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Tag Archives: coronavirus

Coronavirus Catastrophe

December 18, 2020   Humor

On Wednesday, the US had the worst day ever for the pandemic, setting new records for Covid-19 cases, hospitalizations, and deaths.

Yes, it is bad in the US. In just one day, 3,656 people died from Covid-19 (more than the number who died from the terrorist attacks on 9/11).

The US will pass 17 million cases today. In two states, more than 10% of the population have contracted the disease.

In some states, hospitals have run out of beds for new cases and are now rationing. Health care workers are overworked and burned out. The number of cases is doubling every two months, so this will get much worse.

Be safe. Stay home. Wear a mask if you have to go out. Thanksgiving was a super-spreader event. Christmas will be even worse. We are not out of the woods yet, and vaccinations will take many months to have a significant effect.

© Matt Bors
 If you liked this, you might also like these related posts:
  1. The bigger catastrophe?
  2. Fighting the coronavirus?
  3. Coronavirus Concertos
  4. Why Wear a Mask?
  5. We Have a Cure!

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“Disruptive” Technology in the Time of Coronavirus

December 15, 2020   TIBCO Spotfire
TIBCO DisruptiveTechnology scaled e1606856003209 696x365 “Disruptive” Technology in the Time of Coronavirus

Reading Time: 5 minutes

This blog was written by TIBCO Director of Digital Strategy Alessandro Chimera and originally published on Italian tech blog Linea EDP.

The current social and economic climate, generated by the global pandemic, has put many companies in crisis which, if they do not rethink their business operations, will have serious problems of survival. Not only companies but also many professionals face a challenge, which places a change in habits at the top of the priorities of the actions to be taken.

Suddenly, we are asked to travel less, attend fewer meetings, and limit business lunches. At the same time, we are streaming more content, participating in virtual meetings, and using eLearning platforms, as well as taking advantage of home delivery services.

A severely affected market sector is travel, which now has to reorganize its offers to optimize the business and restart as quickly as possible. In short, what is needed now is a kind of “business review ”—the new business imperative.

If the current situation and history have taught us anything, it is that when a crisis arises, traditional operating models are no longer valid. Companies need to react quickly and create, validate, and adopt entirely new strategies to keep their business running and generate sufficient margins to overcome the current crisis. It’s not just the travel market that’s impacted: financial services, telecommunications, industry, transportation, retail, healthcare, government, hospitality, and the energy sector are all facing the same challenges in adapting to the new reality.

How to adapt

If we look at the initiatives that financial services should take, the fastest action available to them is to quickly rebalance all their investment lines with event-driven strategies. On the other hand, the telecommunications sector faces the unexpected increase in connections and an increased data load on its networks. Focusing on providing reliable services to an increasing number of people, whose only means of connecting with their communities is private and business, it passes through its own network.

Another heavily impacted sector is the manufacturing industry, as orders are falling sharply or being canceled due to customers focusing their primary needs on other sectors. There are significant delays in the supply chain, commodities purchased internationally are delivered late. New procedures are being implemented which, following the pandemic, must guarantee the safety of workers. Some of these companies may also be forced to consider a temporary reduction in their workforce.

The transport sector was the first to suffer direct impact due to flight cancellations, border closures, reassignment of passengers to new flights, and flight rescheduling and changes with virtually no notice. The IATA (International Air Transport Association) predicts that on a global level and due to a limited contagion scenario, the current measures will cause a loss of turnover on passenger air traffic equal to approximately 63 billion dollars. While, for an extended contagion scenario, the losses could amount to as much as 113 billion dollars.

Travel bans issued by the United States, Europe, Africa, and Asia have blocked thousands of flights. With 550 flights canceled per day, the loss in terms of daily passengers is 125,000. There are also cargo flights to consider: it has been calculated that in January, which was not even the peak of the crisis, the air cargo sector lost 3.3%. In the latest IATA report of 1 April, it was found that European airlines recorded a reduction in freight traffic of 4.1%.

Who is ready

Very few players in these market sectors were ready: in reality, in most cases, they were totally unprepared. Let’s see the consequences of the lockdown in Italy, our country: when this measure was first implemented, it generated a 56.8% increase in eCommerce, mobile traffic doubled and systems had to be upgraded to withstand the loads additional to which they were subjected.

