The Tampa air was a breezy 63 degrees at kickoff for Super Bowl LV, but Dr. Christina Mack, an epidemiologist who led the NFL’s COVID-19 contact tracing efforts this season, needed a heavier jacket.
“I had chills when I saw [the] kickoff,” said Mack, an adviser to the NFL for the past decade and the vice president of epidemiology and clinical evidence at IQVIA.
The Super Bowl was the culmination of an extraordinary effort from the NFL’s medical community throughout the 2020 season. Aaron Rodgers may have been the NFL’s MVP, but the league’s medical personnel were the real stars this season.
The “6G and the Future of the Internet” online panel that featured Cerf (since 2005, a VP and the chief internet evangelist at Google) didn’t put 6G in much of a sharper focus. Instead, he used the event hosted by the nonprofit research organization Mitre to suggest two other pieces of technology that play a critical role in the internet’s future: low-Earth-orbit satellites and undersea cables.
TL;DR: time of use rates are, on net, a Good Thing; markets are great, except when they fail; low risk isn’t the same as no risk; we’re dealing with a homicidal planet of our own creation; grids are incredibly complex, the people running them are generally competent professionals, and we should mostly be in awe that it all works in the first place.
Stowers Institute for Medical Research, News & Media
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“We had these beautiful data from many studies,” explains Julia Zeitlinger, PhD, study lead and Stowers investigator. The Zeitlinger Lab had pioneered ChIP-nexus, a protocol that generates high-resolution profiles on what is happening on regulatory DNA. In particular, it reveals footprints of specialized proteins called transcription factors bind DNA, right down to the specific DNA base-pairs. “We could see in the binding profiles of many experiments that transcription factors were interacting, but with the limited computational tools we had, we couldn’t identify the DNA sequence patterns that promoted these interactions. It was very frustrating.”
“We knew that there are patterns to be found,” adds Melanie Weilert, second author on the paper and a bioinformatician in the Zeitlinger Lab. “The problem is that these patterns are so complex, that one postdoc staring at a computer for four years is not even going to begin to uncover the complexity of the nature of some of these sequences.”
The U.S. and allies are using a new forum started by the Pentagon’s top artificial intelligence office to work toward developing AI systems that can connect in the future to help them fight better together.
The Partnership for Defense, started by the Joint Artificial Intelligence Center last September, is laying the groundwork for future AI-enabled joint war-fighting capabilities that will need to connect to each other for the U.S. and its allies to effectively fight as a coalition.
One day, the countries could collaborate on other AI-backed efforts, such as sharing data from sensors that track how machines run to predict when maintenance is needed before parts fail, possibly during a mission when there’s no time to lose for repairs or replacements. Or the allies could use AI for data about shipping and supply movements to improve logistics efficiency.
The end goal is for the allied nations to be ready to cooperate easily on AI-driven projects in the future.
World Economic Forum, Adriana Bora and David Alexandru Timis
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The AI integration within industry and society and its impact on human lives, calls for ethical and legal frameworks that will ensure its effective governance, progressing AI social opportunities and mitigating its risks. There is a need for sound mechanisms that will generate a comprehensive and collectively shared understanding of AI’s development and deployment cycle. Thus, at its core, this governance needs to be designed under continuous dialogue utilizing multi-stakeholder and interdisciplinary methodologies and skills.
Yet, this dialogue is hampered by the fact that creators of AI technology have all the information and understanding of the subject, while policymakers trying to regulate it often have very little. On the one hand, there is a limited number of policy experts who truly understand the full cycle of AI technology. On the other hand, the technology providers lack clarity, and at times interest, in shaping AI policy with integrity by implementing ethics in their technological designs (with, for example, ethically aligned design).
The National Science Foundation (NSF) could receive an additional $600 million as part of the massive coronavirus pandemic relief bill moving through Congress this week.
The money is not mentioned in the $1.9 trillion plan being taken up today by the budget committee in the U.S. House of Representatives. But ScienceInsider has learned it is expected to be added to the legislation before the full House votes on the package later this week. The National Institute of Standards and Technology (NIST) would get a one-time budget increase of $150 million. The money comes from a $750 million allocation made available to the House science committee, led by Representative Eddie Bernice Johnson (D–TX), for programs under its jurisdiction.
Under the terms of the overall relief package, the two agencies would be required to use the one-time bonanza to help the nation recover from the devastating impact of the pandemic, including damage to its science and technology enterprise. At NSF, whose current budget is $8.2 billion, the new money is likely to be spent on more research on pandemic-related topics, as well as more support for educating the next generation of scientists and engineers. The funds for NIST, which now has a budget of $1 billion, are expected to bolster its network of manufacturing research institutes.
These twin phenomena — an admissions standstill and a shaken-up research enterprise — might seem relatively minor when set against what else the pandemic has wrought. Budgetary carnage. Possible college closures. Downstream threats to college completion.
