More than 11 million people have been tested in the U.S. for COVID-19, all with the assurance that their private medical information would remain protected and undisclosed.
Yet, public officials in at least two-thirds of states are sharing the addresses of people who tested positive with first responders — from police officers to firefighters to EMTs. An Associated Press review found that at least 10 of those states also share the patients’ names.
University of Texas at Austin, Oden Institute for Computational Engineering & Sciences
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A Memorandum of Understanding (MoU) has been signed between The Alan Turing Institute in London and the Oden Institute for Computational Engineering and Sciences at The University of Texas (UT) at Austin. This formally creates an ambitious agreement led by the Turing’s data-centric engineering program, a major research initiative funded by the Lloyd’s Register Foundation, a UK nonprofit seeking to protect life and property and support education, engineering-related research and public engagement.
This new collaboration aims to deliver research advances in a number of key impact areas: artificial intelligence for science and engineering, computational science and engineering (CSE), scientific machine learning, and data-centric engineering.
Facebook Shops make it easy for businesses to set up a single online store for customers to access on both Facebook and Instagram. Creating a Facebook Shop is free and simple. Businesses can choose the products they want to feature from their catalog and then customize the look and feel of their shop with a cover image and accent colors that showcase their brand. This means any seller, no matter their size or budget, can bring their business online and connect with customers wherever and whenever it’s convenient for them.
GZERO Media, Gabrielle Debinski and Gabriella Turrisi
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The head of the IMF has already warned that the state of the global economy is “worse than our already pessimistic projections.” But while the pandemic is taking a huge economic toll on every country in the world, many emerging-market economies, which currently owe a collective $8.4 trillion in foreign debt, face a particularly grim tradeoff between paying their bondholders or funding their hospitals.
Artificial intelligence could play a decisive role in stopping the Covid-19 pandemic. To give the technology a push, the MIT-IBM Watson AI Lab is funding 10 projects at MIT aimed at advancing AI’s transformative potential for society. The research will target the immediate public health and economic challenges of this moment. But it could have a lasting impact on how we evaluate and respond to risk long after the crisis has passed. The 10 research projects are highlighted below.
A recording of a cough, the noise of a person’s breathing or even the sound of their voice could be used to help diagnose patients with Covid-19 in the future, according to Professor Cecilia Mascolo, co-director of the centre for mobile, wearable systems and augmented intelligence at the University of Cambridge, UK.
Prof. Mascolo has developed a sound-collecting app to help train machine learning algorithms to detect the tell-tale sounds of coronavirus infection. Created as part of a project called EAR, she hopes it might eventually lead to new ways of diagnosing respiratory diseases and help in the global fight against coronavirus.
Montreal will add 327 kilometres of bicycle paths and pedestrian lanes, while some thoroughfares will be closed to motorized traffic this summer. It is part of an effort to open up the city — and its businesses — to residents after months of COVID-19 lockdown.
However, the head of the official opposition at city hall said the plan was short on details and didn’t seem to have considered the businesses it is supposed to help. And Lionel Perez wondered about the motivation behind Mayor Valérie Plante’s announcement on Friday.
To date, at least 1,200 reports of AI incidents have been recorded in various public and research databases. That means that now is the time to start planning for AI incident response, or how organizations react when things go wrong with their AI systems. While incident response is a field that’s well developed in the traditional cybersecurity world, it has no clear analogue in the world of AI. What is an incident when it comes to an AI system? When does AI create liability that organizations need to respond to? This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. Our aim is to help explain when and why AI creates liability for the organizations that employ it, and to outline how organizations should react when their AI causes major problems.
Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world’s most pressing challenges, and deliver positive social impact in accordance with the priorities outlined in the United Nations’ 17 Sustainable Development Goals (SDGs). The AI for Social Good (AI4SG) movement aims to establish interdisciplinary partnerships centred around AI applications towards SDGs. We provide a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good. [full text]
Alexa can tell you the weather. Siri knows a few jokes. In China, voice-computing company iFlytek built similar smart assistants beloved by users. But its tech is also helping the government listen in.