In manufacturing, many large manufacturers have begun to optimize their processes and operations, analyzing their data to understand how to cope with the new situation they have found themselves in. A particularly true statement for industrial food processing plants, which have seen remarkable growth in demand, due to the fact that Italians were forced to stay at home. On the other hand, the retailers and the distributors have shown a 12.2% growth in sales resulting from the new demand.

The on-demand media services and entertainment streaming have also begun to suffer additional load: sudden growth of customers with the most extensive mode of use that has dealt a blow to providers, bringing close to saturation their networks. For example, Netflix and YouTube have accepted the European Union’s request to take action to avoid saturating the available bandwidth by lowering the definition quality.

But not everyone has seen demand grow: the entire hospitality market has had to stop abruptly. Major events have been canceled or postponed, corporate travel restrictions have caused hotels to empty, and major hotel chains are canceling cancellation fees for current and upcoming bookings to at least secure future business while avoiding losing potential customers.

Complete turnaround

We often talk about the evolution of business and business transformation and how it must happen quickly. However, no one could have imagined the speed with which the pandemic hit the world. At the time of writing this article, only a few countries had decided to close all non-essential activities (lockdown). Today, however, all countries have decided to implement the lockdown, and some (including Italy) have already exited or are exiting the so-called Phase 1 of tight lockdown.

With the exit from the lockdown it is necessary to increase your efforts to completely reinvent your go-to-market strategy.

Unfortunately, many companies have never invested in the tools they need to analyze their business data more deeply, and without sound supportive analysis, it is not possible for them to make correct strategic choices to decide whether the new processes or business models they want implement can really work.

The spotlight is therefore on all companies to act quickly to integrate and unify the various data sources and extract their potential value thanks to Advanced Analytics tools to apply Machine Learning or AI on their data so that they can explore new sales channels and seize new revenue opportunities.

It is a lesson to understand and adapt your business strategies to what customers really want, monitoring their behavior to understand how quickly you can adapt your business to new customer requests. If the term reinvention was ever relevant, it certainly happens today, in the business climate we live in. The key is to understand that decision-making processes must be supported by analyzing your own data, which provides the know-how on how to optimize your execution models to make the alternative business models you are exploring work.

If the current situation and history have taught us anything, it is that when a crisis arises, traditional operating models are no longer valid. Companies need to react quickly to keep their business running. Click To Tweet

Failure is not contemplated. Strategies must be tested quickly and digitally to predict the outcome. Last but not least, you need to be closer to your customers. Understanding that their purchasing power has shifted online, that they are more selective, more frugal, and more insightful, and that this customer intimacy called customer intimacy is today a primarily digital concept. If you get this mix right and when the world returns to the new normal, their loyalty will make them return as your customers more than ever.

Visit tibco.com to see how we can help you begin your digital transformation today.

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COVID-KG uses AI to scan thousands of studies to answer doctors’ coronavirus questions

July 3, 2020   Big Data

The number of studies about COVID-19 has risen steeply from the start of the pandemic, from around 20,000 in early March to over 30,000 as of late June. In an effort to help clinicians digest the vast amount of biomedical knowledge in the literature, researchers affiliated with Columbia, Brandeis, DARPA, UCLA, and UIUC developed a framework — COVID-KG, for “knowledge graph” — that draws on papers to answer natural language questions about drug purposing and more.

The sheer volume of COVID-19 research makes it difficult to sort the wheat from the chaff. Some false information has been promoted on social media and in publication venues like journals. And many results about the virus from different labs and sources are redundant, complementary, or even conflicting.

COVID-KG aims to solve the challenge by reading papers to build multimedia knowledge graphs consisting of nodes and edges. The nodes represent entities and concepts extracted from papers’ text and images, while the edges represent relations involving these entities.

COVID-KG ingests entity types including genes, diseases, chemicals, and organisms; relations like mechanisms, therapeutics, and increased expressions; and events such as gene expression, transcription, and localization. It also draws on entities annotated from an open source data set tailored for COVID-19 studies, which includes entity types like coronaviruses, viral proteins, evolution, materials, and immune response).

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COVID-KG extracts visual information from figure images (e.g., microscopic images, dosage response curves, and relational diagrams) to enrich the knowledge graph. After detecting and isolating figures from each document with text in its caption or referring context, it then applies computer vision to spot and separate non-overlapping regions and recognize the molecular structures within each figure.

COVID-KG provides semantic visualizations like tag clouds and heat maps that allow researchers to get a view of selected relations from hundreds or thousands of papers at a single glance. This, in turn, allows for the identification of relationships that would typically be missed by keyword searches or simple word cloud or heatmap displays.

