Over the past several years, our world has been confronted with a range of unprecedented and, at times, deadly challenges—from the covid-19 pandemic to severe weather conditions, and a concurrent rise of societal issues including aging population, urban congestion, and unequal access to health care.
But as the development of artificial intelligence (AI) and its applications grow, AI technologies are playing an instrumental role in addressing socio-economic and environmental challenges faced by the modern world, ultimately helping us to reach a better standard of living.
Filling gaps, providing quality care
One of the most promising applications of AI in recent years has been in augmenting human workers in key sectors that are chronically understaffed, contributing to major advances in solving challenging social issues.
In China, for instance, the medical system has long grappled with a shortage of health-care professionals, with an average of just 17.9 doctors for 10,000 people. The situation is even more imbalanced in small towns and rural areas, forcing many patients to travel long distances to cities to access quality medical care and specialist treatments.
Baidu’s Clinical Decision Support System (CDSS) was developed to address this urgent need. Built on a foundation of medical natural language processing and knowledge graph technology, the system provides real-time assistance to doctors, informing their judgments, helping them more accurately recognize symptoms, and providing corresponding treatment options. By bringing the expertise and resources of top-tier medical institutions to local clinics, the system offers patients a quality of treatment that would otherwise be out of reach. To date, Baidu’s CDSS has been applied in thousands of primary care facilities, and the number is rapidly growing.
“In the diagnosis stage, sometimes young doctors may miss or ignore some symptoms due to a lack of experience,” says one doctor from a hospital in Beijing that has been using CDSS for two years. “Through the consultation support and real-time alert functions of CDSS, which provide more suggestions and references to physicians, we were able to significantly improve the quality of our medical department.”
Accessible solutions through humanized technology
By 2022, approximately 14% of China’s population will be aged 65 and over, according to forecasts by the China Development Foundation, with the number expected to grow to more than 30% by 2050.
For older populations, AI-powered smart speakers and displays can serve as a vital lifeline. Baidu has developed a popular smart display unit with computer vision capabilities and voice interaction technology, called Xiaodu, which can provide a wide range of essential services, including offering health tips, arranging shopping and transportation assistance, providing access to emergency care, and even daily conversation and emotional support.
The success of Xiaodu made it one of the stars of the recent Baidu World, the company’s annual flagship technology conference, which explored how local welfare associations are increasingly distributing Xiaodu installations to seniors.
Xiaodu’s popularity among the elderly highlights another key potential of AI: breaking down barriers and inequalities in access to technology in today’s world. While previous generations saw older populations disenfranchised by the advent of new technologies, AI offers the possibility of applications that will be accessible to all.
Transforming infrastructure, revolutionizing society
Beyond solving targeted problems, new developments show how AI has even greater potential to reduce errors and improve efficiency in the systems that permeate our daily lives, including urban infrastructure in a growing number of cities.
In China’s Shandong province, Baidu AI Cloud supports safety inspections of the electric power grid, providing instant alerts to avert power outages that could affect millions. In Quanzhou, Baidu AI Cloud is being used to accurately forecast water consumption needs at the city’s main water treatment plant for its population of 8 million people. The system analyzes a range of factors, from weather patterns to holidays, helping to boost the plant’s efficiency and cutting its electricity usage by 8%.
“We always need to make sure the system is functioning and the water quality is stable, but it would be impossible for a worker to stay awake and alert for 24 hours a day, never sleeping,” says Shen Peikun, a worker at the Quanzhou plant. “But now this system can handle the equipment and alert us if there are any sudden changes.”
Baidu’s AI technology has revolutionized one of the most ordinary but vital features of city life: the traffic light. Smart traffic systems can monitor vehicle and pedestrian flows, analyzing a vast array of data to predict future traffic conditions and optimize the traffic flow. In the northern Chinese city of Baoding, the use of Baidu’s smart traffic lights has reduced waiting times by up to 20% during peak rush hours, giving people back more time in their daily lives.