A specter is haunting the U.S. education system—the specter of not being able to carry out the routine administration of standardized tests. While written achievement tests were considered controversial in U.S. schools throughout the 19th century, by the mid-20th century it became acceptable to measure the “merit” of individuals via instruments such as IQ tests. Nowhere was this more true than in the higher education system, where competition between institutions led to shifting definitions of merit and to assertions about the role standardized testing should play in a meritocracy. Today, in the middle of a public health crisis that makes such testing difficult (if not impossible), both critics and advocates of standardized testing are raising new questions about teaching and the measurement of learning in the U.S. What role will academics—and teachers, students, university administrators, and others—play in this process?
One answer comes from a new proposal issued by University of California President Janet Napolitano. While many colleges and universities have suspended standardized test requirements for Fall 2021 admissions in light of the coronavirus pandemic
Some workers at Amazon.com Inc.’s Troutdale, Oregon, warehouse think of the coronavirus testing pilot in their facility as a sort of lottery. Managers have been reaching out to employees this month and, with their permission, testing them for the disease.
The self-administered tests, offered as a nasal swab or saliva sample, are shipped to labs under contract with Amazon. Eventually, if things go to plan, the samples may fly in Amazon cargo jets to a lab the company is setting up near its main air freight hub in northern Kentucky.
Plenty of companies are trying to keep their businesses afloat in these challenging times. Amazon wants to innovate its way out of the pandemic.
POLITICO, Alice Miranda Ollstein and Mohana Ravindranath
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A half-dozen states have announced they’re building their own apps to pinpoint the spread of coronavirus so they won’t have to rely on similar efforts from distrusted big tech firms. So far, it’s not going well.
North Dakota is getting spotty data from cell phone towers after relying on an app originally designed to connect its state university football fans on road trips to away games. Utah delayed the rollout of a GPS tracking function after technical difficulties. Other states, like Georgia, are promoting tools that rely on people to self-report new Covid-19 infections, potentially creating gaps in the effort to track the spread of the virus.
At its Build developer conference, Microsoft today announced that it has teamed up with OpenAI, the startup trying to build a general artificial intelligence, with — among other things — a $1 billion investment from Microsoft, to create one of the world’s fastest supercomputers on top of Azure’s infrastructure. Microsoft says that the 285,000-core machine would have ranked in the top five of the TOP500 supercomputer rankings.
Because Microsoft doesn’t actually tell us much more than that, except for a few more specs that say it had 10,000 GPUs and 400 gigabits per second of network connectivity per server, we’ll just have to take Microsoft’s and OpenAI’s word for this.
Dana-Farber Cancer Institute, Department of Data Science
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Online May 26, starting at 1 p.m. EDT. “See Jeff Leek (@jtleek
) of @JohnsHopkinsSPH discuss “Teaching data science to the masses” at the @dfcidatascience Zoominar.” [rsvp required]
Online June 25. ” We invite you present your work at #SciNLP workshop at #AKBC2020! Please submit short (1 page) abstracts by June 1st. More details at http://scinlp-workshop.github.io. Excited about our invited speakers.” Deadline for abstract submissions is June 1.
“We are gearing up our tool building and outreach, but we want your input how best to do that. Please take (&share!) our 10-15 min survey – link + more info at the post below”
“Our goal for this workshop is to educate researchers about the technological needs of people with vision impairments while empowering researchers to improve algorithms to meet these needs. A key component of this event will be to track progress on a new dataset challenge, where the task is to caption images taken by people who are blind. Winners of this challenge will receive awards sponsored by Microsoft. The second key component of this event will be a discussion about current research and application issues, including by invited speakers from both academia and industry who will share about their experiences in building today’s state-of-the-art assistive technologies as well as designing next-generation tools.” Deadline for challenge submissions is June 1.
From improved disease screening to authoritarian surveillance, ML advances will have positive and negative social impacts. Policymakers are struggling to understand these advances, to build policies that amplify the benefits and mitigate the risks. ML researchers need to be part of this conversation: to help anticipate novel ML applications, assess the social implications, and promote initiatives to steer research and society in beneficial directions.
Innovating in this respect, NeurIPS has introduced a requirement that all paper submissions include a statement of the “potential broader impact of their work, including its ethical aspects and future societal consequences.” This is an exciting innovation in scientifically informed governance of technology (Hecht et al 2018 & Hecht 2020). It is also an opportunity for authors to think about and better explain the motivation and context for their research to other scientists.