In a case study, the researchers posed a series of 11 questions typically answered in a drug repurposing report to COVID-KG, like “Was the drug identified by manual or computation screen?” and “Has the drug shown evidence of systemic toxicity?” With three drugs suggested by DARPA biologists (benazepril, losartan, and amodiaquine) as targets, they used COVID-KG to construct a knowledge base from 25,534 peer-reviewed papers.

Given the question “What is the drug class and what is it currently approved to treat?” for benazepril, COVID-KG responded with:

 COVID KG uses AI to scan thousands of studies to answer doctors’ coronavirus questions

The team reports that in the opinion of clinicians and medical school students who reviewed the results, COVID-KG’s answers were “informative, valid, and sound.” In the future, the coauthors plan to extend the system to automate the creation of new hypotheses by predicting new links. They also hope to produce a common semantic space for literature and apply it to improve COVID-KG’s cross-media knowledge grounding, inference, and transfer.

“With COVID-KG, researchers and clinicians are able to obtain trustworthy and non-trivial answers from scientific literature, and thus focus on more important hypothesis testing, and prioritize the analysis efforts for candidate exploration directions,” the coauthors wrote. “In our ongoing work we have created a new ontology that includes 77 entity subtypes and 58 event subtypes, and we are re-building an end-to-end joint neural … system following this new ontology.”

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AI Weekly: Introducing the AI and surveillance in the age of coronavirus special issue

May 16, 2020   Big Data
 AI Weekly: Introducing the AI and surveillance in the age of coronavirus special issue

With unprecedented and historic impact, the pandemic has changed everything. It forced the entire world to slow to a near halt as health professionals and world leaders scrambled to contain and track the spread of the coronavirus, while citizens fled into their homes to shelter in place and quarantine. Technology has played a central role in much of it, and as we all look to flatten the curve while we reboot society, get back to work, and create treatments for COVID-19, it will continue to do so.

In our upcoming special issue, titled “AI and surveillance in the age of coronavirus,” we focus on one of the most immediate needs: finding the balance between safety and freedom.

We ponder this tension through the lens of the technologies that are involved in contact tracing and quarantine tracking and enforcement. We discuss the methods and technologies involved — like smartphone surveillance, thermal scanning, drones, big data, and facial recognition — and how and where they’re being used around the world. And we unpack the battle in Congress over data privacy law and how to avoid the rise of permanent new surveillance measures. We dig deep into the situation unfolding in France, where all these issues are coalescing.

For VentureBeat, the coronavirus has changed our editorial focus. We had several special issue topics lined up — and then the pandemic descended, and none of those topics felt salient or timely anymore. And so we scrapped weeks of careful planning virtually overnight and began anew, pivoting our focus to the emerging topics created by the effects of the coronavirus.

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Now we’re focusing on subjects like data privacy, tracking, and how AI and big data come into play; how we’re getting back to work; the role automation will play in the immediate future of the workforce; and the ways AI and other transformative technologies are affecting both frontline health care and the search for COVID-19 cures.

We also had to rethink our approach to creating our special issues. These are huge topics, and they deserve thoughtful, careful, and in-depth attention. But they’re also rapidly emerging and developing, and so we’re moving faster and creating leaner special issues. And because these stories don’t end once we hit the publish button, we’ll continue reporting on the related stories that emerge. Our special issues are becoming more like living, breathing documents.

“AI and surveillance in the age of coronavirus” is the first special issue to emerge from our revamped focus and approach. You can get it delivered straight to your inbox next week by signing up here.

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Researchers release data sets to train coronavirus chatbots

May 15, 2020   Big Data

A preprint paper published by researchers at the University of California, San Deigo; Carnegie Mellon University; and the University of California, Davis proposes AI chatbots that generate responses to patient questions about the coronavirus. The team trained the models underpinning these chatbots on a data set in English and one in Chinese. The data sets contained conversations between doctors and patients talking about the coronavirus, and the researchers claim experiments demonstrate that their approach to meaningful medical dialogues is “promising.”

As the coronavirus rages on around the world, some hospitals are discouraging unnecessary visits to prevent the risk of cross-infection. Telemedical apps and services have consequently been overwhelmed by an influx of patients. In March, virtual health consultations grew by 50%, according to Frost and Sullivan research. Against this backdrop, autonomous chatbots designed for coronavirus triage seem primed to help relieve the burden on health providers.

