Data Science newsletter – September 24, 2019

Newsletter features journalism, research papers, events, tools/software, and jobs for September 24, 2019

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Data Science News



Opinion: UC investments are going fossil free. But not exactly for the reasons you may think

Los Angeles Times, Jagdeep Singh Bachher and Richard Sherman


from

We are investors and fiduciaries for what is widely considered the best public research university in the world. That makes us fiscally conservative by nature and by policy — “Risk rules” is one of the 10 pillars of what we call the UC Investments Way. We want to ensure that the more than 320,000 people currently receiving a UC pension actually get paid, that we can continue to fund research and scholarships throughout the UC system, and that our campuses and medical centers earn the best possible return on their investments.

We believe hanging on to fossil fuel assets is a financial risk. That’s why we will have made our $13.4-billion endowment “fossil free” as of the end of this month, and why our $70-billion pension will soon be that way as well.


AI competitions don’t produce useful models

Luke Oakden-Rayner


from

The conversation continued from there, with thoughts ranging from “but since there is a hold out test set, how can you overfit?” to “the proposed solutions are never intended to be applied directly” (the latter from a previous competition winner).

As the discussion progressed, I realised that while we “all know” that competition results are more than a bit dubious in a clinical sense, I’ve never really seen a compelling explanation for why this is so.

Hopefully that is what this post is, an explanation for why competitions are not really about building useful AI systems.


Alabama’s Artificial Intelligence Commission getting started

al.com, The Washington Post, William Thornton


from

The commission is expected to examine several areas of focus, such as how schools and universities can develop AI-educational programs and privacy issues for consumers. It will meet over the next seven months and deliver a report to Ivey in May 2020 on how AI can benefit the economy.

The board also picked five subcommittees to begin work next month.


Neil Lawrence departs Amazon to take up DeepMind professorship at Cambridge

New Statesman (UK), Oscar Williams


from

One of Amazon’s most senior computer scientists has left to join Cambridge University as the first DeepMind Professor of Machine Learning.

Neil Lawrence, who had served as a director of machine learning at Amazon UK since 2016, was appointed to the new role following an “international” recruitment search, according to the university.


Report: Walmart and Oracle among secret funders behind ‘grassroots’ campaign to blast Amazon – GeekWire

GeekWire, Taylor Soper


from

Peruse through the social media feed and website of the Free & Fair Markets Initiative, and it’s clear that the “nonprofit watchdog” has Amazon in its crosshairs.

What’s not so clear is that the so-called “grassroots” campaign has the financial support of Walmart, Oracle, and mall owner Simon Property Group — three of Amazon’s biggest rivals across industries such as retail and cloud computing.

The Wall Street Journal reported Friday morning that those three companies are secret funders behind the campaign, which has blasted Amazon’s business practices — including its treatment of warehouse workers; its use of personal data; its lack of support for local communities; and more — since launching last year.


NLRB Proposes to Make Student Workers Ineligible to Unionize (1)

Bloomberg Law, Hassan A. Kanu


from

The current proposal—which the board is pursuing through the rulemaking process rather than in an individual case decision—is supported by three of President Donald Trump’s Republican appointees to the NLRB, with the lone Democratic board member dissenting. The Republican members have faced backlash through much of their terms for a string of rulings that critics say favor large corporations, and an ethical violation by member William Emanuel.

“The basis for this proposed rule is the Board’s preliminary position, subject to revision in light of public comment, that the relationship these students have with their school is predominately educational rather than economic,” the agency said in the release.


Privacy Dependencies

SSRN, Washington Law Review, Solon Barocas and Karen Levy


from

This Article offers a comprehensive survey of privacy dependencies—the many ways that our privacy depends on the decisions and disclosures of other people. What we do and what we say can reveal as much about others as it does about ourselves, even when we don’t realize it or when we think we’re sharing information about ourselves alone.

We identify three bases upon which our privacy can depend: our social ties, our similarities to others, and our differences from others. In a tie-based dependency, an observer learns about one person by virtue of her social relationships with others—family, friends, or other associates. In a similarity-based dependency, inferences about our unrevealed attributes are drawn from our similarities to others for whom that attribute is known. And in difference-based dependencies, revelations about ourselves demonstrate how we are different from others—by showing, for example, how we “break the mold” of normal behavior or establishing how we rank relative to others with respect to some desirable attribute.

