Is China Winning the Innovation Race?
Over the past two millennia, Chinese ingenuity has spawned some of humanity's most consequential inventions. Without gunpowder, guns, bombs, and rockets; without paper, printing, and money printed on paper; and without the compass, which enabled ships to navigate the open ocean, modern civilization might never have been born.
Today, a specter is haunting the developed world: Chinese innovation dominance. And the results have been so spectacular that the United States feels its preeminence threatened.
Yet China lapsed into cultural and technological stagnation during the Qing dynasty, just as the Scientific Revolution was transforming Europe. Western colonial incursions and a series of failed rebellions further sapped the Celestial Empire's capacity for innovation. By the mid-20th century, when the Communist triumph led to a devastating famine and years of bloody political turmoil, practically the only intellectual property China could offer for export was Mao's Little Red Book.
After Deng Xiaoping took power in 1978, launching a transition from a rigidly planned economy to a semi-capitalist one, China's factories began pumping out goods for foreign consumption. Still, originality remained a low priority. The phrase "Made in China" came to be synonymous with "cheap knockoff."
Today, however, a specter is haunting the developed world: Chinese innovation dominance. It first wafted into view in 2006, when the government announced an "indigenous innovation" campaign, dedicated to establishing China as a technology powerhouse by 2020—and a global leader by 2050—as part of its Medium- and Long-Term National Plan for Science and Technology Development. Since then, an array of initiatives have sought to unleash what pundits often call the Chinese "tech dragon," whether in individual industries, such as semiconductors or artificial intelligence, or across the board (as with the Made in China 2025 project, inaugurated in 2015). These efforts draw on a well-stocked bureaucratic arsenal: state-directed financing; strategic mergers and acquisitions; competition policies designed to boost domestic companies and hobble foreign rivals; buy-Chinese procurement policies; cash incentives for companies to file patents; subsidies for academic researchers in favored fields.
The results have been spectacular—so much so that the United States feels its preeminence threatened. Voices across the political spectrum are calling for emergency measures, including a clampdown on technology transfers, capital investment, and Chinese students' ability to study abroad. But are the fears driving such proposals justified?
"We've flipped from thinking China is incapable of anything but imitation to thinking China is about to eat our lunch," says Kaiser Kuo, host of the Sinica podcast at supchina.com, who recently returned to the U.S after 20 years in Beijing—the last six as director of international communications for the tech giant Baidu. Like some other veteran China-watchers, Kuo believes neither extreme reflects reality. "We're in as much danger now of overestimating China's innovative capacity," he warns, "as we were a few years ago of underestimating it."
A Lab and Tech-Business Bonanza
By many measures, China's innovation renaissance is mind-boggling. Spending on research and development as a percentage of gross domestic product nearly quadrupled between 1996 and 2016, from .56 percent to 2.1 percent; during the same period, spending in the United States rose by just .3 percentage points, from 2.44 to 2.79 percent of GDP. China is now second only to the U.S. in total R&D spending, accounting for 21 percent of the global total of $2 trillion, according to a report released in January by the National Science Foundation. In 2016, the number of scientific publications from China exceeded those from the U.S. for the first time, by 426,000 to 409,000. Chinese researchers are blazing new trails on the frontiers of cloning, stem cell medicine, gene editing, and quantum computing. Chinese patent applications have soared from 170,000 to nearly 3 million since 2000; the country now files almost as many international patents as the U.S. and Japan, and more than Germany and South Korea. Between 2008 and 2017, two Chinese tech firms—Huawei and ZTE—traded places as the world's top patent filer in six out of nine years.
"China is still in its Star Trek phase, while we're in our Black Mirror phase." Yet there are formidable barriers to China beating America in the innovation race—or even catching up anytime soon.
Accompanying this lab-based ferment is a tech-business bonanza. China's three biggest internet companies, Baidu, Alibaba Group and Tencent Holdings (known collectively as BAT), have become global titans of search, e-commerce, mobile payments, gaming, and social media. Da-Jiang Innovations in Science and Technology (DJI) controls more than 70 percent of the world's commercial drone market. Of the planet's 262 "unicorns" (startups worth more than a billion dollars), about one-third are Chinese. The country attracted $77 billion in venture capital investment between 2014 and 2016, according to Fortune, and is now among the top three markets for VC in emerging technologies including AI, virtual reality, autonomous vehicles, and 3D printing.
