In general, those who are most likely to suffer serious consequences due to the illness or perceive the risk of illness to be high are more likely to adopt preventative measures. There’s also evidence that people who are less tolerant of risk — that is, less risk-loving — are more likely to adopt preventative health measures in general. And in the context of infectious diseases, we may expect that people who are more altruistic, or care for their community independent of the benefits to themselves, are more likely to comply. This is because their compliance will reduce transmission, therefore reduces the likelihood of others becoming infected.
These were the main characteristics we focused on in our research, because we expected that they would be predictive of compliance based on the academic literature in other health contexts, as well as from the theoretical foundations of infectious diseases and decision-making. They are also characteristics that we felt were commonly highlighted in conversations and public discourse on assumed motivations for the policy and expected compliance (or lack thereof).
After prototyping and testing a range of new technologies to help tackle food waste and food insecurity, we’re moving to Google to scale up our work
Around the world, 820 million people don’t have access to the food they need, yet one third of the world’s food is wasted. Here in the U.S., the problems are just as stark — 30 to 40 percent of our food supply goes to waste, costing retailers $57 billion annually, while one in eight people in America don’t have enough to eat. This waste isn’t just bad for people and businesses, it’s terrible for our planet too. Enormous amounts of water, fuel, electricity and fertilizer, and human labor are poured into food that never gets eaten and the methane produced from rotting food in landfill is a potent and toxic greenhouse gas.
This was the complex set of challenges Project Delta, our early stage moonshot, set out to solve.
You’ve heard it before, but never like this: The MTA, facing a brutal budget crunch, is threatening apocalyptic cuts to subway service. The proposed plan, as reported by the New York Daily News, would enact a 40 percent cut to weekday subway service, eliminate some weekend service in its entirety, and lay off more than 9,000 workers, primarily from bus and subway service. That’s if the agency doesn’t receive $12 billion in federal aid by the end of 2021 to deal with the financial catastrophe brought on by COVID-19. It’s the type of scare tactic the agency has used in the past — as recently as, oh, August, and during the financial crisis in 2009 — to varying degrees of success. The MTA was forced to make cuts in 2010, including elimination of the W and V trains. The agency restored some of the bus-service cuts two years later, and brought back the W train in 2016. But this time, there’s a real disaster in the making: We’re facing less tactic and more scare.
Queen Mary University of London (UK), News stories
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A major new project led by Queen Mary University of London is transforming the way historians can view the past. Tudor Networks of Power is an innovative project funded by the Arts and Humanities Research Council (AHRC). It is the first of its kind to analyse and visualise communication networks from Tudor times.
Open data has not only played a key role in mitigating the COVID-19 pandemic and will continue to be crucial for the dissemination and uptake of the new vaccines, but it’s also been a core component of the data revolution since its inception. But just how many countries around the world are actively making their data open? Last week, we received a snapshot of countries’ progress with the release of the fifth edition of Open Data Watch’s 2020/21 Open Data Inventory (ODIN 2020/21). ODIN 2020/21 assesses the coverage and openness of official statistics for 187 countries worldwide and includes 22 data categories, grouped under social, economic and financial, and environmental statistics. The edition also features a gender index which scores countries on the availability of 20 indicators in 8 statistical categories, such as reproductive health and education outcomes, that require sex-disaggregated data or apply only to women. Some of the most interesting takeaways from this year’s edition include the following:
The Electronic Privacy Information Center (EPIC) has filed a complaint with the DC Attorney General’s office against five online test-proctoring services: Respondus, ProctorU, Proctorio, Examity, and Honorlock. EPIC claims that the firms violate the privacy rights of students.
The five companies sell software designed to prevent cheating in online tests and exams. Some are designed to track applications that are running on test-takers’ computers or restrict access to certain programs during the testing period. Others track students’ activity during the test via their webcams and microphones and flag potentially suspicious behavior to their instructor, using either algorithms or live monitoring. In some cases, test-takers need to show a proctor their surroundings and verify their identity with personal information before the test can begin.
These methods — the collection of personal information and the use of “secret algorithms” — amount to “unfair and deceptive trade practices,” EPIC argues.
Change Healthcare and Carnegie Mellon University’s Delphi Research Group announced the launch of Delphi’s enhanced COVIDcast real-time COVID-19 indicators.
Since April, Delphi has been collecting real-time data on self-reported COVID-19 symptoms and other disease indicators nationwide. This county-level information about the coronavirus pandemic is updated continuously and shared with both the public and health researchers. Now, COVIDcast is taking a further step by adding de-identified COVID-19 claims from Change Healthcare to its unique combination of survey, testing and mobility data.
“Tracking and forecasting the spread of a novel disease such as COVID-19 is a challenging task that requires new types and sources of data,” said Ryan Tibshirani, an associate professor of statistics who co-directs Delphi with Roni Rosenfeld, head of the Machine Learning Department. “We are always evaluating our data streams and looking at ways of filling gaps in our knowledge. Change Healthcare has stepped up in the biggest way possible to give us crucial information for understanding the current state of the pandemic. We are extremely appreciative of their contributions to our effort.”