The researchers trained several dialogue models — CovidDialog — on data sets that they scraped from iCliniq, Healthcare Magic, HealthTap, Haodf, and other online health care forums. The English data set contained 603 consultations, while the Chinese data set had 1,088 consultations. Each consultation starts with a short description of a patient’s medical conditions, followed by a conversation between that patient and a doctor, and it optionally includes diagnoses and treatment suggestions provided by the doctor.

The coauthors trained their models based on:

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  • Google’s Transformer architecture, an encoder and decoder architecture that takes the conversation history as inputs and generates the response. Self-attention is used to capture the long-range dependency among words.
  • OpenAI’s GPT, a language model based on the Transformer decoder. When generating a response, GPT predicts the
    next word using its context, including the already-decoded words in this response and the conversation history.
  • BERT-GPT, an encoder-decoder architecture, where the pretrained BERT is used to encode the conversation history and GPT is used to decode the response.

Because direct training of the models on the relatively small data sets would result in poor generalization, the team leveraged transfer learning, which involves pretraining models on large corpora and then fine-tuning them on on the CovidDialog data sets. The pretraining corpora were largely blurbs from Reddit users, Wikipedia, Chinese chatbots, news, books, stories, and miscellaneous web texts.

In experiments post-training, the Transformer, GPT, and BERT-GPT models were tested against common metrics for evaluating machine translation, including perplexity (which is used to judge the quality and “smoothness” of generated responses) and entropy and dist (which are used to measure lexical diversity). They performed poorly overall, but one model — the BERT-GPT model — produced responses to patient questions that were more relevant, informative, and humanlike compared with the baselines, with correct grammar and semantics.

 Researchers release data sets to train coronavirus chatbots

Above: Snippets generated by the various trained coronavirus chatbots. “BART” refers to the BERT-GPT model.

“In this work, we make the first attempt to develop dialogue systems that can provide medical consultations about [coronavirus],” wrote the researchers. “Experimental results show that these trained models are promising in generating clinically meaningful and linguistically high-quality consultations for [coronavirus].”

Both the data sets and code are available in open source.

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ProBeat: Alphabet’s Sidewalk Labs won’t be the last to play the coronavirus card

May 8, 2020   Big Data
 ProBeat: Alphabet’s Sidewalk Labs won’t be the last to play the coronavirus card

Yesterday, Alphabet’s Sidewalk Labs killed its Toronto smart city project. raincoats designed for buildings, heated pavement, and object-classifying cameras will not be traded for unprecedented data collection. Privacy advocates celebrated — Big Brother would not be gaining even more invasive power to surveil residents. But this story is far from over. Whether one hoped for a smart city or feared it, the reality is this project did not live or die on its merits. Nor did it get axed because of “unprecedented economic uncertainty,” as Sidewalk CEO Daniel Doctoroff suggested. The pandemic was just the scapegoat.

The rest of 2020, and possibly beyond, is going to be filled with stories about companies pulling back due to the economy. Look out for them, because they are going to be instructive of what were the riskiest bets in the first place. If you run a business, it might be time to rip off the Band-Aid yourself.

Pandemic or not, it is always instructive to follow the money. Sidewalk Labs is a Google sister company under the Alphabet umbrella. Other Alphabet companies include Calico, CapitalG, DeepMind, GV, Google Fiber, Jigsaw, Loon, Makani, Verily, Waymo, Wing, and X. These moonshots are not broken out in Alphabet earnings because frankly, none are profitable. Instead, they are lumped together under a line item called “Other Bets.” Last week, Alphabet reported its Q1 2020 earnings during which Other Bets revenue was down 21% to $ 135 million, while losses were up 29% to $ 1.1 billion. Yes, Other Bets burned eight times more cash than it generated.

Q1 2020 was a special quarter for Alphabet. Not because it was the worst quarter for Other Bets — there have been worse ones, if you can believe it. Not because it overlapped with the pandemic — Alphabet seems to be handling the downturn, so far. Q1 2020 was special because it was the first full quarter in which Sundar Pichai oversaw Alphabet.

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In December, when Google’s CEO also became Alphabet’s CEO, I explained we knew what to expect: Alphabet companies will either become more focused or get folded into Google. Maybe Pichai has made a decision about Sidewalk Labs. Maybe he hasn’t. Either way, the Sidewalk Labs project was low-hanging fruit — the ROI for a Google smart city was never there.

