groups with teachers and children, ongoing pedagogical evaluations, or tracking families over time to assess reading motivation, for example.
Taking steps towards collaboration will ensure that more tools are grounded in science. A bigger challenge will be to convince businesses that research is a valuable learning process, not a service to confirm positive impact and boost sales.
With well-designed tools, edtech could improve the prospects of many children. If nothing is done, badly made tools will reinforce educational gaps by disrupting learning, misrepresenting student performance and promoting investments in ‘snake oil’, rather than in education.
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What harmful microbes are lurking in the world’s 7 billion tonnes of plastic waste?
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In June, more than 2,000 volunteers participated in the 2024 Global Ocean Cleanup campaign and netted nearly 40 tonnes of plastic debris from just some 80 kilometres of ocean and coasts across the world, including sites from Vietnam to California. Although representing one week’s hard work for the volunteers, such initiatives are a drop in the ocean of plastic waste that is generated each year — about 400 million tonnes, equivalent to the weight of all adult humans currently on Earth.
A plethora of projects and policies, both national and international, aim to tackle plastic pollution. In 2019, for example, the Association of Southeast Asian Nations set up a Framework of Action to reduce marine debris. The European Plastics Pact, in place since 2021, brings 15 governments and 82 private businesses together to reduce, reuse and recycle plastics as much as possible. And the legally binding UN Global Plastics Treaty, currently under discussion through the Intergovernmental Negotiating Committee on Plastic Pollution, should be finalized by the end of the year.
Yet one aspect is often overlooked: the communities of microbes hosted by plastic debris, which form the ‘plastisphere’1,2. Initial studies suggest that this human-made habitat serves as a widespread, mobile reservoir of various microbial hazards such as pathogens3–5 — yet little else is known.
As scientists working on the environmental and health implications of plastic pollution, we urge both the public and private sectors to map plastisphere microbiomes, to understand how they interact with existing ecosystems, assess the risk they pose to humans and ecosystems, and develop mitigation strategies.
What we know
The ubiquity of plastic waste means that the plastisphere covers vast expanses of water and land. More than 7 billion tonnes of plastic waste have been generated globally so far, about 80% of which has accumulated in the environment.
As even more plastic waste is generated and degrades extremely slowly, the plastisphere is expanding rapidly — an ideal place for colonization by microorganisms, which tend to attach to a surface. More than 80,000 diatoms were found in one square centimetre of the marine plastisphere6. One gram of marine plastic can harbour ten times the microbial biomass of a cubic metre of open ocean water7.
Plastics consist of, and take up, a variety of compounds that can serve as nutrients for microbes, which in turn can affect the biogeochemical cycling processes on land and in water. Microbes of the plastisphere can be an important part of the carbon and nitrogen cycles3,8,9, for example, and might drive the production of greenhouse gases, including carbon dioxide, methane and nitrous oxide.
Even remote regions such as the Himalayas contain plastic pollution.Credit: Alamy
And the plastisphere hosts a variety of pathogens, including viruses and antibiotic-resistant bacteria that affect the health of plants, animals and humans3,4,10,11. Many of these microbes are not detected in the surrounding media3. Vibrio bacteria, for example, which are normally rare in the open ocean, are widely distributed in plastispheres throughout the mid-North Atlantic Ocean1,5, where they can cause diseases in marine life, including fish, shellfish and corals, as well as in humans. Genes that can render microorganisms resistant to antibiotics are also more common in the plastisphere than in surrounding areas4,5. Within it, viruses survive longer and are more infectious10. Harmful algae such as Pseudo-nitzschia, known for producing the neurotoxin domoic acid that causes amnesic shellfish poisoning, have also been shown to thrive in the plastisphere6.
The fact that the plastisphere is composed of plastic fragments ranging in size from micrometres to several metres means that it can carry inhabiting microbiomes that enter ecosystems and the food chain in many ways. Crops such as wheat and lettuce, for example, can directly absorb submicrometre-sized plastic particles and transport them from roots to shoots12. Plastic particles with sizes larger than tens of micrometres have been found in a range of human tissues, such as the carotid artery, lung and colon tissue, and in faeces13,14. Larger fragments, around a few centimetres long, can easily be ingested by animals such as fish, turtles, birds and terrestrial herbivores.
Finally, plastic particles and their microbial residents often travel long distances, either through trade routes or in the form of waste carried by streams, rivers and wind, for example, and can skew the natural distribution of microbial species. This can accelerate the spread of pathogens and antimicrobial resistance, disturb ecosystems and prompt disease outbreaks.
Quantify effects
Metrics are needed to quantify the influence that plastisphere microbiomes have on ecosystems and their populations, and to forecast the potential risks.
Researchers should collaborate across disciplines to combine findings from monitoring efforts on the ground, from laboratory experiments and from models that simulate the transport of plastic materials.
