How Artificial Intelligence-backed technology is helping in the battle against COVID-19 – THE WEEK

COVID-19 has caused some irrevocable damages to the public healthcare systems in countries across the world. As scientists race against time to find the right vaccine and cure for the pandemic, technologists too have chipped in with solutions in the field of Artificial Intelligence (AI), offering assistance in testing, tracing and treatment.

A number of institutions and companies in India are coming up with indigenously developed, AI-backed technologies, which are likely to take the country and the world a step closer to tackling the virus. In an interview to THE WEEK, Prashant Warier, CEO and founder, Qure.ai, which is now deploying AI-powered solutions for COVID-19 management by using chest X-rays which are about 10 to 15 times cheaper than the RT-PCR tests, speaks about how technology is helping in the battle against the pandemic.

You use Artificial Intelligence to detect and triage COVID-19. Please elaborate on how it is done

COVID-19 ranges in severityfrom asymptomatic, mild to severe. The virus is known to mutate and change, making it extremely hard to treat and contain. Having all information at hand and having actionable insights is something that will aid healthcare providers in offering better care. Today, the usage of chest X-rays is being recommended by the American College of Radiology, the Royal College of Radiology and the Canadian Association of Radiologists to screen for COVID-19. Many hospitals across the globe have already implemented chest X-rays in their COVID-19 diagnosis and progression protocols.

The lungs of a COVID-19 patient is very different from that of a healthy person. That is where Qure.ais technology comes into the picture. In 2017, we developed an AI technology that could identify abnormal findings on a chest X-ray. Research shows that in COVID-19 patients, lungs will have consolidations and ground-glass opacities, all of which are detected and marked out using our algorithm. The solution can also quantify the volume of infection, automating a time-consuming step for the already resource-strapped physicians. This is ideal to monitor ICU patients to understand if their lung condition is improving or worsening on a daily basis.

Our solution has also found use in locations where there are not enough swab test kits. The chest X-ray is about 10 to 15 times cheaper than RT-PCR tests, widely available and also can be done in a few minutes, compared to several hours taken for the RT-PCR tests. As such, they have been adopted by various hospital groups in triaging who should be further tested for COVID-19. Unfortunately, radiologist interpretations of the chest X-rays might take hours, sometimes days. That is where Qure comes in, by automatically processing a chest X-ray in under a minute and identifying the COVID risk level of the patient.

What has been the role of Qure.ai in the field of tuberculosis over the past years?

Tuberculosis (TB) is one of the oldest and most infectious diseases of all times. While it is totally curable, it is still one of the top 10 causes of deaths worldwide. In India and some of the emerging economies, there is a huge dearth of radiologists to read chest X-rays that are used as a screening for TB. In India alone, 80 million chest X-rays are being acquired every year. There arent enough radiologists to read them within an acceptable timeline. Depending on the availability of radiology expertise, it can take anywhere between one to 14 days to get diagnostic reports. This leads to delayed diagnosis of the TB patient and further spread of the disease. This gap can be minimised by automating and classifying chest X-ray readings as normal or abnormal with a solution that is scalable and requires little manual intervention. This is precisely how Qures solution, trained on more than 2.5 million chest X-rays, supports the grassroot level health infrastructure. The tool automates reading chest X-rays and generates reports within seconds, thereby reducing the waiting time for TB confirmatory tests, from weeks to a couple of hours and allowing for treatments to be started on the same day. Today, we are present in more than 40 sites across some of the highest TB-burdened countries and have touched more than 200,000 lives.

Can Artificial Intelligence backed technology by Qure be applied in high population density areas of Mumbai such as slums?

Yes, Qure is already working in Maharashtra with Municipal Corporation of Greater Mumbai (MCGM). Qure has partnered with MCGM and other private entities and launched the first mobile COVID-19 testing unit earlier this month.

The COVID-19 bus, equipped with Qures AI and a host of other medical testing facilities like oxygen saturation and body temperature checks, mass screens individuals in the high-risk areas of Worli. Densely populated Worli-Koliwada, one of the first containment zones in Mumbai, is a region of specific interest since it is a high-risk area, comprising of slums and fisherman colonies. The COVID-19 screening bus enables close contacts of positive patients and other asymptomatic residents to be screened via X-rays on the spot, along with checks for fever and oxygen saturation levels. Following the qXR analysis, medium and high- risk candidates are immediately directed for the next steps in the pandemic management process.

In the last 30 days, we have screened more than 2,000 cases and around eight per cent have been instructed for further medical attention. More such screening buses are in the pipeline for other high-risk areas in the city.

What have been your observations so far, with regard to disease progression, given that your technology has been used by health systems in India and abroad?

The progression monitoring capability of qXR is currently being used in San Raffaele Hospital in Milan, Italy, and at the NHS with Royal Bolton Hospital in the UK. They have had very positive feedback for us since we are now supplementing their reports with the ability to give a quantified report, something which was previously rare for chest X-rays. This adds a lot of value in their workflow.

According to the Bolton Critical care team leader: From my experience, the implementation of this innovative solution has been very positive, I am still getting our junior team used to looking at the additional information the software provides. The software has identified successfully a range of pathology from different patterns of consolidation to pneumothorax. I think a significant

benefit will be seen in the post COVID era when we return to our more usual range of clinical presentations. Im hoping this will improve the diagnostic accuracy when our junior doctors first assess patients, and should also improve the correct coding and identification of community-acquired pneumonia.

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How Artificial Intelligence-backed technology is helping in the battle against COVID-19 - THE WEEK

Artificial intelligence harnessed to enforce face mask use on public transport and beyond – Verdict

Artificial intelligence (AI) that can detect if a person is wearing a face mask or similar protective face covering has been launched for deployment in public and private locations.

Developed by Aerialtronics, a subsidiary of French civilian drone manufacturer Drone Volt, the AI is compatible with all forms of cameras, including surveillance cameras and those equipped in drones.