Don’t get me wrong. I was critical of the Sidewalk Labs approach and have generally argued that tech company expansions need to be less arrogant and more transparent. It’s one thing for a company to be able to halt development of an app overnight. It’s completely another to walk away from building a smart city overnight. Imagine if the smart city already had residents living in it and Sidewalk Labs decided to pull the plug. Is that really the type of control we want to hand over to tech giants?

And yet, Sidewalk Labs’ withdrawal from Toronto is not democracy thwarting surveillance capitalism. Soon after the news broke, the government-backed agency Waterfront Toronto stated “this is not the outcome we had hoped for.”

This case had more to do with the chickens coming home to roost at Alphabet; the pandemic was just the excuse. Keep an eye out for other companies using “unprecedented economic uncertainty” as cover to cancel projects, leave markets, and/or pivot — regardless of whether you are cheering for them or not.

ProBeat is a column in which Emil rants about whatever crosses him that week.

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Google and Facebook: Digital ad market is avoiding coronavirus disaster

May 1, 2020   Big Data
 Google and Facebook: Digital ad market is avoiding coronavirus disaster

(Reuters) — Reports of the demise of the digital advertising market due to the coronavirus outbreak appear exaggerated as the tech giants dominating the online ads business, Google and Facebook, said this week they saw early signs that the worst could be over. Their remarks countered Wall Street expectations of a devastation of the market as hard-hit brands in travel and autos, traditionally big ad spenders, have pulled marketing dollars and as small businesses, the lifeblood of big tech companies’ businesses, have shut down.

At Google’s parent, Alphabet, first-quarter total revenue grew 13% from the previous year to $ 41.2 billion, while Facebook‘s ad sales rose 17% to $ 17.44 billion. They issued first-quarter results that factored in only two weeks of the widespread stay-at-home orders in the United States. But both companies also reassured investors that revenue for the first three weeks of April showed signs of stability, following lower revenue in March.

Alphabet, Facebook, and Snap credited direct response ads, or ads that solicit a direct action, such as clicking a link, using a coupon code or downloading mobile games, for propping up sales during the pandemic. Such ads help advertisers get the most for their money by encouraging immediate response from audiences and are easier to measure, since brands can see how many people clicked on a link or took an action after seeing the ad.

Brand advertising that is used to spread awareness and name recognition for a company, but whose effectiveness is often more difficult to measure, was harder hit. Alphabet said on Tuesday brand advertising declined on YouTube in mid-March, when the pandemic accelerated in the United States.

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Ad prices drop when marketers lower their spending and demand for digital ads decline, and direct response advertisers have been taking advantage of that, said David Campanelli, chief investment officer at ad agency Horizon Media. “This will likely continue through 2Q as we expect pricing to remain low for the foreseeable future,” he said.

Facebook executives said on Wednesday they expected direct response advertising to continue to drive ad sales and that the coronavirus pandemic only reinforced the importance of the strategy. Still, Facebook was cautious, given economists are forecasting a global downturn in the second quarter and “if history were a guide, would suggest the potential for an even more severe advertising industry contraction,” said David Wehner, Facebook’s chief financial officer, during an earnings call.

Alphabet warned that the second quarter could be difficult because the early April trends may not hold. Snap, which owns messaging app Snapchat, said it would shift resources on its ad sales team to serve direct response advertisers better, due to the success of the category.

But Twitter alarmed investors on Thursday as it pointed to a 27% decline in ad revenue as a sign of what the company has seen so far in April. Twitter’s ad business is heavily event-driven and “the suspension of major sporting leagues in March will have hurt its bottom line and will continue to do so as long as social distancing and stay-at-home measures remain in place,” said Jasmine Enberg, senior analyst at research firm eMarketer.

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Amazon bought cameras from Chinese company on U.S. blacklist to screen for coronavirus

April 29, 2020   Big Data
 Amazon bought cameras from Chinese company on U.S. blacklist to screen for coronavirus

(Reuters) — Amazon has bought cameras to take temperatures of workers during the coronavirus pandemic from a firm the United States blacklisted over allegations it helped China detain and monitor the Uighurs and other Muslim minorities, three people familiar with the matter told Reuters.

China’s Zhejiang Dahua Technology Co. shipped 1,500 cameras to Amazon this month in a deal valued close to $ 10 million, one of the people said. At least 500 systems from Dahua — the blacklisted firm — are for Amazon’s use in the United States, another person said.

The Amazon procurement, which has not been previously reported, is legal because the rules control U.S. government contract awards and exports to blacklisted firms, but they do not stop sales to the private sector.

