Data Science newsletter – March 21, 2021

With booming populations and poor health infrastructure, parts of Africa are the perfect place for the next pandemic to arise. Now a new disease surveillance network is trying to stop the next pandemic before it happens

Artificial intelligence will create so much wealth that every adult in the United States could be paid $13,500 per year from its windfall as soon as 10 years from now.

So says Sam Altman, co-founder and president of San Francisco-headquartered, artificial intelligence-focused nonprofit OpenAI.

“My work at OpenAI reminds me every day about the magnitude of the socioeconomic change that is coming sooner than most people believe,” Altman, who posted Tuesday. “Software that can think and learn will do more and more of the work that people now do.”

The Covid-19 pandemic has tested the public health and medical workforces like never before. And yet people in those fields say they see emerging signs that the crisis will inspire the next generation of doctors, nurses, and public health professionals to join the ranks.

Public health schools, for example, saw a 23% jump in applicants for master’s and doctoral programs from fall 2019 to fall 2020, and are reporting an even bigger increase so far in this application cycle, according to the Association of Schools and Programs of Public Health.

One reason is what Laura Magaña, the CEO of the association, called “the Fauci effect,” after the now-famous U.S. health official Anthony Fauci.

We asked five experts to help us understand why it’s so hard to build good government technology, and for their advice on how to create a healthy technological infrastructure for the people who rely on the outcomes.

A fractured landscape of data

Cyd Harrell: “Government” in the US means a lot of different things. After the federal government, we’ve got 50 state governments, 3,000 counties—which play different roles in different parts of the country—and 20,000 municipalities.

The world is experiencing a computer chip shortage due to a perfect storm of problems including a global pandemic, a trade war, fires, drought and snowstorms. It has coincided with a period of soaring, unprecedented demand – in January alone, chip sales reached a record $40 billion. Chips are now in everything from watches to fridges and your car probably has several dozen. Manufacturers simply can’t produce them fast enough.

What is causing the shortages?

The covid-19 pandemic caused an initial slump in car sales of up to 50 per cent, because few people were travelling anywhere and confidence in the economy was low. Car companies reacted by slimming down manufacturing and reducing orders for parts. This included huge numbers of computer chips, because modern cars contain dozens of them to control everything from braking to steering and engine management. According to research firm IHS Markit, 672,000 fewer vehicles than usual will have been made in the first quarter of 2021 as a result.

Facebook is working on a new neural wristband that can read the electrical signals sent to your hands and send them to an augmented reality interface. Essentially, it’s a bracelet that lets you type without a keyboard (potentially without even moving your fingers) or control something on soon-to-be-released AR glasses.

It seems as if Facebook, after years of harvesting data on your marketing possibilities, is finally starting to be able to read your mind?

“I cannot emphasize this enough: This cannot read your brain,” Andrew “Boz” Bosworth, VP of Facebook Reality Labs, the team responsible for AR and VR (and Portal), told BuzzFeed News.

Hundreds of thousands of surveillance cameras throughout China have been hoovering up facial recognition data without notifying the people attached to the faces. Now, the companies behind the tech are finally under the microscope after a blistering recent exposé — one carried by a major mouthpiece for Beijing, the same government known for its own untrammeled intrusions into private life.

On March 15, China Central Television broadcast its annual consumer rights gala, a long-running annual special that has uncovered many high-level consumer frauds. One segment revealed that facial recognition security cameras located at chain stores nationwide have been picking up shoppers’ personal information without their knowledge or consent. The revelations ignited a furious backlash against the companies. “Two characters,” went one popular online comment about the findings: “wu chi (无耻),” meaning “shameless.” It’s another instance of grassroots pushback against surveillance tech in China, a global leader in surveillance research as well as in deployment.

Computers learned to see only recently. For decades, image recognition was one of the grand challenges in artificial intelligence. As I write this, I can look up at my shelves: they contain books, and a skein of yarn, and a tangled cable, all inside a cabinet whose glass enclosure is reflecting leaves in the trees outside my window. I can’t help but parse this scene—about a third of the neurons in my cerebral cortex are implicated in processing visual information. But, to a computer, it’s a mess of color and brightness and shadow. A computer has never untangled a cable, doesn’t get that glass is reflective, doesn’t know that trees sway in the wind. A.I. researchers used to think that, without some kind of model of how the world worked and all that was in it, a computer might never be able to distinguish the parts of complex scenes. The field of “computer vision” was a zoo of algorithms that made do in the meantime. The prospect of seeing like a human was a distant dream.

