Half of the newly promised $200 million from the Benioffs will go to 1t.org, a project of the World Economic Forum launched in January 2020 to “conserve, restore and grow” one trillion trees globally by 2030. The Benioffs previously donated an undisclosed amount to launch 1t.org. Though many areas of the world can benefit from more trees, some critics say that tree planting may be more hype than solution.
The other $100 million is an impact investment rather than a donation; the Benioffs’ Time Ventures fund will back “ecopreneurs” launching companies that do things like reduce emissions, sequester carbon and protect natural resources. The couple’s Time Ventures fund has previously invested $100 million in climate-focused startups such as earth imaging firm Planet and renewable bioproducts firm Mango Materials. It’s unclear what the time horizon is for investing the newly promised $100 million sum.
The Health Insurance Portability and Accountability Act, known as HIPAA, protects individuals’ medical information when it’s handled by doctors, hospitals, and health insurance companies. This applies to genetic tests ordered by your doctor but not to those you can buy online directly from companies like 23andMe and Ancestry because these kits aren’t considered medical tests. As a result, the companies have largely operated in a legal gray area. Firms write their own privacy policies that customers agree to when they purchase a kit, but the companies can change these policies at any time.
That’s a problem, since genetic data can reveal all sorts of sensitive information about you—your ethnicity, your family connections, and even your likelihood of developing Alzheimer’s disease or certain cancers. Law enforcement officers are increasingly using consumer genetic databases to investigate violent crimes.
But a growing number of states are adopting genetic privacy laws in an effort to close these gaps.
Bulletin of Atomic Scientists, Yale Environment 360, Saul Griffith
from
For too long, the climate solutions conversation has been dominated by the supply-side view of the energy system: What will replace coal plants? Will natural gas be a bridge fuel? Can hydrogen power industry? These are all important questions, but, crucially, they miss half the equation. We must bring the demand side of our energy system to the heart of our climate debate.
The demand side is where humans, households, and voters live. It is where we use machines on a daily basis, and where the choices about what kind of machines we use—whether powered by fossil fuels or electricity—make our climate actions and climate solutions personal. We don’t have a lot of choice on the supply side, but we have all of the choice on the demand side. For the most part, we decide what we drive, how we heat our water, what heats our homes, what cooks our food, what dries our laundry, and even what cuts our grass. This constitutes our “personal infrastructure,” and it is swapping out that infrastructure that will be a key driver of the global transition from fossil fuels to green energy.
“I don’t know much about whales. I have never seen a whale in my life,” says Michael Bronstein. The Israeli computer scientist, teaching at Imperial College London, England, might not seem the ideal candidate for a project involving the communication of sperm whales. But his skills as an expert in machine learning could be key to an ambitious endeavor that officially started in March 2020: an interdisciplinary group of scientists wants to use artificial intelligence (AI) to decode the language of these marine mammals. If Project CETI (for Cetacean Translation Initiative) succeeds, it would be the first time that we actually understand what animals are chatting about—and maybe we could even have a conversation with them.
It started in 2017 when an international group of scientists spent a year together at Harvard University in Cambridge, Massachusetts, at the Radcliffe Fellowship, a program that promises “an opportunity to step away from usual routines.” One day, Shafi Goldwasser, a computer scientist and cryptography expert also from Israel, came by the office of David Gruber, a marine biologist at City University of New York. Goldwasser, who had just been named the new director of the Simons Institute for the Theory of Computing at the University of California, Berkeley, had heard a series of clicking sounds that reminded her of the noise a faulty electronic circuit makes—or of Morse code. That’s how sperm whales talk to each other, Gruber told her.
Child psychiatric disorders, such as oppositional defiant disorder and attention-deficit/hyperactivity disorder (ADHD), can feature outbursts of anger and physical aggression. A better understanding of what drives these symptoms could help inform treatment strategies. Yale researchers have now used a machine learning-based approach to uncover disruptions of brain connectivity in children displaying aggression.
While previous research has focused on specific brain regions, the new study identifies patterns of neural connections across the entire brain that are linked to aggressive behavior in children. The findings, published in the journal Molecular Psychiatry, build on a novel model of brain functioning called the “connectome” that describes this pattern of brain-wide connections.
Thanks to a $1.95 million grant from the Air Force Office of Scientific Research, Markos Katsoulakis and Luc Rey-Bellet, both professors in the mathematics and statistics department at the University of Massachusetts Amherst, and Paul Dupuis, of Brown University, will spend the next four years developing a new approach to machine learning that extends beyond the traditional reliance on big data.
Traditional machine learning relies on enormous caches of data that an algorithm can sift through in order to “train” itself to accomplish a task, resulting in a data-based mathematical model. But what about situations for which there is very little data, or when generating enough data is prohibitively expensive? One possible, emergent remedy—often referred to as scientific machine learning—is to incorporate into the algorithms expert knowledge gained from years of scientific research in developing physical principles and rules.
