Data Science newsletter – August 23, 2021

Newsletter features journalism, research papers and tools/software for August 23, 2021

 

Study: As cities grow in size, the poor ‘get nothing at all’

Santa Fe Institute, News


from

Cities are hubs of human activity, supercharging the exchange of ideas and interactions. Scaling theory has established that, as cities grow larger, they tend to produce more of pretty much everything from pollution and crime to patents and wealth. On average, people in larger cities are better off economically. But a new study published in the Journal of the Royal Society Interface builds on previous research that says, that’s not necessarily true for the individual city-dweller. It turns out, bigger cities also produce more income inequality.

“Previous literature has looked at [urban scaling] through a lens of homogeneity,” says SFI Omidyar Fellow Vicky Chuqiao Yang, an author on the study. These studies have shown a per-capita increase in wealth as cities grow. “But we know from other literature, especially in economics, that many societies are unequal and economic outputs are not distributed evenly.”

Using data from municipal areas across the U.S., the authors took another look at urban wealth through a lens of heterogeneity. Breaking the income in their dataset into deciles, the team found that, as cities grow larger, the top ten percent of income earners gain an increasingly large portion of the wealth.


Scientists map urban heat islands—and track how communities are affected

Science, Anil Oza


from

Driving through New York City’s south Bronx borough on a steamy Saturday in July, Mary Dillon and Kimberly Elicker cringe as another fire hydrant douses the 20-centimeter polyvinyl chloride pipe hanging out their car window.

Fortunately, the cooling spray didn’t prevent the sensor inside the pipe from collecting air temperature and humidity readings as part of a national project to map urban heat islands. The route the two New York City elementary school teachers followed on their 1-hour drive was drawn up with the help of community leaders, who had pinpointed spots where the heat radiating from the pavement and densely packed dwellings feels most oppressive. The input helps Dillon and Elicker, two of the volunteers with the project, map not just heat buildup, but its impact on urban communities.

The approach reflects a growing awareness among climate scientists that environmental equity must be one of their research objectives. “The fact that climate change disproportionately affects communities marginalized along race and class lines is just completely dismissed if these communities are not involved,” says Liv Yoon, a social scientist at Columbia University and lead investigator of the New York City campaign. Scientists, she says, can’t accurately study climate equity without accounting for how people directly experience global warming.


New project brings AI to environmental research in the field

The Ohio State University, Ohio State News


from

A new 30-foot tower has sprouted on the edge of The Ohio State University Airport, but it has nothing to do with directing the thousands of planes that take off and land there each year.

Instead, this tower is the focal point of an Ohio State research project that will explore using artificial intelligence and a variety of sensors to monitor environmental conditions on a minute-to-minute basis.

A key part of the project is the use of machine learning to interpret the data as it is collected, said Tanya Berger-Wolf, director of Ohio State’s Translational Data Analytics Institute (TDAI) and the leader of the project.

“This is a unique opportunity for our researchers to help understand environmental conditions in urban areas, such as carbon emissions, noise and air pollution, and how it changes in real time,” Berger-Wolf said.


Most powerful laser in the US to begin operations soon, supported by $18.5M from the NSF

University of Michigan, Michigan News


from

Said to put the U.S. back on the map of high power laser facilities, the 3 petawatt ZEUS laser at the University of Michigan has been awarded $18.5 million by the National Science Foundation to establish it as a federally funded international user facility.

ZEUS is expected to begin its first experiments in early 2022.

“We are really looking forward to the exciting experiments that this new facility will make possible,” said Karl Krushelnick, director of the Center for Ultrafast Optical Science, where ZEUS’s construction is almost finished.


Our cities are making mammals bigger

ZME Science, Tibi Puiu


from

These findings were surprising. Theoretically, climate is a very important driver of animal body size variation, which is supported by centuries worth of animal measurements. In warm climates, animals tend to be smaller than populations of the same species living in colder environments. Among biologists, this principle is known as Bergmann’s Rule.

Due to climate change, cities across North America have experienced warming. Moreover, cities experience urban heat island effects, a phenomenon in which the temperature in a city is noticeably higher than in the surrounding rural area due to concrete, asphalt, and other urban buildings trapping heat.


