Welcome to the July 10, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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U.S. map as printed circuit, illustration ACM U.S. Technology Policy Committee Urges Supreme Court to Narrowly Interpret Computer Fraud Act
ACM Media Center
July 9, 2020

ACM's U.S. Technology Policy Committee (USTPC) on Thursday filed an amicus curiae brief with the U.S. Supreme Court in the case of Van Buren v. United States, urging the court to narrowly interpret the Computer Fraud and Abuse Act (CFAA). The case entails the prosecution of a police sergeant who allegedly accessed a state license plate database for impermissible purposes. The USTPC brief said the high court should interpret the statute as deeming data scraping (computer scientists’ use of tools to find and amass data from online sources) a form of illegal "unauthorized access." The USTPC suggested rendering data scraping impermissible would discourage important research and innovation. Said ACM global Technology Policy Council chair Lorraine Kisselburgh, “Prosecutors and lawyers for large corporate interests have too often sought to use the heavy penalties connected with the Computer Fraud and Abuse Act as a cudgel against infractions that should be remedied with other, more appropriate statutes.” She added, “We look to the Court to properly narrow the Act.”

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drone and drone operator Researchers Discover How to Pinpoint a Malicious Drone Operator
Help Net Security
July 7, 2020

Researchers at Israel's Ben-Gurion University of the Negev (BGU) have learned to identify the location of a potentially malicious aerial drone operator operating near airports or protected airspace by analyzing the drone's flight path. Drone operators are currently pinpointed via radio-frequency techniques, using sensors around the flight area, which can then be triangulated; however, other wireless signals can mask drone signals. The BGU team trained a deep neural network to predict the location of drone operators using only the flight path of the drones, making additional sensors unnecessary. In tests with simulated drone routes, the model predicted operator locations with 78% accuracy.

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R on a pedestal Programming Languages: R Makes a Comeback, But There's Debate About Its Rise
Liam Tung
July 6, 2020

Tiobe Software's latest programming language popularity index shows the statistical programming language R making a comeback, rising to eighth place after falling out of the top 20 in May for the first time in three years. Tiobe's Paul Jansen believes demand in universities and from global efforts to find a vaccine for Covid-19 has given a boost to R and Python. Said Jansen, "Lots of statistics and data mining needs to be done to find a vaccine for the Covid-19 virus. As a consequence, statistical programming languages that are easy to learn and use gain popularity now." Tiobe's rankings are based on search engine results related to programming language queries. The C programming language topped the latest index, followed in descending order by Java, Python, C++, C#, Visual Basic, JavaScript, R, PHP, and Swift.

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figure with expansive brain, illustration Study: Only 18% of Data Science Students Are Learning AI Ethics
The Next Web
Thomas Macaulay
July 3, 2020

A survey by the software firm Anaconda found that only 15% of university instructors and professors are teaching artificial intelligence (AI) ethics, and just 18% of students say they are learning about the issue. In the survey of 2,360 data science students, academics, and professionals from more than 100 countries, nearly half of respondents said the biggest issues to address in the area of AI and machine learning are the social impacts of bias or privacy. Just 15% of respondents said their organization has a fairness system in place, and only 19% said an explainability tool has been implemented. Said the researchers, "Of all the trends identified in our study, we find the slow progress to address bias and fairness and to make machine learning explainable the most concerning. While these two issues are distinct, they are interrelated, and both pose important questions for society, industry, and academia."

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Bio-Ink for 3-D Printing Inside the Body
IEEE Spectrum
Charles Q. Choi
July 1, 2020

Researchers at The Ohio State University (OSU) have developed a bio-ink that can be three-dimensionally (3D) printed at human body temperature, and solidified using visible light. Bio-inks are composed of living cells suspended in a gel and are safe for use inside people, potentially paving the way for 3D printing inside the body. Using a 3D printing nozzle affixed to robotic machinery to dispense bio-ink in a controlled manner, the researchers were able to bio-print onto soft materials, with interlocking knobs left beneath the surface anchoring the printed structure to the body like surgical staples. OSU's David Hoelzle said the goal is not to bio-print an entire organ, but to "augment a standard surgery by delivering a biomaterial with a tethered growth factor to jumpstart healing, or a tethered drug to prevent infection. ... We envision a biomaterial bio-ink printing tool as another tool in the surgeon's toolset."

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Deepfake Technology Enters the Documentary World
The New York Times
Joshua Rothkopf
July 1, 2020

Documentary filmmaker David France is leveraging deepfake technology in his new HBO film Welcome to Chechnya, shielding the identity of at-risk gay and lesbian Chechens fleeing the region while maintaining an emotional connection with viewers. The film's postproduction work involved the use of advanced computer technology to superimpose fabricated faces over 23 individuals, with an intentionally added "underblur" or "halo" to make viewers aware of the manipulation. Visual effects supervisor Ryan Laney said in some instances, the deep-learning computer process "worked better than we ever expected. There were times when we actually backed off on some areas, the machine did better or sharper, and we were concerned that we weren't telling the audience that something was going on."

