AI Regulation Limits: The Cluster

The second edition of the DATAx data science newsletter, The Cluster.

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Vertical Limits

Let's not ground artificial intelligence applications before they reach exit velocity.

On the spectrum of how much restraint and regulation should be applied in developing artificial intelligence applications, there’s New York University on the left, Europe in the center, and the United States to the far right. NYU’s AI Now Institute released a breast-thumping report in January, reporting suggestions for a ban on the use of affect recognition and a halt to government use of facial recognition technologies. Some also believe the AI industry “needs to make significant structural changes to address systemic racism, misogyny, and lack of diversity.” The report also suggests governments should mandate public disclosure of the AI industry’s climate impact.

All laudable goals, or, at least, areas of discussion. But aren’t we getting a little ahead of ourselves? Fortunately, governments sound like they want to be careful not to throw out the baby with the bathwater; at least Europe and the United States do. The Europen Union put out a very sensible document last spring, calling for “a human-centric approach to AI that strives to ensure that human values are central to the way in which AI systems are developed, deployed, used, and monitored.” That sounds like a good starting point.

Here in the good ol’ U.S.A., the White House Office of Science and Technology Policy promised a lighter touch. It trodded out its common trope of the dangers of over-regulation. It also took a swipe at Europe: “Europe and our allies should avoid heavy-handed innovation-killing models, and instead consider a similar regulatory approach.” Finally, the @WHOSTP also couldn’t resist trash-talking China: “Governments elsewhere are co-opting companies and deploying their AI technology in the service of the surveillance state, where they monitor and imprison dissidents, activists, and minorities, such as Beijing’s treatment of the Muslim Uyghur." Gee, well, we’re doing great, then.

Social Impact?

Last week, The Rockefeller Foundation and the Mastercard Center for Inclusive Growth unveiled, a platform for partnerships that aims to build the field of data science for social impact. The organizations decided on a $10 million impact challenge to crowdsource data science solutions for the social sector. Will the program generate anything truly impactful? Color us skeptical, but hopeful. We tend to hear more about the superfluous and silly applications: (1) AdWeek’s Super Bowl ad bot spitting out ideas for Super Bowl ads that were either gibberish or downright disturbing (2) DataRobot’s Grammy Awards prediction model. The model, which data scientist Taylor Larkin says does about 77% better than random predictions, had Billie Eilish #1 for top song and #2 for top record (she won both). (3) Amazon researchers using AI to improve Alexa’s joke selection. Hmm, maybe we’ll need no regulation after all.

AI Feel Better

Wait! Here’s a “feel better” story about the use of AI. While we have been, er, enjoying the “real-time” John Hopkins’ Wuhan coronavirus map, we would have known more and sooner, apparently, if we had been customers of BlueDot. The infectious disease monitoring platform, which uses an AI-driven algorithm, warned its clients of the outbreak in Wuhan, China, a week before the Centers for Disease Control informed the public. BlueDot sifts through news reports, airline data, and news of animal disease outbreaks. “What we have done is use natural language processing and machine learning to train this engine to recognize whether this is an outbreak of anthrax in Mongolia [or] a reunion of the heavy metal band Anthrax,” founder Kamran Khan told Wired. Epidemiologists check that the conclusions make sense from a scientific standpoint. BTW, there’s no U.S. department listed among Blue Dot’s clients, but Canada’s public health agency is a client.

AI Joe

I guess the “experience” of barista-made coffee is on the backburner again at Starbucks. More artificial-intelligence-enabled espresso machines will arrive in Starbucks stores in 2020, said the coffee chain’s COO Rosalind Brewer. Sensors in the machine collect data and warn of needed repairs. Triple espressos will also be easier to whip up, speeding customer wait times.

AI Microsoft

Less than 5% of the world's AI professionals work in health and nonprofit organizations, according to Microsoft. The computing giant announced AI for Health last week, a $40 million program that will leverage AI technology to empower researchers and organizations addressing some of the world's toughest challenges in health. Those include discovering the cause of sudden infant death syndrome (SIDS), eliminating leprosy, detecting diabetic retinopathy to prevent blindness, and building an ecosystem that allows for safe and secure sharing of biomedical data.

