Category Archives: Artificial Intelligence

April 9, 2020 - LONDON, UK: Prior to the COVID-19 pandemic, the IDC (International Data Corporation) Worldwide Artificial Intelligence Spending Guide had forecast European artificial intelligence (AI) spending of $10 billion for 2020, and a healthy growth at a 33% CAGR throughout 2023. With the COVID-19 outbreak, IDC expects a variety of changes in spending in 2020. AI solutions deployed in the cloud will experience a strong uptake, showing that companies are looking at deploying intelligence in the cloud to be more efficient and agile.

"Following the COVID-19 outbreak, many industries such as transportation and personal and consumer services will be forced to revise their technology investments downwards," said Andrea Minonne, senior research analyst at IDC Customer Insights & Analysis. "On the other hand, AI is a technology that can play a significant role in helping businesses and societies deal with and solve large scale disruption caused by quarantines and lockdowns. Of all industries, the public sector will experience an acceleration of AI investments. Hospitals are looking at AI to speed up COVID-19 diagnosis and testing and to provide automated remote consultations to patients in self-isolation through chatbots. At the same time, governments will use AI to assess social distancing compliance"

In the IDC report, What is the Impact of COVID-19 on the European IT Market? (IDC #EUR146175020, April 2020) we assessed the impact of COVID-19 across 181 European companies and found that, as of March 23, 16% of European companies believe automation through AI and other emerging technologies can help them minimize the impact of COVID-19. With large scale lockdowns in place, a shortage of workers and supply chain disruptions will drive automation needs across manufacturing.

Applying intelligence to automate processes is a crucial response to the COVID-19 crisis. Not only does automation allow European companies to digitally transform, but also to make prompt data-driven decisions and have a positive impact on business efficiency. IDC expects a surge in adoption of automated COVID-19 diagnosis in healthcare to speed up diagnosis and save time for both doctors and patients. As the virus spreads quickly, labor shortages in industries where product demand is surging can become a critical problem. For that reason, companies are renovating their hiring processes, applying a mix of intelligent automation and virtualization in their hiring processes. Companies will also aim to automate their supply chains, maintain their agility and avoid production bottlenecks, especially for industries with vast supplier networks. With customer service centers becoming severely restricted, automation will be a crucial part for remote customer engagement and chatbots will help customers in self-isolation get the support they need without having to wait a long time.

"As a short-term response to the COVID-19 crisis, AI can play a crucial part in automating processes and limiting human involvement to a necessary minimum," said Petr Vojtisek, research analyst at IDC Customer Insights & Analysis. "In the longer term, we might observe an increase in AI adoption for companies that otherwise wouldn't consider it, both for competitive and practical reasons."

IDC's Worldwide Semiannual Artificial Intelligence Spending Guide provides guidance on the expected technology opportunity around the AI market across nine regions. Segmented by 32 countries, 19 industries, 27 use cases, and 6 technologies, the guide provides IT vendors with insight into this rapidly growing market and how the market will develop over the coming years.

For IDCs European coverage of COVID-19, click here.

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Spending in Artificial Intelligence to accelerate across the public sector due to automation and social distancing compliance needs in response to...

Imagine being a recent graduate at a competitive job fair. You look to the suit-clad candidates on your left and right, and you start to wonder, Am I smart enough to compete with my peers?

But todays college graduates have a new question on their radar: Will I have to compete with artificial intelligence (AI), too?

In a word, no. I believe fears around AI wiping out jobs are largely overblown, but you cant fault new grads for worrying. A quick scan of tech news could lead anyone to believe that AI is the Grim Reaper of the job market. But attention-grabbing headlines dont paint the full picture; they overlook the historical impact of productivity-enhancing technology on a modern workforce.

Like every major technological advancement in the last 500 years, AI will change the way we live and work, but this isnt a bad thing. Todays nervous job seekers have no reason to panic; theres more room for AI to enhance their careers than to cause harm. To help new graduates ensure their value is fully appreciated, here are three best practices for them to keep in mind as they enter the workforce.

Collaborate; dont compete.

As humans, its natural to see other job candidates, or even co-workers, as potential competition. But when it comes to AI, job seekers should embrace the potential for AI to enhance their opportunities. The introduction of the calculator didnt eliminate the need for engineers; it made them more efficient, and AI will do the same.