It is crucial to harmonize sampling procedures, experimental methodologies and instrumentation to characterize the complex genetic, microbial and metabolic landscapes of the plastisphere. Some existing projects and organizations, such as the Global Microplastics Initiative (run by Adventure Scientists in Bozeman, Montana); the Ocean Cleanup in Rotterdam, the Netherlands; the 5 Gyres Institute in Santa Monica, California; and the UN Global Estuaries Monitoring Programme, should establish standards and protocols on local, regional and global scales. Sharing samples and data would help. During clean-up activities, for example, plastic samples and contamination data should be collected and shared according to standardized procedures.
Plastics carry microorganisms that can harm animals, such as Kodiak bears in Alaska. Credit: Martin Almqvist/Alamy
Researchers should aim to accurately map the location and abundance of pathogens, antibiotic-resistant microbes and genes associated with plastispheres, and quantify their influence on climate change through the emission of greenhouse gases, for example.
It is also important to map the trajectory, transport dynamics and fate of plastic debris carrying microbiomes across ecosystems, regions and countries, such as from landfills to rivers and oceans, and from waste-exporting countries to waste-importing ones. Studying where microorganisms, especially pathogens, come from by analysing genetic elements or environmental factors can be useful. And modelling can help to track the ecological perturbations resulting from the increasing concentration, and transport, of plastispheres in ecosystems.
Redefine plastic pollution
Currently, risk assessments associated with plastic pollution mostly involve effects arising from the physical and chemical aspects of plastics — their size, shape, polymer type and additives. Turtles and seals get entangled in large debris; smaller fragments can block the digestive systems of fish or seabirds. Harmful compounds such as bisphenol A and phthalates also leach out of plastics.
Now, the microbial risks they pose must be considered, too. We propose four priorities for risk assessments.
Identify hotspots. Locations such as farms, urban rivers and coastal areas are key sources and sinks of plastic waste, and have intensive interactions with humans and food-safety concerns.
Protect vulnerable sites. Aquaculture zones, wild fisheries, nature reserves, wildlife sanctuaries, coral reefs and wetlands have crucial roles in maintaining biodiversity, regulating climate factors and providing food. They are also highly sensitive to pollution and microbial invasion.
Target transport. Regions and entities where plastics transit and accumulate — such as estuaries, harbours, wastewater treatment plants and vessels engaged in long-range transport — also need targeted risk assessments.
Focus on the food chain. Microplastics build up in foods ranging from leafy vegetables to seafood, directly threatening human health.
Sustain funding
Organizations such as the United Nations Environment Programme (UNEP), the Global Environment Facility in Washington DC, the Belmont Forum in Montevideo, Uruguay, and the World Bank should initiate funding programmes to support large-scale surveillance and assessment efforts.
Studies that track the flow of plastics and assess their health risks should focus on countries in the global south. They often need better waste-treatment capacity and public health safeguards — and often have to deal with waste exports from the global north, including Germany and the United Kingdom.
Relevant research funding bodies, such as the National Natural Science Foundation of China, the US Environmental Protection Agency and Horizon Europe, should establish collaborative research actions to co-finance projects involving scientists from different geographical regions.
Establish expert panels
Science-policy bodies must act, too. The Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention, for example, was created in 2022 under a UNEP mandate to bridge the gap between science and policymaking, and to address global issues related to chemical waste and pollution. It should have a branch that focuses specifically on plastic pollution and risks from plastispheres. Such a centralized approach might help to establish standards, support research and track outcomes that are relevant to policy.
Adjust management strategies
Environmental policymakers and regulators should prioritize plastisphere management and control for key regions that are identified as at-risk by researchers. It is crucial to mitigate the transport of microbes through global trade networks for plastic waste. Collaborations between the UNEP, the World Trade Organization, the teams involved in relevant UN Sustainable Development Goals, the Basel Convention’s Global Plastic Waste Partnership and local governments must be put in place to continue reducing trade routes. All countries must also work to diminish the production of single-use plastics and to innovate eco-friendly alternatives. Promoting a focus on the entire life cycle of plastics and shifting from a linear model (take–make–waste) to a circular economy (in which plastics are reused, repurposed, recycled, composted or biodegraded) will help significantly.
Protect people
With talks on the UN global plastics treaty under way, we urge the Intergovernmental Negotiating Committee on Plastic Pollution to comprehensively address the environmental and health risks of plastic pollution.
For populations at high risk of exposure, protective measures against pathogens and antimicrobial resistance are paramount. Environmental and health authorities should expand existing food-safety programmes — which already monitor contaminants such as heavy metals, pesticides and bacterial pathogens — to include microplastics and communicate these potential risks to consumers. For people working as waste pickers, in landfill sites and in the import and export of plastic waste, employers should provide customized protective gear, wage supplements and regular health screenings.
