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The way Jordi Cruyff tells the story, it all started with an email. The former Manchester United midfielder was working as the sports director of Maccabi Tel Aviv in 2017 when he was offered a trial with a little-known artificial intelligence company that said it could help the team to prevent injuries. It certainly sounded interesting, and there was nothing to lose, so he decided there was no harm in giving it a go.

The club promptly sent over their squads fitness data and, in return, a warning soon landed in Cruyffs inbox: according to the companys calculations, seven first-team players were at risk of injury. The head coach was not too impressed to be told this, and chose not to act upon it. Five of those players were then injured. It then happened again, and again, and Cruyff soon realised that what was unfolding before him was no coincidence.

Cruyff is now an investor in the company, called Zone7, and more and more clubs across the world are starting to realise that they too might benefit from a technology that could revolutionise the medical side of the sport. With major leagues now preparing for a condensed run of league fixtures, the likes of which they have not seen in the modern era, the need to reduce injuries has become a more pressing problem than ever. And so, as coronavirus put a halt to leagues all over Europe, Zone7 suddenly found they were offering a service that has never been more valuable.

We now have data from over 50 teams across the UK, Italy, France, Germany, Spain and the US, says Tal Brown, Zone7s co-founder and CEO. Brown is based in Silicon Valley and, prior to launching Zone7, founded the first artificial intelligence team at software giant Salesforce. He is not, therefore, what the sport might consider a football person. Neither is the technology what the sport might consider to be football tech.

The instant reaction from many in the game, much like the coach at Maccabi Tel Aviv, is to be sceptical. Silicon Valley technology experts advising football teams how to manage their players? It is not hard to see why there might be some resistance, especially given the stubborn nature of the sport. But the evidence suggests that the Zone7 algorithm works, and that it works spectacularly.

Among the first clubs to sign up were Getafe, who are far from being the most glamorous or wealthy side in La Liga. In two seasons working with Zone7, their injury rate reduced by 70 per cent. Last season, they suffered just eight injuries, by far the lowest in the division, as they punched well above their weight to finish fifth. Atletico Madrid, meanwhile, had 47 injuries. Real Madrid had 32. Javier Vidal, Getafes fitness coach, has described the technology as a tool that will change elite sport.

So how does it work? In its simplest terms, Zone7 uses pattern recognition to rapidly interpret the huge amounts of data that clubs collect on their players. As a sport, we know almost everything that we can know about our athletes, says Brown. We have deployed medical products to measure strength and flexibility, we know how much they are moving around the pitch, we know things about how they play the game. That data is vast.

Digesting it, and converting it into practical information, is therefore a significant challenge. A lot of the interpretation itself is usually left in the hands of the human operator, says Brown. The analysis process relies on these individuals looking at charts, contextualising them and trying to drive decisions.

Using artificial intelligence, Zone7 helps to make those decisions. Rather than a physio having to comb through eight or nine charts per day for 25 first-team players, looking for indicators of fatigue or dips in performance, Zone7s algorithm can do it for them. With all the data stored in its system, it can recognise the patterns that lead to injury.

From there, the clubs are told which players could be at risk and what the next training session should look like for those individuals. An example would be Zone7s algorithm identifying a detrimental pattern in a players sprinting. The club might then be advised that the player should only be doing 400m of high-speed running the next day, rather than 1,000m.

Teams have scientists and physios and strength coaches that are great professionals who know what they are doing, says Eyal Eliakim, the chief technology officer and co-founder. They have to take care of at least 25 players every day in a training programme that is for everyone. It is hard to understand what tweaks are needed and it is really hard to cover all the players. It takes hours and hours every day to manually look at each players data. That is where we come in.

The temptation is to view this as the latest chapter in the data revolution of football, which has led in the past decade to a considerable surge in interest in the statistical analysis of recruitment and tactics. The Moneyball effect, as it is known. On the coaching and medical side of the game, though, things have moved slower until now. The nerds are not taking over, says Brown. But they are making a bigger impact.

The success of Getafe has helped to spread the word about Zone7 and their technology. Leading La Liga clubs are jumping on board and the company is currently in conversation with Premier League teams. Two Championship sides have already signed up, while in the last few weeks alone Zone7 have taken on two new German clients and three teams in Italys Serie A.

Evidently, these sides know the importance of keeping their injury rate low. There is a financial benefit to this, of course, but it is the performance benefit that is so appealing. Getafes success in La Liga tells its own story, although perhaps an even better example would be Leicester Citys title victory in 2016.

For whatever reason (they were not working with Zone7), Claudio Ranieris Leicester enjoyed the most extraordinary season with regard to injuries. Physioroom data shows that in the 2015/16 campaign, Leicesters players lost a total of 275 days to injury, by far the best record in the league. By way of comparison, the league average for the 20 Premier League clubs that year was 1130 days. Being able to consistently deliver high squad availability is a metric that is often overlooked, says Brown.