All this changed in 2012, when Alex Krizhevsky, a graduate student in computer science, released AlexNet, a program that approached image recognition using a technique called deep learning. AlexNet was a neural network, “deep” because its simulated neurons were arranged in many layers. As the network was shown new images, it guessed what was in them; inevitably, it was wrong, but after each guess it was made to adjust the connections between its layers of neurons, until it learned to output a label matching the one that researchers provided.

Few scientific mysteries can be solved with the help of nearly 400 adorably naughty puppies, but a new study is a pleasant exception. Researchers have used the furballs to show dogs’ ability to understand human pointing—a rarity in the animal kingdom and key to social intelligence—appears to be hardwired in doggy DNA.

“Using puppies to answer this question is a great approach,” says Heidi Parker, a geneticist at the U.S. National Institutes of Health’s Dog Genome Project who was not involved with the work. “Behavior is the holy grail of dog genetics,” she says. Before scientists go searching for genes that may have turned dogs into our faithful companions, they need to make sure they’re there in the first place, she says. “I feel like this study shows that.”

“The SEC is a centerpiece of the University’s mission to create a healthier, more sustainable campus,” said Katie Lapp, executive vice president. “Together, Harvard’s community and its partners — faculty, students, architects, sustainability experts, engineers, and manufacturers — are transforming the definition of sustainable building to address climate, health, and equity for all. Our shared vision for a healthier built environment has motivated the broader supply chain to support a healthier building at local, regional, and global levels.”

Harvard used the construction of the SEC to evaluate and test 6,033 building materials, ranging from wire coatings to furniture fabrics to lighting fixtures, and worked with manufacturers and designers to create safer global supply chains. More than 1,200 companies publicly disclosed the ingredients in their products and created labels to help others make healthy decisions. Many manufacturers reformulated their products to remove harmful chemicals. Harvard eventually approved and selected more than 1,700 products that both comply with the Living Building Challenge Red List and meet the rigorous requirements of Harvard’s Healthier Building Academy, a partnership among faculty from SEAS, the Harvard T.H. Chan School of Public Health, Harvard Medical School, and the Harvard Office for Sustainability.

Inside, we’re driving the field of robotics toward a future that puts people—not just technology—first.

Carnegie Mellon University and the University of Pittsburgh are jointly launching a new center to study extremist hate. Scholars at both universities will partner through the Collaboratory Against Hate – Research and Action Center to develop effective tools that inhibit hate’s creation, growth and destructive consequences.

The center will bring together the collective expertise from all relevant disciplines — including computer science, data science, social sciences, psychology, psychiatry and the law — as collaborators seek to better understand and combat hatred based on race, ethnicity, religion, gender identity, sexual orientation and other prejudices.

University of Michigan researchers will enlist the help of citizen scientists in a new project to digitize thousands of historical records—some dating back more than a century—about Michigan inland lake conditions and fish abundances.

Scientists will feed the digitized data into computer models to study the impacts of climate change and other factors on the fish in Michigan’s inland lakes.

The lake survey data were originally collected on tens of thousands of 5-by-7 paper observation cards that are archived at the Institute for Fisheries Research, a collaboration between the university and the Michigan Department of Natural Resources.

In January, researchers led by associate professor of psychology Robb Rutledge launched The Happiness Project, an app that will help scientists study decision-making, happiness and mental health.

Created by neuroscientists working in the Rutledge lab at Yale University and at University College London in the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging, the app allows users to play four different games, unlocking new levels and tracks their happiness as they continue to play.

“With this app, we’re inviting the general public to play games for science where we can see how they make decisions and how they feel about the outcomes,” Rutledge said. “We know there are certain things that affect people’s well-being and happiness, including uncertainty, rewards and learning. The data from this app will allow us to draw conclusions about how these factors are actually affecting the way people feel.”

Simon J. Sheather, dean of the Gatton College of Business and Economics at the University of Kentucky, has been named as the first holder of the Truist Chair in Data Analytics.

The inaugural chair in the Department of Finance is part of a $2.5 million endowment established in 2019 by Truist Financial Corporation through its Truist Charitable Fund, a donor-advised fund at The Winston-Salem Foundation.

“Endowed chairs are recognized for their outstanding academic service, leadership and significant scholarly contributions to their disciplines,” David Blackwell, UK provost, said. “Sheather is among the top mathematical scientists worldwide; his work is very highly cited and he has received awards for excellence by multiple institutions and professional societies.”

“Luminaire is a python package that provides ML-driven solutions for monitoring time series data. Luminaire provides several anomaly detection and forecasting capabilities that incorporate correlational and seasonal patterns as well as uncontrollable variations in the data over time.”