Today @EricLander46 published an update on how the White House plans to implement new research security requirements for federally funded scientists and institutions

Twitter, FYI Science Policy


from

The requirements are outlined in a presidential directive issued at the end of the Trump administration, known as NSPM-33. Lander states that over the next 90 days, @WHOSTP
is developing guidance that agencies will use to implement the directive: https://trumpwhitehouse.archives.gov/presidential-actions/presidential-memorandum-united-states-government-supported-research-development-national-security-policy/ 2/9


Stanford engineers develop algorithm to aid kidney transplant exchanges

Stanford University, Stanford News


from

This was the first such exchange between Israel and an Arab nation, a transaction that was only made possible by the Abraham Accords, the historic peace agreement signed in August 2020.

Without the peace treaty and Ashlagi’s collaboration with the Alliance for Paired Kidney Donation and Israel Transplant, the Israelis and the Emiratis likely would never have known about each other and the complex matching would have been a longshot, at best.

Ashlagi works in a field of engineering focused on optimization. It is common, if not expected, that much of an engineer’s effort goes into optimizing systems and processes – a kilogram shaved here, an extra volt eked out there, a millisecond trimmed over here. As optimization challenges go, however, none may be so weighty as that of matching kidney transplant donors and recipients. The consequences are, literally, life-altering.


At a leading health tech conference, enthusiasm for machine learning mixes with calls for greater scrutiny

STAT, Casey Ross


from

Health care organizations and entrepreneurs are collectively spending billions of dollars to develop, implement, and refine machine learning models in medicine. But several speakers said those investments are being jeopardized by a lack of standards to evaluate these tools or guardrails to protect patients against errant results and unintended consequences. Even prominent developers of clinical algorithms said the potential harms merit a more stringent regulatory approach.

“We should think of any machine learning algorithm that is predicting a condition for somebody as a lab test,” said Tanuj Gupta, a physician and vice president at Cerner Corp., the electronic health record vendor, which has developed a number of algorithms being deployed in hospitals. “If it’s off, and you potentially cause some morbidity and mortality issue, it’s a problem.”

Those concerns run counter to the current hands-off approach to regulating such products, especially those that operate within electronic health records. The Food and Drug Administration, which reviews algorithms used to interpret medical images and data from wearables, does not provide equivalent scrutiny to many tools hospitals use within their record-keeping software to guide diagnosis and treatment. A recent STAT investigation found that multiple algorithms developed by Epic, the nation’s largest electronic health record vendor, are delivering inaccurate or irrelevant information to clinicians about the care of seriously ill patients, including a product designed to predict the onset of sepsis, a life-threatening complication of infection.


Can Holly+ Solve the Problem of Deepfake Vocals?

Billboard, Kristin Robinson


from

But for experimental electronic musician Holly Herndon, who has been working at the intersection of music and artificial intelligence for years, including a doctoral stint at Stanford University, she sees this space as a brave new world for musicians. Instead of fighting to destroy the inevitable behemoth of AI, Herndon is showing others how to control it and even use it to their advantage by releasing her new AI voice instrument, Holly+.

Created with start-up Never Before Heard Sounds and longtime collaborator Mat Dryhurst, Holly+ is a cloud-based instrument that allows users to upload up to five minutes of audio and map a rendering of Herndon’s voice over top. Programmed through the amalgamation of hours of Herndon’s voice recordings, the Holly+ instrument solves a few of the biggest challenges with AI voice renderings, most notably, the ownership and monetization of one’s digital likeness. “We’re really trying to figure out robust, foundational logic for how to deal with this technology through Holly+,” says Dryhurst.


Re-Imagining Espionage in the Era of Artificial Intelligence

Stanford University, Stanford Institute for Human-Centered Artificial Intelligence, Edmund L. Andrews


from

Armchair researchers and ordinary citizens are changing the rules of spycraft. Expert Amy Zegart explains how U.S. agencies must adapt.


S&T Artificial Intelligence and Machine Learning Strategic Plan

U.S. Department of Homeland Security


from

The U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) presents goals that will enable S&T to conduct Artificial Intelligence and Machine Learning (AI/ML) research, development, test, and evaluation activities to support DHS mission needs, and to advise stakeholders on developments in AI/ML and the associated opportunities and risks.


Jeannette Wing promoted to executive vice president for research

Columbia University, Columbia Spectator


from

Jeannette Wing, the Avanessians director of Columbia’s Data Science Institute and a professor of computer science, will become the next executive vice president for research, University President Lee Bollinger announced on Wednesday. She will officially start her new role on Sept. 1.

Wing has led the Data Science Institute since 2017. Under her tenure, she has supported a variety of research initiatives in personalized medicine, the impacts of climate change, wireless technology, and other areas.

