The Boston Globe, Rebecca Ostriker and Deirdre Fernandes
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A financially troubled Chinese real-estate developer has reneged on a major pledge to Harvard University,leaving a shortfall of millions of dollars for a major COVID-19 research effort involving hundreds of experts from academia and industry across Massachusetts.
Higher education stands to be a big winner in the budget proposal unveiled Monday by California Governor Gavin Newsom. With California’s coffers flush with cash and increased reserves, the Governor’s recommended budget includes five years of annual 5% increases in base support for the University of California and California State University, and it promises about $1.6 billion in new money for California’s community colleges.
Newsom’s proposal comes with a catch: the institutions will need to make progress on a number of outcome priorities they’ve agreed to address over the coming years. Those goals are aimed in part at attaining 70% of working-aged Californias holding a college degree or certificate.
The trade org describes itself as the “big tent” where all tiers of the online advertising ecosystem gather to establish rules of engagement; it expanded its membership still further in December, allowing agencies to join its board for the first time.
Its working model has yielded some accomplishments, including the establishment of the real-time bidding protocol, plus agreeing on standards over whether ads served were actually viewed by consumers.
But the IAB’s membership model also gives Big Tech players, primarily Google and Facebook, a place at the table (some would argue an outsized one) when it comes to formulating such standards. And in recent years smaller players among its number have grown to question whether they get their money’s worth in return for their membership dues.
Think your bishop’s opening, queen’s gambit, and pawn play are unique? A new artificial intelligence (AI) algorithm has got your chess style pegged. AI software can already identify people by their voices or handwriting. Now, an AI has shown it can tag people based on their chess-playing behavior, an advance in the field of “stylometrics” that could help computers be better chess teachers or more humanlike in their game play. Alarmingly, the system could also be used to help identify and track people who think their online behavior is anonymous.
“Privacy threats are growing rapidly,” says Alexandra Wood, a lawyer at the Berkman Klein Center for Internet & Society at Harvard University. She says studies like this one, when conducted responsibly, are useful because they “shed light on a significant mode of privacy loss.”
Using artificial intelligence and machine learning, LSU professor Hartmut Kaiser is joining up with a team of scientists to help communities near the coast better prepare for flooding.
Kaiser, an adjunct professor in the Division of Computer Science, is working with scientists from three other universities on a project titled ‘MuSiKAL’ that will help predict coastal flooding with better accuracy.
Kaiser said the Gulf of Mexico is ideal for research on protecting coastal watershed parishes and counties. More than half the U.S. population lives in those areas, and they generate about 58 percent of the country’s gross domestic product, he said.
On a cloudless morning last May, a pilot took off from the Niagara Falls International Airport, heading for restricted military airspace over Lake Ontario. The plane, which bore the insignia of the United States Air Force, was a repurposed Czechoslovak jet, an L-39 Albatros, purchased by a private defense contractor. The bay in front of the cockpit was filled with sensors and computer processors that recorded the aircraft’s performance. For two hours, the pilot flew counterclockwise around the lake. Engineers on the ground, under contract with DARPA, the Defense Department’s research agency, had choreographed every turn, every pitch and roll, in an attempt to do something unprecedented: design a plane that can fly and engage in aerial combat—dogfighting—without a human pilot operating it.
The exercise was an early step in the agency’s Air Combat Evolution program, known as ACE, one of more than six hundred Department of Defense projects that are incorporating artificial intelligence into war-fighting. This year, the Pentagon plans to spend close to a billion dollars on A.I.-related technology. The Navy is building unmanned vessels that can stay at sea for months; the Army is developing a fleet of robotic combat vehicles. Artificial intelligence is being designed to improve supply logistics, intelligence gathering, and a category of wearable technology, sensors, and auxiliary robots that the military calls the Internet of Battlefield Things.
My newest book for kids and teens, Welcome to the Future: Robot Friends, Fusion Energy, Pet Dinosaurs and More, explores how ten different technologies could change the world in the future, starting with robot servants and ending with superintelligence. My job when I begin to write a new article or book, including this one, is to work towards understanding the topic as completely as I can. I care very much about giving kids accurate information. With very technical topics, such as artificial neural networks, grasping the concepts poses a huge challenge! On several occasions throughout my career, I’ve realized that I’d been thinking about things all wrong.
