Data Science newsletter – July 26, 2021

Newsletter features journalism, research papers and tools/software for July 26, 2021


I SEE U, Episode 10: Black A I = Artificial Inclusion

Houston Public Media, Eddie Robinson


A young computer scientist who grew up in Mississippi is focusing her efforts on fairness and identifying biases in technology. Though she’s working in Atlanta as an artificial intelligence researcher for Amazon, she’s reinvesting much of her earnings towards the development of a multi-million dollar innovation center that’s set to transform her native downtown Jackson. Dr. Nashlie Sephus is also CEO of The Bean Path — a non-profit that works to bridge the “tech gap” in communities where access to technical expertise, computer coding and other resources are limited. She speaks candidly with host Eddie Robinson about her experiences in closing commercial real estate deals in the Deep South and how she’s worked in a field of study where there’s not many Black women with PhDs. [audio, 52:23]

Want to go viral? Influencers won’t be much help if you’re trying to spread a complex idea

Fast Company, Arianne Cohen


Marketing and public relations gospel has long banked on the idea that simply reaching the well-connected people at the centers of social networks will create success. If you can just get your brilliant innovation to Kevin Bacon, then virality and riches will follow, right?

Wrong, say social network researchers at the University of Pennsylvania, who have found that influencers are rather impotent when it comes to changing the behavior and beliefs of others, and might be detrimental to some messaging.

It comes down to the fact that people only adopt complex information from influencers whose beliefs they support. For example, say you’re not a fan of the Kardashians. Because of this, your perception of any idea they support will be tarnished. Multiply that by tens of millions of people.

Surprisingly, the researchers discovered that new and provocative ideas emerge at the edge of networks, from people with fewer contacts and little obvious pull.

The Inevitable Weaponization of App Data Is Here

VICE, Motherboard, Joseph Cox


A Substack publication used location data from Grindr to out a priest without their consent.

For Many Covid Survivors, the Battle Isn’t Over

Dr. Tom Frieden


Although we don’t know for certain how many people are suffering from lasting symptoms, the numbers we do have are striking. Studies suggest it may be between 1 in 10 to more than half of those infected with Covid. In the UK as of June 6, 2021, an estimated 962,000 people (1.5% of the population) reported symptoms persisting more than four weeks after their suspected infection, with 178,000 (18.5%) reporting that their ability to undertake day-to-day activities had been “limited a lot” by their symptoms. Further, 385,000 people reported ongoing symptoms more than a year after their initial Covid illness. Even with so many people suffering from long Covid, many questions remain unanswered.

People with lasting symptoms, who may be known as long haulers, have formed online groups such as the Body Politic COVID-19 Support Group, and launched patient-led research initiatives in an attempt to find answers to their unresolved questions about the illness. Their efforts increased scientific, medical and public recognition of the phenomenon of persistent health problems among Covid survivors and coined the now widely-used term “long Covid.”

AI and the COVID-19 Vaccine: Moderna’s Dave Johnson

MIT Sloan Management Review; Me, Myself, and AI podcast, Sam Ransbotham


“We tend not to be a company of half measures,” notes Dave Johnson, chief data and artificial intelligence officer at Moderna, “so when we decide we’re going to do something, we’re going to do it.” This characterization certainly seems to fit the Cambridge, Massachusetts-based biotech company that made a name for itself in 2020 upon releasing one of the first COVID-19 vaccines approved by the U.S. Food and Drug Administration for emergency use to combat the coronavirus.
Dave Johnson

Dave Johnson, Moderna

Dave Johnson is chief data and artificial intelligence officer at Moderna, where he is responsible for all enterprise data capabilities, including data engineering, data integration, data science, and software engineering. Johnson earned a doctorate in information physics and has more than 15 years of experience in software engineering and data science. He has spent more than a decade working exclusively in enterprise pharma and biotech companies.

In this bonus episode of the Me, Myself, and AI podcast, our hosts learn how Moderna used artificial intelligence to speed up development of the vaccine and how the technology has helped to automate other key systems and processes to build efficiencies across the organization. Dave also describes Moderna’s digital-first culture and offers insights around collaboration that can be applied across industries.

Joe and Clara Tsai Foundation commits $220M to Wu Tsai Human Performance Alliance

ESPN, Stephania Bell


… “When you’re close to these athletes and you see what they’re going through, you start to wonder, ‘How could that have been prevented? What is the right time to return to play? What is the correct kind of healing, including diet, including timing, including sleep?” Wu Tsai said. “And if it’s not science-based, then it becomes anecdotal and it’s less reliable. I think we want to put that scientific rigor into it so the regimens we put them through can become standard.

