It’s rare that a scientist becomes a folk hero. But in China, Qian Xuesen draws crowds almost a decade after his death. On a Saturday morning in a three-storey museum in Shanghai, tourists admire Qian’s faded green sofa set, the worn leather briefcase he carried for four decades and a picture of him shaking hands with opera star Luciano Pavarotti.
They file past a relic from a turning point in Qian’s life – and in China’s rise as a superpower: a framed ticket from his 1955 voyage from San Francisco, in the United States, to Hong Kong aboard the SS President Cleveland. Once a professor at the Jet Propulsion Laboratory (JPL) research and development centre in Pasadena, California, which was later controlled by Nasa, he had been accused of having communist sympathies in the heat of the cold war’s “red scare” in the US, and placed under virtual house arrest.
Upon his release, Qian and his family set sail for his motherland.
After arriving in China, Qian went on to spearhead the rapid ascent of the country’s nuclear weapons programme, an achievement that explains some of the adulation. But his legacy is still unfolding in a second area that could have great consequences for China – and for the world. Qian, who died in 2009 at the age of 97, helped lay the groundwork for China’s modern surveillance state.
Early in his career, the scientist embraced systems engineering – an interdisciplinary field focused on understanding the general properties common to all physical and societal systems, and using that knowledge to exert control. By mapping a system’s dynamics and constraints, including any feedback loops, systems theorists learn how to intervene in it and shape outcomes. Since the field’s founding in the 1950s, systems approaches have been applied to areas as varied as biology and transport infrastructure.
In the West, systems engineering’s heyday has long passed. But in China, the discipline is deeply integrated into national planning. The city of Wuhan is preparing to host this month the International Conference on Control Science and Systems Engineering, which focuses on topics such as autonomous transport and the “control analysis of social and human systems”. Systems engineers have had a hand in projects as diverse as hydropower dam construction and China’s social credit system, a vast effort aimed at using big data to track citizens’ behaviour.
Systems theory “doesn’t just solve natural sciences problems, social science problems and engineering technology problems”, says Xue Huifeng, director of the China Aerospace Laboratory of Social System Engineering (CALSSE) and president of the China Academy of Aerospace Systems Science and Engineering in Beijing. “It also solves governance problems.”
The field has resonated with Chinese President Xi Jinping, who in 2013 said that “comprehensively deepening reform is a complex systems engineering problem”. So important is the discipline to the Chinese Communist Party that cadres in its Central Party School in Beijing are required to study it.
By applying systems engineering to challenges such as maintaining social stability, the Chinese government aims to “not just understand reality or predict reality, but to control reality”, says Rogier Creemers, a scholar of Chinese law at the Leiden University Institute for Area Studies, in the Netherlands.
With the discipline now touted at the highest levels of government, Qian has been deified, with biographies, television segments and symposia regularly devoted to him. In the 90s, the Chinese government even spearheaded a “learn from Qian Xuesen” movement. Popular discourse now acknowledges that modern China’s first leader, Mao Zedong, “was a human being”, says Zhu Zhichang, a systems scientist at Xiamen University Malaysia, an overseas campus of the Chinese educational facility. “But to a circle of scientists in China, Qian Xuesen is now, in their mind, the new god.”
The traditional, or “hard”, brand of systems engineering that Qian pioneered has lately come under attack from Zhu and other scholars, both inside and outside China. They contend that it discounts the experiences of everyday people affected by systems models and values state power above all else. They are trying to carve out an alternative vision for systems science, one less reliant on mathematical formulas and more attuned to civic participation. But that could prove an uphill battle in a country where maintaining stability trumps scholarly debate.
In a building flanked by military guards, systems scientists from CALSSE sit around a large conference table, explaining the complex diagrams behind their studies on controlling systems. The researchers have helped model resource management and other processes in smart cities powered by artificial intelligence. Xue, who oversees a project named for Qian at CALSSE, traces his work back to the US-educated scientist. “You should not forget your original starting point,” he says.
Qian was born in 1911 in Hangzhou, eastern China. In 1935, a scholarship took him to the Massachusetts Institute of Technology, in the US. He then went on to the California Institute of Technology, where he worked with Hungarian mathematician Theodore von Kármán. When von Kármán and others founded JPL, in 1944, to develop rocket technology, Qian was given security clearance and brought in to work on classified weapons research.