But, surveying the years following the pandemic, observers of graduate education acknowledge an alarming possibility: that, in the United States, frozen admissions, curtailed graduate cohorts, and stalled-out research could severely squeeze the ranks of professional researchers for at least the short term, and maybe longer.
In other words, the pandemic may have set about a shrinking of the scholar class.
“The way that we’re testing fairness in algorithms doesn’t really ensure fairness for all,” [Zaid] Khan says. “It may only ensure fairness in the vague, stereotypical sense of fairness.”
What it comes down to, he explains, is how a computer vision algorithm learns to identify people of different races. Like other artificial intelligence systems, a computer vision algorithm is tasked with learning to identify patterns by studying a massive dataset in a process called machine learning. Every image in the dataset is given a label to identify the subject’s race. In theory, the programmers can then ensure adequate representation among all racial groups.
“People depend on these datasets to make sure that their algorithms are fair,” Khan says. So he decided to test the datasets himself. And he found that the racial labels themselves seem to encode the very biases they’re designed to avoid.
Khan wrote his own algorithms and used four different datasets that are considered benchmarks for fairness in the industry to train those computer vision systems to classify images of people according to race. He found that while the classifier algorithms developed using different datasets agreed strongly about the race of some individuals depicted, they also disagreed strongly about others.
What steps has the University Privacy Office taken recently to help protect privacy at Stanford?
We recently developed the Stanford Minimum Privacy Standards – or MinPriv, for short. These are a set of fundamental standards for how all personal data at Stanford should be treated. All of us in the Stanford community share a responsibility in protecting personal information that we access in our daily lives; and MinPriv is a simple way for all faculty, staff and students to align with our expectations and follow privacy best practices.
As new privacy risks arise with evolving technologies like artificial intelligence, machine learning and facial recognition, we need simple “rules of the road” like MinPriv that everyone can easily understand and use to handle data responsibly. The University Privacy Office also provides guidance on novel uses of data and other topics significantly affecting the university community.
A new multidisciplinary collaboration between the University of Rochester’s departments of biology, biomedical engineering, and optics and the Goergen Institute for Data Science will establish an innovative microscopy resource on campus, allowing for cutting-edge scientific research in biological imaging.
Michael Welte, professor and chair of the Department of Biology, is the lead principal investigator of the project, which was awarded a $1.2 million grant from the Arnold and Mabel Beckman Foundation.
“The grant supports an endeavor at the intersection of optics, data science, and biomedical research, and the University of Rochester is very strong in these areas,” Welte says. “The University has a highly collaborative culture, and the close proximity of our college and medical center makes Rochester ideally suited to lead advances in biological imaging.”
Northeastern University’s Roux Institute is launching an accelerator program to bring startup companies to Portland, Maine, and help them build their businesses in the region. Together with Techstars, a leading accelerator provider and global network that helps entrepreneurs succeed, they are creating The Roux Institute Techstars Accelerator, an immersive entrepreneurship program to help startups grow their businesses, attract investors, build partnerships, and strengthen the regional economy.
The newly opened Interdisciplinary Science and Engineering Building at the University of California, Irvine was conceived with one goal in mind: providing a place where researchers in disparate academic fields could work together to address grand challenges, principally in human health and the planet’s climate crisis.
Faculty, students and staff are now moving into the facility after three and a half years of construction. Made possible by seed financing from Susan and Henry Samueli, through the Samueli Foundation, combined with resources from the UC Office of the President and UCI, the gleaming, six-story edifice of glass, steel and concrete adds more than 200,000 square feet of laboratory, office and meeting space to the university.
But algorithmic auditors were also displeased about HireVue’s public statements on the audit.
“In repurposing [ORCAA’s] very thoughtful analysis into marketing collateral, they’re undermining the legitimacy of the whole field,” Liz O’Sullivan, co-founder of Arthur, an AI explainability and bias monitoring startup, said.
And that is the problem with algorithmic auditing as a tool for eliminating bias: Companies might use them to make real improvements, but they might not. And there are no industry standards or regulations that hold the auditors or the companies that use them to account.
Good question—it’s a pretty undefined field. Generally, audits proceed a few different ways: by looking at an algorithm’s code and the data from its results, or by viewing an algorithm’s potential effects through interviews and workshops with employees.
Online March 6-14. “Every year, New Yorkers come together all across the boroughs to celebrate New York City’s Open Data Law, which was signed into law on March 7, 2012. Coincidentally, the first weekend of March is also International Open Data Day. Together, we use both dates to anchor NYC’s Open Data Week and increase civic engagement with our municipal open data.” [registration required]
Online March 30. “Open Source 101 is a one-day conference featuring 10, 45 and 90 minute live talks covering the “basics” of open source. While many believe “everyone knows the basics” and can effectively contribute and consume, we disagree based on more than a decade of feedback and input from our community.” [free, registration required]