“Seeing how devastating these injuries can be for athletes as individuals but also to the team in general, we just felt that this was a role where we should step up.”

With a $220M philanthropic investment from the foundation, the Alliance will pursue a set of scientific “moonshots” to uncover the fundamental principles of human performance and pioneer new technologies to transform how people train, heal and perform throughout their lifespan. By comprehensively studying athletes of various ages, genders, ethnicities, abilities and disciplines, the goal is to discover the biological principles that govern optimum performance, from the molecular level to the whole body.

An Uncommon Thread – New Ag Data Science Certificate binds grad student’s studies, research, and career prospects

North Carolina State University, CALS News


To say Shelly Hunt is busy would be an understatement. She is a graduate student in biological and agricultural engineering, a team member on a major NC State research project supporting the sweetpotato industry, and a year-round intern at SAS, one of the world’s top data analytics companies.

Hunt is also enrolled in the Ag Data Sciences Certificate program, which she chose to pursue instead of a minor in statistics. So far, the 12-credit program is proving to be the perfect complement to her studies, her field research, and her career goals.

We interviewed Hunt to better understand how this unique certificate is simultaneously solidifying her success as a student, providing an avenue to practice what she is learning, and brightening her prospects for a future career as a data analyst in the agriculture industry.

New USF Institute for Microbiomes created to advance human and environmental health

University of South Florida, USF Health


USF Health today announced the launch of a major university-wide institute dedicated to harnessing the huge populations of bacteria, viruses, fungi and other microbes inhabiting our bodies and our planet – known as microbiomes – to improve health and develop new treatments.

Based at USF Health Morsani College of Medicine, the new USF Institute for Microbiomes builds upon an ambitious microbiome initiative begun two years ago. That USF Initiative on Microbiomes has sparked interdisciplinary collaborations across the university to better understand how the diverse collections of microorganisms, unique to each person, might be exploited to benefit human health. It has also included studies of marine and soil microbial communities, which hold the potential to protect environmental as well as human health by mitigating climate change and food insecurity and generating alternative energy sources.

$1.5 million grant will improve wildfire spotting from the air and space

University of California-Berkeley, Berkeley News


California’s fire season is in full swing and could well be worse than in 2020, but new tools are on the way to help responders more rapidly locate wildfires once they break out and, ideally, quickly extinguish them before they get out of control.

With the help of a $1.5 million grant from the Gordon and Betty Moore Foundation, a University of California, Berkeley, physicist and a firefighter-turned-scientist plan to outfit spotter planes with improved infrared detectors to learn more about how fires spread. And within four years, they hope to send similar systems into space for 24/7 fire discovery and monitoring.

How the National Science Foundation is taking on fairness in AI

The Brookings Institution, Alex Engler


Most of the public discourse around artificial intelligence (AI) policy focuses on one of two perspectives: how the government can support AI innovation, and how the government can deter its harmful or negligent use. Yet there can also be a role for government in making it easier to use AI beneficially—in this niche, the National Science Foundation (NSF) has found a way to contribute. Through a grant-making program called Fairness in Artificial Intelligence (FAI), the NSF is providing $20 million in funding to researchers working on difficult ethical problems in AI. The program, a collaboration with Amazon, has now funded 21 projects in its first two years, with an open
call for applications in its third and final year. This is an important endeavor, furthering a trend of federal support for the responsible advancement of technology, and the NSF should continue this important line of funding for ethical AI.

DeepMind and EMBL release the most complete database of predicted 3D structures of human proteins

European Molecular Biology Laboratory, EMBL News


Partners use AlphaFold, the AI system recognised last year as a solution to the protein structure prediction problem, to release more than 350,000 protein structure predictions including the entire human proteome to the scientific community.

CMU AI, Robotics Team Up With Apple To Improve Device Recycling

Carnegie Mellon University, News


Researchers at Carnegie Mellon University are working with Apple to develop new ways to disassemble old technology.

This builds on Apple’s existing recycling innovations, including its recycling robots Daisy and Dave. As Apple sought to support research initiatives that reimagine disassembly of devices and recovery of materials, the company worked with CMU’s Biorobotics Lab in the Robotics Institute.

Matt Travers and Howie Choset, co-director of the lab, and their team are designing machine learning models that will enable robots to teach themselves how to disassemble a device they have never seen before.