It is designed to identify faces and classify them as either wearing or not wearing a mask, and can provide real-time notifications to the operator of people who are not wearing a suitable protective face covering.

The technology is intended to be used in areas where a face mask is required, such as in transit zones such as airports, and on public transport, as well as in spaces such as construction sites, shopping centres and sports venues, to assist security with the enforcement of mask wearing policies.

The development of the artificial intelligence technology comes as many countries and private organisations are mandating the wearing of face masks in areas where the concentration of people is high, as part of ongoing efforts to limit the spread of the coronavirus beyond lockdown.

In the UK, for example, face masks will become mandatory to be worn on public transport from 15 June, while over 50 countries have now made the wearing of such face coverings mandatory in public spaces.

However, enforcing the wearing of face masks is immensely challenging for police and other security, giving this artificial intelligence product particular promise.

The objective of this solution is to simplify the mission of security services through effective real-time monitoring of faces with or without masks, said Olivier Gualdoni, chairman and CEO of Drone Volt.

This tool contributes to both the health challenges involved in the fight against viruses such as the coronavirus and to the prevention of occupational risks.

As with any technology that involves identifying faces, the installation of such a technology is likely to be met with privacy concerns.

In a bid to alleviate this, Aerialtronics has included an optional face blur to protect users faces from being recorded. However, in large-scale environments or spaces where enforcement is through after-the-fact fines, this will not be an option.

Read more: NHS trials AI system to predict coronavirus ventilator demand

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Artificial intelligence harnessed to enforce face mask use on public transport and beyond - Verdict

Artificial intelligence that mimics the brain needs sleep just like humans, study reveals – The Independent

Artificial intelligence designed to function like a human could require periods of rest similar to those needed by biological brains.

Researchers at Los Alamos National Laboratory in the US discovered that neural networks experienced benefits that were "the equivalent of a good night's rest" when exposed to an artificial analogue of sleep.

"We were fascinated by the prospect of training a neuromorphic processor in a manner analogous to how humans and other biological systems learn from their environment during childhood development," said Yijing Watkins, a computer scientist at Los Alamos.

Sharing the full story, not just the headlines

The discovery was made by the team of researchers while working on a form of artificial intelligence designed to mimic how humans learn to see.

The AI became unstable during long periods of unsupervised learning, as it attempted to classify objects using their dictionary definitions without having any prior examples to compare them to.

When exposed to a state that is similar to what a human brain experiences during sleep, the neural network's stability was restored.

Russia has launched a humanoid robot into space on a rocket bound for the International Space Station (ISS). The robot Fedor will spend 10 days aboard the ISS practising skills such as using tools to fix issues onboard. Russia's deputy prime minister Dmitry Rogozin has previously shared videos of Fedor handling and shooting guns at a firing range with deadly accuracy.

Dmitry Rogozin/Twitter

Google celebrates its 21st birthday on September 27. The The search engine was founded in September 1998 by two PhD students, Larry Page and Sergey Brin, in their dormitories at Californias Stanford University. Page and Brin chose the name google as it recalled the mathematic term 'googol', meaning 10 raised to the power of 100

Google

Chief engineer of LIFT aircraft Balazs Kerulo demonstrates the company's "Hexa" personal drone craft in Lago Vista, Texas on June 3 2019

Reuters

Microsoft announced Project Scarlett, the successor to the Xbox One, at E3 2019. The company said that the new console will be 4 times as powerful as the Xbox One and is slated for a release date of Christmas 2020

Getty

Apple has announced the new iPod Touch, the first new iPod in four years. The device will have the option of adding more storage, up to 256GB

Apple

Samsung will cancel orders of its Galaxy Fold phone at the end of May if the phone is not then ready for sale. The $2000 folding phone has been found to break easily with review copies being recalled after backlash

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Apple has cancelled its AirPower wireless charging mat, which was slated as a way to charge numerous apple products at once

AFP/Getty

India has claimed status as part of a "super league" of nations after shooting down a live satellite in a test of new missile technology

EPA

5G wireless internet is expected to launch in 2019, with the potential to reach speeds of 50mb/s

Getty

Uber has halted testing of driverless vehicles after a woman was killed by one of their cars in Tempe, Arizona. March 19 2018

Getty

A humanoid robot gestures during a demo at a stall in the Indian Machine Tools Expo, IMTEX/Tooltech 2017 held in Bangalore

Getty

A humanoid robot gestures during a demo at a stall in the Indian Machine Tools Expo, IMTEX/Tooltech 2017 held in Bangalore

Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

The giant human-like robot bears a striking resemblance to the military robots starring in the movie 'Avatar' and is claimed as a world first by its creators from a South Korean robotic company

Jung Yeon-Je/AFP/Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi

Rex

Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session

Rex

A test line of a new energy suspension railway resembling the giant panda is seen in Chengdu, Sichuan Province, China

Reuters

A test line of a new energy suspension railway, resembling a giant panda, is seen in Chengdu, Sichuan Province, China

Reuters

A concept car by Trumpchi from GAC Group is shown at the International Automobile Exhibition in Guangzhou, China

Rex

A Mirai fuel cell vehicle by Toyota is displayed at the International Automobile Exhibition in Guangzhou, China

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A visitor tries a Nissan VR experience at the International Automobile Exhibition in Guangzhou, China

Reuters

A man looks at an exhibit entitled 'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London

Getty

A new Israeli Da-Vinci unmanned aerial vehicle manufactured by Elbit Systems is displayed during the 4th International conference on Home Land Security and Cyber in the Israeli coastal city of Tel Aviv

Getty

Russia has launched a humanoid robot into space on a rocket bound for the International Space Station (ISS). The robot Fedor will spend 10 days aboard the ISS practising skills such as using tools to fix issues onboard. Russia's deputy prime minister Dmitry Rogozin has previously shared videos of Fedor handling and shooting guns at a firing range with deadly accuracy.