We elaborate how these dependencies operate, isolating the relevant mechanisms and providing concrete examples of each mechanism in practice, the values they implicate, and the legal and technical interventions that may be brought to bear on them. Our work adds to a growing chorus demonstrating that privacy is neither an individual choice nor an individual value—but it is the first to systematically demonstrate how different types of dependencies can raise very different normative concerns, implicate different areas of law, and create different challenges for regulation.


The Rise of Deepfake Audio Means It’s Time to Revisit Business Email Compromise Scams and Ways to Reduce Risk

NYU School of Law, Program on Corporate Compliance and Enforcement, Avi Gesser, Clara Y. Kim, and Thomas Harris-Warrick (The Crypsis Group)


from

We first wrote about Business Email Compromise (“BEC”) scams in 2015. Over the last four years, these attacks have continued unabated. According to the FBI (PDF: 1.77 MB), in just the last year alone, there were over 20,000 reported BEC scams, with adjusted losses of over $1.2 billion. One reason this threat persists is that cybercriminals have used increasingly sophisticated methods to trick companies into wiring money to them instead of the legitimate payee.

Indeed, in a twist on traditional BEC scams, a fraudster recently used an AI-based software to mimic the voice of a CEO on the phone, successfully tricking another executive into sending money to a supplier. The AI was sophisticated enough that it was able to recreate the slight German accent of the CEO such that the executive thought he recognized his CEO’s voice. With the rise of AI and deepfakes, BEC scams may get harder to detect, so it is worth revisiting the measures companies should consider employing to reduce those risks.


The ecologist who wants to map everythingShare on TwitterShare on FacebookShare via E-MailNewsletterClose banner

Nature, News Feature, Aisling Irwin


from

Thomas Crowther wants to restore the planet, but first he needs to know how many trees, fungi, worms and microbes live on it.


Conservationists harness AI to help wolverine recovery in Washington

The Seattle Times, Melissa Hellman


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Artificial intelligence (AI) technology could play a role in helping scientists further protect these deep snow dwellers vulnerable to climate change and habitat loss.

Washington conservationists are focused on the recovery of the small carnivores. Using remote cameras that detect motion and a machine learning system, a method that finds patterns in a large amount of data, some researchers say they have the answer to tracking the shy creatures during a critical time for their survival.

At the forefront of wolverine recovery in the state, Dr. Robert Long — senior conservation scientist of Seattle’s Woodland Park Zoo — has placed remote cameras throughout Washington, Idaho, and Montana to track the animals for nearly a decade.


Computers and Humans ‘See’ Differently. Does It Matter?

Quanta Magazine, Kevin Hartnett


from

There is a lot we don’t know about human vision, but we know it doesn’t work like that. In our recent story, “A Mathematical Model Unlocks the Secrets of Vision,” Quanta described a new mathematical model that tries to explain the central mystery of human vision: how the visual cortex in the brain creates vivid, accurate representations of the world based on the scant information it receives from the retina.

The model suggests that the visual cortex achieves this feat through a series of neural feedback loops that refine small changes in data from the outside world into the diverse range of images that appear before our mind’s eye. This feedback process is very different from the feed-forward methods that enable computer vision.

“This work really shows how sophisticated and in some sense different the visual cortex is” from computer vision, said Jonathan Victor, a neuroscientist at Cornell University.

But computer vision is superior to human vision at some tasks. This raises the question: Does computer vision need inspiration from human vision at all?


For AI, Hardware’s Just the Start, NVIDIA’s Ian Buck Says

NVIDIA Blog, Brian Caulfield


from

The industry now has to think bigger — much bigger — than the boxes that defined the industry’s past, Buck explained, weaving together software, hardware and infrastructure designed to create supercomputer-class systems with the muscle to harness huge amounts of data.

Training, or creating new AIs able to tackle new tasks, is the ultimate HPC challenge – exposing every bottleneck in compute, networking and storage, Buck said.

“Scaling AI training poses some hard challenges. Not only do you have to build the fast GPU, but optimize for the full data center as the computer,” Buck said. “You have to build system interconnections, memory optimizations, network topology, numerics.”


Meet the Women Leading Netflix Into the Streaming Wars

Fortune, Michal Lev-Ram


from

Apple, Disney, and others are challenging its dominance like never before. Here’s the team behind the tech giant’s big bet on original content.