DeepMind’s AI predicts structures for a vast trove of proteins

Nature, News, Ewen Callaway


AlphaFold neural network produced a ‘totally transformative’ database of more than 350,000 structures from Homo sapiens and 20 model organisms.

Seaver College Students Explore Machine Learning, Artificial Intelligence with New Data Science Minor

Pepperdine University, Seaver College


In fall 2021, Seaver College’s Natural Science Division will officially launch the new data science minor for students interested in machine learning, programming, and more. The minor was made possible with support and careful course design by Fabien Scalzo, associate professor of computer science at Seaver College. The minor’s four new courses will be embedded within the college’s computer science program.

Public health’s next shot at fixing its data problem

POLITICO, Future Pulse, Darius Tahir


The modernization efforts actually predate Covid, starting in earnest when congressional appropriators first secured money for updating public health technology in 2019. But the pandemic exposed critical shortcomings, prompting Congress to send additional tranches of health tech dollars in relief packages and annual spending bills. As much as $100 million more is contained in a House health spending bill for fiscal 2022 soon headed to the floor.

The question is whether it will deliver results in time. Some outside experts say the Centers for Disease Control and other agencies have been slow to respond to the newfound largesse. “I’ve seen allocations, such as >$1B for genomic surveillance data, but not a penny put to work,” wrote Eric Topol, founder and director of the Scripps Research Translational Institute, in an email. And funding for public health is often siloed, going to specific diseases rather than overarching technology.

The concern is driven by what experts say is a familiar pattern of throwing lots of money at a crisis, followed by inattention and lapses in resources. “I’m a bit worried [the momentum] will die,” said Shannon Sartin, an executive with CIOX Health who previously worked in government health technology.



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

Achieving Return on AI Projects

MIT Sloan Management Review, Thomas H. Davenport and Ren Zhang


Companies embarking on AI and data science initiatives in the current economy should strive for a level of economic return higher than those achieved by many companies in the early days of enterprise AI. Several surveys suggest a low level of returns thus far, in part because many AI systems were never deployed: A 2021 IBM survey, for instance, found that only 21% of 5,501 companies said they had “deployed AI across the business,” while the remainder said they are exploring AI, developing proofs of concept, or using pre-built AI applications. Similarly, a VentureBeat analysis suggests that 87% of AI models are never put into production. And a 2019 MIT Sloan Management Review/Boston Consulting Group survey found that 7 out of 10 companies reported no value from their AI investments. This makes sense: If there is no production deployment, there is no economic value.

But other companies have achieved economic return on their AI investments. Their strategies for finding value include establishing close relationships between the data group and interested business units, selecting projects with tangible value and a clear path to production, lining up trust from key stakeholders in advance of development, building reusable AI products, selectively employing “proof of concept” projects, and establishing a management pipeline or funnel leading projects toward production implementation. We describe each of these approaches below.

NASA Expands Access to Planet Data to All US Federal Civilian Agencies, Tanya Harrison


We’re excited to announce that NASA has expanded our contract with their Commercial SmallSat Data Acquisition (CSDA) Program to provide access to PlanetScope imagery for scientific research use for all U.S. Federal Civilian researchers and National Science Foundation funded researchers, including their contractors and grantees – roughly 280,000 eligible users. This expands access on the existing contract that currently supports NASA and NASA funded researchers. Since our first contract with NASA in 2019, scientists have leveraged Planet imagery for a variety of research projects focused on climate change, biodiversity loss, and complex sustainability problems. We are eager to see what projects this expanded pool of researchers will pursue, as it will enable more strategic information sharing across research groups and facilitate greater scientific use. Earlier this month, Planet entered into a definitive merger agreement with dMY Technology Group, Inc. IV (NYSE:DMYQ), a special purpose acquisition company, to become a publicly-traded company.

Night Science: The Creative Side of Scientific Research

Medium, NYU Center for Data Science


Where do ideas come from? This is an important question to Itai Yanai, CDS affiliated professor and the Director at the Institute for Computational Medicine at NYU Langone Health. When many people think of science, creativity may not be the first thing that comes to mind. The Professor of Biochemistry and Molecular Pharmacology holds a different perspective, one in which he has started a new podcast, Night Science, to explore. What is night science? As Itai and his podcast co-host and colleague Martin Lercher, describe in their paper by the same name, night science — a term and concept originally coined by French biologist François Jacob — refers to a process where scientists look at “the unstructured realm of possible hypotheses, of ideas not yet fully fleshed out.”

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