In their own words, Brown and Eliakim come into this with an outsiders perspective. Their expertise is in artificial intelligence, rather than the sport itself. Indeed, some observers with more of a sporting background remain unconvinced that the platform can have enough information to be truly effective.

I am pretty sceptical of AI and machine learning in injury prediction, says Markus Deutsch, the global CEO of sports technology company Fusion Sport. The AI is not there yet. Its not good enough, and the reason for that is that there is not enough data. You are talking about a very low number of actual injuries over the course of the season. It does not lend itself to good statistical modelling.

Zone7, and their clients, would disagree. And perhaps most excitingly for them, the more teams they sign up, the more advanced the algorithm will be. This becomes inherently better automatically, as it is driven by more data, Brown says. Getafe in season two had better metrics than Getafe in season one, because we had more data. That is also true across the board with more teams.

Inevitably, some of the more traditional clubs will still resist the very concept of distant machine learning as an injury prevention tool. For those who commit as readily as a team like Getafe, though, it could change their approach forever.

Most clubs will just use their data to run their own analytics, which is a great start, says Brown. But if you can have an algorithm looking for injury signals and learning from 10,000 injuries, instead of 100, then that is a different ball-game.

Join our football experts, Jamie Carragher, Jason Burt and Sam Wallace for a discussion and Q&A about the return of the Premier League on Tuesday June 16 at Midday. Sign-up to attend, here.

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The best way to avoid injuries? Top clubs are turning to artificial intelligence - Telegraph.co.uk

NEW YORK As Americans prepare to return to offices and other places of work, a new poll reveals that many worry about how long their jobs will last. Many office workers now believe the skills theyve learned wont be able to keep up in a world relying more and more on artificial intelligence.

A study of 2,000 American office workers found that 53 percent fear their skills will be outdated in less than five years. They worry this makes them susceptible to being replaced by robots or other forms of artificial intelligence. The vast majority of respondents said theyd feel more secure about their jobs if they could learn while they earn.

Eighty-six percent of the poll, commissioned by UiPath, wish their employers offered training to learn new skills. Nearly the same percent say theyd be more willing to stay with a company that offered those opportunities.

There is a clear demand amongst todays workforce for new skills, Tom Clancy of UiPath Learning says in a statement. Organizations must meet these demands or risk losing top talent to the competition.

Among the workers who had a chance to get skill training, researchers say 63 percent reported getting more opportunities at work. Fifty-eight percent of those workers added the training helped them earn a raise and more responsibilities at their jobs.

When it comes to what kind of training office workers say they need to stay ahead of AI, nine in 10 respondents believe their bosses should be investing in technology-based training workshops.

Training employees on new technologies, like automation and AI, has proven to be extremely valuable in boosting employee job satisfaction and enhancing individual and organizational productivity, Clancy added.

Nearly 90 percent of office workers say they want to learn about artificial intelligence and machine learning; adding that knowing more about the technological revolution will end up helping their careers.

Data analytics was the most popular skill respondents said would help their careers. Forty-two percent of office workers chose that as the training they needed most, followed by multimedia design and editing, Microsoft Office, and coding.

Despite fearing AI could one day overtake their abilities, workers did see the benefits in turning some tasks over to computers. Fifty-three percent of the poll say automation would increase their productivity, save them time, and create a better work-life balance.

The survey was conducted by OnePoll.

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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

As a young dentist, Dr. David Gane learned quickly that photographic imaging records were a terrific tool for his dental practice in many ways. Within 10 years he segued into his own imaging software company, and today hes the CEO of Apertyx Imaging.

In this discussion, he and Dr. Pamela Maragliano-Muniz agree that April was a challenging month for dentists and dental companies. But theyre encouraged by recent data from the Health Policy Institute and the American Dental Association that indicates dentistry is beginning to bounce back successfully and will continue to do so. Surveys from the HPI also show that most patients want to return to their dentists as soon as they're able.

Dr. Maragliano Muniz notes that to continue to be successful, dentists are investing more in themselves. She and Dr. Gane believe that an efficient imaging system is an excellent tool for dentists to spend their money on. Dr. Gane explains the advantages of Apteryx.

Editor's note:To viewDentistryIQ's full coverage of the COVID-19 pandemic, including original news articles and video interviews with dental thought leaders,visit theDentistryIQCOVID-19 Resource Center.

Pamela Maragliano-Muniz, DMD,is the chief editor ofDentistryIQ.Based in Salem, Massachusetts, Dr. Maragliano-Muniz began her clinical career as a dental hygienist. She went on to attend Tufts University School of Dental Medicine, where she earned her doctorate in dental medicine. She then attended the University of California, Los Angeles, School of Dental Medicine, where she became board-certified in prosthodontics. Dr. Maragliano-Munizowns a private practice, Salem Dental Arts, and lectures on a variety of clinical topics.

