During its pandemic season, the National Football League found that people can transmit the coronavirus in fewer than 15 minutes of interaction with others, according to a new report published Monday by the CDC.
Four major factors played into COVID-19 transmission: whether masks were worn, how well the room was ventilated, how long the interaction lasted and the distance between the people.
“The most impactful interventions were universal use of face masks, holding meetings outside and minimizing in-person meetings, closing dining rooms — those all have broad applicability outside of football,” Allen Sills, MD, the NFL chief medical officer, told NFL.com.
There’s no one-size-fits-all diet. If you want to avoid spiking your blood sugar with a snack, a banana may seem like a better choice than a sugary cookie. But some people in a 2015 study of 800 Israeli volunteers got their biggest blood sugar spike from bananas or bread instead of from sugar-laden baked goods. And as nutrition scientist Elizabeth Parks of the University of Missouri, Columbia, notes, “We all know people who lose weight easily, and others who don’t.”
Now, the U.S. National Institutes of Health (NIH) is making a major push to understand these individual differences. Last week, the agency announced what it calls the largest study yet to probe “precision nutrition,” a $156 million, 5-year effort to examine how 10,000 Americans process foods by collecting data ranging from continuous blood glucose levels to microbes in a person’s gut.
The study “has the potential to truly transform the field of nutrition science,” generating new tools, methods, and “a wealth of data to fuel discovery science for years to come,” Griffin Rodgers, director of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), said last year at an NIH board meeting where he introduced the project. Ultimately, it might enable nutritionists to tailor diets to an individual’s genes and microbiome.
What kind of government regulation, industry standards, or internal business policy is needed for algorithm auditing startups to succeed? And how can they maintain independence and avoid becoming co-opted like some AI ethics research and diversity in tech initiatives have in recent years?
To find out, VentureBeat spoke with representatives from bnh.ai, Parity, and ORCAA, startups offering algorithm audits to business and government clients.
Apps are a central part of our lives. We use them for navigation, fitness, work, gaming, and more—88% of U.S. smartphone usage takes place inside of apps. Increasingly, we’re compelled to install apps for travel, banking, and health records—including Covid-19 vaccine passports. The entertainment and utility provided by smartphone apps, however, is often tarnished by deep privacy issues.
Today, the ExpressVPN Digital Security Lab is shining a light on a pervasive problem that has a tangible effect on human rights: Location tracking of consumers via smartphone apps. We call this effort “Investigation Xoth” (a nod to the intelligence group in Cory Doctorow’s Attack Surface). Though location-tracking methods can be reminiscent of science fiction, they are unfortunately all too real. We identified location tracker SDKs in 450 apps, which have been downloaded at least 1.7 billion times. This threatens not only the privacy of ordinary people around the globe but also their autonomy.
Leonid Tiokhin, a metascientist at Eindhoven University of Technology, learned early on to fear being scooped. He recalls emails from his undergraduate adviser that stressed the importance of being first to publish: “We’d better hurry, we’d better rush.”
A new analysis by Tiokhin and his colleagues demonstrates how risky that competition is for science. Rewarding researchers who publish first pushes them to cut corners, their model shows. And although some proposed reforms in science might help, the model suggests others could unintentionally exacerbate the problem.
Thanks to its association with the attack on the U.S. Capitol, Parler, a social media network popular with supporters of former President Trump, became a household name just in time to vanish from the web. In that narrow window between Jan. 6 and Jan. 10, between the attack and Amazon’s decision to pull the hosting services on which the app relied, an independent researcher who goes by @donk_enby moved to copy as much of the site’s data as she could—preserving a critical body of knowledge about what, exactly, happened at the Capitol. That archive has now underpinned a wave of revealing data journalism, including an extensive ProPublica analysis of live video from the event and a detailed Gizmodo map of the location metadata tied to those posts. But the initial collection effort was shadowed by misconceptions about how archivists were able to access so much of Parler’s data, prompting some too-casual intimations that the app was “hacked”—especially insofar as donk_enby obtained data that the app’s users believed they had deleted.
It’s worth handling carefully the sort of language that can get a person sued or prosecuted, and the Justice Department has, in fact, tried unsuccessfully to prosecute similar conduct under the federal anti-hacking statute: the Computer Fraud and Abuse Act (CFAA). But what donk_enby seems to have done was really just scraping—automating the collection of the same information that a user with no special privileges could have retrieved by hand—and it can’t be said often or clearly enough that scraping is not a crime.
It’s not clear yet that mapping is big business, but it’s quite clear that big business is mapping. The most popular thing I’ve ever written is a piece about the incredible year OpenStreetMap is having, largely because of enormous investment from Facebook, Apple, Amazon, Microsoft, and Mapbox (FAAMm).²
Google’s slight advantage in terms of navigation and foundational features may well be overtaken by the collective effort of their deep-pocketed competitors.