An international not-for-profit forum on plastic pollution should be established by scientists and expert panels to facilitate the exchange of research findings and prompt collaborations among scientists, policymakers, private stakeholders and the public. Organizations that can serve as a blueprint exist in different fields — the World Economic Forum in Cologny, Switzerland, and the Global Water Partnership in Stockholm, for example.
Finally, science communicators and the media must keep the public informed of the existing risks and any mitigation actions taken by public and private entities.
A unified global strategy is needed to tackle the microbial risks associated with the plastisphere; the UN negotiations around the plastics treaty can spur concrete action.
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Artificial intelligence laws in the US states are feeling the weight of corporate lobbying
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The adoption of the Artificial Intelligence (AI) Act in the European Union (EU) this year has triggered speculation about the potential for a ‘Brussels effect’: when EU regulation has a global impact as companies adopt the rules to make it easier to operate internationally, or new laws elsewhere are based on the EU’s approach. The ways in which the General Data Protection Regulation (GDPR) — the EU’s rules on data privacy — influenced state-level legislation and corporate self-governance in the United States is a prime example of how this can happen, particularly when federal legislation is stalled and states take the lead, which is where US AI governance is today.
So far, there is limited evidence that states are following the EU’s lead when drafting their own AI legislation. There is strong evidence of lobbying of state legislators by the tech industry, which does not seem keen on adopting the EU’s rules, instead pressing for less stringent legislation that minimizes compliance costs but which, ultimately, is less protective of individuals. Two enacted bills in Colorado and Utah and two draft bills in Oklahoma and Connecticut, among others, illustrate this.
Nature Index 2024 Artificial intelligence
A major difference between the state bills and the AI Act is their scope. The AI Act takes a sweeping approach aimed at protecting fundamental rights and establishes a risk-based system, where some uses of AI, such as the ‘social scoring’ of people based on factors such as their family ties or education, are prohibited. High-risk AI applications, such as those used in law enforcement, are subject to the most stringent requirements, and lower-risk systems have fewer or no obligations.
In contrast, the state bills are narrower. The Colorado legislation directly drew on the Connecticut bill, and both include a risk-based framework, but of a more limited scope than the AI Act. The framework covers similar areas — including education, employment and government services — but only systems that make ‘consequential decisions’ impacting consumer access to those services are deemed ‘high risk’, and there are no bans on specific AI use cases. (The Connecticut bill would ban the dissemination of political deepfakes and non-consensual explicit deepfakes, for example, but not their creation.) Additionally, definitions of AI vary between the US bills and the AI Act.
Although there is overlap between the Connecticut and Colorado bills and the AI Act in terms of the documentation they require companies to create when developing high-risk AI systems, the two state bills bear a much stronger resemblance to a model AI bill created by US software company Workday, which develops systems for workforce and finance management. The Workday document, which was shared in an article by cybersecurity news platform The Record in March, is structured around the obligations of AI developers and deployers, and regulates systems used in consequential decisions, just like the Colorado and Connecticut bills. Indeed, the documentation that those bills say AI developers should produce is similar in scope and wording to an impact assessment that the Workday draft bill suggests should be produced alongside proposals for AI systems. The Workday document also contains language similar to bills introduced in California, Illinois, New York, Rhode Island and Washington. A spokesperson for Workday says it has been transparent about playing “a constructive role in advancing workable policies that strike a balance between protecting consumers and driving innovation”, including “providing input in the form of technical language” informed by “policy conversations with lawmakers” globally.
The wider tech industry’s power, however, can extend beyond this kind of passive inspiration. The Connecticut draft bill did contain a section on generative AI inspired by part of the AI Act, but it was removed after concerted lobbying from industry. And although the bill then received support from some big tech companies, it is still in limbo. Industry associations maintain that the bill would stifle innovation, causing the governor of Connecticut, Ned Lamont, to threaten to veto it. Its progress is frozen, as are many of the other more comprehensive AI bills being considered by various states. The Colorado bill is expected to be altered to avoid hampering innovation before it takes effect.
One explanation for the lack of a Brussels effect and a strong ‘big-tech effect’ on state laws is that, compared with discussions around data-protection measures over GDPR, the legislative debate on AI is more advanced at the US federal level. This includes a policy roadmap from the Senate, and active input from industry players and lobbyists. Another explanation is the hesitancy embodied by Governor Lamont. In the absence of unified federal laws, states fear that strong legislation would cause a local tech exodus to states with weaker regulations, a risk less pronounced in data-protection legislation.
For these reasons, lobbying groups claim to prefer national, unified AI regulation over state-by-state fragmentation, a line that has been parroted by big tech companies in public. But in private, some advocate for light-touch, voluntary rules all round, showing their dislike of both state and national AI legislation. If neither kind of regulation emerges, AI companies will have preserved the status quo: a bet that two divergent regulatory environments in the EU and United States — with a light-touch regime in the latter — favour them more than the benefits of a harmonized, yet heavily regulated, system.