Dmitry Rogozin/Twitter

Google celebrates its 21st birthday on September 27. The The search engine was founded in September 1998 by two PhD students, Larry Page and Sergey Brin, in their dormitories at Californias Stanford University. Page and Brin chose the name google as it recalled the mathematic term 'googol', meaning 10 raised to the power of 100

Google

Chief engineer of LIFT aircraft Balazs Kerulo demonstrates the company's "Hexa" personal drone craft in Lago Vista, Texas on June 3 2019

Reuters

Microsoft announced Project Scarlett, the successor to the Xbox One, at E3 2019. The company said that the new console will be 4 times as powerful as the Xbox One and is slated for a release date of Christmas 2020

Getty

Apple has announced the new iPod Touch, the first new iPod in four years. The device will have the option of adding more storage, up to 256GB

Apple

Samsung will cancel orders of its Galaxy Fold phone at the end of May if the phone is not then ready for sale. The $2000 folding phone has been found to break easily with review copies being recalled after backlash

PA

Apple has cancelled its AirPower wireless charging mat, which was slated as a way to charge numerous apple products at once

AFP/Getty

India has claimed status as part of a "super league" of nations after shooting down a live satellite in a test of new missile technology

EPA

5G wireless internet is expected to launch in 2019, with the potential to reach speeds of 50mb/s

Getty

Uber has halted testing of driverless vehicles after a woman was killed by one of their cars in Tempe, Arizona. March 19 2018

Getty

A humanoid robot gestures during a demo at a stall in the Indian Machine Tools Expo, IMTEX/Tooltech 2017 held in Bangalore

Getty

A humanoid robot gestures during a demo at a stall in the Indian Machine Tools Expo, IMTEX/Tooltech 2017 held in Bangalore

Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

The giant human-like robot bears a striking resemblance to the military robots starring in the movie 'Avatar' and is claimed as a world first by its creators from a South Korean robotic company

Jung Yeon-Je/AFP/Getty

Engineers test a four-metre-tall humanoid manned robot dubbed Method-2 in a lab of the Hankook Mirae Technology in Gunpo, south of Seoul, South Korea

Jung Yeon-Je/AFP/Getty

Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi

Rex

Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session

Rex

A test line of a new energy suspension railway resembling the giant panda is seen in Chengdu, Sichuan Province, China

Reuters

A test line of a new energy suspension railway, resembling a giant panda, is seen in Chengdu, Sichuan Province, China

Reuters

A concept car by Trumpchi from GAC Group is shown at the International Automobile Exhibition in Guangzhou, China

Rex

A Mirai fuel cell vehicle by Toyota is displayed at the International Automobile Exhibition in Guangzhou, China

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Artificial intelligence that mimics the brain needs sleep just like humans, study reveals - The Independent

Chinese Debates on the Military Utility of Artificial Intelligence – War on the Rocks

The Chinese military believes it is losing a high-stakes competition with the United States and Russia to lead the world in artificial intelligence (AI). In articles like, The Quiet Rise of an Artificial Intelligence Arms Race (), Chinese military authors point to a quote from Russian President Vladimir Putin, that whoever leads in AI will rule the world. As evidence of the U.S. militarys ambition to dominate in this field, they cite findings about AI in future warfare from the U.S. National Security Commission on Artificial Intelligence, calls for the United States to ally with other nations against Chinese AI development, the Department of Defense AI strategy, and the establishment of the Pentagons Joint Artificial Intelligence Center. In 2017, China was among the first nations to advance a national-level AI development strategy that broadly addressed AIs role in economic development.

The Chinese military, however, has been opaque about its AI strategy and intentions. Undoubtedly, Chinese military officials understand they must compete with the United States by adapting quickly to changes in warfare brought about by AI and autonomous systems. An examination of the ongoing debate within the ranks of Chinas Peoples Liberation Army (PLA) about the transformation of warfare by AI what they call intelligentized warfare () reveals that this new form of warfare is an extension of existing Chinese strategy and operational concepts.

AI may allow China to realize its long-standing, information-centric military strategies. The American military tends to focus on how AI can enable lethal attacks against opposing forces. Chinese strategists tend to argue that AI technologies should be used kinetically and non-kinetically to dominate information systems and networks, to effectively paralyze an opponents joint force. Information warfare and information control are at the heart of the PLAs approach to warfare and AI. Countering Chinas strategy will require a defensive and offensive use of new AI technologies. In a future confrontation, the U.S. military will need to employ AI and autonomous capabilities to enable and defend its information system-of-systems while simultaneously using AI technologies to attack Chinas information-centric strategy and capabilities.

Chinas Established Military Strategy Will Be Enhanced by AI

The PLAs overarching strategy for defeating the U.S. military, or any foreign adversary, is to dominate in a system-of-systems confrontation. This method of warfighting focuses on creating disruption or paralysis across an enemy system-of-systems versus emphasizing the attrition of forces. First, the PLA will attempt to crash the adversarys information networks using kinetic and non-kinetic means. The Chinese military believes that information is the critical element that binds and enables a larger military system-of-systems. Second, the PLA intends to eliminate individual elements of a now-disaggregated enemy force with long-range precision fires. This Chinese military doctrine has been described as systems confrontation, but that short-hand does not accurately capture the potential for a cascade of compounding effects within a complex system-of-systems and the resulting paralyzing outcomes. AI may provide a critical means to that end.

American assessments of military AI often focus on the second step coordinated lethal attacks using autonomous systems against opposing forces. Drones and other autonomous systems are certainly under development in the PLA. However, the Chinese focus is currently on developing AI technology, methods, and tactics to precisely target key elements within an enemy system-of-systems. The objective is to paralyze the adversary, and goes well beyond merely throwing sand in the gears of the enemy joint force. If successful, the large-scale attrition of forces may not even be necessary.