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Coronavirus impact on dental practices: Imaging software capabilities and artificial intelligence (Video) - Dentistry IQ

The coronavirus crisis demands a regulatory framework for the application of AI to protect public health without jeopardising human rights.

Our world has been shaken by the Covid-19 pandemic, pushing policy-makers to scramble for solutions. And even though the full set of such solutions remains elusive, already a return to normal is debated.

But what will this normal be? Powerful forces presume that the world before Covid-19 is the normal to which to return and it falls on progressives to push for new fundamentalsto help formulate a new normal. Clearly this is multifaceted and one facet is the role of technology.

Artificial intelligence, as a revolutionary force in restructuring production and consumption patterns, has long been on the agenda of policy-makers. The role of AI, as a creative but disruptive process in the job market, in healthcare, in educationeven in shaping our democraciesis undeniable.

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Given the health focus of the continuing crisis, overcoming the regulatory, ethical and medical challenges posed by the use of AI in healthcare must be a priority. Defining the framework to do so will be a pivotal initial step in guaranteeing thatthe new normal producesa fair outcomethat fundamental rights are safeguarded while simultaneously improving healthcare for all.

If supported by adequate and effective regulation, AI promises a wide array of opportunities to improve public health as well as the quality and efficiency of the healthcare sector. Without such a framework, AI has the potential to be just another instrument in a system where rights are sidelined for profit maximisation and biases are reproduced systemically.

The Parliamentary Assembly of the Council of Europe (PACE) is preparing a number of reports on the implications of AI. Asrapporteuron AI in healthcare, I must point to existingCouncil of Europe legal instrumentssuch as theConventionfor the Protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine(the Oviedo convention) and theConventionfor the Protection of Individuals with regard to the Automatic Processing of Personal Dataas guides for national regulatory efforts.

Clearly AI has played a critical role in the initial detection of the pandemic. It has been used in tracking the spread of disease and hospital capacity, in identifying high-risk patients and in developing drugs and, potentially, a vaccine. Maybe the most visible public debate regarding AI in healthcare has been over testing and tracing apps, which have been claimed as important tools to control the spread of the virus and provide valuable information to design strategies for exit from lockdown.

AIs highly promising potential for the future of public health in Europe is however not the only reality which the pandemic has laid bare. It has offered a stark reminder of socio-economic inequalitiesof the need to restrain over-marketisation and regulate markets, and to govern potential conflicts between ethical principles and market forces.

The lasting legacy of neoliberalism is manifested most notably in privatised healthcare and highly precarious job markets. This has aggravated the consequences of the pandemic, particularly for working people, for the unemployed and for the precariat. The unequal social and economic structures established and reinforced under neoliberal hegemony impede our capacity to address the challenges it has thrown up.

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Equally,had there been a trusted and well-defined regulatory framework, maybe AI could have had a much larger positive impact on the coronavirus crisis. The publics concern regarding the misuse and abuse of data by states, as well as the private sector, would have been mitigated.

We need to set a new framework capable of creating social benefits from AI while safeguarding fundamental rights and democratic governance and ensuring equality. These questions fit snugly into the debate as to what the new normal will be: will the means of surveillance for the sake of health purposes accelerate a totalitarian drift or will they be governed by an empowered citizenry? And will isolationist reflexes deepen or will multilateralism, co-operation and solidarity rise to the challenge?

These questionsare relevant to any discussion of AI and healthcarethe former to a regulatory framework that will ensure protection of human rights, the latter to whether AI in healthcare will be driven by co-operation and solidarity or, in their absence, profit-seeking objectives.

Evidently, health and personal privacy can never be alternativesthey must go hand in hand. Public trust in the state and the private sector can only prevail if all their agents guarantee basic human rights in developing and using AI.

Given the urgency of doing so in the struggle against the coronavirus, it is of utmost importance to agree on at least a workable basic framework that will enhance trust and make AI operational for the better. And the Covid-19 outbreak has shed light on its critical aspects.

Such a framework should ensure that AI in healthcare empowers citizens in making better-informed decisions and provides information to hold governments accountable for the decisions they make. So that AI does not become instrumental in aggravating inequalities, it should also ensure that data and algorithms are unbiased, and that processes are transparent and inclusive.

It should be based on well-defined liability and a well-balanced public-private dialogue. It should put in place the conditions and guarantees to ensure that pursuing the collective interest does not override individual rights. It should require that technology used for monitoring and tracking is only used temporarily and does not become a permanent feature.

When the new regulatory framework is designed, the point of departure should be recognition of access to healthcare and protection of personal data and privacy as fundamental, indispensable rights. Technology-driven opportunities such as AI should be incorporated into healthcare systems in ways that guarantees equal access while safeguarding those rights. Only then will we not only overcome this pandemic but ensure we are ready to tackle the next one better.

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Artificial intelligence, healthcare and the pandemic - Social Europe