Wing is widely recognized for her scholarly leadership and contributions in computer science and data science. Following the publication of her essay “Computational Thinking” in 2006, she is credited with innovating the application of core computer science principles to other disciplines.


Creating the Materials of the Future Using Machine Learning

University of Southern California, USC Viterbi School of Engineering


from

The USC Viterbi School of Engineering’s Mork Family Department of Chemical Engineering and Materials Science has launched the new M.S. in Materials Engineering with Machine Learning, a first-of-its-kind Master of Science course, taught by experts in computational materials science and machine learning methods.


Over $5M spent on COVID testing for NC college athletes

WCNC Money (NC), Nate Morabito


from

The three largest public universities in North Carolina spent a combined $5 million testing student-athletes for COVID-19 last school year.

The added expense proved costly at a time when fans weren’t allowed in the stands, games were canceled and athletic departments lost money.

Records show UNC Charlotte alone spent more than $1 million in Higher Education Emergency Relief Fund (HEERF) money on thousands of COVID-19 tests for student-athletes. For comparison, the university spent roughly $1.4 million in HEERF funds improving technology for distance and hybrid learning, according to quarterly reports.


This is a good time to remind people of Hanlon’s razor: “Never ascribe to malice what can be adequately explained by incompetence.”

Twitter, Calling Bullshit


from

To which we add “Never explain by incompetence what can be adequately explained as an understandable mistake.”

Not sure the latter applies here.


Deadlines



NFL Game Data Prediction Game

You must sign in with Twitter to participate!

Want to get started with game AI programming?

“Try the latest @kaggle
simulation competition: Lux AI, a 1v1 resource-gathering game to produce enough light for your city to survive the night https://kaggle.com/c/lux-ai-2021” Deadline for entries is December 6.

SPONSORED CONTENT

Assets  




The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.

 


Tools & Resources



How to curate (just about) anything

Psyche, Glenn Adamson


from

Our complex relationship with our things is behind the runaway popularity of Marie Kondo, the diminutive Jedi of decluttering, who has conquered the world with her ‘six rules of tidying’ – most memorably, the injunction to ask of every single thing in your environment: ‘Does it spark joy?’ If not, she counsels, out it goes.

Kondo gives good advice. But we should go further. Her injunctions aren’t much use in helping me figure out how to reduce my book pile, for instance. I do read for joy, sometimes, and occasionally even find it. But I have books for many other reasons, too: for reference, to learn things, to transform my understanding and see the world a bit differently. Kondo’s combination of empathy and minimalism makes for good television. But it won’t get you to the kind of lived-in, peculiarly personalised space that, for most people, defines the ideal of home.


6 steps for leading successful data science teams

MIT Sloan School of Management, Ideas Made to Matter, Rama Ramakrishnan


from

Supporting and getting the best out of data science teams requires a particular set of practices, including clearly identifying problems, setting metrics to evaluate success, and taking a close look at results. These steps don’t require technical knowledge and instead place a premium on clear business thinking, including understanding the business and how to achieve impact for the organization.

Data science teams can be a great source of value to the business, but failing to give them proper guidance isn’t a recipe for success. Following these steps will help data science teams realize their full potential, to the benefit of your organization.

1. Point data science teams toward the right problem.


So You Want to be a Data Curator?

DATAVERSITY, Keith D. Foote


from

Data curators fill the gap between data scientists and data analysts. They will typically have a better understanding of the data and the analytics workloads than the data engineers, because they work more closely with management and marketing.

Data scientists find meaning in data, but rely on IT to provide the data. It is normal for data scientists to begin an analytics project by initiating a work request with IT. The request describes the data required for the project, as well as detailed formatting requirements, update frequencies, and the tools they need to perform the analysis. IT then assigns the request to a data engineer, who checks for any additional requirements, and then finds the requested data.

However, if the data isn’t organized, there is often a fair amount of confusion as data scientists attempt to communicate their needs to the IT department. Data engineers come with an understanding of infrastructure, and data scientists understand the meaning of the data, but without organized data, the two groups have trouble communicating their needs. The data curator provides a system that allows IT and data scientists to work together smoothly and efficiently (most of the time).


Careers


Postdocs

Postdoctoral position in Language and Cognitive Computational Neuroscience



Max Planck Institute for Psycholinguistics; Nijmegen, Netherlands

Leave a Comment

Your email address will not be published.