In certain ways, humans will never stack up against AI; people cant crunch numbers and make data-driven predictions as fast as AI can, and it would be disheartening and beside the point to even try. But there are a number of uniquely human qualities creativity, innovation, compassion that employees can harness to add value where AI cant. The future of work isnt about trying to be better, faster or smarter than technology; its about working alongside it for better overall results.

I recently spoke with Tom Davenport, a leading expert on digital business, about the future of work for an episode of my companys podcast, The ConversAItion. As a longtime industry authority, hes had a front-row seat watching attitudes around AI and jobs evolve, moving from widespread alarm to a subsequent reality checkto todays relative calm. Despite shifting outlooks, hes never seen significant AI-driven layoffs.

Instead, modern businesses are committed to leveraging AI to augment existing jobs, rather than replace them. By combining smart humans and smart machines, both employees and technology can play to their strengths, giving businesses the best of both worlds.

Become a lifelong student.

Theres no reason for todays employees to panic, but its also no time to be complacent. With technologys rapid advancement, even a college education wont prepare them indefinitely. Its more important than ever for professionals to remain eager to learn long after the diplomas have been handed out.

New skill sets, even entire industries, are constantly popping up. Upskilling is paramount to collaborating with technology and keeping employees professional development on track. Its every employees responsibility to take control of their own learning and pursue training that will make them more valuable, but employers can be a major help here as well.

Shell, for example, just announced that it will enroll thousands of employees in online AI training to boost technical competency. As graduates begin the job hunt, its important to be on the lookout for companies with ongoing professional development programs to start a lifetime of learning on the right foot.

Embrace change; with upheaval comes new opportunity.

If you told someone 30 years ago that they could make a killing driving people around in their familys car or selling mattresses on the internet, they probably would have thought you were crazy. But with new technologies come new opportunities. In fact, the World Economic Forum estimated that AI could create 58 million jobs between 2018 and 2022 some of which we cant even begin to imagine yet.

New opportunities will arise within existing roles, too. As AI tackles the most monotonous and time-consuming tasks, employees will have more room to stretch. But whether theyre pursuing entirely new paths or shifting existing responsibilities, those who embrace change will be best positioned to reap the professional benefits of AI.

The bottom line is that AI is here to stay, and thats a good thing. While tomorrows workforce will certainly look different than it does today, new graduates will have the opportunity to work alongside AI from the very beginning. If they remain willing to collaborate with the technology and committed to ongoing learning, upcoming graduates can walk fearlessly into the job fair knowing they have what it takes to add value in the age of AI.

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Don't Be Afraid Of The New Kid At The Job Fair: Artificial Intelligence - Forbes

When Machines Design: Artificial Intelligence and the Future of Aesthetics

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Are machines capable of design? Though a persistent question, it is one that increasingly accompanies discussions on architecture and the future of artificial intelligence. But what exactly is AI today? As we discover more about machine learning and generative design, we begin to see that these forms of "intelligence" extend beyond repetitive tasks and simulated operations. They've come to encompass cultural production, and in turn, design itself.

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When artificial intelligence was envisioned during thethe 1950s-60s, thegoal was to teach a computer to perform a range of cognitive tasks and operations, similar to a human mind. Fast forward half a century, andAIis shaping our aesthetic choices, with automated algorithms suggesting what we should see, read, and listen to. It helps us make aesthetic decisions when we create media, from movie trailers and music albums to product and web designs. We have already felt some of the cultural effects of AI adoption, even if we aren't aware of it.

As educator and theorist Lev Manovich has explained, computers perform endless intelligent operations. "Your smartphones keyboard gradually adapts to your typing style. Your phone may also monitor your usage of apps and adjust their work in the background to save battery. Your map app automatically calculates the fastest route, taking into account traffic conditions. There are thousands of intelligent, but not very glamorous, operations at work in phones, computers, web servers, and other parts of the IT universe."More broadly, it's useful to turn the discussion towards aesthetics and how these advancements relate to art, beauty and taste.

Usually defined as a set of "principles concerned with the nature and appreciation of beauty, aesthetics depend on who you are talking to. In 2018, Marcus Endicott described how, from the perspective of engineering, the traditional definition of aesthetics in computing could be termed "structural, such as an elegant proof, or beautiful diagram." A broader definition may include more abstract qualities of form and symmetry that "enhance pleasure and creative expression." In turn, as machine learning is gradually becoming more widely adopted, it is leading to what Marcus Endicott termed a neural aesthetic. This can be seen in recent artistic hacks, such as Deepdream, NeuralTalk, and Stylenet.