As with the GDPR, there might be some cases where compliance with EU rules makes business sense for US firms, but it would mean the United States would be left overall less regulated, meaning that individuals will be less protected from AI abuses. Although Brussels faced its fair share of lobbying and compromises, the core of the AI Act remained intact. We will see if US state laws stay the course.
Competing Interests
The author declares no competing interests.
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Rage against machine learning driven by profit
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Illustration: Neil Webb
The current boom in artificial intelligence (AI) would probably not exist were it not for work that began in academia. Many of the techniques that are now being used on an everyday basis, such as machine learning and natural-language processing, are underpinned by academic work into artificial neural networks that dates back decades. But it is true to say that much of the latest cutting-edge and high-profile research in AI is being done not in university labs, but behind the closed doors of private companies.
“We’re increasingly looking at a situation where top-notch AI research is done primarily within the research labs of a rather small number of mostly US-based companies,” says Holger Hoos, an AI researcher at RWTH Aachen University in Germany.
Nature Index 2024 Artificial intelligence
Much of this work is not published in leading peer-reviewed scientific journals. In 2023, research by corporations accounted for only 3.84% of the United States’ total Nature Index output in AI. But data from other sources show the increasingly influential role that companies play in research. In a paper published in Science1 last year, Nur Ahmed, who studies innovation and AI at the Massachusetts Institute of Technology in Cambridge, and his colleagues, found that research articles with one or more industry co-author grew from 22% of the presentations at leading AI conferences in 2000 to 38% in 2020. Industry’s share of the biggest, and therefore most capable, AI models went from 11% in 2010 to 96% in 2021. And on a set of 20 benchmarks used to evaluate the performance of AI models — such as their capabilities in image recognition, sentiment analysis and machine translation — industry alone, or in collaboration with universities, had the leading model 62% of the time before 2017, a share that has grown to 91% since 2020. “Industry is increasingly dominating the field,” says Ahmed.
That growing dominance of the outputs of AI research is largely a result of industry’s massive advantage in funding. In 2021, US government agencies (excluding the Department of Defense) spent US$1.5 billion on AI research and development, and the European Commission spent €1 billion (US$1.1 billion). Industry worldwide spent more than US$340 billion.
This outlay has given industry a stranglehold on the three most important inputs: computing power, large data sets and talent, says Ahmed.
Companies have access to much greater computing power than academic institutions, including the ability to buy the graphics-processing units (the most common chips used in AI) they need, or even design and manufacture their own. This allows firms to create much larger and more complex models than their academic counterparts. In 2021, industry AI models were 29 times bigger, on average, than academic models.
Companies also have access to much larger data sets with which to train those models because their commercial platforms naturally produce that data as users interact with them. “When it comes to training state-of-the-art large language models for natural-language processing, academia is going to be hard-pressed to keep up,” says Fabian Theis, a computational biologist at Helmholtz Munich, in Germany.
Lucrative salaries, and the promise of being able to work on the cutting edge of AI technology allows companies to snap up much of the top talent from universities, while hiring inside academic computer-science departments has remained largely flat.
“Industry hiring is much higher than the overall growth of computer science research faculty,” says Ahmed. In 2004, just 21% of AI PhDs at North American universities went to work in industry, but by 2020, that number was almost 70%. This growing imbalance worries some in academia. The biggest concern is that companies are by necessity focused on profits, which influences not only the kinds of AI products they seek to develop, but also the research questions they ask in the first place. “If developments of major consequence for society are driven primarily by short-term commercial interests, we have a problem,” says Hoos.
Academic AI research is needed to contribute to the development of a body of knowledge that did not originate from a commercial imperative, says Shannon Vallor, who studies the ethics of AI at the University of Edinburgh, UK. “Academia is the only place where researchers still have the ability to work without an obvious roadmap to profit,” she says.
Academics can provide a critical and dispassionate view on AI and be an independent source of information on what works and what doesn’t, as well as identifying the potential harms of new technologies and how to mitigate them, says Vallor. Academics can also help to align AI research with what is in the public interest. “At the moment, there is a deficit of AI applications focused on the kinds of problems we most need to address,” says Vallor — including challenges such as climate change, health-care needs, and the social and democratic stresses that have been amplified by digital technologies.
Despite the importance of engaging with the ethical and social consequences of AI, many scholars are concerned that, because of the incentive structures in place in industry, firms are underinvesting in research into the responsible use of AI and failing to incorporate the lessons from such research. An analysis2 by Ahmed and other colleagues confirms that suspicion. Leading AI firms have significantly lower output for responsible-AI research compared with conventional AI papers. The responsible-AI research they do perform is also narrower in scope and lacks diversity in the topics addressed.