Avast, Ye Matey!

Antivirus program Avast is immediately shutting down its data-collection arm Jumpshot after it was found that the unit had been harvesting and selling the private web browsing histories of its users (of which it has 435 million) to several companies, including Microsoft and Google. Avast Chief Executive Ondrej Vleck said in a public letter that he felt "personally responsible" and apologized "to all concerned” for “hurting the feelings of many of you.” Source: Motherboard.

New Moooooodel

Kilkenny, Ireland, is horse country. But that didn’t stop a startup based there from helping develop an “image recognition algorithm that will save vets and farmers considerable time and money in identifying parasites in their herds,” reported the Irish Times. The algorithm from Telenostic and the Irish Centre for High-End Computing boasts a 95% accuracy rate in identifying cow parasites. Normally, specialists in labs identify parasites looking at biological samples through microscopes. Enough of this item, we’re getting itchy.


All those “how do I become a data scientist” posts on Reddit’s r/datascience must be legitimate. Apparently, enterprises face a data scientist shortage. TechTarget has five ways to cope. … Machine learning spam news: If you hate your blog or other content being bested in search results, beware. Spammers are taking advantage of Google algorithms to place content at the top of Google search. They are doing it by automatically creating video content from web pages and vice versa, according to Search Engine Journal. … It’s a big job to optimize car parking throughout North America. Here’s what SpotHero is using to build its data pipeline. … Big projects like the Large Hadron Collider and the Square Kilometre Array are each expected to produce an exabyte of data yearly, “which is about 20 times the digital content of all the written works throughout human history,” according to Physics. This information overload requires new thinking about data management. Efforts are underway to create “science clouds,” and 60 scientists are meeting in Germany this week to hash out some details.

CEO View

Lands End CEO Jerome Griffith says there’s a huge appetite for data within the clothing retailer: “Everything from product data to consumer data to demographic data, everything that we can get our hands on we've been able to utilize,” he told attendees of the ICR conference. “The hardest thing was really getting everything into a single format from all the different areas where we pull data…”

Reference Shelf

Want some data to play around with? Google’s Dataset search has passed beta, and it has indexed 25 million datasets. The most datasets are in geosciences, biology, and agriculture, according to Natasha Noy, research scientist at Google Research. The most popular data format is tables. Given the amount of sniffling on the NYC subway recently, we looked up the “common cold.” The search returned “the most common remedies adults in the U.S. used for the common cold in 2017.” What did 18-to-30-year-olds do most often when they got a cold? “Sleep long” and “eat soup.”

Money Flow$

Outgoing only. Sports betting startup SimpleBet let go of 24 data scientists (two-thirds of its total) in January as part of an effort to become a “leaner” organization. The company’s executive VP of data science Varun Sriram resigned. The NYC startup had “pledged to build an entirely automated algorithmic pricing and trading platform for the sports betting industry but had yet to announce any partners or the launch of the product,” according to Legal Sports Report.

Big Jobs

Levi Strauss & Co. appointed Yael Garten, director of Siri data science and engineering for Apple, to its board of directors. … The Vermont Agency of Digital Services has hired Kristin McClure, a former IBM executive, as its new chief data officer. McClure has also worked at GlobalFoundries and Capgemini.

Join Us in June

Major league baseball is not far away, and neither is DATAx San Francisco — June 10 and 11. If you’re like us and enjoy a more intimate conference (@ 400 attendees) that offers great content, this event is for you. Recent speaker additions include Meghan Anzelc, head of data & analytics at executive recruiter Spencer Stuart; Charles B. Kusterer, professor of analytics at Hult International Business School, and Nels Lindahl, director of clinical decision systems at CVS Health.

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(Billie Eilish photo by Jeff Kravitz/FilmMagic; other images by Getty)

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