The use of AI in a system-of-systems confrontation conforms with and enables existing Chinese military doctrine on informationized warfare. The PLA believes that the center of gravity in modern military operations has shifted from concentrations of forces to information systems-of-systems everything from target detection to communication to information processing to command of action. Modern military information systems-of-systems are vast, complex, and in the future will likely be managed by AI. Therefore, it follows that they can only be analyzed in real-time and attacked using AI.

The PLAs objective is to use AI algorithms, machine learning, human-machine teaming, and autonomous systems collaboratively to paralyze its adversaries. The ultimate goal for the Chinese military appears to be cognitive advantage the ability to adapt ones system-of-systems faster than ones adversary. The Chinese seek to use AI to deliver precise effects to immobilize their adversary while defending their own system-of-systems. Any Chinese military challenger would be wise to understand the implications of how future AI capabilities may be employed to realize Chinese goals in system-of-systems confrontation.

An Intelligentized Form of War

The English-language version of Chinas 2019 Defense White Paper observes a change in modern warfare: War is evolving in form towards informationized warfare, and intelligent warfare is on the horizon. A translation of the Chinese-language version, however, reveals that the change is not about moving toward informationized warfare, it is about an evolution in informationized warfare: The form of war is accelerating toward an informationized warfare evolution, there are indications intellgentized warfare is emerging (). The Chinese form of war () speaks to the changing character of war; an assessment of the objective basis that will drive the conduct of present and future warfare. The information age had yielded informationized warfare () forming the basis for PLA development since the early-2000s. Chinese military leaders now believe that informationized war is evolving and intelligentized warfare will become the prevailing form of war.

The 2019 forecast of an evolution in the form of war toward intelligentization is very similar to where the PLA found itself in the early 2000s. The 2002 Chinese Defense White Paper stated, The form of war is developing in the direction of informationization. What happened in the wake of that top-level proclamation was a vigorous discussion among Chinese military writers parsing out the transformation of warfare by information and modern information technology. That debate and the dialectical back-and-forth ultimately formed the foundations of Chinese informationized warfare theory and doctrine. It bore out informationized warfare patterns of operations () and basic guiding thought () informationized warfare theory that placed information control at the center of PLA operational concepts. As with those explorations of informationized warfare in the early 2000s, Chinese military authors are currently discussing the changes that intelligentized warfare will bring to the PLA.

The Chinese military is not a hive mind. Debates within the Chinese military are robust and often contrarian. Western analysts must distinguish between guidance from central leadership and what may be dissent or consensus in a debate. The pages of the PLAs official newspaper, the PLA Daily () and the PLAs official web site provide a venue for the discussion of emerging phenomenon on any number of topics, including intelligentized warfare. While far from authoritative guidance, the publication of research, opinions, and proposals in official media comes with the tacit endorsement of the Chinese military establishment. The PLA Daily newspapers Military Forum () offers monographs by select military authors and provides insights into the consensus that may be emerging within the PLA over intelligentized warfare.

Since the Defense White Paper was published in mid-2019, authoritative commentaries have appeared with increasing frequency in official PLA media discussing informationized warfare, intelligentized warfare, unmanned systems, autonomous decision-making, and cognitive warfare. In articles like, Seize the Commanding Heights of Artificial Intelligence Technology Development (), authors discuss the development of this new type of intelligentized warfare, forecast new types of intelligentized technologies and operational concepts, and ultimately seek to propel PLA thinking ahead of counterparts in the United States. These commentaries demonstrate a trajectory of PLA military thinking that integrates AI with Chinese thinking on informationized warfare and the PLAs information-centric military strategy.

Six Principles of Chinas Intelligentized Warfare

There is a significant amount of overlap among Chinese, Russian, and Western militaries on the topic of military AI. For example, all seem to recognize that autonomous swarms of unmanned platforms may generate advantages in terms of cost, scale, dispersion, and adaptation, enabling lethal saturation attacks. Articles like Intelligentized Warfare, Where are the Constants? (, ) (January 2020), remind readers that AI may have changed the character of war, but the nature of war endures war is still a violent action taken to a political end with humans central to the endeavor. Several Chinese authors emphasize that humans will still plan, organize and initiate wars. While man-machine teaming may enhance human cognition and action, Chinese analysts are directed to guard against the anthropomorphization of weapons and the weaponization of humans and always place humans in the dominant role.

However, there are a number of unique perspectives emerging from the Chinese debate over AI that may merit attention by Western analysts. Most appear to reflect the premise that AI will enable and evolve existing Chinese warfare theory and doctrine.

First, PLA strategists believe that intelligentized warfare is an evolution of informationized warfare. Several authors point out that intelligentized warfare is essentially highly evolved informationized warfare system-of-systems confrontation reliant on information moving through digital systems and networks. How to Integrate the Mechanization, Informationization and Intelligentization of Weapons and Equipment (, , ) (October 2019) acknowledges that informationization and intelligentization are inextricably linked. But articles like this have begun to categorize intelligentization as an independent, aspirational stage of future military development.

Next, Chinese military authors argue that ubiquitous networks will enable systems-of-systems warfare. In articles such as, Picturing a New Combat System () (June 2019) they refer to the emergence of ubiquitous networks () that will shorten the distance between perception, judgement, decision-making, and action. The Chinese concept of ubiquitous networks appears similar to the U.S. Defense Advanced Research Projects Agencys (DARPA) Mosaic Warfare concept of system-agnostic, flexible, and rapidly configurable networks. The PLA has been focused on military systems-of-systems development for well over 15 years. Ubiquitous networks and AI may give the PLA its own version of mosaic warfare with Chinese characteristics.