However, the United States “considers that transactions of any nature with listed entities carry a ‘red flag’ and recommends that U.S. companies proceed with caution,” according to the Bureau of Industry and Security’s website. Dahua has disputed the designation.

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The deal comes as the U.S. Food and Drug Administration warned of a shortage of temperature-reading devices and said it wouldn’t halt certain pandemic uses of thermal cameras that lack the agency’s regulatory approval. Top U.S.-based maker FLIR Systems has faced an up to weeks-long order backlog, forcing it to prioritize products for hospitals and other critical facilities.

Amazon declined to confirm its purchase from Dahua, but said its hardware complied with national, state and local law, and its temperature checks were to “support the health and safety of our employees, who continue to provide a critical service in our communities.”

The company added it was implementing thermal imagers from “multiple” manufacturers, which it declined to name. These vendors include Infrared Cameras Inc, which Reuters previously reported, and FLIR, according to employees at Amazon-owned Whole Foods who saw the deployment. FLIR declined to comment on its customers.

Dahua, one of the biggest surveillance camera manufacturers globally, said it does not discuss customer engagements and it adheres to applicable laws. Dahua is committed “to mitigate the spread of the COVID-19” through technology that detects “abnormal elevated skin temperature — with high accuracy,” it said in a statement.

The U.S. Department of Commerce, which maintains the blacklist, declined comment. The FDA said it would use discretion when enforcing regulations during the public health crisis as long as thermal systems lacking compliance posed no “undue risk” and secondary evaluations confirmed fevers.

Dahua’s thermal cameras have been used in hospitals, airports, train stations, government offices and factories during the pandemic. IBM placed an order for 100 units, and the automaker Chrysler placed an order for 10, one of the sources said. In addition to selling thermal technology, Dahua makes white-label security cameras resold under dozens of other brands such as Honeywell, according to research and reporting firm IPVM.

Honeywell said some but not all its cameras are manufactured by Dahua, and it holds products to its cybersecurity and compliance standards. IBM and Chrysler’s parent Fiat Chrysler did not comment.

The Trump Administration added Dahua and seven other tech firms last year to the blacklist for acting against U.S. foreign policy interests, saying they were “implicated” in “China’s campaign of repression, mass arbitrary detention, and high-technology surveillance against Uighurs, Kazakhs, and other members of Muslim minority groups.”

More than one million people have been sent to camps in the Xinjiang region as part of China’s campaign to root out terrorism, the United Nations has estimated.

Dahua has said the U.S. decision lacked “any factual basis.” Beijing has denied mistreatment of minorities in Xinjiang and urged the United States to remove the companies from the list.

A provision of U.S. law, which is scheduled to take effect in August, will also bar the federal government from starting or renewing contracts with a company using “any equipment, system, or service” from firms including Dahua “as a substantial or essential component of any system.”

Amazon’s cloud unit is a major contractor with the U.S. intelligence community, and it has been battling Microsoft for an up to $ 10 billion deal with the Pentagon.

Top industry associations have asked Congress for a year-long delay because they say the law would reduce supplies to the government dramatically, and U.S. Secretary of State Mike Pompeo said last week that policies clarifying the implementation of the law were forthcoming.

Face detection and privacy

The coronavirus has infected staff from dozens of Amazon warehouses, ignited small protests over allegedly unsafe conditions and prompted unions to demand site closures. Temperature checks help Amazon stay operational, and the cameras – a faster, socially distant alternative to forehead thermometers – can speed up lines to enter its buildings. Amazon said the type of temperature reader it uses varies by building.

To see if someone has a fever, Dahua’s camera compares a person’s radiation to a separate infrared calibration device. It uses face detection technology to track subjects walking by and make sure it is looking for heat in the right place.

An additional recording device keeps snapshots of faces the camera has spotted and their temperatures, according to a demonstration of the technology in San Francisco. Optional facial recognition software can fetch images of the same subject across time to determine, for instance, who a virus patient may have been near in a line for temperature checks.

Amazon said it is not using facial recognition on any of its thermal cameras. Civil liberties groups have warned the software could strip people of privacy and lead to arbitrary apprehensions if relied on by police. U.S. authorities have also worried that equipment makers like Dahua could hide a technical “back door” to Chinese government agents seeking intelligence.

In response to questions about the thermal systems, Amazon said in a statement, “None of this equipment has network connectivity, and no personal identifiable information will be visible, collected, or stored.”