The board took action on a new building – the Bridge Complex for the Digital Future – planned for the corner of Jane Stanford Way and Lomita Mall, where Herrin Hall, former home to the Department of Biology, is currently being demolished.
[Jeff] Raikes said the board provided concept and site approval for the new academic building. At future meetings, the board will be asked to consider design approval and then construction approval. The tentative completion date for the project is fall 2023.
The building will be an interdisciplinary hub for computation and data research, providing space for programs in Statistics, Computer Science, Symbolic Systems and related fields.
To ensure that California’s groundwater is sustainably managed in the future and over the long-term, current state definitions of what constitutes groundwater may need to be revised, according to research published this week in PNAS. A McGill University-led research team has analyzed big data of more than 200,000 groundwater samples taken from across the state and found that there are problems with the guidelines used for groundwater management. Known as the ‘Base of Fresh Water’, the guidelines are close to fifty years old and don’t reflect current uses, knowledge, concerns or technologies related to managing groundwater in this coastal state with a multi-billion-dollar agricultural industry.
The research shows that existing groundwater wells already penetrate and encroach upon the bases of fresh water that are used to define basin bottoms. In addition, brackish waters exist within current groundwater basins, and fresh water exists outside delineated groundwater basins. Brackish water, which was once deemed unusable, can now be used, thanks to technological advances. Finally, there are concerns about regulating groundwater on the basis of its quality rather than its usage, as is currently the case, since this provides a loophole for potential groundwater users who could drill deeper and skirt existing restrictions on freshwater pumping.
Next fall, La Salle University’s School of Business will welcome the inaugural cohort of its new Master of Science in Business Systems and Analytics program.
The multi-disciplinary curriculum of this 30-credit graduate-degree program is rooted in management science and operations research, with statistics and information systems serving as other core areas of programmatic focus.
Pacific Northwest National Laboratory, News & Media
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As wildfires burn more often across the Western United States, researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory are working to understand how extensively blazes burn. Their investigation, aided by machine learning techniques that sort fires by the conditions that precede them, not only reveals that the risk of wildfire is rising, but also spells out the role moisture plays in estimating fire risk.
In findings shared virtually at the American Geophysical Union’s 2020 fall meeting on Tuesday, Dec. 1, atmospheric scientists Ruby Leung and Xiaodong Chen detailed their study of decades-long wildfire records and new simulations of past climate conditions, which they used to identify variables that lead to wildfires.
The episode is a pointed reminder of tech companies’ influence and power over their field. AI underpins lucrative products like Google’s search engine and Amazon’s virtual assistant Alexa. Big companies pump out influential research papers, fund academic conferences, compete to hire top researchers, and own the data centers required for large-scale AI experiments. A recent study found that the majority of tenure-track faculty at four prominent universities that disclose funding sources had received backing from Big Tech.
Ben Recht, an associate professor at University of California, Berkeley, who has spent time at Google as visiting faculty, says his fellow researchers sometimes forget that companies’ interest doesn’t stem only from a love of science. “Corporate research is amazing, and there have been amazing things that came out of the Bell Labs and PARC and Google,” he says. “But it’s weird to pretend that academic research and corporate research are the same.”
Ali Alkhatib, a research fellow at University of San Francisco’s Center for Applied Data Ethics, says the questions raised by Google’s treatment of Gebru risk undermining all of the company’s research. “It feels precarious to cite because there may be things behind the scenes, which they weren’t able to talk about, that we learn about later,” he says.
New York University Center for Data Science “is thrilled to once again partner with DeepMind in offering a series of scholarships aimed at increasing representation of underrepresented students in higher education AI programs. Increasing representation in AI is a significant opportunity to bring diverse voices to the conversation, and ultimately shape continuing developments in AI as a technology that benefits everyone.”
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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.
EurekAlert! Science News, Cambridge University Press
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Cambridge University Press is launching a new, Open Access journal – Environmental Data Science – dedicated to the potential of artificial intelligence and data science to enhance our understanding of the environment, and to address climate change.
It will promote interdisciplinary approaches that allow researchers to use insights from the world’s ever-growing store of environmental data to support analysis and inform decision-making.
I generally have lots of ideas when I’m thinking about machine learning. I dream up new architectures and new methods all the time, but often find myself with a combinatorial explosion of ideas to test.
If you’re a researcher, there are likely 5–10 different ideas you are working with in your head at any one time. Within just one of those ideas, are probably 5–10 more variations or offshoots of the idea.
In this article, I introduce a framework that I use to help me prioritize and most importantly, execute, my ideas. I hope that this framework will help you be more successful, whether you are an independent researcher, a working data scientist or machine learning engineer, or a researcher at an institution.