Chinese strategists also contend that AI enables command and operational design. For example, How Unmanned Combat can Change the Form of War () (August 2019) highlights an underappreciated feature of Chinese military theory the way in which command and control is exercised through operational design and pre-conflict campaign planning. There are misperceptions that the PLA has a Soviet-style centralized command and control system the premise being that if PLA conventional forces or autonomous systems are cut off from centralized control, they either will be unable to function or will make haphazard decisions. However, the PLA believes that command and control can be built-in to system design and operational plans to mitigate threats of either human or machine errors in combat. Consistent with its Marxist-Leninist intellectual heritage, the PLA conceptualizes war as a scientific process that can be deconstructed, allowing for calculated outcomes. AI and machine-learning may provide the Chinese military with the algorithms and tools it believes it needs to determine end results and develop invulnerable systems-of-systems, operational capabilities and military plans.

Fourth, there is an expectation that AI will enable new operational concepts. Intelligentized Warfare, Where are the Changes? (, ) (January 2020) is the companion piece to Intelligentized Warfare, Where are the Constants? cited above. In this article, the authors identify several future patterns of operations Chinese operational concepts including autonomous swarm attrition warfare (), autonomous dormant assault warfare () autonomous cross-domain mobile warfare () and autonomous cognitive control warfare (). Swarm attrition warfare capitalizes on decentralized operations and coordinated saturation attacks by large numbers of autonomous, unmanned systems. Dormant assault warfare portends surprise attacks at key points or against critical adversary capabilities by autonomous platforms programmed to lie in wait until activated. Autonomous cross-domain mobile warfare envisions an autonomous force that is highly mobile and can strike on a large-scale and at long-ranges. This last concept presumably borrows from the U.S. Armys Multi-Domain Operations concept.

Autonomous cognitive control warfare is not explicitly described in the January 2020 article. However, articles like Cognitive Warfare: Dominating the Intelligence Age (: ) (March 2020) describe a shift in opposing military centers of gravity toward the cognitive domain. Chinese military authors are fond of invoking the U.S.-originated OODA loop (observe, orient, decide, act). These Chinese authors observe that decision-making is the bottleneck in the OODA loop. Future autonomous systems, they say, will compete for cognitive advantage and thus decision advantage enabling faster cycling of military action to dominate an adversary in parallel operations drawing from the U.S.-originated parallel warfare concept.

Fifth, AI offers the PLA the ability to precisely release kinetic energy and paralyze an opponents system-of-systems. A Chinese state-media (Xinhua) article, Military Intelligentization is Profoundly Affecting Future Operations () was posted to the Chinese Ministry of National Defense website in September 2019. The article observes that in intelligentized warfare cognitive-centric warfare AI and autonomous systems will allow for precise energy release, either dispersed across a system-of-systems or concentrated on a critical node to impose highly persistent paralysis on an adversary. Battlefield advantage will go to the force that can dominate the cognitive domain perceiving, adapting and acting faster than an opponent to impose or reverse system-of-systems paralysis.

Finally, Chinese military analysts recognize that the PLA must accelerate progress on AI. The military scholars cited here uniformly believe that China is well behind the United States in the development of military AI. The emphasis on AI in the Defense Departments Third-Offset Strategy, or even Russias progress in unmanned and autonomous systems, are often cited to illustrate the PLAs lagging progress, adding a sense of urgency to the need for military AI development in China.

The PLA Overtaking on the Curve

AI is a clear priority for the Chinese military. The PLA has adopted a strategy of overtaking on the curve (), catching up with and passing the United States and Russia by metaphorically turning more tightly in corners as trends in science and technology change direction. There will be myriad innovations that change the trajectory of AI technology in the coming years. Each one will be a potential opportunity for the PLA to close the technology gap with the United States and allow the Chinese military to realize its information-centric military strategy.

According to recent Western studies of the AI industry, the United States appears to be in the lead with China rapidly closing the gap. Assessing military competition in AI is more difficult. The U.S. militarys Fiscal Year 2021 budget proposed $841 million in direct spending on AI (0.1 percent of the $705 billion proposal), but that fails to capture how AI is being integrated throughout different weapons systems budgets. Chinese defense spending is even more opaque. However, a significant number of Chinese military institutions do appear to be working diligently on AI innovation.

Assessing how the Chinese and U.S. militaries compare in terms of AI is made even more difficult by the fact that innovation and technical progress on AI has been driven by industry for civil applications. Armed forces will continue to capitalize on the dual-use nature of big data processing and AI algorithms that increase industrial efficiencies and enable commercial autonomous systems.

In the competition to lead in AI, China enjoys the advantage of scale. The Chinese government is accelerating the development of AI technology using entire cities as laboratories. In early April 2020, in the wake of the COVID-19 outbreak, Chinese President Xi Jinping visited Hangzhou and called for Chinese cities to become smarter. Hangzhou is just one of several Chinese smart cities experimenting with the use of AI for city-wide management and security. Ultimately, the PLA will capitalize heavily on Chinas cutting edge progress in civil and commercial AI technology, much of it in cooperation with U.S. and other foreign industries. Accounting for these different development models directed by government or left to private industry may be critical in forecasting outcomes in a military AI arms race.

The Big Picture

The Chinese military, in its own self-assessment, falls well short of a globally present U.S. military that can project an overwhelming joint force anywhere in the world with cutting-edge military technology and a wealth of combat experience. President Xi has mandated that the Chinese military be fully modernized by 2035 and a world-class military on par with the United States military by 2050.

Chinas strategy for the use of AI technology is evolving from their interpretation of the character of war and is ultimately an extension of the PLAs informationized warfare concepts. While there is certainly overlap with U.S. military thinking on the use of AI, Chinese military scholars appear to be reaching different conclusions. U.S. thinking tends to emphasize the role of AI in enhancing firepower- and maneuver-centric strategies. The PLA, on the other hand, is advancing AI concepts that enhance its information-centric military strategies.

New technologies related to artificial intelligence, machine learning, and autonomous systems may provide the PLA with necessary tools to realize its long-standing goals of controlling the information domain, manipulating perception, and paralyzing adversary decision-making. In developing strategies to counter Chinese military capabilities, the Pentagon should pay close attention to the PLAs evolving warfighting concepts and views on AI in future combat.

