An empirical method for measuring Internet censorship.
Five years ago, when Phillipa Gill began a research fellowship at the University of Toronto’s Citizen Lab, she was surprised to find that there was no real accepted approach for empirically measuring censorship. So Gill, now an assistant professor of computer science at the University of Massachusetts, Amherst, built a set of new measurement tools to detect and quantify such practices. One technique automatically detects so-called block pages, which tell a user if a site has been blocked by a government or some other entity. In 2015, Gill and colleagues used her methods to confirm that a state-owned ISP in Yemen was using a traffic-filtering device to block political content during an armed conflict.
At the forefront of turning AI into consumer-ready products.
Artificial intelligence has reached “a critical point,” says Gang Wang—it’s moved beyond the lab and is now ready for mass-market consumer products. Wang, who joined Alibaba’s AI lab in March, is at the forefront of the push to make AI practical for consumer products, and he’s doing it for one of the world’s most ambitious companies in the world’s biggest consumer market. He was one of the scientists behind the Tmall Genie, Alibaba’s first AI-based product, released in July. Analogous to Amazon’s Echo, the device can make purchases on Alibaba’s shopping sites and perform other tasks, such as playing music and checking calendars through voice commands.
“The design of neural networks needs to be intertwined with real-world applications,” says Wang. “Only in this way can we create a product that’s useful in a commercial environment.”
A method for measuring temperatures at the nanoscale.
Problem: Complex microprocessors—like those at the heart of autonomous driving and artificial intelligence—can overheat and shut down. And when it happens, it’s usually the fault of an internal component on the scale of nanometers. But for decades, nobody who designed chips could figure out a way to measure temperatures down to the scale of such minuscule parts.
Solution: Fabian Menges, a researcher at IBM Research in Zurich, Switzerland, has invented a scanning probe method that measures changes to thermal resistance and variations in the rate at which heat flows through a surface. From this he can determine the temperature of structures smaller than 10 nanometers. This will let chipmakers come up with designs that are better at dissipating heat.
Personalized simulations of blood flow in the body.
Amanda Randles, an assistant professor of biomedical engineering at Duke University, is building software that simulates blood flowing throughout the human body in a model based on medical images of a particular person. The code base is called “HARVEY,” after William Harvey, a 17th-century surgeon who first described the circulatory system. The software requires a supercomputer to crunch calculations on the fluid dynamics of millions of blood cells as they move through the blood vessels. Randles has other plans for her fluid-dynamic model of the circulatory system. Next up: scanning newborns with heart problems to guide surgeons and predicting how cancer cells move through the body.
A computer scientist who founded Somalia’s first incubator and startup accelerator.
Like many Somalis, I ended up fleeing my homeland because of the civil war, back in the late 1980s. At age five I moved to the U.K. because I had family there and was able to get asylum. I grew up in a fairly nice part of London and went on to get a PhD in computer science at University College London.
“At university I started becoming more aware of the world and realized I was quite fortunate to be where I am, to have had all the opportunities that I did. So, in 2012, I helped start an organization called Innovate Ventures to train and support Somali techies. The first program we ran was a two-week coding camp in Somalia for about 15 people. Though the impact was small at the time, for those individuals it meant something, and it was my first time going back to the continent; I hadn’t visited in more than two decades.
“I started to think how Innovate Ventures could have a much bigger impact. In 2015, we teamed up with two nonprofits that were running employment training for Somali youths, found some promising startups, and put them through a series of sessions on marketing, accounting, and product design. Five startups came out of that five-month incubator, and we awarded one winner around $2,500 in seed money to help kick-start its business.
“The next year saw us partner with Oxfam, VC4Africa [an online venture-capital community focused on Africa], and Telesom [the largest telco in Somaliland], and we ran a 10-week accelerator for startups. We were hoping to get 40 to 50 applicants, but we ended up getting around 180. We chose 12 startups for a two-week bootcamp and 10 to participate in the full 10-week training and mentoring program. The top four received a total of $15,000 in funding.
“This year, the accelerator will be 12 weeks long, and we’ve received almost 400 applicants. There are some large Somali companies that are interested in investing in startups and we want to bring them on board to help catalyze the startup scene. We also hope to persuade the Somali diaspora, including some of my colleagues at IBM, to donate their skills and invest in the local technology scene.
“Countries like Kenya and Rwanda have initiatives to become technology and innovation hubs in Africa. Somaliland and Somalia face fundamental challenges in health care, education, and agriculture, but innovation, technology, and startups have the potential to fast-track the country’s development. I think we’ve started to take steps in that direction with the programs we’ve been running, and we’re slowly changing the impression people have when they view Somalia and Somaliland.”
