In January, a Swedish entrepreneur named Joakim Hultin co-founded Sidehide, a new digital app intended to streamline hotel reservations. Weeks later, some of the first confirmed cases of COVID-19 were reported in Europe. Almost instantly, Hultin told me, "demand stopped." Before the pandemic, Sidehide was working with a London-based company called Onfido, which uses artificial intelligence and facial recognition to verify identities. Hultin learned that Onfido had created a way for users to upload a serology test to a private server and use facial biometric data to unlock the data and display the results.
Australian Health Minister Greg Hunt has denied state health officials are unable to access COVIDSafe app data to perform coronavirus contact tracing. During a press conference on Wednesday, Hunt was asked if reports, originally from The Guardian, that New South Wales Health officials have been unable to access the data for contact tracing were true. It was reported that despite the app being live for nearly a month and state officials having received training on how to use the data, they were yet to get their hands on it. In a statement, NSW Health said that while it could confirm the COVIDSafe app is working, data from it has reflected details already obtained by the state's own dedicated contact tracing team. "As recent positive cases in NSW have been in hotel quarantine, they have not generated community contacts, so even our own tracing efforts have been unnecessary," a spokesperson said.
Dr. David Bray is the Inaugural Director of the new global GeoTech Center & Commission of the Atlantic Council, a nonprofit for international political, business, and intellectual leaders founded in 1961. Headquartered in Washington, DC, the Council offers programs related to international security and global economic prosperity. In previous leadership roles, Bray led the technology aspects of the Centers for Disease Control's bioterrorism preparedness program in response to 9/11, the outbreak response to the West Nile virus, SARS, monkey pox and other emergencies. He also spent time on the ground in Afghanistan in 2009 as a senior advisor to both military and humanitarian assistance efforts, serving as the non-partisan Executive Director for a bipartisan National Commission on R&D, and providing leadership as a non-partisan federal agency Senior Executive focused on digital modernization. He also is a Young Global Leader for 2017-2021 of the World Economic Forum. Bray is a member of multiple Boards of Directors and has worked with the U.S. Special Operations Command on counter-misinformation efforts. He was invited to give the 2019 UN Charter Keynote on the future of AI & IoT governance. His academic background includes a PhD from Emory University; he also has held affiliations with MIT, Harvard, and the University of Oxford. He recently took a few moments to speak to AI Trends Editor John P. Desmond about current events, including the geopolitics of the COVID-19 pandemic. AI Trends: Thank you David for talking to AI Trends today.
Recent projections by the US federal government estimate that there will be 200,000 new coronavirus cases in the US by June 1. At the same time, governments around the world are grappling with the complexities of safely reopening businesses, schools and other public institutions. Technology companies are rushing into that gap with software aimed at keeping people safe, while citizens navigate a patchwork approach to easing shelter-in-place orders. One well-known approach is the use of contact-tracing apps on smart phones created by tech and telecom companies. These apps alert people if they've been in close proximity to an infected person.
COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic by the WHO on 11 March 2020. Artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID-19 pandemic. AI can, for present purposes, be defined as Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions can be useful to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. Since the outbreak of the pandemic, there has been a scramble to use and explore AI, and other data analytic tools, for these purposes. In this article, I provide an early review, discussing the actual and potential contribution of AI to the fight against COVID-19, as well as the current constraints on these contributions. It aims to draw quick take-aways from a fast expanding discussion and growing body of work, in order to serve as an input for rapid responses in research, policy and medical analysis. The cost of the pandemic in terms of lives and economic damage will be terrible; at the time of writing, great uncertainty surrounded estimates of just how terrible, and of how successful both non-pharmaceutical and pharmaceutical responses can be. Improving AI, one of the most promising data analytic tools to have been developed over the past decade or so, so as to help reduce these uncertainties, is a worthwhile pursuit.
Europe's first known coronavirus case may have been in December A man who was treated at a hospital in France for suspected pneumonia may have had covid-19 as early as 27 December, according to a retest of old samples. France reported its first cases of coronavirus on 24 January, and these were among the first that were detected in Europe. World Health Organization (WHO) spokesperson Christian Lindmeier has now urged countries to check their records for similar cases in order to provide a clearer picture of how and when outbreaks began. The testing result may not be conclusive however – it could possibly be a false positive. Anthony Fauci, a lead member of the Trump administration's coronavirus task force, has warned that any easing of restrictions in the US could lead to a "dire" increase in the country's covid-19 death toll. "How many deaths and how much suffering are you willing to accept to get back to what you want to be some form of normality, sooner rather than later?" he said.
The pandemic caused by COVID-19 is the first global public health crisis of the 21st century. And today, multiple AI-powered projects based on data science, 'machine learning' or'big data', are being used across a broad range of fields to predict, explain and manage the different scenarios caused by the health crisis. AI is being used to support and help those making decisions. "No decisions, at any step, are fully and exclusive delegated on the algorithm," explains Nuria Oliver, data scientist, who holds a Ph.D. from the Media Lab at Massachusetts Institute of Technology (MIT) and is the Regional Government of Valencia's commissioner on AI matters. In the context of the pandemic, AI is being applied and delivering results in three fields: in virus research and the development of drugs and vaccines; in the management of services and resources at healthcare centers; and in the analysis of data to support public policy decisions aimed at managing the crisis, such as the confinement measures.
The coronavirus (COVID-19) outbreak is having a growing impact on the global economy. So, how is the impact of COVID-19 going to be on the tech job market and what are the latest trends for data science, AI/ML, analytics, IoT, cloud computing? What are the key in-demand tech job profiles and domains during and after the COVID-19 phase? There have been more than 12,750 confirmed cases of COVID-19 in India so far. Between April 6 – 12, 46% and 39% of new confirmed cases have been reported in Europe and the USA respectively.
MIT recently trained a machine learning model to accurately predict the spread of COVID-19. According to the AI, we should be seeing a plateau where the amount of new cases begins to level off in the US and Italy in the next week. This good news, however, comes with a dire warning: relaxing quarantine measures too soon will be catastrophic. The engineers behind the AI explain the results as being very similar to the situation that happened in Singapore where quarantine and social distancing efforts managed to almost completely flatten the curve before an ill-advised return to business as usual caused a massive resurgence in COVID-19 cases. The MIT team trained the AI to extrapolate publicly-available data for insights into the disease's spread, taking into account how different governments handled social distancing and quarantine orders as well as other standard epidemiology parameters.