Beyond these adaptive processes, there are other ways AI shapes cultural creation. Artificial intelligence hasrecently made rapid advances in the computation of art, music, poetry, and lifestyle. Manovich explains that AIhas given us the option to automate our aesthetic choices (via recommendation engines), as well as assist in certain areas of aesthetic production such as consumer photography and automate experiences like the ads we see online. "Its use of helping to design fashion items, logos, music, TV commercials, and works in other areas of culture is already growing." But, as he concludes, human experts usually make the final decisions based on ideas and media generated by AI. And yes, the human vs. robot debate rages on.

According to The Economist, 47% of the work done by humans will have been replaced by robots by 2037, even those traditionally associated with university education. The World Economic Forum estimated that between 2015 and 2020, 7.1 million jobs will be lost around the world, as "artificial intelligence, robotics, nanotechnology and other socio-economic factors replace the need for human employees." Artificial intelligence is already changing the way architecture is practiced, whether or not we believe it may replace us. As AI is augmenting design, architects are working to explore the future of aesthetics and how we can improve the design process.

In a tech report on artificial intelligence, Building Design + Construction explored how Arup had applied a neural network to a light rail design and reduced the number of utility clashes by over 90%, saving nearly 800 hours of engineering. In the same vein, the areas of site and social research that utilize artificial intelligence have been extensively covered, and examples are generated almost daily. We know that machine-driven procedures can dramatically improve the efficiency of construction and operations, like by increasing energy performance and decreasing fabrication time and costs. The neural network application from Arup extends to this design decision-making. But the central question comes back to aesthetics and style.

Designer and Fulbright fellow Stanislas Chaillou recently created a project at Harvard utilizing machine learning to explore the future of generative design, bias and architectural style. While studying AI and its potential integration into architectural practice, Chaillou built an entire generation methodology using Generative Adversarial Neural Networks (GANs). Chaillou's project investigates the future of AI through architectural style learning, and his work illustrates the profound impact of style on the composition of floor plans.

As Chaillou summarizes, architectural styles carry implicit mechanics of space, and there are spatial consequences to choosing a given style over another. In his words, style is not an ancillary, superficial or decorative addendum; it is at the core of the composition.

Artificial intelligence and machine learningare becomingincreasingly more important as they shape our future. If machines can begin to understand and affect our perceptions of beauty, we should work to find better ways to implement these tools and processes in the design process.

Architect and researcher Valentin Soana once stated that the digital in architectural design enables new systems where architectural processes can emerge through "close collaboration between humans and machines; where technologies are used to extend capabilities and augment design and construction processes." As machines learn to design, we should work with AI to enrich our practices through aesthetic and creative ideation.More than productivity gains, we can rethink the way we live, and in turn, how to shape the built environment.

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When Machines Design: Artificial Intelligence and the Future of Aesthetics - ArchDaily

The Artificial Intelligence (AI) tool has been shown to accurately predict which patients that have been newly infected with the COVID-19 virus would go on to develop severe respiratory disease.

Named SARS-CoV-2, the new novel coronavirus, as of March 30, had infected 735,560 patients worldwide. According to the World Health Organization, the illness has caused more than 34,830 deaths to date, more often among older patients with underlying health conditions.

The study, published in the journalComputers, Materials & Continua, was led by NYU Grossman School of Medicine and the Courant Institute of Mathematical Sciences at New York University, in partnership with Wenzhou Central Hospital and Cangnan Peoples Hospital, both in Wenzhou, China.

The study has revealed the best indicators of future severity and found that they were not as expected.

Corresponding author Megan Coffee, clinical assistant professor in the Division of Infectious Disease & Immunology at NYU Grossman School of Medicine, said: While work remains to further validate our model, it holds promise as another tool to predict the patients most vulnerable to the virus, but only in support of physicians hard-won clinical experience in treating viral infections.

Our goal was to design and deploy a decision-support tool using AI capabilities mostly predictive analytics to flag future clinical coronavirus severity, says co-author Anasse Bari, PhD, a clinical assistant professor in Computer Science at the Courant institute. We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, with hospital resources stretched thin.