Michael Dahm is a senior researcher at the Johns Hopkins University Applied Physics Laboratory (APL) and retired U.S. Navy intelligence officer. Mr. Dahms perspectives presented in War on the Rocks are his own and do not necessarily reflect those of APL or its sponsors.

Image: China Military

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Chinese Debates on the Military Utility of Artificial Intelligence - War on the Rocks

UWA researchers to predict suicide risk with artificial intelligence – University News: The University of Western Australia

Researchers from The University of Western Australia are developing a system using artificial intelligence that can predict the likelihood of suicide in individuals most at risk, and assist with clinical decision-making.

The research team from UWA and the Mental Health Service at Armadale Kalamunda Group has been awarded a Mental Health Research Fund Grant by the East Metropolitan Health Service to create a system that will improve the existing risk assessment framework used by healthcare providers.

The current methodology to predict an individuals risk of suicide or self-harm is highly subjective and can be influenced by the assessors experience, recent negative outcomes and other biases.

Through the development of a computer-based system using artificial intelligence algorithms, the researchers will be able to determine the factors in actual behaviour which are better predictors of risk.

The system would be developed as a companion tool to be used alongside the current risk assessment models and protocols.

Professor Mohammed Bennamoun from UWAs Department of Computer Science and Software Engineering said a system that could successfully improve prediction of self-harm or suicide would have worldwide implications.

It will also be particularly useful in places where there are fewer mental health specialists available to carry out the risk analysis, Professor Bennamoun said.

Dr Dharjinder Rooprai, Head of Psychiatry and Consultant Psychiatrist at the Armadale Kalamunda Group, said a high proportion of individuals who went on to commit suicide often suffered with a mental illness, including depression.

An artificial intelligence system that can be employed by healthcare providers to assist their patients risk of suicide or self-harm assessment would have a profoundly positive impact on their patients care journey, Dr Rooprai said.

The researchers are also considering facial recognition as a tool to identify an individuals mental state and predict the likelihood of adverse outcomes.

Professor Bennamoun said that while, for example, facial recognition was increasingly used for tracking and surveillance, artificial intelligence overall would have a significant impact on humans in new ways.

The capability of facial recognition to identify patients at risk of suicide would be revolutionary in the field of psychiatry and would have implications far beyond risk prediction, he said.

Simone Hewett (UWA Media and PR Manager) 08 6488 3229 / 0432 637 716

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UWA researchers to predict suicide risk with artificial intelligence - University News: The University of Western Australia

Artificial Intelligence as a Service Market Research, Dependability And Innovations In Technology – Cole of Duty

The report on the Artificial Intelligence as a Service Market provides a birds eye view of the current proceeding within the Artificial Intelligence as a Service market. Further, the report also takes into account the impact of the novel COVID-19 pandemic on the Artificial Intelligence as a Service market and offers a clear assessment of the projected market fluctuations during the forecast period. The different factors that are likely to impact the overall dynamics of the Artificial Intelligence as a Service market over the forecast period (2020-2026) including the current trends, growth opportunities, restraining factors, and more are discussed in detail in the market study.

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Artificial Intelligence as a Service Market Research, Dependability And Innovations In Technology - Cole of Duty

VisionQuest Biomedical and The University of New Mexico combine artificial intelligence and infrared imaging to diagnose early signs of diabetic foot…

VisionQuest Biomedical and the University of New Mexico School of Medicine have been awarded a three-year US$3 million grant from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health (NIH), to complete the clinical validation of a new technology to detect early signs of diabetic peripheral neuropathy (DPN), also known as diabetic foot.

Peter Soliz, founder and chief technology officer of VisionQuest, says, Our patented technology for detecting early signs of peripheral neuropathy will fundamentally change how physicians manage this severe complication of diabetes. This system will complement our already successful EyeStar system for the detection of diabetic retinopathy and will allow us to screen for multiple diabetes complications in one visit.

Mark Burge, deputy director of the University of New Mexicos Clinical & Translational Science Center (CTSC) and co-principal investigator on this project, adds, A simple test that can be performed by the primary care physician in the clinic and which is highly sensitive and specific does not currently exist. This device will fill an important gap in providing comprehensive care to individuals diagnosed with diabetes.

Diabetes affects 34.2 million people in the USA, or 10.5 percent of the population. The Foundation for Peripheral Neuropathy estimates that over 70% of people diagnosed with diabetes have developed DPN, a painful complication of diabetes that leads to loss of sensation, foot ulcers, and nearly 54,000 amputations per year.

Current screening methods cannot reliably detect the early stages of DPN, when preventative care can improve outcomes. VisionQuests fully automated, noninvasivesystem analyses real-time thermal video of changing temperatures on the bottom of the foot to produce highly sensitive and consistent measurements of blood flow that can be used for diagnosis in primary-care clinics and do not require interpretation. The device and technique were awarded a US patent in 2014.

Through this NIDDK grant, VisionQuest will complete the clinical validation needed to pursue clearance by the US Food and Drug Administration (FDA) to bring the device to market in the USA.

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VisionQuest Biomedical and The University of New Mexico combine artificial intelligence and infrared imaging to diagnose early signs of diabetic foot...

UM-Flint professor uses artificial intelligence to study diseases, food contamination – University of Michigan Flint News

A look at Halil Bisgins published research shows an eclectic selection of topics: an analysis of the structure of ISIS propaganda, detecting automated activity on Twitter, predicting fetal development diseases, drug repositioning, assessing the performance of cancer panels, and identifying food contaminating beetles to name a few. His work spans such a wide number of fields, from bioinformatics to social computing, that you may be left wondering what his particular area of expertise actually is.

In fact, Bisgin is an assistant professor of computer science in the College of Arts & Sciences at UM-Flint with expertise in data mining and machine learning. And while, for many of us, the term computer science conjures up images of building computer programs and smartphone apps, Bisgins interdisciplinary approach has allowed him to make advances in numerous fields outside the typical realm of computer science.