With the rapid development of autonomous driving, including Baidu’s Apollo Moon robotaxis unveiled earlier this year, a more comprehensive smart traffic infrastructure is taking shape, with each component building upon the other to enable safer and more efficient travel for all.
In its research on smart traffic solutions, for example, Baidu has found that even a 15% improvement in traffic efficiency correlates to a 2.4% growth in GDP for a given area, as time and resources formerly ensnared in daily inconvenience are freed up to drive economic productivity. In economies grasping for new levers of growth and competitive advantage, optimization like this can provide an invaluable solution. Greater efficiency can also lead to a better use of the earth’s resources, and a reduction in carbon emissions.
As AI applications multiply—including in smart cities and autonomous driving—and become more integrated with one another, their potential to unlock positive value and to help find solutions to some of the world’s most pressing social concerns will continue to grow.
This content was produced by Baidu. It was not written by MIT Technology Review’s editorial staff.
Why can’t tech fix its gender problem?
Not competing in this Olympics, but still contributing to the industry’s success, were the thousands of women who worked in the Valley’s microchip fabrication plants and other manufacturing facilities from the 1960s to the early 1980s. Some were working-class Asian- and Mexican-Americans whose mothers and grandmothers had worked in the orchards and fruit canneries of the prewar Valley. Others were recent migrants from the East and Midwest, white and often college educated, needing income and interested in technical work.
With few other technical jobs available to them in the Valley, women would work for less. The preponderance of women on the lines helped keep the region’s factory wages among the lowest in the country. Women continue to dominate high-tech assembly lines, though now most of the factories are located thousands of miles away. In 1970, one early American-owned Mexican production line employed 600 workers, nearly 90% of whom were female. Half a century later the pattern continued: in 2019, women made up 90% of the workforce in one enormous iPhone assembly plant in India. Female production workers make up 80% of the entire tech workforce of Vietnam.
Venture: “The Boys Club”
Chipmaking’s fiercely competitive and unusually demanding managerial culture proved to be highly influential, filtering down through the millionaires of the first semiconductor generation as they deployed their wealth and managerial experience in other companies. But venture capital was where semiconductor culture cast its longest shadow.
The Valley’s original venture capitalists were a tight-knit bunch, mostly young men managing older, much richer men’s money. At first there were so few of them that they’d book a table at a San Francisco restaurant, summoning founders to pitch everyone at once. So many opportunities were flowing it didn’t much matter if a deal went to someone else. Charter members like Silicon Valley venture capitalist Reid Dennis called it “The Group.” Other observers, like journalist John W. Wilson, called it “The Boys Club.”
The venture business was expanding by the early 1970s, even though down markets made it a terrible time to raise money. But the firms founded and led by semiconductor veterans during this period became industry-defining ones. Gene Kleiner left Fairchild Semiconductor to cofound Kleiner Perkins, whose long list of hits included Genentech, Sun Microsystems, AOL, Google, and Amazon. Master intimidator Don Valentine founded Sequoia Capital, making early-stage investments in Atari and Apple, and later in Cisco, Google, Instagram, Airbnb, and many others.
Generations: “Pattern recognition”
Silicon Valley venture capitalists left their mark not only by choosing whom to invest in, but by advising and shaping the business sensibility of those they funded. They were more than bankers. They were mentors, professors, and father figures to young, inexperienced men who often knew a lot about technology and nothing about how to start and grow a business.
“This model of one generation succeeding and then turning around to offer the next generation of entrepreneurs financial support and managerial expertise,” Silicon Valley historian Leslie Berlin writes, “is one of the most important and under-recognized secrets to Silicon Valley’s ongoing success.” Tech leaders agree with Berlin’s assessment. Apple cofounder Steve Jobs—who learned most of what he knew about business from the men of the semiconductor industry—likened it to passing a baton in a relay race.