Researchers at MIT and elsewhere launched a research project to identify and tackle machine learning usability challenges in child welfare screening. In collaboration with a child welfare department in Colorado, the researchers studied how call screeners assess cases, with and without the help of machine learning predictions. Based on feedback from the call screeners, they designed a visual analytics tool that uses bar graphs to show how specific factors of a case contribute to the predicted risk that a child will be removed from their home within two years.
The researchers found that screeners are more interested in seeing how each factor, like the child’s age, influences a prediction, rather than understanding the computational basis of how the model works. Their results also show that even a simple model can cause confusion if its features are not described with straightforward language.
Dartmouth University, The Dartmouth student newspaper, Taylor Haber
from
The College’s endowment will no longer be directly invested in fossil fuels and the Dartmouth Investment Office intends to allow its remaining public holdings in the sector to expire, according to an Oct. 8 announcement.
Although this release marks the College’s first formal announcement of its divestment plan, the DIO banned fossil fuel holdings in 2020.
Quantum entanglement—or what Albert Einstein once referred to as “spooky action at a distance”— occurs when two quantum particles are connected to each other, even when millions of miles apart. Any observation of one particle affects the other as if they were communicating with each other. When this entanglement involves photons, interesting possibilities emerge, including entangling the photons’ frequencies, the bandwidth of which can be controlled.
Researchers at the University of Rochester have taken advantage of this phenomenon to generate an incredibly large bandwidth by using a thin-film nanophotonic device they describe in Physical Review Letters.
World Economic Forum, Times Higher Education, Ellie Bothwell
from
With the 2021 United Nations Climate Change Conference (COP26) rapidly approaching, and the warning klaxon on the climate emergency getting ever louder, a new report from Times Higher Education (THE) examines how well higher education institutions across the globe are performing when it comes to reducing their own greenhouse gas emissions and transitioning to net zero.
The report is linked to THE’s Impact Rankings, which are focused on understanding the progress higher education is making against all 17 of the United Nations’ Sustainable Development Goals (SDGs). Titled ‘The race to net zero: How global universities are performing’, it takes a magnifying glass to the 566 universities that have submitted data against SDG 13, which is a call to take urgent action to combat climate change and its impacts.
Soil may be one of the best tools we have to tackle climate change, if we can curtail the vast amounts of greenhouse gas it emits into the atmosphere, suggest a group of researchers writing in Nature Food.
They’ve created a comprehensive map that identifies dozens of global hotspots where we could do that, to bring agriculture in line with climate targets. Intriguingly, they find that cutting emissions across just 20% of global cropland where fertilizers are prevalent could achieve the majority of reductions we need to reach that goal—while leaving food production unchanged.
The state’s flagship school doesn’t have any dedicated space for the thousands of students who want to study computer science and be part of the next big development. … It’s an acute problem for the biggest major on campus and in a state where the tech economy is the fastest growing in the country, according to one recent report. With the expansion of Silicon Slopes, it’s become a $20-billion-a-year industry here. … The U. is working on a solution now that, like a computer, will involve some 1s and 0s. It announced last week that it received a $15 million donation as the starting funds to construct a $120 million building to finally house computer science
Amazon and UCLA have collaborated to establish the Science Hub for Humanity and Artificial Intelligence, marking the technology company’s first such alliance with a public university.
Based at the UCLA Samueli School of Engineering, the research hub will aim to leverage the cross-pollination of industry and academic research on artificial intelligence to address society’s most pressing challenges and develop solutions that will ultimately benefit humanity. The collaboration will support doctoral fellowships, research projects and community outreach programs.
Financial incentives and other nudges by local governments and employers have failed to increase Covid-19 vaccinations among Americans who are hesitant about getting the shot, a new study shows.
What’s more, financial incentives and “negative messages” actually decreased vaccination rates among some groups, underscoring fears about a public backlash, according to the paper circulated by the National Bureau of Economic Research.
“The AI on the Ground Initiative invites applications for Data & Society’s academic workshop, The Social Life of Algorithmic Harms.” Deadline for applications is November 29.
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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.
Anaconda, Inc. announced a collaboration with Microsoft to enable customers to confidently access Anaconda’s curated library of open-source packages within Microsoft Cloud-hosted products and services, including Azure services like Azure Machine Learning, as well as GitHub services such as GitHub Codespaces and GitHub Actions, without the requirement of a separate license.
Sponsoring someone is often presented as a one-off act; provide them with an opportunity, whether that be in the form of an award, a talk at a conference or a promotion, and your responsibility ends. But you might limit what they achieve if you do not take the extra step of fully preparing them for their opportunity. It is not enough to nominate someone: you need to support them through the process.