For the study, demographic, laboratory, and radiological findings were collected from 53 patients as each tested positive in January 2020 for COVID-19 at the two Chinese hospitals. In a minority of patients, severe symptoms developed with a week, including pneumonia.

The researchers wanted to find out whether AI techniques could help to accurately predict which patients with the virus would go on to develop Acute Respiratory Distress Syndrome or ARDS, the fluid build-up in the lungs that can be fatal in the elderly.

To do this they designed computer models that make decisions based on the data fed into them, with programmes getting smarter the more data they consider. Specifically, the current study used decision trees that track series of decisions between options, and that model the potential consequences of choices at each step in a pathway.

The AI tool found that changes in three features levels of the liver enzyme alanine aminotransferase (ALT), reported myalgia, and haemoglobin levels were most accurately predictive of subsequent, severe disease. Together with other factors, the team reported being able to predict risk of ARDS with up to 80% accuracy.

ALT levels, which rise dramatically as diseases like hepatitis damage the liver, were only a bit higher in patients with COVID-19, but still featured prominently in prediction of severity. In addition, deep muscle aches (myalgia) were also more commonplace and have been linked by past research to higher general inflammation in the body.

Lastly, higher levels of haemoglobin, the iron-containing protein that enables blood cells to carry oxygen to bodily tissues, were also linked to later respiratory distress. Could this be explained by other factors, like unreported smoking of tobacco, which has long been linked to increased haemoglobin levels?

Of the 33 patients at Wenzhou Central Hospital interviewed on smoking status, the two who reported having smoked, also reported that they had quit.

Limitations of the study, say the authors, included the relatively small data set and the limited clinical severity of disease in the population studied.

I will be paying more attention in my clinical practice to our data points, watching patients closer if they for instance complain of severe myalgia, adds Coffee. Its exciting to be able to share data with the field in real time when it can be useful. In all past epidemics, journal papers only published well after the infections had waned.

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How Artificial Intelligence is helping the fight against COVID-19 - Health Europa

London, April 07, 2020 (GLOBE NEWSWIRE) -- According to a new market research report Automotive Artificial Intelligence (AI) Market by Component (Hardware, Software), Technology (Machine Learning, Computer Vision), Process (Signal Recognition, Image Recognition) and Application (Semi-Autonomous Driving) - Global Forecast to 2027, published by Meticulous Research, the automotive artificial intelligence market is expected to grow at a CAGR of 39.8% from 2019 to 2027 to reach $15.9 billion by 2027.

Various well-established automotive organizations across the globe are increasingly struggling with rising cost of operations, dissatisfied customers, declining sales, and unidentified competition. Therefore, the adoption of artificial intelligence technologies in the automotive sector is on the rise in order to create new opportunities and enhance operational capabilities by leveraging new possibilities, speeding up processes, and making organizations flexible to changes in the future.

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Realizing the fact, various organizations are investing heavily in order to reap profits in highly dynamic and competitive market environment. The organizations are aggressively adopting AI-based solutions and services to reshape their business processes and increase profitability. The rapid adoption of advanced automotive solutions, increasing demand for autonomous vehicles, and widening implementation of computer vision technologies across vehicles are the key factors driving steady growth in the global automotive artificial intelligence market.

Impact of COVID-19 on Global AI in Automotive Market

The global spread of COVID-19 has resulted in stalled automotive production across Europe and America. The scenario in Asia appears to be improving but the production capacities of leading automobile manufacturers have taken a hit due to lower demand and reduced consumer spending. With the current situation expected to persist until the global numbers recede, the global automobile industry may be looking at a recovery period of at least 3-6 months due to disrupted supply chain, economic loss, and reduced consumer confidence in the market.

Read Our Latest Insights onCOVID-19's Impact on Various Industries, Visit:https://www.meticulousresearch.com/covid-19.php

However, if the reports by health experts are to be believed and the epidemic can be controlled by June 2020, the automotive industry can bounce back in terms of revenue growth during the latter half of 2020. This would enable AI technology suppliers to capitalize on market consolidation during Q2, 2020. It is also predicted that with better control of the COVID-19 situation and normalcy established, the global automakers could witness an upsurge in demand for advanced technology enabled vehicles and thereby drive the automotive AI market revenue 2021 onwards.