Two of his most recent collaborations have been with the Food & Drug Administration and Beaumont Health System.

Insect pests can contaminate as much as ten percent of the total food produced in the United States. Identifying the species involved usually requires a food inspection analyst with years of training to determine the microscopic differences.

Bisgin worked with the Food & Drug Administration to create an AI system that automatically detects insect contaminants from images. The research project focused on 15 of the most common beetle species detected in food inspections.

We cropped the images into smaller pieces because, with processed food, the whole beetle will probably not remain intact, Bisgin explains. I also used the Great Lakes supercomputer at U-M Ann Arbor to train my model because this is a very computationally demanding process.

With an overall accuracy rating of 80 percent, Bisgins program can quickly identify the species contaminating stored foods, which in turn informs possible causes and solutions to the infestation.

In a collaboration with the Beaumont Health System, Bisgin used machine learning to identify specific biomarkers associated with a condition known as Intrauterine Growth Restriction (IUGR).

With IUGR, developing babies dont grow to normal weight during pregnancy. A common defining feature of the condition is a birth rate lower than the 10th percentile, controlling for factors such as gender and ethnicity. Still, it is important to distinguish IUGR from other causes of small stature to avoid unnecessary medical testing and interventions during pregnancy.

Beaumont research scientist Ali Yilmaz would share files with hundreds of metabolic data points from blood samplesboth from pregnant women with IUGR and without the condition.

From those hundreds of data points, Bisgins approach can narrow it down to a handful of potential biomarkers associated with the condition. Medical researchers can then spend their time and resources more effectively.

It would take quite some time to figure out what is happening without an efficient method. [Bisgin] was a huge help, Yilmaz says. These are proof of concept studies, and hopefully it will lead us to working with thousands of samples and identifying countless potential biomarkers for disease.

The innovative manner in which Bisgin has applied his computer science expertise in solving real-world issues exemplifies the creative mindset embraced by both students and faculty in UM-Flints College of Arts & Sciences.

Dr. Bisgin has shown incredible flexibility in utilizing his skillset to solve complex issues across disciplines, explains Susan Gano-Phillips, dean of CAS. This work highlights the value of creativity in solving new problems, something we emphasize every day in the college and across the UM-Flint campus.

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UM-Flint professor uses artificial intelligence to study diseases, food contamination - University of Michigan Flint News

Opinion: Artificial intelligence should be integrated into our workforce – Los Angeles Times

The recent news headlines have been scattered with multiple topics of discussion on Artificial Intelligence, or AI, and its wide application. Artificial Intelligence has been altering and mediating all forms of human interaction, ranging from companies/businesses in risk management to national security and warfare.

However, the pinnacle of debates seems to center around Americas workforce and the replacement of labor-intensive work with robots. According to Fortune, by 2030, more than 800 million jobs will be replaced. Numerous jobs of varying skill requirements are at risk of being replaced by machines.

Many technology companies such as Apple, Google and Uber have already undergone development for self-driving cars and the progress is alarming. Several car corporations such as Mercedes-Benz, Tesla and Waymo have already assimilated self-parking mechanics and self-driving car services as of right now. Transportation automation may risk 5.2 million jobs in the US alone, according to the Bureau of Transportation Statistics.

White-collared jobs are no safe-haven either. Journalists, lawyers, even medical researchers and doctors are at risk of losing their jobs. According to Forbes, computer creativity is taking leaps forward in all forms of art, including literature. Much of a lawyers job consists of contracting and document-scanning which can be done more efficiently and effectively by computers than humans can.

Many of todays most brilliant minds have said that artificial intelligence will be the downfall of humanity, however, we should not rush to such conclusions. In many cases, AI will not be replacing humans, but rather, will be aiding. There have been multiple examples of new machinery affecting an area of job security, yet in many cases, weve learned to adapt and make use of it.

In recent times, many people have shown disapproval of such artificial intelligence with violence and vandalism. There has been increased fear over job security with AI, but many seem to ignore any idea of a mixture of both the organic and inorganic in the workplace. AI can improve our labor force rather than replace it, and jobs will be reaffirmed to fit with these machines.

With this rise of technology, comes its ethics and AI will learn based on what we feed it. By giving such machines the tedious tasks that we do not wish to do, there is more time for creativity, flexibility and growth. For example, self-driving cars will replace drivers, but it will also open other jobs such as maintenance of these automobiles. In the same sense, AI will open new windows for the economy.

Joshua Nam, a sophomore at Van Nuys High School, is an avid computer programmer, and one of many minds that will be living in an era of AI integration. He responded positively to machine learning.

Artificial Intelligence can sometimes come up with ideas that we cant come up with ourselves, Nam said. It depends on whos controlling the AI. If there is a monopoly on AI, its not good, as one person can affect so many people. Were constantly moving in the future, [and] people can find other jobs that are more beneficial.

Not only limited to the auto industry, but AI will also benefit warehouse employees, security and medicine. Robots have become comparatively better at medical diagnosis than humans. As a result of the growing influence of artificial minds, they will become more effective than us at performing these tasks.

However, there will always be aspects of customer service and care that humans will be better at. When going to a hospital, people want to be comforted by people, and similarly, the human aspect of many jobs will never be replaced by a machine.

There are many unanswered questions about machines in a workspace such as a robot workers rights, changes in legal standards, laws written about safety, to say the least. At the end of the day, AI is an apparatus with wide application, but control lies in the hands of the user, us.

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Opinion: Artificial intelligence should be integrated into our workforce - Los Angeles Times

Coronavirus tests the value of artificial intelligence in medicine – FierceHealthcare

Albert Hsiao, M.D., Ph.D., and his colleagues at the University of California San Diego (UCSD) health system had been working for 18 months on anartificial intelligence program designed to help doctors identify pneumonia on a chest X-ray.

When thecoronavirushit the U.S., they decided to see what it could do.

