Data Science newsletter – November 20, 2019

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As AI researchers, we are both invested and sensitive to how AI is portrayed in the media. In this article, we suggest a list of best practices for media coverage of AI, some of which may not be obvious to people without a technical background in AI. In being a set of best practices, this list will not be representative of what even we as researchers always do, but rather principles to keep in mind and try to stick to (and ignore as needbe according to good judgement). The list is inspired both by our own observations, and the observations of the AI researchers we surveyed online and at the Stanford AI Lab. We hope it will be useful to journalists, researchers, and anyone who reads or writes about AI.

Today the world has the uncanny shimmer of future weirdness, its every week stuffed with new events that seem to open up strange new realities only to be forgotten as the next wave of strangeness hits. But as the decade pulls to a close, we’re unpacking the last year of it in a timeline of crucial 2019 dates that played like premonitions of where we’ll be ten years from now. The future is present in these moments — epic, like the battle for Hong Kong; eerie, like virtual makeup; and personal, like contemplating gender-confirmation surgery.

The promise of artificial intelligence—that it can turn masses of fuzzy data into money-making moves—is becoming less sci-fi and more business as usual.

Nearly 80% of chief information officers at U.S. companies plan to increase the use of artificial intelligence and machine learning over the next 12 months, according to Adobe’s 2019 CIO Perspectives Survey. Fortune was provided an early look at the San Jose-based software company’s survey results.

Among the more than 200 CIOs that participated in Adobe’s October survey, none said they’re planning to scale back the use of A.I. or machine learning. That apparent confidence speaks to the success of recent AI breakthroughs.

Apple’s push into health is continuing apace with the announcement of three new health studies that users can get involved in through their Apple Watch and iPhone.

Apple has officially launched its Research app, which iPhone and Watch users can download from the App Store to take part in health studies. Once users have downloaded the app, and opted in to sharing their information with the studies, their hardware will collect data that will be used to inform the trio of studies.

Stanford researchers just published a paper in the New England Journal of Medicine about the Apple project, “Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.”

Researchers concluded that the Watch is pretty good at detecting irregular heart beat, which is a significant advance in medical technology. That’s great for people who have their own Apple Watch as well as the people who can get a watch through their Medicare plan.

The study also highlights the limitations of using the Watch for clinical trials. Researchers relying on the Watch to notice health problems face some of the same limitations traditional researchers. Here are three flaws found in the virtual health study that Apple should fix next time around.

As it becomes easier for individuals and organizations to amass large numbers of documents, a new opportunity presents itself. What if you aren’t looking for a single needle in a haystack? What if you wanted to leverage the vast number of existing documents on a subject to help you better understand the subject? One needs an understanding of the totality of the collection. What topics are represented, and how do you create a meaningful overview for troves of documents? To answer these sorts of questions, an approach other than search is needed. At Fathom, we’ve spent the past few years exploring this approach to large document sets. Laniakea is the culmination of much of that work.

With Laniakea, we have mapped out the areas of interest in a set of documents. We combined our design approach with natural language processing techniques to create a general overview of a document set. You can browse documents or drill in to see how subtopics break into categories of their own.

The U.S. Department of Energy’s (DOE’s) Advanced Research Projects Agency-Energy (ARPA-E) announced $15 million in funding for 23 projects to accelerate the incorporation of machine learning and artificial intelligence into the energy technology and product design processes as part of the Design Intelligence Fostering Formidable Energy Reduction (and) Enabling Novel Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program.

It was the second calamity in a year for the centre, which is also known as the Fritz Lipmann Institute (FLI). Police had raided it in 2016 after allegations that the centre had violated European regulations on animal experiments. The experiments were suspended, and although the FLI was cleared of the allegations, not all of the experiments had been re-authorized when the Rudolph affair broke. “The second crisis sent us into shock — it seemed more personal,” says molecular geneticist Christoph Englert, a group leader at the FLI, which employs 270 scientists. Most researchers at the centre hadn’t even known their director was under investigation.

FLI leaders set about restoring the centre’s reputation. They began by phasing in mandatory electronic databases and creating a system of thesis advisory committees to replace single PhD supervisors. The FLI’s head of core facilities, Matthias Görlach, had a less conventional idea. He contacted Enrico Bucci, a molecular biologist who had visited the FLI for some PhD work 18 years earlier, and with whom he’d kept in touch. Bucci was now in the business of checking research papers, Görlach knew; in 2016, he’d founded a science-integrity firm called Resis, based in Samone, Italy. Could the company perhaps help the institute to avoid errors in future?