“Major AI companies demonstrate minimal public engagement in responsible-AI research, indicating that speed is prioritized over safety in AI development,” says Ahmed. They also found a disconnect between responsible-AI research and its practical implementation. “The AI products reaching the market show limited influence from responsible-AI research findings,” says Ahmed.
Companies had invested more heavily in responsible-AI research in the past, says Vallor, but that interest waned with the boom in generative AI, prompting a “race to the bottom” to capitalize on the market. “The knowledge about responsible AI is all there, the problem is that large AI companies don’t have incentives to apply it,” she says. “But we could change the incentives.”
Companies that develop and deploy AI responsibly could face a lighter tax burden, she suggests. “Those that don’t want to adopt responsible-AI standards should pay to compensate the public who they endanger and whose livelihoods are being sacrificed,” says Vallor.
As we wait for new regulations, academia has an important role to play in keeping an eye on its industry colleagues. Academic studies that identify and offer solutions for issues such as the inherent biases built into AI systems are needed to help the field develop in a more responsible direction. “There need to be checks and balances and they cannot be achieved by regulation alone, there also needs to be scrutiny by independent experts,” says Hoos. “It’s crucial that similar expertise to that of industry exists at publicly funded institutions, like universities.”
For that scrutiny to happen, however, it is imperative that academics have open access to the technology and code that underpins commercial AI models. “Nobody, not even the best experts, can just look at a complex neural network and figure out exactly how it works,” says Hoos. “We know very little about the capabilities and limitations of these systems, so it is absolutely essential that we know as much as possible about how they are created.”
Theis says many companies are making moves towards open access for their AI models, because they want more people to be able to work with them. “It’s a core interest for industry to have people trained on their tools,” he says. Meta, the parent company of Facebook, for example, has been pushing for more open models because it wants to better compete with the likes of OpenAI and Google. Giving people access to its models will allow an inflow of new, creative ideas, says Daniel Acuña, a computer scientist at the University of Colorado Boulder.
But it is unrealistic to expect that companies will give away all of their “secret sauce”, says Hoos — another reason it is important that academia retains the capability, in both technology and talent, to keep up with industry developments.
Mutual benefits
Not everyone is overly concerned with industry dominating parts of AI development, as they expect academics and companies to find their way to an equilibrium. “It needs to be clear that there are benefits for both sides” of industry and academia being heavily involved in AI research, says Theis.
Companies benefit from the freedom that academics have to pursue unexpected or high-risk research directions, which could result in novel breakthroughs that solve some of the problems their products face. “Some of the limits of the current AI tools may not be overcome without a radically different approach,” says Vallor. And that approach is more likely to be found by researchers who are less concerned with whether their ideas can be turned into a successful product.
Academics, for their part, although they are free to pursue curiosity-driven projects, can also gain knowledge and support from industry to help them solve interesting and tricky problems. “It’s very common for trainees from my and other labs to go to big tech, or pharma, to learn about the industry experience,” says Theis. “There’s actually a back and forth and diffusion between the two.”
Acuña and his colleagues have studied the different approaches of industry and academic researchers to AI3. They analysed papers presented at a variety of AI conferences between 1995 and 2020 to see how the composition of a research team was related to the novelty of their work, and its impact in terms of citations and models created.
They found that work by teams comprising solely of industry researchers tends to be more highly cited and to result in state-of-the-art models. Academic teams, in contrast, tend to produce higher novelty work, with their papers more likely to contain unconventional and atypical ideas. Interestingly, academic–industry collaborations tend to see similar results to industry teams, working on difficult engineering problems that attract lots of citations but losing the novelty that is the hallmark of academic projects.
This division of labour, familiar to many other fields of science, is why Acuña says he is more optimistic than some others about the future of AI research in academia. Even if academics don’t have the resources or computing power to build the biggest large language models, they have the ability to do work that is even more novel and ground-breaking. “Just go crazy,” he says. “Don’t disregard a field just because you’re in academia, you have the freedom to do whatever you want.”
Keeping pace with industry
To make the most of that freedom, however, academics will need support — most importantly in the form of funding. “A strong investment into basic research more broadly, so it is not just happening in a few eclectic places, would be useful,” says Theis.
Although governments are unlikely to be able to match the huge amounts of money being splashed around by industry, smaller, more focused investments can have outsized influence. “Canada’s AI strategy hasn’t cost a ton of money, but has been very effective,” says Hoos. The country has invested around Can$2 billion (US$1.46 billion) in AI initiatives since 2016, and in 2024 announced plans to spend another Can$2.4 billion over the next few years. Much of that money is earmarked for providing university researchers with access to the computing power they need for AI applications, to support responsible AI research and to recruit and retain top talent. This strategy has contributed to Canada’s ability to punch above its weight and remain near the top of the global leaderboard in both academic research and commercial development. It placed 7th in the world for Nature Index output in AI research in 2023, and 9th in natural sciences overall.
