Data Science newsletter – December 12, 2019

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A documentary exploring how artificial intelligence is changing life as we know it — from jobs to privacy to a growing rivalry between the U.S. and China. [video, 1:54:16]

More than 47,000 bridges in the U.S. are structurally deficient, a report found earlier this year.

A new Center for Intelligent Infrastructure (CII) at Purdue University is bringing together researchers of various fields to develop technology that a bridge, building, road or other infrastructure could use to communicate directly with humans and respond to disasters, preventing collapse.

“Intelligent infrastructure would be able to understand human needs and autonomously adapt to them,” said Luna Lu, the director of CII and an associate professor in Purdue’s Lyles School of Civil Engineering. “The goal of our center is to advance knowledge and education in the intelligent infrastructure space.”

In his office in Denning House on the Stanford campus, Hennessy, 67, spoke with strategy+business about the similarities — and crucial differences — involved in leading high-performance organizations in the realms of education and technology.

In the last decade, scientists have made tremendous progress in understanding that groups of bacteria and viruses that naturally coexist throughout the human body play an important role in some vital functions like digestion, metabolism and even fighting off diseases. But understanding just how they do it remains a question.

Researchers from Drexel are hoping to help answer that question through a clever combination of high-throughput genetic sequencing and natural language processing computer algorithms. Their research, which was recently published in the journal PLOS ONE, reports a new method of analyzing the codes found in RNA that can delineate human microbial communities and reveal how they operate.

Having operated under the radar for almost two years, Grai Matter Labs recently stepped into the spotlight, announcing its first products. According to the fabless semiconductor scale-up with Eindhoven roots, Grai One is the world’s first AI chip optimized for ultra-low-latency and low-power processing at the edge. It’s based on the company’s brain-like Neuronflow architecture.

A Silicon Valley startup has completed what appears to be the first commercial freight cross-country trip by an autonomous truck, which finished a 2,800-mile-run from Tulare, California to Quakertown, Pennsylvania for Land O’Lakes in under three days. The trip was smooth like butter, 40,000 pounds of it.

Plus.ai, a 3-year-old company in Cupertino, announced the milestone Tuesday. A safety driver was aboard the autonomous semi, ready to take the wheel if needed, along with a safety engineer who observed how things were going.

The recordings she and her co-workers were listening to were often intense, awkward, or intensely awkward. Lonely sounding people confessing intimate secrets and fears: a boy expressing a desire to rape; men hitting on Alexa like a crude version of Joaquin Phoenix in Her. And as the transcription program grew along with Alexa’s popularity, so did the private information revealed in the recordings. Other contractors recall hearing kids share their home address and phone number, a man trying to order sex toys, a dinner party guest wondering aloud whether Amazon was snooping on them at that very instant. “There’s no frickin’ way they knew they were being listened to,” [Ruthy Hope] Slatis says. “These people didn’t agree to this.” She quit in 2016.

In the five years since Slatis first felt her skin crawl, a quarter of Americans have bought “smart speaker” devices such as the Echo, Google Home, and Apple HomePod. (A relative few have even bought Facebook’s Portal, an adjacent smart video screen.) Amazon is winning the sales battle so far, reporting that more than 100 million Alexa devices have been purchased. But now a war is playing out between the world’s biggest companies to weave Alexa, Apple’s Siri, Alphabet’s Google Assistant, Microsoft’s Cortana, and Facebook’s equivalent service much deeper into people’s lives.

I’m happy to announce the roll out of the third LinkedIn Emerging Jobs Report, particularly because — judging by the results — this may be the last year we’ll need a person to write the introduction. Next year, it will probably be produced with artificial intelligence by, say, Robot Louis Stevenson.

This year we’ve scoured LinkedIn to identify the fastest-growing jobs (see Methodology below) in 17 countries across four continents. And, while there are many fascinating and nuanced differences nation to nation, one thing stands out everywhere: Artificial intelligence and robots are no longer on their way. They’ve arrived. In a big way.

AI specialist was the top emerging job in eight countries and was in the top ten in another five. Robotics engineer was among the top emerging jobs in nine countries.

It almost seems like every year is a new, incredible year for human evolution discoveries! There was no exception in 2019, keeping human evolution researchers (and students) on their toes. This year’s blog post is going to focus on discoveries that give us a new twist on old ideas – from previously unknown hominin species to other evidence that sheds new light on old questions. If you want to learn more about our favorite discoveries from previous years, read our 2017 and 2018 blog posts.

1) The human family tree gets another branch: Homo luzonensis

Last month, as Sacha Baron Cohen was delivering his made-for-social-media anti-social-media diatribe at the Anti-Defamation League, Tim Berners-Lee, the literal inventor of the World Wide Web, was preparing to step out from the shadows to acknowledge that, well, things online hadn’t gone exactly how he’d hoped — that the internet was at a “tipping point” and in need of root-and-branch remodeling. But Berners-Lee isn’t alone. In fact, it can seem these days like tech apostates might outnumber evangelists in Silicon Valley, which once looked from afar like a practical cult of sunny-side-up solutionism but now offers a new opportunity for self-promotional branding: pivoting to tech-flagellation. Here, a survey of which of those new turncoats are most likely to make an impact, which are speaking out as a salve to their own consciences, and which are just reading the direction of public opinion and torquing themselves accordingly.

1. Google Workers

Given that machine learning in the health domain can have a direct impact on people’s lives, broad claims emerging from this kind of research should not be embraced without serious vetting. Whether conducting health care research or reading about it, make sure to consider what you don’t see in the data and analyses.

Two decades on, genetics has transformed how people untangle correlation from causation. But it has come to raise epidemiology, not bury it. Genetic differences, it turns out, can help remove confounding variables from analyses, by standing in as proxies for environmental exposure. The technique is called Mendelian randomization.

Scientists have used it to re-evaluate observational data and draw fresh, firmer conclusions on long-standing questions of cause and effect. The analyses have affirmed that low cholesterol levels do not cause cancer2, for example, that drinking small amounts of alcohol does not protect the heart3 and that — yes — schooling can make children short-sighted4.

“Mendelian randomization in principle is a really, really cool idea. It attempts to solve one of the most daunting challenges in epidemiology,” says Philipp Koellinger, a social-science geneticist at the Free University of Amsterdam.

Google snaps up AliveCor’s chief medical officer. Dr. Jacqueline Shreibati will join Google’s health clinical team and report to the chief health officer, Dr. Karen DeSalvo.

A device in development at the University of Chicago nudges your muscles into the exact actions needed to keep a beat — and plenty more.

Vancouver, BC, Canada December 13 starting at 3 p.m., University of British Columbia, DFP Classroom: FSC 2300. “We will review case studies in three arenas—data wrangling, exploratory visualization, and natural language translation—that integrate proactive computational support into interactive systems. To improve outcomes and support learning by both people and machines, I will describe the use of shared representations of tasks augmented with predictive models of human capabilities and actions.” [free]

We describe the multi-layer temporal network which connects a population of more than 700 university students over a period of four weeks. The dataset was collected via smartphones as part of the Copenhagen Networks Study. We include the network of physical proximity among the participants (estimated via Bluetooth signal strength), the network of phone calls (start time, duration, no content), the network of text messages (time of message, no content), and information about Facebook friendships. Thus, we provide multiple types of communication networks expressed in a single, large population with high temporal resolution, and over a period of multiple weeks, a fact which makes the dataset shared here unique. We expect that reuse of this dataset will allow researchers to make progress on the analysis and modeling of human social networks.

“Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite, and the source is available on GitHub.”