Facebook and Apple’s fight over your data is heating up. Apple’s tracking-optional mobile operating system update is coming to iPhones this spring, and the new privacy-preserving features will give users the ability to opt out of being followed around the internet via trackers in their apps. Facebook — which makes the vast majority of its money from data collected through those trackers — really doesn’t like Apple’s new features. Now Facebook is considering suing Apple, and Apple is digging in its heels.
In this Article, Professor Daniel Solove deconstructs and critiques the privacy paradox and the arguments made about it. The “privacy paradox” is the phenomenon where people say that they value privacy highly, yet in their behavior relinquish their personal data for very little in exchange or fail to use measures to protect their privacy. … Professor Solove argues instead that the privacy paradox is a myth created by faulty logic. The behavior involved in privacy paradox studies involves people making decisions about risk in very specific contexts. In contrast, people’s attitudes about their privacy concerns or how much they value privacy are much more general in nature. It is a leap in logic to generalize from people’s risk decisions involving specific personal data in specific contexts to reach broader conclusions about how people value privacy.
In Los Angeles County, Latino residents face the deadliest risk from COVID-19. Black and Asian residents are also dying at higher rates than white residents. And the poorer you are, the greater your risk of dying from the virus, according to LA County public health data. Housing is one factor contributing to these deep disparities.
Across the country, Latino, Asian and Black residents are all more likely to live in multigenerational households than white people, according to a study by the Pew Research Center. And in homes with at least three generations of family members, vulnerable older residents risk exposure from younger relatives.
Separately, Los Angeles is also one of the country’s most overcrowded housing markets. Overcrowding, which the federal government defines as having more people than rooms (minus bathrooms) sharing a home, can make COVID-19 outbreaks more difficult to contain because of the lack of space to isolate.
It’s not a stretch to say that we live in a microbial world. Microbes can make us sick (as they are demonstrating right now), lead the way for medicines like targeted therapeutics and probiotics, and are crucial to almost every biological ecosystem. But there is much we don’t understand about them, so one group of researchers has taken a deeper look at one of the world’s most compact and dense bacterial hot spots: the human mouth.
In a study published last month in Genome Biology, a team of Harvard-led researchers used a recently developed technique combining state-of-the-art genetic sequencing and analysis to get an up-close look at the mouth and the ecosystem of microbial communities living within it, including those that cannot be cultured.
In response to this admissions report and widening attention being paid to issues of diversity in higher education, a group of graduate students from the Department of Earth Sciences at Oxford decided to initiate a student-led diversity audit.
Our aim in executing this audit was to empower students in our community to raise issues that they saw or experienced at the university that burdened ethnic minority students, without the expectation that those students would be required to enact these solutions themselves. Instead, our team would assess the responses and offer suggestions to the faculty with some direction for how they could implement each solution. Key to this plan was engaging white students to assist with brainstorming and developing ideas and in making an extra effort to encourage fellow allies to attend.
We approached this effort from the point of view of concerned graduate students, rather than experts in diversity, equity, and inclusion. As such, we offer this as an example of an experimental project, which has sparked progress from our department so far.
It’s called “chegging.” College students everywhere know what it means. “If I run out of time or I’m having problems on homework or an online quiz,” says Matt, a 19-year-old sophomore at Arizona State, “I can chegg it.”
He means he can use Chegg Study, the $14.95-a-month service he buys from Chegg, a tech company whose stock price has more than tripled during the pandemic. It takes him seconds to look up answers in Chegg’s database of 46 million textbook and exam problems and turn them in as his own. In other words, to cheat.
The Arkansas Higher Education Coordinating Board (AHECB) has approved Arkansas State University’s proposal to offer a new bachelor of science degree program in data science and data analytics.
The need for data scientists and data analysts within the state and nation is growing extremely fast, as recognized in 2017 by Gov. Asa Hutchinson when he constituted a blue ribbon commission to report on “the economic competitiveness of Arkansas in data analytics and computing.”
Rice University is launching a master’s degree program in data science with online and on-campus options.
The Master of Data Science program offers recent graduates and professionals a Rice degree that will enhance their current careers or help them pivot to new ones. The degree is offered through the George R. Brown School of Engineering and managed by the Department of Computer Science, which is ranked as one of the nation’s top 20 by U.S. News & World Report. Applications are now open and classes begin this fall.
“The new fellowship, which will provide 3-year fellowship opportunities for new Ph.D. students in the computing disciplines, was released in response to the increased demand for people with a Ph.D. in computer science (CS), the continued decrease of domestic students pursuing research and completing a Ph.D., and the overall small number of bachelor’s degree recipients in CS pursuing graduate school.” Deadline for applications is April 13.
“a workshop at #cvpr2021 focused on computer vision for making the visual world accessible to people who are blind — includes both a captioning and question answering challenge” Deadline for submissions is May 21.
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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.
There is a secret that needs to be understood in order to write good software documentation: there isn’t one thing called documentation, there are four.
They are: tutorials, how-to guides, technical reference and explanation. They represent four different purposes or functions, and require four different approaches to their creation. Understanding the implications of this will help improve most documentation – often immensely.