Working to improve cancer diagnosis and treatment.
n his lab at the Broad Institute in Cambridge, Massachusetts, Viktor Adalsteinsson has put an automated system in place that scans blood samples for traces of tumor DNA—a so-called liquid biopsy. Collecting genetic information on advanced cancers might lead to clues about what drives the disease in later stages and what drugs to give patients. Adalsteinsson, whose mother succumbed to breast cancer while he was earning his PhD, is now looking to improve treatment as part of several projects, including one that sends blood collection tubes to women fighting breast cancer across America. “The doctors and patients cross their fingers and there’s a lot of watching and waiting,” says Adalsteinsson. “Now we can closely monitor patients’ responses to therapy and see what’s causing treatments to fail.”
Bringing tech’s dismal diversity numbers out into the open.
Silicon Valley loves data. But until recently, there was one subject where tech companies showed little interest at all in the numbers: the diversity of their workforces. It’s not that the statistics were downplayed—the numbers didn’t even exist.
Today most big tech companies have issued public reports on diversity, and there’s an independent, crowdsourced data repository at GitHub that collects information on tech workforces. And this has happened in no small part because Tracy Chou, a Pinterest software engineer at the time, wrote a post on Medium in the fall of 2013 called simply “Where are the numbers?”
Chou wrote the post after returning from a conference where she heard Facebook COO Sheryl Sandberg say the number of women in tech was dropping. “I didn’t think she was wrong,” Chou says. “But I also thought: ‘How does she know? There are no numbers.’ I knew there was this problem.”
Chou’s Medium post quickly went viral. And soon the numbers began to flow—first via Twitter, and then via that GitHub repository, which Chou set up. Within a few weeks, Chou had data on more than 50 companies (the repository now has numbers for hundreds), and by the summer of 2014, a host of the Valley’s most powerful companies had released demographic reports on their workforces. The numbers were dismal—in general, somewhere between 10 and 20 percent of workers in technology positions were women, and one study found that 45 percent of Silicon Valley companies didn’t have a single female executive. But at least the data now existed.
As this was happening, Chou continued her coding work at Pinterest, but she also found herself in demand as a speaker and panelist. Last spring, she teamed up with a group of seven other women—including venture capitalist Ellen Pao and Slack engineer Erica Joy Baker—to form Project Include, an organization designed to help CEOs implement diversity and inclusion strategies at their companies.
Chou isn’t, and doesn’t want to be, a professional activist. “It’s fulfilling to work on this issue, and I can have an impact here,” she says. “But I see it as a complement to my main work, which is building things and making products.” Nonetheless, she’s become a voice of authority on tech’s diversity problem because she’s unusually good at articulating the connections between the personal experience of women in the Valley and the systemic sexism they face, while also identifying how a lack of diversity hurts companies themselves. For instance, there is clearly a pipeline problem when it comes to gender and technology—not enough young women take classes in science, technology, engineering, and math or graduate with STEM degrees. But it’s also true, as Chou argues, that the pipeline problem can’t explain the high rate of attrition for women in tech, or the lack of women in senior positions. In other words, the pipeline for women gets even more narrow once you’re inside a company.
Sometimes that’s because of extraordinarily retrograde, garden-variety sexism, exemplified by the recent problems at Uber or the men who regularly told Chou, “You’re too pretty to be a coder.” It’s also because at many companies there’s an implicit (and sometimes explicit) assumption that women are less naturally adept at coding, and less willing to work hard.
Chou, for example, went to Stanford for an undergrad degree in electrical engineering and got a master’s there in computer science, and had internships at Facebook and Google. Yet at her first job she regularly dealt with casually dismissive sexism, making her question whether she belonged in the industry. “I loved coding,” she says. “But I just felt something was off. I felt out of place, and I had serious questions about whether I was going to stay in tech. And I really thought the problem was me.”
A large body of research shows that making organizations and teams more diverse also improves their performance. Diversity makes teams less likely to succumb to groupthink and helps companies reach untapped markets. “Products tend to be built to solve the problems of the people building them,” Chou says. “And that’s not a bad thing, necessarily. But it means that in the Valley lots of energy and attention goes into solving the problems of young urban men with lots of disposable income, and that much less attention goes to solving the problems of women, older people, children, and so on.”
Despite the evidence, plenty of companies still need convincing. “There’s lots of diversity theater and lip service paid to the concept,” Chou says. “And maybe we’ve helped weed out some of the most egregious actors. But there’s a long way to go.”