Sony Corp. has launched Sony AI, a new organization to pursue advanced R&D in artificial intelligence. With this move, the Japanese consumer electronics giant intends to go head-to-head with Google and Facebook, competing for AI talent and projects, and targeting a much bigger role in an ever-accelerating global AI race.

The new organization will be worldwide from day one, with research sites in Tokyo, Austin, Texas, and an unnamed city in Europe. Sony AI will formally start operation next month.

Columbia University, the Flatiron Institute in New York City and the Max Planck Society in Germany are joining forces. Their new partnership, called the Center for Nonequilibrium Quantum Phenomena, aims to understand, control and manipulate the uniquely useful properties of quantum materials.

The new center links these three distinguished organizations, which will work together to harness these materials for a large set of applications, including quantum computing, sensing, cryptography and other technologies not yet imaginable.

Rise is a new talent program designed to increase opportunity for exceptional young people who need it to do more for others, together, throughout their lives.

This program—an initiative of Schmidt Futures and the Rhodes Trust—will build a network of exceptional young people who are committed to helping others throughout their lives.

The program will be designed to encourage a lifetime of service and learning by providing support that could include scholarships, career services, and funding opportunities to help these leaders serve others for decades to come.

Computational sociology leverages new tools and data sources to expand the scope and scale of sociological inquiry. It’s opening up an exciting frontier for sociologists of every stripe—from theorists and ethnographers to experimentalists and survey researchers. It expands the sociological imagination. [full text]

AI and machine learning model architectures developed by Alphabet’s DeepMind have substantially improved the Google Play Store’s discovery systems, according to Google. In a blog post this morning, DeepMind detailed a collaboration to bolster the recommendation engine underpinning the Play Store, the app and game marketplace that’s actively used by over two billion Android users monthly. It claims that as a result, app recommendations are now more personalized than they used to be.

In recent years, America has increasingly been defined by a winner-take-all geography, with coastal superstar cities like New York, Los Angeles, Seattle, and Washington, D.C., garnering a disproportionate share of high-tech startups, corporate headquarters, and innovation and talent. But surging costs and inequality in these places—elements of what I call the New Urban Crisis—may be shaping the beginnings of a shift in talent to other parts of the country.

That’s the upshot of the newly released 2019 Talent Attraction Scorecard from Emsi, a company that analyzes labor-market data. This edition of the scorecard covers America’s 3,000-plus counties, breaking out the data for three types: big counties (with more than 100,000 people), small and medium-size counties (with between 5,000 and 100,000 residents), and very small, micro-counties (with fewer than 5,000 people). The analysis is based on Emsi’s Talent Attraction Index, which is comprised of six key metrics: job growth, skilled job growth, net migration, annual openings for skilled workers (per capita), educational attainment growth (based on adults with associate degrees and above), and a broad measure of regional competitiveness.

Scotiabank announced a donation of $1.25 million to the University of Alberta this morning, to fund the Scotiabank Artificial Intelligence Research Initiative in the Department of Computing Science.

The Scotiabank Artificial Intelligence Research Initiative aims to understand and build practical tools and predictive models for fraud detection and speech to text analytics. In addition, this investment supports the growth and development of women in science, technology, engineering and mathematics (STEM), by funding student participation in a variety of initiatives including in the Canadian Women in Computers Conference and the Grace Hopper Celebration, the world’s largest gathering of women technologists.

Houston, TX November 22, starting at 3 p.m., Rice University. [free]

The recent release of PostGIS 3.0 brings an updated spatial reference system table that includes over 8000 projections out-of-the-box. We’re happy to report that the Equal Earth Projection is one of them!

Developed in 2018, the Equal Earth Projection is gaining in popularity due in part to its ability to maintain accurate area without distortion. As of this new release, CARTO users can start using this popular projection in their maps right away!

“Whether you’re a Fitbit user worried about Google’s recent $2.1 billion purchase of the company or just generally privacy conscious, you should pay attention to where your health and fitness data goes and who has access. It’s among the most sensitive data you have.” … “It shouldn’t take long, and it follows the same principles as any other data privacy audit: Check which data is being collected, which parts of it are public, and how many of your apps can access it.”

“This talk introduces a new flexible and extensible probabilistic programming system called Gen, that is built on top of Julia. Gen’s extensible set of modeling DSLs can express probabilistic models that combine Bayesian networks, black box simulators, deep learning, structure learning, and Bayesian nonparametrics; and Gen’s inference library supports custom algorithms that combine Markov chain Monte Carlo, particle filtering, variational inference, and numerical optimization.” [GitHub source]