Recruitment programmes such as the Canada Excellence Research Chairs initiative, which offers up to Can$8 million over eight years to entice top researchers in various fields to move to, or remain in, Canada, and Germany’s Alexander von Humboldt Professorships in AI, worth €5 million over five years, have both helped to shore up AI research in the countries. Hoos himself holds one of the Humboldt professorships.
Europe is also home to several initiatives to boost academic research in AI. Theis is scientific director of Helmholtz AI, an initiative run by the Helmholtz Association of German Research Centres. The unit provides funding, computing access and consulting for research labs to help them apply AI tools to their work, such as finding new ways of using the large data sets they produce in areas such as drug discovery and climate modelling. “We want to enable researchers in AI by democratizing access to it,” says Theis. “To really accelerate those research labs.”
An even more ambitious plan has been put forward by CLAIRE, the Confederation of Laboratories for Artificial Intelligence Research in Europe, which was co-founded by Hoos in 2018. The plan is inspired by the approach in physical sciences of sharing large, expensive facilities across institutions and even countries. “Our friends the particle physicists have the right idea,” says Hoos. “They build big machines funded by public money.”
Hoos and his colleagues in CLAIRE have proposed a ‘moonshot’ plan to create a facility to provide the computing infrastructure necessary for academic scientists to keep pace with industry when it comes to AI research — a sort of CERN for AI, referring to the particle-physics laboratory near Geneva, Switzerland. They estimate that the project would require around €100 billion in funding from the European Union over six years, an amount Hoos says is quite reasonable compared with the cost of the original moonshot — NASA’s Apollo space programme, which cost about €240 billion in today’s money — and to CERN itself. Such a facility would be used to do AI research ‘out in the open’, rather than in private company labs, he says, making it fully transparent to the public. And just like the Apollo programme and CERN, it would have great benefits to both society and industry, he says.
Whatever approach is taken, keeping publicly funded, independent academic researchers at the forefront of AI progress is crucial for the safe development of the technology, says Vallor. “AI is a technology that has the potential to be very dangerous if it’s misused, if it doesn’t have the right guardrails and governance, and if it’s not developed in responsible ways,” she says. “We should be concerned about any AI ecosystem where the commercial incentives are the only ones driving the bus.”
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Japan moves to halt long-term postgraduate decline by tripling number of PhD graduates
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A PhD student works in a clean room at the University of Tokyo.Credit: Yuichi Yamazaki/AFP via Getty
In response to a decline in the number of PhD holders in Japan, the Japanese government has announced plans to not only stop the trend but reverse it, by tripling the number by 2040.
Japan is the only major economy that has recorded a dip in PhD numbers since 2000. In 2022, there were 14,382 new PhD admissions across the country — down 21% from a high of 18,232 in 2003.
As a proportion of the population, there are now fewer PhD holders in Japan than in many other leading research countries. According to Japan’s National Institute of Science and Technology Policy (NISTEP), in 2020, the country had 123 PhD graduates per million people, well below the rate of 315 per million in Germany and 313 per million in the United Kingdom for that year, and 285 per million in the United States in 2019.
A survey published by NISTEP in 2021 revealed that many doctoral students in Japan feel demoralized because of financial uncertainty, career insecurity and a lack of career progression.
To address the problem, Japan’s Ministry of Education, Culture, Sports, Science and Technology (MEXT) announced a three-pillared plan in March, with a focus on boosting career opportunities as well as institutional support and outreach for PhD students. The government is hoping to promote a cultural shift that raises the status of PhD holders in Japanese society.
“We want to create an environment that increases the number of people aiming for doctoral degrees, produces many excellent candidates, and realizes a fruitful life for each candidate and the sustainable development of society as a whole,” Mitsunari Yoshida, director of the Policy Division in MEXT’s Higher Education Bureau, told Nature Index.
Career choices
The first pillar of the initiative focuses on diversifying career choices, to ensure that doctoral candidates have a more active role in research outside academia, such as in local and central government, start-up companies and other private-sector groups.
2024 Research Leaders
This focus on industry and government roles aims to address a long-standing cultural issue in Japan, namely that having a PhD might actually limit someone’s chances of being hired.
“The greatest obstacle is the perception that once one gets a PhD in a subject, one is regarded as an expert in that particular field,” says Ken Mogi, a researcher in neuroscience at Sony Computer Science Laboratories in Tokyo, and a visiting academic at the University of Tokyo. “With that image comes the assumption that a person with a PhD is inflexible in work in the real world. For that reason, Japanese companies are typically not forthcoming in employing people with PhDs, discouraging students to consider a career with a PhD.”