Predicting the climate bill’s effects is harder than you might think
Human decision-making can also cause models and reality to misalign. “People don’t necessarily always do what is, on paper, the most economic,” says Robbie Orvis, who leads the energy policy solutions program at Energy Innovation.
This is a common issue for consumer tax credits, like those for electric vehicles or home energy efficiency upgrades. Often people don’t have the information or funds needed to take advantage of tax credits.
Likewise, there are no assurances that credits in the power sectors will have the impact that modelers expect. Finding sites for new power projects and getting permits for them can be challenging, potentially derailing progress. Some of this friction is factored into the models, Orvis says. But there’s still potential for more challenges than modelers expect.
Putting too much stock in results from models can be problematic, says James Bushnell, an economist at the University of California, Davis. For one thing, models could overestimate how much behavior change is because of tax credits. Some of the projects that are claiming tax credits would probably have been built anyway, Bushnell says, especially solar and wind installations, which are already becoming more widespread and cheaper to build.
Still, whether or not the bill meets the expectations of the modelers, it’s a step forward in providing climate-friendly incentives, since it replaces solar- and wind-specific credits with broader clean-energy credits that will be more flexible for developers in choosing which technologies to deploy.
Another positive of the legislation is all its long-term investments, whose potential impacts aren’t fully captured in the economic models. The bill includes money for research and development of new technologies like direct air capture and clean hydrogen, which are still unproven but could have major impacts on emissions in the coming decades if they prove to be efficient and practical.
Whatever the effectiveness of the Inflation Reduction Act, however, it’s clear that more climate action is still needed to meet emissions goals in 2030 and beyond. Indeed, even if the predictions of the modelers are correct, the bill is still not sufficient for the US to meet its stated goals under the Paris agreement of cutting emissions to half of 2005 levels by 2030.
The path ahead for US climate action isn’t as certain as some might wish it were. But with the Inflation Reduction Act, the country has taken a big step. Exactly how big is still an open question.
China has censored a top health information platform
The suspension has met with a gleeful social reaction among nationalist bloggers, who accuse DXY of receiving foreign funding, bashing traditional Chinese medicine, and criticizing China’s health-care system.
DXY is one of the front-runners in China’s digital health startup scene. It hosts the largest online community Chinese doctors use to discuss professional topics and socialize. It also provides a medical news service for a general audience, and it is widely seen as the most influential popular science publication in health care.
“I think no one, as long as they are somewhat related to the medical profession, doesn’t follow these accounts [of DXY],” says Zhao Yingxi, a global health researcher and PhD candidate at Oxford University, who says he followed DXY’s accounts on WeChat too.
But in the increasingly polarized social media environment in China, health care is becoming a target for controversy. The swift conclusion that DXY’s demise was triggered by its foreign ties and critical work illustrates how politicized health topics have become.
Since its launch in 2000, DXY has raised five rounds of funding from prominent companies like Tencent and venture capital firms. But even that commercial success has caused it trouble this week. One of its major investors, Trustbridge Partners, raises funds from sources like Columbia University’s endowments and Singapore’s state holding company Temasek. After DXY’s accounts were suspended, bloggers used that fact to try to back up their claim that DXY has been under foreign influence all along.
Part of the reason the suspension is so shocking is that DXY is widely seen as one of the most trusted online sources for health education in China. During the early days of the covid-19 pandemic, it compiled case numbers and published a case map that was updated every day, becoming the go-to source for Chinese people seeking to follow covid trends in the country. DXY also made its name by taking down several high-profile fraudulent health products in China.
It also hasn’t shied away from sensitive issues. For example, on the International Day Against Homophobia, Transphobia, and Biphobia in 2019, it published the accounts of several victims of conversion therapy and argued that the practice is not backed by medical consensus.
“The article put survivors’ voices front and center and didn’t tiptoe around the disturbing reality that conversion therapy is still prevalent and even pushed by highly ranked public hospitals and academics,” says Darius Longarino, a senior fellow at Yale Law School’s Paul Tsai China Center.