In recent years, the funding for development and implementation of artificial intelligence solutions for autonomous vehicles has increased significantly. For instance, in 2019, the U.K., government and industry launched an AI Sector Deal to boost technology potential, with 250 million ($324.1 million) budget for the development of connected and autonomous vehicles. By the end of 2020, the South Korean government has planned to expand the countrys production of automation systems and industrial robotics with investments worth $6.1 billion. In addition, the government of Korea will launch an Intelligent Robot Industry Development Strategy led by the Ministry of Trade, Industry, and Energy. Such initiatives are enabling the automotive sector, to develop intelligent solutions for autonomous vehicles through the incorporation of robotics and artificial intelligence technologies.

The automotive artificial intelligence market study presents historical market data in terms of value (2017 and 2018), current data (2019), and forecasts for 2027 by component, technology, process, applications, and geography.

Based on component, the software segment is estimated to account for the largest share of the overall automotive artificial intelligence market in 2019. The large share of this segment is attributed to the decrease in the cost of cloud-enabling technology deployment, growing usage of learning analytics and awareness towards cloud computing, and increasing demand for automated solutions to meet changing business needs in the automotive sector. On the other hand, the services segment is slated to grow at the fastest CAGR during the forecast period, due to the demand for AI-capable services in autonomous vehicles and a rise in the adoption of cloud-based solutions.

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Based on technology, the machine learning segment is estimated to account for the largest share of the overall automotive artificial intelligence market, in 2019. This is primarily due to the growing demand for AI-based intelligent solutions, increasing government initiatives, and the ability of AI solutions to efficiently handle and analyze big data and quickly scan, analyze, and react to anomalies. On the other hand, computer vision technology is slated to grow at the fastest CAGR during the forecast period, due to a widespread implementation of computer vision in autonomous vehicles for signal recognition, image recognition, driver monitoring, spotting suspicious objects, and avoid vehicle collision.

Based on the process, signal recognition is estimated to hold the largest share of the overall automotive artificial intelligence market, in 2019. This is driven by the growing demand for autonomous vehicles, and safety controls implemented to enable driver assistance systems in the automotive sector. On the other hand, the demand for AI solutions and services for the image recognition process is slated to grow at the fastest CAGR during the forecast period, owing to its ability to enhance and automate operations, enrich user experience, and growing need for security solutions.

Based on the application, the human-machine interface is estimated to hold the largest share of the overall automotive artificial intelligence market, in 2019. Increasing demand for enhancing the in-car user experience, growth in terms of smart IoT devices, and proliferation of internet infrastructure, are some key factors contributing to growth of human-machine interface segment. On the other hand, semi-autonomous driving application is slated to grow at the fastest CAGR during the forecast period, mainly due to rising preference of consumers to adopt semi-autonomous mode of driving.

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Geographically, North America commanded the largest share of the the global automotive AI market in 2019. The large share of this region is mainly attributed to factors such as presence of several developed economies, such as the United States and Canada; the presence of leading automotive players; demand for enhanced user experience; growing adoption of autonomous vehicles; and availability of high-end infrastructure. However, Asia Pacific region is predicted to challenge the dominance of North America in the overall automotive artificial intelligence market in the near future.

The report also includes an extensive assessment of the key strategic developments adopted by leading market participants in the industry over the past 4 years (2016-2019). The automotive artificial intelligence market has witnessed a number of partnerships & agreements in recent years. For instance, in 2019, Intel Corporation collaborated with Mobileye and Great Wall Motors to explore the development of highly autonomous systems. This collaboration will further push computing, safety and mapping to develop future L2+ semi-autonomous capabilities. Also, in 2018, Microsoft Corporation partnered with Volkswagen to create a new automotive cloud. This will enable Volkswagen to deliver new Azure-based connected vehicle services.

The global automotive artificial intelligence market is highly fragmented with the presence of key players, such as Google LLC (U.S.), IBM Corporation (U.S.), Intel Corporation (U.S.), Microsoft Corporation (U.S.), Nvidia Corporation (U.S.), Tesla, Inc. (U.S.), Xilinx, Inc. (U.S.), Micron Technology, Inc. (U.S.), Uber Technologies, Inc. (U.S.), Ford Motor Company (U.S.), General Motors Company (U.S.), Harman International Industries Inc. (South Korea), Honda Motor Co., Ltd. (Japan), Audi AG (Germany), and Qualcomm Technologies, Inc. (U.S.) along with several local and regional players.