MEXT plans to promote long-term, paid internships for PhD students in the private sector, as part of a broader effort to entrench internships in Japanese society.
Symbolic of this is Cooperative Education Through Research Internships, a programme introduced in 2021 with the support of 45 universities and 45 companies, including major Japanese brands. The paid internships run for at least two months, are eligible for academic credit, and aim to support doctoral researchers by matching them to companies and diversifying their career options. The ministry wants to increase the number of PhD candidates in these internships to 5,000 by 2030, up from 3,000 as of May this year.
Boosting support
As its second pillar, MEXT wants to raise the quality of graduate schools by providing extra funding and tracking their progress.
MEXT will part-fund PhD students’ living and research expenses through the Support for Pioneering Research Initiated by the Next Generation (SPRING) scheme, which is run by the Japan Science and Technology Agency to support outstanding doctoral students; and the Japan Society for the Promotion of Science’s Research Fellowship for Young Scientists programme, which supports doctoral students to pursue innovative research of their own choosing.
“Financial issues are significant in Japan, and many PhD students are struggling,” says Tomokazu Iwabuchi, a PhD student in urban planning at Kyushu University in Fukuoka.
After years of taking on part-time jobs during his master’s programme, Iwabuchi says he can now spend more time focusing on PhD research because he was chosen for the university’s Future-Creation course, which is part of the SPRING programme. Doctoral students on the programme receive ¥200,000 (US$1,360) per month to cover living expenses and language training, up to ¥850,000 yen per year in research expenses, and a 50% reduction in tuition fees.
In 2023, Iwabuchi started his own consulting business rooted in his research on urban planning and geographic information system (GIS) data. “I’m really happy to hear that the government is putting more resources into supporting PhD students,” he says. “I hope they will have more career options in the near future.”
Strengthening motivation
The third pillar is about boosting student motivation by supporting more outreach programmes. One example is the Future Doctoral Festival, an annual gathering in Tokyo at which doctoral students give presentations and take part in panel discussions related to their research. The goal of initiatives such as this is to showcase the appeal of pursuing a PhD, not just to students, but also to leading figures in the public and private sectors.
Ranny Herdiantoputri, a doctoral student in oral pathology at the Tokyo Medical and Dental University welcomes this outreach, but says more attention must be given to the mental health of prospective PhD students, especially those from overseas who might struggle with the Japanese language and feelings of isolation.
“Students can suffer from imposter syndrome and anxiety, and wonder, ‘Am I really good enough for this?’,” says Herdiantoputri. “Without proper support, outreach gatherings can make it worse.” She adds that teaching jobs at Japan’s public universities are almost impossible to get, and she plans to return to her home country, Indonesia, after her degree.
Will it work?
Koichi Sumikura, who studies science and technology policy at the National Graduate Institute for Policy Studies in Tokyo, thinks that a change in mindset among those in industry is a must. “A majority of industry managers in Japan consider that the expertise and the area of interest of PhD holders are too narrow and do not fit their business,” he says. “However, PhD holders tend to be trained for acquiring a wider field of view.”
Sumikura emphasizes the importance of PhD programmes teaching skills that are relevant to industry. “PhD holders themselves should be trained not only in a specific academic expertise, but also general scientific knowledge, communication skills and business and social literacy,” says Sumikura.
Nobuko Kobayashi, who works for EY-Parthenon, a consultancy based in Boston, Massachusetts, and who writes about innovation and human resources in the Japanese media, says she hopes that Japan will consider and support entrepreneurship opportunities for its PhD holders.
“It’s important that universities strengthen education and opportunities around entrepreneurship, so students can bridge their research with real-world applications,” says Kobayashi. One encouraging factor is the increase in start-ups in Japan. In particular, she says, the number of start-ups spun off from Japanese universities has increased every year, and these firms “also hire significantly more PhD graduates compared to other Japanese companies”.
It is to soon to tell whether the measures Japan is now undertaking can motivate its doctoral students, change hiring practices and overhaul its research culture. But Sumikura agrees that the effort is worthwhile. “It is not easy to achieve that goal, but it is worth trying,” Sumikura says.
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Nail your tech-industry interviews with these six techniques
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In my 30 years in the technology industry, including 13 years at Google, I have interviewed hundreds of candidates and filled dozens of positions. I’ve seen many mistakes and awkward moments. Now, as a technology-industry interview coach, I help prospective candidates to avoid those mistakes so they can stand out and get an offer.
These days, most technology-industry interviews are conducted by video call. They typically include an initial screening with a recruiter before moving on to a series of interviews — mostly one-on-one — with project leads, hiring managers and other individuals.
Careers advice from scientists in industry
Although every company, job and candidate is unique, I’ve identified a few techniques that apply across the industry. They’re also useful for PhD students in science and engineering and might even help in climbing the academic ladder. Here are my key tips.