The researchers quickly deployed the application, which dots X-ray images with spots of color where there may be lung damage or other signs of pneumonia. It has now been applied to more than 6,000 chest X-rays, and its providing some value in diagnosis, said Hsiao, director of UCSDs augmented imaging and artificial intelligence data analytics laboratory.

His team is one of several around the country that has pushed AI programs developed in a calmer time into the COVID-19 crisis to perform tasks like deciding which patients face the greatest risk of complications and which can be safely channeled into lower-intensity care.

The machine-learning programs scroll through millions of pieces of data to detect patterns that may be hard for clinicians to discern. Yet few of the algorithms have been rigorously tested against standard procedures. So while they often appear helpful, rolling out the programs in the midst of a pandemic could be confusing to doctors or even dangerous for patients, some AI experts warn.

AI is being used for things that are questionable right now, said Eric Topol, M.D., director of the Scripps Research Translational Institute and author of several books on health IT.

Topol singled out a system created by Epic, a major vendor of electronic health records software, that predicts which coronavirus patients may become critically ill. Using the tool before it has been validated is pandemic exceptionalism, he said.

RELATED:Boston startup using AI, remote monitoring to fight coronavirus

Epic said the companys model had been validated with data from more 16,000 hospitalized COVID-19 patients in 21 healthcare organizations. No research on the tool has been published, but, in any case, it was developed to help clinicians make treatment decisions and is not a substitute for their judgment, said James Hickman, a software developer on Epics cognitive computing team.

Others see the COVID-19 crisis as an opportunity to learn about the value of AI tools.

My intuition is its a little bit of the good, bad and ugly, said Eric Perakslis, Ph.D., a data science fellow at Duke University and former chief information officer at the Food and Drug Administration. Research in this setting is important.

Nearly $2 billion poured into companies touting advancements in healthcare AI in 2019. Investments in the first quarter of 2020 totaled $635 million, up from $155 million in the first quarter of 2019, according to digital health technology funderRock Health.

At least three healthcare AI technology companies have made funding deals specific to the COVID-19 crisis, including Vida Diagnostics, an AI-powered lung-imaging analysis company, according to Rock Health.

Overall, AIs implementation in everyday clinical care is less common than hype over the technology would suggest. Yet the coronavirus crisis has inspired some hospital systems to accelerate promising applications.

UCSD sped up its AI imaging project, rolling it out in only two weeks.

Hsiaos project, with research funding from Amazon Web Services, the University of California and the National Science Foundation, runs every chest X-ray taken at its hospital through an AI algorithm. While no data on the implementation has been published yet, doctors report that the tool influences their clinical decision-making about a third of the time, said Christopher Longhurst, M.D., UCSD Healths chief information officer.

The results to date are very encouraging, and were not seeing any unintended consequences, he said. Anecdotally, were feeling like its helpful, not hurtful.

RELATED:Headlines have touted AI over docs in reading medical images. New review finds evidence is limited

AI has advanced further in imaging than other areas of clinical medicine because radiological images have tons of data for algorithms to process, and more data makes the programs more effective, said Longhurst.

But while AI specialists have tried to get AI to do things like predict sepsis and acute respiratory distressresearchers at Johns Hopkins University recently won a National Science Foundation grantto use it to predict heart damage in COVID-19 patientsit has been easier to plug it into less risky areas such as hospital logistics.

In New York City, two major hospital systems are using AI-enabled algorithms to help them decide when and how patients should move into another phase of care or be sent home.

AtMount Sinai Health System, an artificial intelligence algorithm pinpoints which patients might be ready to be discharged from the hospital within 72 hours, said Robbie Freeman, vice president of clinical innovation at Mount Sinai. Freeman described the AIs suggestion as a conversation starter, meant to help assist clinicians working on patient cases decide what to do. AI isnt making the decisions.

NYU Langone Health has developed a similar AI model. It predicts whether a COVID-19 patient entering the hospital will suffer adverse events within the next four days, said Yindalon Aphinyanaphongs, M.D., Ph.D., who leads NYU Langones predictive analytics team.

The model will be run in a four- to six-week trial with patients randomized into two groups: one whose doctors will receive the alerts, and another whose doctors will not. The algorithm should help doctors generate a list of things that may predict whether patients are at risk for complications after theyre admitted to the hospital, Aphinyanaphongs said.

RELATED:Microsoft launches $40M AI for Health program to accelerate medical research

Some health systems are leery of rolling out a technology that requires clinical validation in the middle of a pandemic. Others say they didnt need AI to deal with the coronavirus.

Stanford Health Careis not using AI to manage hospitalized patients with COVID-19, saidRon Li, M.D., the centers medical informatics director for AI clinical integration. The San Francisco Bay Area hasnt seen the expected surge of patientswho would have provided the mass of data needed to make sure AI works on a population, he said.

Outside the hospital, AI-enabled risk factor modeling is being used to help health systems track patients who arent infected with the coronavirus but might be susceptible to complications if they contract COVID-19.

At Scripps Health in San Diego, clinicians are stratifying patients to assess their risk of getting COVID-19 and experiencing severe symptoms using a risk-scoring model that considers factors like age, chronic conditions and recent hospital visits. When a patient scores 7 or higher, a triage nurse reaches out with information about the coronavirus and may schedule an appointment.

Though emergencies provide unique opportunities to try out advanced tools, its essential for health systems to ensure doctors are comfortable with them, and to use the tools cautiously, with extensive testing and validation, Topol said.

When people are in the heat of battle and overstretched, it would be great to have an algorithm to support them, he said. We just have to make sure the algorithm and the AI tool isnt misleading, because lives are at stake here.

ThisKHNstory first published onCalifornia Healthline, a service of theCalifornia Health Care Foundation.Kaiser Health Newsis a nonprofit news service covering health issues. It is an editorially independent program of the Kaiser Family Foundation, which is not affiliated with Kaiser Permanente.

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Coronavirus tests the value of artificial intelligence in medicine - FierceHealthcare