These developments have fueled a buoyant techno-optimism in China that contrasts sharply with the darker view increasingly prevalent in the West—in part, perhaps, because China's historic limits on civil liberties have inured the populace to the intrusive implications of, say, facial recognition technology or social-credit software, which are already being used to tighten government control. "China is still in its Star Trek phase, while we're in our Black Mirror phase," Kuo observes. By contrast with Americans' ambivalent attitudes toward Facebook founder Mark Zuckerberg or Amazon's Jeff Bezos, he adds, most Chinese regard tech entrepreneurs like Baidu's Robin Li and Alibaba's Jack Ma as "flat-out heroes."
Yet there are formidable barriers to China beating America in the innovation race—or even catching up anytime soon. Many are catalogued in The Fat Tech Dragon, a 2017 monograph by Scott Kennedy, deputy director of the Freeman Chair in China Studies and director of the Project on Chinese Business and Political Economy at the Center for Strategic and International Studies. Among the obstacles, Kennedy writes, are "an education system that encourages deference to authority and does not prepare students to be creative and take risks, a financial system that disproportionately funnels funds to undeserving state-owned enterprises… and a market structure where profits can be made through a low-margin, high-volume strategy or through political connections."
China's R&D money, Kennedy points out, is mostly showered on the "D": of the $209 billion spent in 2015, only 5 percent went toward basic research, 10.8 percent toward applied research, and a massive 84.2 percent toward development. While fully half of venture capital in the States goes to early-stage startups, the figure for China is under 20 percent; true "angel" investors are scarce. Likewise, only 21 percent of Chinese patents are for original inventions, as opposed to tweaks of existing technologies. Most problematic, the domestic value of patents in China is strikingly low. In 2015, the country's patent licensing generated revenues of just $1.75 billion, compared to $115 billion for IP licensing in the U.S. in 2012 (the most recent year for which data is available). In short, Kennedy concludes, "China may now be a 'large' IP country, but it is still a 'weak' one."
"[The Chinese] are trying very hard to keep the economy from crashing, but it'll happen eventually. Then there will be a major, major contraction."
Anne Stevenson-Yang, co-founder and research director of J Capital Research, and a leading China analyst, sees another potential stumbling block: the government's obsession with neck-snapping GDP growth. "What China does is to determine, 'Our GDP growth will be X,' and then it generates enough investment to create X," Stevenson-Yang explains. To meet those quotas, officials pour money into gigantic construction projects, creating the empty "ghost cities" that litter the countryside, or subsidize industrial production far beyond realistic demand. "It's the ultimate Ponzi-scheme economy," she says, citing as examples the Chinese cellphone and solar industries, which ballooned on state funding, flooded global markets with dirt-cheap products, thrived just long enough to kill off most of their overseas competitors, and then largely collapsed. Such ventures, Stevenson-Yang notes, have driven China's debt load perilously high. "They're trying very hard to keep the economy from crashing, but it'll happen eventually," she predicts. "Then there will be a major, major contraction."
"An Intensifying Race Toward Techno-Nationalism"
The greatest vulnerability of the Chinese innovation boom may be that it still depends heavily on imported IP. "Over the last few years, China has placed its bets on a combination of global knowledge sourcing and indigenous technology development," says Dieter Ernst, a senior fellow at the Centre for International Governance Innovation in Waterloo, Canada, and the East-West Center in Honolulu, who has served as an Asia advisor for the U.N. and the World Bank. Aside from international journals (and, occasionally, industrial espionage), Chinese labs and corporations obtain non-indigenous knowledge in a number of ways: by paying licensing fees; recruiting Chinese scientists and engineers who've studied or worked abroad; hiring professionals from other countries; or acquiring foreign companies. And though enforcement of IP laws has improved markedly in recent years, foreign businesses are often pressured to provide technology transfers in exchange for access to markets.