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A medical illustration of Clostridioides difficile bacteria. Researchers Develop Software to Find Drug-Resistant Bacteria
WSU Insider
Tina Hilding
July 6, 2020

Washington State University (WSU) researchers have developed an easy-to-use software program to spot drug-resistant genes in bacteria. The team's machine learning algorithm uses game theory to identify antimicrobial resistance (AMR) genes by studying the interactions of several features of the genetic material, including its structure and the physiochemical and composition properties of protein sequences. The software classified resistant genes with up to 90% accuracy when analyzing genes found in species of several types of infectious disease-causing bacteria. WSU's Abu Sayed Chowdhury said, "This can be an important tool to identify novel antimicrobial resistance genes that eventually could become clinically important."

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A Google self-driving car with LiDAR on its roof cruising down a California interstate. Leap in LiDAR Could Improve Safety, Security of New Technology
CU Boulder Today
Kelsey Simpkins
July 6, 2020

University of Colorado Boulder (CU Boulder) researchers have designed a new silicon chip that improves the resolution and scanning speed required for a LiDAR system, without any moving parts or electronics. CU Boulder's Nathan Dostart and colleagues have spent the past three years developing a wavelength steering system for laser beams, which aims each laser wavelength/color at a unique angle. The system can facilitate this action along two dimensions simultaneously, and uses a "rainbow" pattern to capture three-dimensional images; this allows concurrent control of multiple phased arrays to generate a larger aperture and a higher resolution image. CU's Kelvin Wagner said, "We've figured out how to put this two-dimensional rainbow into a little teeny chip."

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AR Comes to the Fight Against Covid-19
Australian Financial Review
John Davidson
July 6, 2020

Researchers at La Trobe University in Australia have developed an augmented reality (AR) visualization of the effects of Covid-19 on the lungs, in an effort to aid diagnosis and treatment. The researchers converted two-dimensional (2D) computed tomography (CT) scans of Covid-damaged lungs into three-dimensional (3D) images. Microsoft's HoloLens 2 headset lets researchers view those images, superimposed into the space in front of their eyes. Said La Trobe's Henry Duh, "If you only see a 2D scan, without HoloLens, you need to do more mental rotations and reconstructions in order to figure out what it looks like in the body." The researchers hope to use machine learning to analyze original CT scans and identify areas of the lungs damaged by the disease.

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An illustration showing a speech bubble inferring inappropriate language. Context Reduces Racial Bias in Hate Speech Detection Algorithms
USC Viterbi News
Caitlin Dawson
July 7, 2020

University of Southern California (USC) researchers have come up with a context-aware hate speech classifier that outperforms current social media hate speech detection algorithms. Such algorithms can exacerbate racial bias by blocking inoffensive tweets by minority group members, because they overlook context. USC's Brendan Kennedy said hate speech detection models often make poor predictions when introduced to real-world data, as they reflect bias within the data they are trained on to associate the appearance of social identifying terms with hate speech. The USC team programmed its algorithm to gauge both the context in which the group identifier is used, and whether specific features of hate speech are present as well. Their model outperformed a state-of-the-art model in terms of accurately flagging hate versus non-hate speech in 12,500 New York Times articles devoid of hate speech (excluding quotations).

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A photo of Google smartwatches Google Fixes Smartwatch Security Problem
Purdue University News
Kayla Wiles
July 8, 2020

Google has corrected a security vulnerability in its Wear OS smartwatches that could have allowed attackers to crash specific applications, render the app or the watch unresponsive, or cause continuous reboots. Purdue University’s Saurabh Bagchi and colleagues uncovered the flaw using the Vulcan tool, which feeds a program or app different permutations of data until one exposes a weakness. Through this fuzzing technique, the researchers learned that a hacker could hijack an app or the smartwatch by manipulating the language, or Intents, that apps use to communicate. Sending such Intents at high volumes when the operating system is less stable could overload the app or watch, even without root-level privileges. The Purdue team demonstrated a proof-of-concept mitigation method, and released its codebase on GitHub after Google issued a patch for the Wear OS vulnerability on June 24.

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A photo of a young man and his reflection. Research Reflects How AI Sees Through the Looking Glass
Cornell Chronicle
Melanie Lefkowitz
July 2, 2020

Cornell University researchers used artificial intelligence to measure the differences between original images and their mirror reflections. The team's technology generates a heat map indicating the parts of the image of interest to the algorithm to help understand how the algorithm decided to focus on them. Text was the most commonly used clue, and with text removed, the next set of clues the model focused on included wristwatches, shirt collars, faces, phones, and other factors indicating right-handedness; when concentrating on faces, the heat map picked up on areas including hair part, eye gaze, and beards. The algorithm builds confidence by combining multiple clues, and employs low-level signals, stemming from the way cameras process images, to make decisions. Cornell's Noah Snavely said analyzing how reflected images differ from originals could expose information about possible biases in machine learning that might lead to inaccurate results, with further ramifications for training machine learning models and detecting doctored images.

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Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio Micali
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