As the “red scare” took hold in the 50s, the scientist came into the Federal Bureau of Investigation’s crosshairs. His security clearance was revoked and after years of bilateral negotiations, Qian was allowed to return to China. Back in Beijing, his previous experience designing complicated weapons systems and rockets for the US became integral to China’s budding efforts.
On October 16, 1964, at 3pm local time, China detonated its first atomic bomb. Xue says the programme succeeded in part because Qian modelled a complex weapons system down to its most unpredictable parts. He automated China’s weapons command and control system, enabling planners to direct the activities of thousands of people at once.
As Qian honed China’s weapons systems, scientists in North America and Europe began applying systems approaches to intractable policy problems, modelling them as a collection of inputs and variables linked by direct or inverse relationships and feedback loops. In the 60s, for example, school districts across California tried systems approaches. To help educators set budget priorities, multimillion-dollar data-processing programs designed by JPL and rocket manufacturer Aerojet General Corporation collated children’s academic records, IQ scores and attendance.
According to critics, such efforts wasted money that could have gone toward hiring teachers and reduced to rational analysis what should have been a complex political process. “When the policymakers came in and started asking questions, [they] were talking about variables that weren’t in the models,” says Gerald Midgley, a systems scientist at the University of Hull, in Britain. California’s data-driven approach to education was eventually scrapped. Those and other embarrassments brought the field into disrepute in the West.
In China, though, the notion that scientists could neatly model societal endeavours resonated with leaders reared on central planning. An early major contribution of social systems scientists occurred in the late 70s, when Qian’s protégé, missile scientist Song Jian, led a team whose computer-generated projections showed China’s population rising to 4 billion by 2080. That work helped justify extreme restrictions on births after the government implemented the one-child policy in 1979.
Soon after, systems scientists began assessing the feasibility of building the titanic Three Gorges Dam on the Yangtze River. The goal was to determine the optimal dam height and water level in the reservoir, balancing the demands of power generation with other factors, including the massive project’s negative impacts. One group working on the project took stock of 14 “subsystems”, including geology, ecology and human migration.
The researchers then analysed how various water levels would affect outputs such as seismic activity or the number of people forced to relocate. Ultimately, the group arrived at an ideal water impoundment level of 175 metres. The dam’s operator hewed to that advice, raising water levels to 175 metres by 2012.
As with the one-child policy, though, the systems scientists entrusted with studying the Three Gorges Dam devoted little time to consulting people whom the project would affect most. (Dam building and the reservoir that formed behind the structure displaced 1.3 million people in southwestern China.) Because the dam’s construction was a foregone conclusion, the feasibility study was limited to outcomes that reinforced government plans.
Researchers in China often approach mega-projects such as the Three Gorges “from the perspective of how to successfully implement the project whose execution has already been decided politically”, says Yoshiteru Nakamori, a systems scientist and former dean of the School of Knowledge Science, at Japan Advanced Institute of Science and Technology, in the city of Nomi.
More recently, the involvement of China’s systems scientists in designing the country’s digital infrastructure has raised similar questions about whether the scientists are aiding the state at the expense of the public.
Take China’s “smart cities” initiative. Beijing claims to have wired hundreds of cities with sensors that collect data on topics including city service usage and crime. At the opening ceremony of China’s 19th Party Congress last year, Xi said smart cities were part of a “deep integration of the internet, big data and artificial intelligence with the real economy”.
The initiative, which has received funding from the United Nations Development Programme, has benign components. Xue and colleagues, for example, are working on how smart cities can manage water resources. In Guangdong province, the researchers are evaluating how to develop a standardised approach for monitoring water use that might be extended to other smart cities.
But Xue says that smart cities are as much about preserving societal stability as streamlining transport flows and mitigating air pollution. Samantha Hoffman, a consultant with the International Institute for Strategic Studies, in London, says the programme is tied to long-standing efforts to build a digital surveillance infrastructure and is “specifically there for social control reasons”. The smart cities initiative builds on 90s systems engineering projects – the “golden” projects – aimed at dividing cities into geographic grids for monitoring, she adds.
Layered onto the smart cities project is another systems engineering effort: China’s social credit system. In 2014, the country’s State Council outlined a plan to compile data on individuals, government officials and companies into a nationwide tracking system by 2020. The goal is to shape behaviour by using a mixture of carrots and sticks.