I’d like to share some of the new understandings I’ve come to about AI and cognitive science along the way, as well as what changed my mind or shifted my perspective. I hope these pointers help when you are communicating about AI to those who aren’t experts.
In June 2020, a NOAA review panel found that Neil Jacobs, an atmospheric scientist and the agency’s acting administrator, and Julie Roberts, its deputy chief of staff and communications director, had “engaged in misconduct intentionally, knowingly or in reckless disregard” for the agency’s scientific-integrity policy by backing Trump’s incorrect assertion.
The incident, dubbed Sharpiegate, features in ‘Protecting the Integrity of Government Science’, a long-awaited report that the Biden administration’s Task Force on Scientific Integrity released last week (see go.nature.com/3ztsjv6; see also Nature 601, 310–311; 2022). Ordered by the current US president seven days after his inauguration in January last year, the task force’s review of scientific-integrity policies at federal agencies sets out how trust in government can be restored through scientific integrity and evidence-based policymaking.
The report calls for an overarching body that works across federal government agencies to ensure and promote best practices, and to tackle scientific-integrity violations by senior officials that cannot be handled at the agency level. These include political interference and suppression or distortion of data.
n the past several years, governments have attempted to control advertising for foods and beverages with poor nutritional quality on television and other forms of traditional media. Although this has been met with some success, there aren’t any rulesthat regulate food and drinks on social media, which is an extremely common source of information and entertainment for children and teenagers. Many celebrities include mentions, images and videos of foods and beverages in their posts, both sponsored and unsponsored. A new study examines the nutritional quality of the food and drinks featured in celebrity posts.1
The investigators performed a cross-sectional study that looked at the content of posts on Instagram that included food and beverages. The pool of celebrities included athletes, actors, and musicians. The Nutrient Profile Index was used to rate the nutritional quality of the posted food and beverages and was based on the sugar, sodium, energy, saturated fat, fiber, protein, and fruit and/or vegetable content per 100-g sample (a score of 0 indicated least healthy and 100, healthiest). A score of less than 64 for foods and less than 70 for drinks was considered “less healthy.” A secondary outcome was if a link existed between the nutritional quality of items in a post and the sponsorship status.
Statistics Canada data for 2020-21 show university participation rates for 20 year-olds at 41 per cent, a significant increase from the usual 36 or 37 per cent of the previous five years. The participation rates were also higher than in previous years for all other ages between 18 and 25.
Enrolment data for the winter term is not yet available, but these numbers suggest the prospect of online learning hasn’t pushed many students away.
Universities also seem to be retaining students at high rates.
Growth has been explosive. In 2008, 17 years after it went online, arXiv hit 500,000 papers. By late 2014 that total had doubled to one million. Seven years later arXiv has doubled its library again but continues to grapple with its role: Is it closer to a selective academic journal or more like an online warehouse that indiscriminately collects papers?
Amid this confusion, some researchers are concerned about arXiv’s moderation policies, which they say lack transparency and have led to papers being unfairly rejected or misclassified. At the same time, arXiv is struggling to improve the diversity of its moderators, who are predominantly men based at U.S. institutions.
Among physicists, there is a common refrain: “If it’s not on arXiv, it doesn’t exist.”
The Cambridge Centre for Risk Studies (CCRS) at the University of Cambridge Judge Business School is launching a new research consortium that aims to find ways to protect society against future systemic risks.
Funding will be provided by an international consortium of companies including Pool Re, the UK’s reinsurance mutual.
Like any technology, AI poses personal, societal, and economic risks. It can be exploited by malicious players in the market in a variety of ways that can substantially affect both individuals and organizations, infringe on our privacy, result in catastrophic errors, or perpetuate unethical biases along the lines of protected features such as age, sex, or race. Creating responsible AI principles and practices is critical.
