Welcome to the May 19, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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The Future of Virus Tracking Can Be Found on This College Campus
The New York Times
Emily Anthes
May 17, 2021
Colorado Mesa University (CMU) and the Broad Institute of the Massachusetts Institute of Technology and Harvard University have transformed CMU's campus into an epidemiological laboratory researching new avenues of pandemic management. CMU students use the Scout application to report COVID symptoms to the Lookout digital dashboard for tracking viral transmission. When CMU students returned to campus last August, Scout became their daily wellness passport, used to report symptoms and whether they had recently traveled outside the area; Lookout furnished a holistic perspective of campus activities, and factored in hourly results from CMU's coronavirus testing site. Sabeti said the detailed, high-resolution data from CMU "will help us better understand viral spread in congregate settings and how we can help mitigate it in the future."
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Amazon Blocks Police from Using Its Facial Recognition Software Indefinitely
CNN Business
Rachel Metz
May 18, 2021
Amazon has indefinitely extended its ban on police use of its facial recognition software, which lawmakers and company employees have said discriminates against African-Americans. When announcing the moratorium last June, the Internet retailer said it hoped a year would give Congress sufficient time to develop legislation regulating the ethical use of the technology. The American Civil Liberties Union (ACLI) said it was glad to see the ban extended indefinitely. ACLI's Nathan Freed said, "Now, the Biden administration and legislatures across the country must further protect communities from the dangers of this technology by ending its use by law enforcement entirely, regardless which company is selling it."
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Helping Drone Swarms Avoid Obstacles Without Hitting Each Other
EPFL News (Switzerland)
Clara Marc
May 18, 2021
A predictive control model developed by engineers at Swiss Federal Institute of Technology Lausanne (EPFL) allows individual drones to predict their own behavior and that of neighboring drones in a swarm, to keep them from bumping into each other. EPFL's Enrica Soria said, "Our model gives drones the ability to determine when a neighbor is about to slow down, meaning the slowdown has less of an effect on their own flight." In the new model, Soria explained, "Drones are commanded using local information and can modify their trajectories autonomously." Tests conducted in the university’s Laboratory of Intelligent Systems found that in areas with multiple obstacles, the model improves a drone swarm's speed, order, and safety.
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France Embraces Google, Microsoft in Quest to Safeguard Sensitive Data
Reuters
Mathieu Rosemain
May 17, 2021
The French government has indicated that cloud computing technology developed by Google and Microsoft could be used to store sensitive state and corporate data, providing it is licensed to French companies. French Finance Minister Bruno Le Maire acknowledged U.S. technological superiority in the field but said guaranteeing the location of servers on French soil, and European ownership of the companies that store and process the data, could help ensure a "trustworthy" cloud computing alternative. Companies that offer cloud computing services that meet these principles and other conditions set forth by France's cybersecurity agency ANSSI could receive a "trustworthy cloud" designation. Two French companies already meet the criteria.
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Interactive Typeface for Digital Text
Technische Universitat Darmstadt (Germany)
May 12, 2021
A team of researchers at Germany's Technische Universitat Darmstadt (TU Darmstadt) has developed a computer font that can adjust its appearance based on the user's textual interaction. AdaptiFont quantifies the user's reading speed and adapts font shape continuously so the user can read text more easily. A machine learning algorithm facilitates on-the-fly font personalization, enabling AdaptiFont to produce an infinite number of fonts that are any intermediate configuration of others. In a laboratory experiment involving users reading texts over one hour, the team demonstrated that AdaptiFont can create new fonts that boost individual users' reading speed, although an individual’s preferred typeface is not always optimal for every situation.
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COVID-19 Wrecked the Algorithms That Set Airfares, but They Won't Stay Dumb
The Wall Street Journal
Jon Sindreau
May 17, 2021
The COVID-19 pandemic crippled the reliability of algorithms used to set air fares based on historical data and has accelerated a hybrid model that combines historical and live data. Before the pandemic, airlines used the algorithms to predict how strong ticket demand would be on a particular day and time, or exactly when people will fly to visit relatives before a holiday. Corporate travel constitutes a large share of airline profits, with business fliers avoiding Tuesdays and Wednesdays, favoring short trips over week-long ones, and booking late. The pandemic undermined historical demand patterns while cancellations undercut live data, causing the algorithms to post absurd prices. Overall, the pandemic has stress-tested useful advancements to the algorithms, like assigning greater weight to recent booking numbers, and applying online searches to forecast when and where demand will manifest.