Browse In-depth Summary of This Research Report:https://www.meticulousresearch.com/product/automotive-artificial-intelligence-market-4996/

Scope of the Report:

Automotive AI Market, by Component

Automotive AI Market, by Technology

Automotive AI Market, by Process

Automotive AI Market, by Application

Automotive AI Market, by Geography

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Artificial Intelligence in Manufacturing Marketby Component, Technology (ML, Computer Vision, NLP), Application (Cybersecurity, Robot, Planning), Industry (Electronics, Energy, Automotive, Metals and Machine, Food and Beverages) Global Forecast to 2027

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Automotive Artificial Intelligence (AI) Market Worth $15.9 Billion by 2027 - Exclusive Report by Meticulous Research - Yahoo Finance

By publishing the White Paper[1] in February, the European Union opened a public consultation (due to expire on May 19, 2020) about the Artificial Intelligence in order to assess the possibility of adopting a common regulatory approach to overcome nationalism and partial visions of the issue. According to the Commission, the development of common legislation on Artificial Intelligence would enable businesses and citizens of the Union to face more consciously the most current social challenges such as the fight against climate change, challenges related to sustainability and demographic change, the protection of democracies and the fight against crime. However, will these issues still be perceived in the same manner to be topical following the advent of the health emergency resulting from the spread of the COVID-19 virus?

Artificial Intelligence: definition and status of the EU legislation

As part of the definition of a common strategy for the digital single market, the European Union began to take a more active interest in Artificial Intelligence (AI) in 2017, when the European Council recognized the issue as urgent and rapidly evolving, inviting the European Commission to lay the foundations for a common legislation. According to the Council, it was necessary to approach AI in a uniform manner throughout the Union "while ensuring a high level of data protection, digital rights and ethical standards[2]".

Hence, the Commission responded to the Council's invitation and on April 25, 2018[3] published a Communication to the other European institutions concerned in which it made public the IA strategy that would lead to an exponential increase in the Union's resources allocated to the development of IA projects (almost 2.5 billion euro between 2018 and 2020, in addition to private investment and an economic support plan for the decade 2020-2030), also with a view to making IA-based technologies as accessible as possible to citizens and businesses. This initiative is clearly aimed at competing with other powers on the globe (USA, China, Japan and Canada) in the technology race to exploit the opportunities offered by the "home" development of AI.

In short, the European industry cannot miss the train, borrowing the Commission's words. This was reiterated by the Commission itself in its subsequent Communication of December 7, 2018 in which it set out its coordinated plan on IA[4].

Setting this apart, the Commissions Communication of April 25, 2018 contains a (although imprecise) definition of AI, which was absent until then in the legislative texts of the Union. Scholars and technicians have provided partially different definitions over the years, but no agreement was reached on one specific definition[5]. In the Communication, the Commission defined IA as "systems that show intelligent behaviour by analysing their environment and taking actions, with a certain degree of autonomy, to achieve specific objectives[6]". This definition was then further elaborated by the so-called Independent High Level Expert Group on Artificial Intelligence[7] which, in its report "Ethical Guidelines for Reliable AI", specified the notion of artificial intelligence as follows: "Software systems (and possibly hardware) designed by humans that, given a complex objective, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the structured or unstructured data collected, reasoning on knowledge or processing the information derived from this data and deciding the best actions to be taken to achieve the given objective". To this definition it was added that "AI systems can use symbolic rules or learn a numerical model, and can also adapt their behavior by analyzing the effects that their previous actions have had on the environment".

White Paper on IA, pillars to promote common regulation

It is clear that the adoption of a common regulation desired by the Council in 2017 on AI has been abruptly accelerated by the publication of the White Paper on AI by the Commission on last February 19th. The public consultation launched by the Commission will expire on May 19, 2020, date in which proposals and comments on how to further boost AI research and development, improve the development of AI knowledge by European small and medium-sized enterprises and provide the essential elements for a legislative framework on AI can be received by the Commission itself. In the Commission's view, AI systems can help the Union to address current social challenges such as the fight against climate change, challenges related to sustainability and demographic change, the protection of democracies and the fight against crime. All this without neglecting respect for fundamental human rights, such as human dignity and the protection of individuals' privacy.