Google’s Ad Business Undergoes Massive Reorganization

Ad Exchanger, Sarah Sluis


from

Google’s advertising chief Prabhakar Raghavan is reorganizing Google’s ads business – and adding new heads of measurement and privacy, according to multiple AdExchanger sources.

As part of the reorg, he’s re-visualizing the company as four “concentric circles.” The innermost circle is Google’s owned-and-operated properties, including search and YouTube. The next circle outside of that is Google’s buy-side and sell-side businesses. The two outermost circles span the organization: measurement and privacy.

As part of the change, Raghavan created two new roles: a head of measurement, Vidhya Srinivasan, and a head of privacy, Mike Schulman.


Your Navigation App Is Making Traffic Unmanageable

IEEE Spectrum, Jane Macfarland


from

Miguel Street is a winding, narrow route through the Glen Park neighborhood of San Francisco. Until a few years ago, only those living along the road traveled it, and they understood its challenges well. Now it’s packed with cars that use it as a shortcut from congested Mission Street to heavily traveled Market Street. Residents must struggle to get to their homes, and accidents are a daily occurrence.

The problem began when smartphone apps like Waze, Apple Maps, and Google Maps came into widespread use, offering drivers real-time routing around traffic tie-ups. An estimated 1 billion drivers worldwide use such apps.

Today, traffic jams are popping up unexpectedly in previously quiet neighborhoods around the country and the world.

 
Events



GPU Technology Conference

NVIDI


from

Washington, DC November 4-6. “NVIDIA’s GPU Technology Conference is the premier event on artificial intelligence. Connect with experts to get hands-on technical training and insights into the latest AI and data science approaches, applications and breakthroughs.” [$$$, discounts A


2019 Grace Hopper Celebration

AnitaB.org, Association of Computing Machinery (


from

Orlando, FL October 1-4. “2019 Grace Hopper Celebration (GHC 19)! GHC is the world’s largest gathering of women technologists.” [sold out]


Networks 2021: A Joint Sunbelt and NetSci Conference

Indiana University


from

Washington, DC July 6-11, 2020. Abstract submissions will open on November 1. [save the date]

 
Deadlines



Call for Proposals: News Coverage of US Elections

“To encourage new research on the evolving nature of US election coverage, the Media & Democracy program at the Social Science Research Council is proud to announce an open call for papers for an interdisciplinary research development workshop to be held in Brooklyn, NY, on April 23–24, 2020. This workshop will be co-chaired by Professor Julia Azari (Marquette University) and Professor Michael Wagner (University of Wisconsin–Madison).” Deadline to apply is November 4.

Call for Participation – C+J 2020

“Save the Date! C+J 2020 will be held at Northeastern University in Boston on March 20-21, 2020. Submission deadline Dec. 13th, 2019.”
 
Tools & Resources



Balancing Makers and Takers to scale and sustain Open Source

Dries Buytaert


from

  • Small Open Source communities can rely on volunteers and self-governance, but as Open Source communities grow, their governance model most likely needs to be reformed so the project can be maintained more easily.
  • There are three models for scaling and sustaining Open Source projects: self-governance, privatization, and centralization. All three models aim to reduce coordination failures, but require Open Source communities to embrace forms of monitoring, rewards and sanctions. While this thinking is controversial, it is supported by decades of research in adjacent fields.
  • Open Source communities would benefit from experimenting with new governance models, coordination systems, license innovation, and incentive models.

  • What It Will Take to Improve Diversity at Conferences

    Harvard Business Review, Ruchika Tulshyan


    from

    We must also recognize and acknowledge the systematic barriers holding back people of color (especially) from being recognized as experts. A conference organizer has the power to lift up speakers of color and present them a platform to showcase their expertise. As a professional speaker myself, I can confirm that my skill has been directly impacted by the number of opportunities I’ve received to speak in public; the more I get asked, the better I become through practice.

    There are also very practical things you can do to change the tide, whether you are organizing a conference, or attending, speaking at, or sponsoring one.

    Don’t only look for experts by title. When we default to the “best” in a category, we usually default to white men, a reality reinforced by long-held power dynamics in society. I’ve found this to be true even outside of the U.S. and western Europe.

     
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