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AI Uses Timing, Weather Data to Accurately Predict Cardiac Arrest Risk
SciTechDaily
May 17, 2021
Machine learning can predict one’s risk of out-of-hospital cardiac arrest by combining timing and meteorological data, according to researchers at U.S. and Japanese institutions. The researchers trained their algorithm on 525,374 of roughly 1.23 million cases of out-of-hospital cardiac arrests using either weather or timing data, or both. The results were compared with 135,678 such cases occurring in 2014-2015 to test the model's accuracy; they also were assessed for local-level accuracy via a heatmap analysis using another dataset drawn from the location of out-of-hospital cardiac arrests in Kobe between January 2016 and December 2018. The researchers said the combination of weather and timing data was most accurate in predicting an out-of-hospital cardiac arrest in both the training and testing datasets.
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Top Educational Apps for Children Might Not Be as Beneficial as Promised
Penn State News
Katie Bohn
May 11, 2021
An analysis of the most frequently downloaded educational apps for kids by a team of researchers led by the Pennsylvania State University Brandywine found such apps may not provide high-quality educational experiences. The researchers used previous research on the pillars of learning to develop criteria for the assessment of the top 100 children's educational apps from the Google Play and Apple apps stores, among others. After the apps were scored from 0 (low) to 3 (high) for each pillar of learning, the researchers found a score of 1 was most common for each app with regard to all four pillars. The University of Michigan’s Marisa Meyer said, “If app designers intend to engender and advertise educational gains through use of their apps, we recommend collaborating with child development experts in order to develop apps rooted in the ways children learn most effectively.”
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Exxon Mobil's Messaging Shifted Blame for Warming to Consumers
Scientific American
Maxine Joselow
May 15, 2021
A computational assessment by Harvard University researchers determined that oil giant Exxon Mobil used language to deflect accountability for climate change from fossil fuel companies to consumers. Harvard's Geoffrey Supran and Naomi Oreskes used algorithms to analyze 180 Exxon Mobil documents from 1972 to 2019, including peer-reviewed publications, advertorials in The New York Times, and internal memos. The analysis showed that the company privately used certain terms while publicly avoiding them. The researchers said Exxon Mobil's tactics mirror the tobacco industry's use of rhetoric to minimize the seriousness of climate change. Supran suggested such findings could be relevant to climate liability litigation cases that allege deceptive marketing.
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Using ML to Predict High-Impact Research
MIT News
Becky Ham
May 17, 2021
Researchers at the Massachusetts Institute of Technology (MIT) have developed an artificial intelligence framework able to predict future high-impact technologies based on patterns found in published scientific studies. The framework, DELPHI (Dynamic Early-warning by Learning to Predict High Impact), identified all pioneering papers on a list of key foundational biotechnologies as early as the first year after their publication. MIT's James W. Weis said the framework "functions by learning patterns from the history of science, and then pattern-matching on new publications to find early signals of high impact." DELPHI, which was trained on a full time-series network of journal article metadata, identified more than twice as many high-impact papers compared to citation numbers alone.
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Study Explores Privacy of Prison Communications
Carnegie Mellon University CyLab Security and Privacy Institute
Daniel Tkacik
May 11, 2021
The constant monitoring of people incarcerated in the U.S. extends to communications between inmates and their relatives, according to a study by researchers at Carnegie Mellon University's CyLab Security and Privacy Institute. Through interviews with 16 family members of people imprisoned in Pennsylvania, the researchers learned that participants were generally aware their communications with inmates were surveilled, but their understanding of more advanced monitoring methods, like voice-printing and location tracking for calls received on a cellphone, was limited. The researchers said while prison communication companies have the technical capabilities to change, there is little evidence they would alter their surveillance practices without being required to do so by regulators.
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Academics Edge Closer to Research on Cloud Platforms
Financial Times
Adam Green
May 17, 2021
A group of 22 higher education institutions, concerned about trailing the technology sector in tapping cloud computing and advancing artificial intelligence (AI), have enrolled in a National Research Cloud initiative to access the computational power they need to keep pace. The proposal for the initiative, authored by Fei-Fei Li and John Etchemendy of the Stanford Institute for Human-Centered Artificial Intelligence, would establish a national cloud platform on which academics and industry players could work on the advancement of AI, while helping to train new experts in the field. Li said, "If we kneecap academia from being an active participant in AI development, we threaten the innovation ecosystem as a whole."
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