Dahua made the decision to market its technology in the United States before the FDA issued the guidance on thermal cameras in the pandemic. Its supply is attracting many U.S. customers not deterred by the blacklist, according to Evan Steiner, who sells surveillance equipment from a range of manufacturers in California through his firm EnterActive Networks.

“You’re seeing a lot of companies doing everything that they possibly can preemptively to prepare for their workforce coming back,” he said.

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Australia launches controversial coronavirus contact tracing app

April 27, 2020   Big Data

(Reuters) — The Australian government launched a controversial coronavirus tracing app on Sunday and promised to legislate privacy protections around it as authorities try to get the country and the economy back onto more normal footing. Australia and neighboring New Zealand have both managed to get their coronavirus outbreaks under control before it strained public health systems, but officials in both two countries continue to worry about the risk of another flareup. “We are winning, but we have not yet won,” Australian Health Minister Greg Hunt said at a televised briefing announcing the app’s launch

The app, which is based on Singapore’s TraceTogether software, uses Bluetooth signals to log when people have been close to one another. It has been criticized by civil liberties groups as an invasion of privacy. The Australian government, which wants at least 40% of the population to sign up to make the effort effective, said the voluntary app, which would not track location, is safe. The app’s stored contact data will enable health officials to trace people potentially exposed to infections. “It will help us as we seek to return to normal and the Australian way of life,” Hunt said. “No one has access to that, not even yourself … only a state public health official can be given access to that data.”

A legislative directive ensuring that will be proposed to the parliament in May, the health ministry said on the app’s website on Sunday. A few countries, including South Korea and Israel, are using high-tech methods of contact tracing which involves tracking peoples’ location via phone networks, though such centralized, surveillance-based approaches are viewed as invasive and unacceptable in many countries.

Trust in governments in Australia and New Zealand has risen since the start of the pandemic, opinion polls show, with leaders of both countries — ideologically opposite — hailed for their management in suppressing the coronavirus. The rate of increase in new cases has been below 1% for two weeks now in both countries – much lower than in many other countries.

On Sunday, Australia’s states of Queensland and Western Australia said they would slightly ease social distancing rules this week to allow for larger outdoor public gatherings, among others, but officials in Victoria, second most populous state, said they were not ready to relax the state’s hardline restrictions. Australia reported 16 new coronavirus cases on Sunday, which took its total to 6,703, according to health ministry data. There have been 83 deaths.

 Australia launches controversial coronavirus contact tracing app

In New Zealand, there were four new confirmed cases, bringing the total to 1,121. Eighteen people have died, health ministry data showed. On Tuesday, New Zealand will start to ease some of the world’s strictest lockdown measures, and is also set to roll out a tracing app soon, but Prime Minister Jacinda Ardern has warned this is not the only panacea. “We have been very clear on from the beginning that no tracking app provides a silver bullet,” Ardern said earlier this month.

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AI Weekly: When to ship or shelve a coronavirus solution

April 18, 2020   Big Data

Apple and Google’s common coronavirus contact tracing solution for smartphones continued to attract a lot of attention and debate over the course of the past week, and understandably so. It’s an unprecedented partnership between the world’s dominant smartphone operating system makers, but people are worried about privacy, and the notion that whatever tracking tool made in the name of coronavirus will outlive the crisis. But debate over Apple and Google’s contact tracing solution seems to have opened up an old argument between people who see a tech solution for every problem and those who say tech can’t solve all our problems. Those debates certainly carry over to the kind of AI being deployed right now, and the important question of when a company should ship or shelve a coronavirus solution.

A lot of AI is being deployed in the pandemic to save lives and someday soon help us resume daily lives, much of which you’ve been able to read about here. But they aren’t all winners.

In February, a robotics company sent its service robot to Times Square in New York for passerbys to answer questions to help them understand if they had coronavirus, but the experience relied on a touchscreen. Given how bad things are in New York City today, that seems pretty irresponsible.

AI is also being used in more productive ways to understand how coronavirus and social isolation are impacting people’s psychological health and well-being. Some AI, like a flu model from Delphi Group at Carnegie Mellon University, is being repurposed to forecast coronavirus models for the United States. An MIT model out this week suggests the effectiveness of social distancing and potential of an “explosion” in cases if those measures were relaxed today.

Of course, also present in this environment is opportunism from startups anxious to remain relevant, raise funding, or attract publicity at a time when much economic activity at a virtual standstill.