Understand the process
The interview procedure can vary between companies. Ask the recruiter to share whatever they can about what will happen, such as what the series of interviews will look like, which tools you will be using — such as video conferencing, presentation or coding software — and who you will be talking to. Larger companies often provide this information as part of their initial meetings with candidates, but don’t be afraid to ask.
Be intentional
In formal interviews, many questions are open-ended, not multiple choice or yes/no. That means there are no right or wrong answers, and you must choose how to focus your response.
Careers toolkit: An early career researcher’s guide to the working world of science, from Nature Careers.
Before answering, take a moment to think and jot down some notes. Consider the larger topic of the question, and ask for clarification or propose some context or constraints in which you will respond.
For example, you could say, ‘Leading a team is a pretty broad topic. Can you elaborate a bit on what you’re after?’
This approach has three benefits: it gives you time to consider and structure your response; it forces you to focus in terms of time and content; and it signals that you recognize the complexity of the subject. Use this opportunity to demonstrate thoughtfulness and purpose in your answer.
Stick to the question
Interviewers usually have a prepared set of questions and some idea of how you might answer. There is some intentional flexibility to provide them with signals beyond the content of your response: what you focus on, your balance of breadth and depth, your structure and your time management.
Even so, there are some boundaries that you should understand and respect. Interviewers typically ask three types of question — those that ask you to relay a story or example, those that probe your skillset and those that explore hypothetical scenarios.
Match your response to what was asked. If you feel strongly that you need to diverge, get the OK from the interviewer first.
Get your story straight
Story questions typically take the form ‘Give me an example of …’ or ‘Tell me about a time when …’. For example, an interviewer could ask you to ‘Tell me about a time when you made a mistake.’
Stories are powerful and revealing, and you are likely to get several questions of this type. Interviewers are looking for your most interesting work experiences. The stories you tell about these experiences are often messy, subjective and time-consuming, with imperfect but hopefully improved outcomes.
Promotion pathways: how scientists can chart their industry career trajectory
Stories are completely yours, so you can prepare well in advance. Spend the time to outline your narrative using a method that works for you, such as STAR: the situation, or set-up and context; the task and your role; the action you took; and the result, or outcome and lessons learnt. Write the story down, highlighting the fascinating, appealing, thought-provoking or messy parts. Find a good balance of breadth and depth. Too many technical specifics, and you’ll lose the interviewer’s attention; too few details, and the story won’t seem real or engaging.
Practise your story over and over — this enables you to tell it confidently and genuinely, and ensures that the interviewer can easily remember your experience for their evaluation. Try different approaches: telling your story to yourself in the mirror, recording yourself or telling it to a trusted friend or colleague. You want to tell the story, not read it. Each story should be around three minutes long.
Show off your toolbelt
Skillset questions ask ‘How do you …’ or ‘What’s your approach to …’, for a common activity in your role. For example, ‘How do you provide direction for your trainees without doing the work for them?’
How to make the leap into industry after a PhD
Interviewers ask these questions to get a sense of the tools at your disposal — your principles, values, best practices, habits and so on. You want to demonstrate a breadth of abilities with enough detail to show that you apply them in your daily work, as opposed to merely having heard or read about them.
You can’t cover all your best practices in one answer, so identify three that are important to you, mention them briefly and then provide more details for each. Details could be anecdotes, but not full-blown stories.
This sets expectations about what you’re going to cover, shows that you have a range of skills and signals that you can communicate concisely — you know how to limit your response to a few highlights.
Think on your feet
Some companies like to see how you would handle a hypothetical situation, which is often challenging and open-ended. There are usually no solutions as such, and your goal should not be to solve the scenario. Think of this as a mini design question, testing your brainstorming approach.
How can I break into industry if my CV keeps disappearing into a black hole?
Scenario questions often take the form of, ‘Assume you have …’ or ‘How would you deal with …’.
For example: ‘Assume that leadership has decided to change direction on a project, but you disagree. How would you approach getting yourself and any team members beyond the disagreement and working towards the new direction?’
These questions are intentionally ambiguous, so first refine the scope as described above. Then, lay out a sequence of steps that you could try. You might have an ‘exactly this thing happened to me’ moment, but resist the urge to tell the story from experience — keep your response hypothetical.
This both demonstrates awareness of the complexity of the scenario and shows that you can plan in the face of ambiguity or a new situation.
Final thoughts
Think of these techniques as guidance or tools, not recipes or scripts. I recommend trying out a mixture of them and using the ones that help you to remain true to your communication style.
Collecting your stories is a great way to prepare, as is practising in a mock interview. That could be by recording yourself or rehearsing in front of peers. If you have the resources, an interview coach can provide well-calibrated questions and feedback.
Good luck, and good interviewing!
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