So, what rules could the industry adopt in order to prevent this and ensure that it’s using AI responsibly? The team at the Institute for Ethical AI and ML has assembled eight principles that can be used to guide teams to ensure that they are using AI responsibly. I’d like to run through four — human augmentation, bias evaluation, explainability, and reproducibility.
Sweating it out through exercise may be a New Year’s resolution but it could also help to provide new insights into the state of your health, according to new sensing technology being developed at Simon Fraser University.
SFU researcher Woo Soo Kim is part of an international research team that is developing a low-cost, 3D-printed wearable sweat sensor. The research is being carried out in SFU’s Additive Manufacturing Lab in collaboration with researchers from Zhejiang University. The team recently published a sweeping review of sweat sensor advances in the journal Bio-Design and Manufacturing.
According to Kim, innovation in technology design over the past decade has seen the rapid development of wearable sensors—including sweat sensors. These wearable sensors can assess an individual’s health by analyzing the chemicals and other health information contained in sweat.
The University of Connecticut’s board of trustees recently approved a new data science master’s degree program that will kickoff in the fall of 2022; Quinnipiac University began offering a data science bachelor’s degree this past fall; and the University of Hartford will begin offering an undergraduate data science degree in the fall of 2022.
College leaders say they are collaborating with the private sector and industry experts to develop curriculums that combine the use of statistics, algorithms and technology — skill sets desired by a broad range of companies as mining large amounts of data to improve business operations and predictive analytics becomes the norm.
For example, Quinnipiac University worked closely with insurers Travelers Cos. and Liberty Mutual before rolling out its new data science program this past fall, according to program director Jill Shahverdian.
St. Lawrence’s new data science major is interdisciplinary, hands-on, and full of opportunities for students to apply their coursework to real-world opportunities like internships and research.
Associate Professor of Statistics Ivan Ramler and Associate Professor of Computer Science Lisa Torrey shared what makes St. Lawrence’s program unique and how its innovative liberal arts curriculum will best prepare graduates to make an impact in the rapidly growing data science field.
The science behind making machines talk just like humans is very complex, because our speech patterns are so nuanced.
“The voice is not easy to grasp,” says Klaus Scherer, emeritus professor of the psychology of emotion at the University of Geneva. “To analyze the voice really requires quite a lot of knowledge about acoustics, vocal mechanisms and physiological aspects. So it is necessarily interdisciplinary, and quite demanding in terms of what you need to master in order to do anything of consequence.”
So it’s not surprisingly taken well over 200 years for synthetic voices to get from the first speaking machine, invented by Wolfgang von Kempelen around 1800 – a boxlike contraption that used bellows, pipes and a rubber mouth and nose to simulate a few recognizably human utterances, like mama and papa – to a Samuel L. Jackson voice clone delivering the weather report on Alexa today.
As artificial intelligence lays claims to growing parts of our social and consumer lives, it’s supposed to eliminate all the creeping flaws humans introduce to the world.
The reality, of course, is quite different. From Facebook algorithms that learn how to stoke anger to facial recognition apps that don’t recognize people of color, AI frequently offers less of an improvement on the status quo than an insidious reinforcement of it.
Now a Silicon Valley upstart says he has a fresh approach to the problem. Alan Cowen, a former Google data scientist with a background in psychology, has created a research company, Hume AI, and a companion not-for-profit that he says can help make the whole messy business of AI more empathetic and human.
Esteban Moro, a professor, researcher and data scientist at Madrid’s Carlos III University and visiting professor at the Massachusetts Institute of Technology (MIT), has sought a scientific answer to this question. In an article published on his blog, he described a strategy that would solve 99% of the 206 challenges posed so far by Wordle in less than six steps, although this method cannot be applied to other versions of the game, such as those that have been circulating in Spanish and even Galician.
His strategy is based on two factors: start the game with a word identified as the best option, and make successive attempts following a simple rule. But how do you find this rule?
Online March 23 starting at 9 a.m. Eastern. “The inaugural SciMLCon of the Scientific Machine Learning Open Source Software Community is focused on the development and applications of the Julia-based SciML tooling. Check out the call for proposals. SciMLCon presentations can range from introductory to advanced, with speakers from industry and academia.”
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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.