Many of China's top tech entrepreneurs—including Ma, Li, and Alibaba's Joseph Tsai—are alumni of U.S. universities, and, as Kuo puts it, "big fans of all things American." Unfortunately, however, Americans are ever less likely to be fans of China, thanks largely to that country's sometimes predatory trade practices—and also to what Ernst calls "an intensifying race toward techno-nationalism." With varying degrees of bellicosity and consistency, leaders of both U.S. parties embrace elements of the trend, as do politicians (and voters) across much of Europe. "There's a growing consensus that China is poised to overtake us," says Ernst, "and that we need to design policies to obstruct its rise."
One of the foremost liberal analysts supporting this view is Lee Branstetter, a professor of economics and public policy at Carnegie Mellon University and former senior economist on President Barack Obama's Council of Economic Advisors. "Over the decades, in a systematic and premeditated fashion, the Chinese government and its state-owned enterprises have worked to extract valuable technology from foreign multinationals, with an explicit goal of eventually displacing those leading multinationals with successful Chinese firms in global markets," Branstetter wrote in a 2017 report to the United States Trade Representative. To combat such "forced transfers," he suggested, laws could be passed empowering foreign governments to investigate coercive requests and block any deemed inappropriate—not just those involving military-related or crucial infrastructure technology, which current statutes cover. Branstetter also called for "sharply" curtailing Chinese students' access to Western graduate programs, as a way to "get policymakers' attention in Beijing" and induce them to play fair.
Similar sentiments are taking hold in Congress, where the Foreign Investment Risk Review Modernization Act—aimed at strengthening the process by which the Committee on Foreign Investment in the United States reviews Chinese acquisition of American technologies—is expected to pass with bipartisan support, though its harsher provisions were softened due to objections from Silicon Valley. The Trump Administration announced in May that it would soon take executive action to curb Chinese investments in U.S. tech firms and otherwise limit access to intellectual property. The State Department, meanwhile, imposed a one-year limit on visas for Chinese grad students in high-tech fields.
Ernst argues that such measures are motivated largely by exaggerated notions of China's ability to reach its ambitious goals, and by the political advantages that fearmongering confers. "If you look at AI, chip design and fabrication, robotics, pharmaceuticals, the gap with the U.S. is huge," he says. "Reducing it will take at least 10 or 15 years."
Cracking down on U.S. tech transfers to Chinese companies, Ernst cautions, will deprive U.S. firms of vital investment capital and spur China to retaliate, cutting off access to the nation's gargantuan markets; it will also push China to forge IP deals with more compliant nations, or revert to outright piracy. And restricting student visas, besides harming U.S. universities that depend on Chinese scholars' billions in tuition, will have a "chilling effect on America's ability to attract to researchers and engineers from all countries."
"It's not a zero-sum game. I don't think China is going to eat our lunch. We can sit down and enjoy lunch together."
America's own science and technology community, Ernst adds, considers it crucial to swap ideas with China's fast-growing pool of talent. The 2017 annual meeting of the Palo Alto-based Association for Advancement of Artificial Intelligence, he notes, featured a nearly equal number of papers by researchers in China and the U.S. Organizers postponed the meeting after discovering that the original date coincided with the Chinese New Year.
China's rising influence on the tech world carries upsides as well as downsides, Scott Kennedy observes. The country's successes in e-commerce, he says, "haven't damaged the global internet sector, but have actually been a spur to additional innovation and progress. By contrast, China's success in solar and wind has decimated the global sectors," due to state-mandated overcapacity. "When Chinese firms win through open competition, the outcome is constructive; when they win through industrial policy and protectionism, the outcome is destructive."
The solution, Kennedy and like-minded experts argue, is to discourage protectionism rather than engage in it, adjusting tech-transfer policy just enough to cope with evolving national-security concerns. Instead of trying to squelch China's innovation explosion, they say, the U.S. should seek ways to spread its potential benefits (as happened in previous eras with Japan and South Korea), and increase America's indigenous investments in tech-related research, education, and job training.
"It's not a zero-sum game," says Kaiser Kuo. "I don't think China is going to eat our lunch. We can sit down and enjoy lunch together."
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.