 AI Weekly: When to ship or shelve a coronavirus solution

Innovation in a crisis can lead to outcomes that better human lives, or distract from priorities like testing, personal protective equipment, and protecting health care workers and the most vulnerable among us.

Some initiatives seem almost outlandish in their ambition, or, however promising, unable to join the fight. One project straddling that chasm between innovation and what can join the fight soon is Coughs Against COVID.

Cough Against COVID, a project by Wadhwani AI in partnership with the Bill and Melinda Gates Foundation and Stanford University, launched this week. The people behind it collect audio recordings of coughs by people who have confirmed cases of COVID-19. Online submissions for people quarantined at home must be accompanied by a photo of a diagnosis from a doctor. To spur additional research, all data sets collected will be made available in an anonymized, open access data set. In addition to a data collection website, Johns Hopkins University doctors are collecting data directly from patients at a hospital in India.

The hope is the voice recording data can power AI for screening apps being made by public health officials and create an additional diagnosis signal that doesn’t exist today. The project was inspired in part by Global Good’s work around tuberculosis identification in Madagascar with sound, and the work of Massachusetts’ FluSense, which uses cough sounds for health forecasting.

Jigar Doshi is senior researcher at Wadhwani AI, a nonprofit in Mumbai, India. Before moving back to India 3 months ago, Doshi headed machine learning efforts at computer vision startup CrowdAI, a company that worked with Facebook AI Research on multiple projects to assess damage after a natural disaster in order to help government or humanitarian organizations assess need.

Doshi admits he doesn’t know if Cough Against COVID will work, or how much data from coronavirus cases they’ll need to make a robust and accurate model, because COVID-19 is a novel disease. But an additional way to detect it could be helpful in parts of the world where hospitals, health professionals, or diagnostic testing are in short supply.

“It’s sort of a moonshot idea where it may work, and if it works it would really help. We don’t know if it will work, but the only way to find out at this point is to collect the data, do our best modeling,” he told VentureBeat. “This is all centered on limited testing ability, especially as we move away from western countries.”

When we asked what he’d say to people dismissive of the Cough Against COVID as a kind of techno-solutionism, Doshi said “This is one of those things where generally some degree of skepticism towards technical people from their high horse, castle, privilege, whatever you want to call it coming down to help, generally is good.”

Doshi continued to highlight the importance of working with medical professionals to keep things grounded and said the project is only asking COVID-19 patients with mild cases for five minutes of their time to find out if it’s possible.

Charles Onu is founder of Ubenwa, a company using AI to detect birth asphyxia in the sound of crying newborn babies. He sees a lot of merit in work like Cough Against COVID and called it a valid and intriguing venture for a respiratory disease. Onu said he sees promise from research published in June 2019 that demonstrated the ability to recognize and distinguish between the sound of respiratory diseases like bronchitis, asthma, and pneumonia with 80-90% accuracy.

With Ubenwa clinical trials in hospitals on hold due to the crisis, Onu, who is based in Montreal, said Ubenwa is in early talks with Canadian government officials on COVID-19 diagnostics with sound. Onu said he generally agrees with the idea of continuing progress toward experimental efforts, particularly as a way to help in areas where testing and resources are limited.

“One side is making it possible in Canada or the U.S., but also in my village in Nigeria and many places where they may have to go on a very long trip to take a test, so this could definitely close that gap,” Onu said.

Like Doshi, Onu thinks companies and developers deploying AI solutions right now should discuss matters with experts.

“I really hope that at the end of the day, people do whatever you like, but at the deploying, you have a gating mechanism with the public health system to make sure that they’re not spitting out fancy things that don’t solve the problem,” he told VentureBeat.

These are unprecedented times, and what’s needed from moment to the next can change. For example, a month ago, public health officials told people they don’t need to wear face masks unless they’re sick or taking care of someone who’s sick. Now the CDC and others suggest people wear them whenever they’re outdoors and near others.

So when should you ship or shelve a coronavirus-related AI solution? Some of the principles to follow seem similar to ethics principles: speak with stakeholders, and consider societal well-being and the potential impact. The decision should also depend upon whether the tech can deliver immediate results, but what’s considered best might change depending on testing and health care resources.

Some solutions and the companies peddling them, as a cryptographer advising the UK government about contact tracing apps put it, may serve best by just staying out of the way.

For AI coverage, send news tips to Khari Johnson and Kyle Wiggers and AI editor Seth Colaner — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI Channel.

Thanks for reading,

Khari Johnson

Senior AI Staff Writer

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