In some citywide and commercial pilot projects already under way, individuals can be dinged for transgressions such as spreading rumours online. People who receive poor marks in the national system may eventually be barred from travel and denied access to social services, according to government documents.
Civil liberties groups charge that the system will deepen monitoring of the citizenry, especially if combined with the state’s growing biometrics capabilities. Social credit is aimed at “further tightening the web of social control”, says Maya Wang, a researcher with Human Rights Watch in Hong Kong. (Beijing maintains that the system is about building trust and accountability, as well as helping law enforcement identify criminals.)
Government documents refer to the social credit system as a “social systems engineering project”. Details about which systems engineers consulted on the project are scant. But one theory that may have proved useful is Qian’s “open complex giant system”, Zhu says.
A quarter of a century ago, Qian proposed that society is a system comprising millions of subsystems: individual persons, in human parlance. Maintaining control in such a system is challenging because people have diverse backgrounds, hold a broad spectrum of opinions and communicate using a variety of media, he wrote in 1993, in the Journal of Systems Engineering and Electronics. His answer sounds like an early road map for the social credit system: to use then-embryonic tools such as artificial intelligence to collect and synthesise reams of data.
According to published papers, China’s hard systems scientists also use approaches derived from Qian’s work to monitor public opinion and gauge crowd behaviour. And systems science approaches are on display in Xinjiang, a region in northwest China with a high percentage of Muslims. According to Human Rights Watch, Xinjiang’s public security bureau is aggregating data from sources such as closed-circuit television cameras, security checkpoints and residents’ networked devices. Authorities then use a form of systems analysis adapted from People’s Liberation Army doctrine to flag people seen as potentially disruptive.
After systems engineering fell from grace in the West, researchers spearheaded a fundamentally new approach. In 1981, Peter Checkland, of Britain’s Lancaster University, called for a “soft” systems science that valued input from stakeholders over mathematical modelling. In Checkland’s vision, experts exist not to impose their values, but instead to learn from people involved in the problem at hand. When Zhu left China in 1988 to earn a master’s degree at the University of Hull, that was the approach he encountered. Zhu studied there under Midgley, just as systems engineering was transforming in the West.
A few years later, Zhu began collaborating in Beijing with Gu Jifa, who had worked on the Three Gorges Dam assessment and become head of the Systems Engineering Society of China. Zhu had come to see Qian’s brand of systems science as “brain without soul”. Gu, meanwhile, had learned first-hand the importance of what he called renli, or “human relations”, in shaping project outcomes.
For example, his recommendations for an urban development plan in Beijing were not adopted because his team neglected to engage key stakeholders. Hard systems engineering worked well for rocket science but not for more complex social problems. “We realised we needed to change our approach,” says Gu, who felt strongly that any methods used in China had to be grounded in Chinese culture.
The duo came up with what they called the “WSR” approach: it integrated wuli, an investigation of facts and future scenarios; shili, the mathematical and conceptual models used to organise systems; and renli. Though influenced by British systems thinking, the approach was decidedly Eastern, its precepts inspired by the emphasis on social relationships in Chinese culture.
Instead of shunning mathematical approaches, WSR tried to integrate them with softer inquiries, such as taking stock of what groups a project would benefit or harm. WSR has since been used to calculate wait times for large events in China and to determine how China’s universities perform, among other projects.
Despite the efforts of Gu and others, systems science in China today remains rooted in the hard systems engineering approaches that rocket scientists pioneered decades ago. That emphasis is apparent at the concrete-block flat in Beijing where Qian lived for nearly half a century, which is now an unofficial museum for state visitors.
Giving a tour of the apartment, Qian Yonggang, Xuesen’s 69-year-old son, gestures to a living room decorated with blond-wood accents. “Many Chinese leaders have sat here,” he says. He moves on to the bedroom, indicating the twin bed in which his father spent his final days. Hanging above it is a framed photo of a sombre-looking Qian Xuesen.
Zhu contends that the time has come to bring the god down to Earth. He recently wrote that systems science in China is “under a rationalistic grip, with the ‘scientific’ leg long and the democratic leg short”. Zhu says he has no doubt that systems scientists can make projects such as the social credit system more effective. However, he cautions, “Systems approaches should not be just a convenient tool in the expert’s hands for realising the Party’s wills. They should be a powerful weapon in people’s hands for building a fair, just, prosperous society.”
This story first appeared in Science magazine