The Commission therefore intends to approach the AI issue through common legislation based on the development of the European economy by exploiting the large amount of data available through trustworthy AI systems that can guarantee fundamental human rights. The economic system of excellence that the Commission intends to develop is based on rationalization of research, on the promotion of collaboration between Member States (as well as between the public and private sectors), increasing investment in the development and dissemination of AI.

In order to make IA systems reliable, the Commission has confirmed the Group of Experts view that any development of reliable IA cannot be without ensuring the following seven key pillars:

(i) human contribution and supervision; (ii) technical soundness and security; (iii) privacy and data governance; (iv) transparency; (v) diversity, non-discrimination and fairness; (vi) social and environmental well-being; (vii) accountability.

This is obviously to prevent the development of AI-based systems from having distorting effects. Indeed, the Commission is well aware that AI systems, through the automation of activities that were previously the exclusive competence of humans, may threaten the privacy of citizens, infringe their right of expression, the principle of non-discrimination and the self-realization of individuals (just to mention some of the risks).

However, the fact that AI systems are able to process an immense amount of data through automated algorithmic processes (predetermined by humans) can be a valuable help to counter the spread of the COVID-19 virus in the current health emergency situation, leading individual Member States to "run alone" on the issue of the medical emergency.

Medical AI systems COVID 19 case

It is no surprise that, in the medical field, the most advanced diagnostic systems are able to process by themselves and in real time a myriad of data from the Internet, public administrations and other networked health facilities on their own. This has been happening for a long time in this area, so much so that it is common to talk about the Internet of Medical Things[8]. Obviously there are many ethical problems underlying the use of AI in the medical field both as reliability of the data processed (acquiring patient data from the Internet or other databases if not sufficiently validated could lead to incorrect diagnoses) and as objectives pursued (AI could pursue unethical objectives such as driving towards medical practices that meet administrative objectives but not the real quality of care)[9].

The White Paper sets the whole health care sector as an example for a high-risk area that should be taken into account in any future regulation.

In the situation now described, the health emergency resulting from the COVID 19 infection, which - with a shocking effect - brought to light two crucial issues: the first concerns the new balance between the medical field and fundamental rights in the emergency health context, while the second concerns the real possibility of continuing, and how, with collaboration between Member States in the European context.

In clear contrast to the indications of principle set out in the White Paper, in fact, in the current health emergency to combat COVID-19 there is a progressive complication of the ways of balancing the pillars of ethics and the protection of fundamental human rights with the objectives of protecting the right to health, precisely in that high-risk field identified in the White Paper. This could mean, on the one hand, that the path of regulation based on ethical principles indicated by the Commission will be subject to harsh criticism for failing to take account of what was already happening in the medical field in relation to AI. In particular, the Commission makes no mention of the necessary balance between fundamental human rights (such as privacy) and the necessary applicability of AI systems, which necessarily have to sacrifice citizens' privacy in order to protect public health. On the other hand, we are already seeing clear positions taken by individual Member States in favor of the applicability of AI in the medical field, with the consequent sacrifice of fundamental human rights as set out in the White Paper, such as privacy.

To confirm this, see the discussion underway in Italy where, among other mandatory measures to be taken, the possibility of using a smartphone application capable of tracking citizens' movements to stop the COVID-19 epidemic is being considered. Obviously, the privacys breach connected to the use of the aforementioned application is clear. Even more clear is the use of AI capable of processing the data received by providing a diagnosis in a short time to contain and fight the pandemic without citizens being able (perhaps) to oppose the tracking of their personal and medical data. In addition to the tracking via smartphone application, the Ministry of Technological Innovation and Digitization, the Ministry of Economic Development and the Ministry of University and Research have published an invitation to research centers and innovative companies to provide a contribution in the field of devices for prevention, diagnostics and monitoring to contain and combat the spread of the COVID-19 virus (including the possible use of a monitoring smartphone application) [10]. On this point, the approach of Antonello Soro, President of the Guarantor for the protection of personal data, appears wavering. On the one hand, in the first days of the emergency, he was in favor of using the app in question if such a system of data collection and processing, even if invasive, is in any case aimed at the general interest of health protection[11]. On the other hand, recently, the Guarantor has expressed an opinion that would appear to be different, arguing that the use of apps of this type can only take place on a voluntary basis. Now, it would seem appropriate to approach the issue from a holistic perspective, asking whether or not the health emergency justifies the compression of fundamental rights. If this is the case (and it seems that Italian constitutionalists have expressed themselves in this sense), the compression of the right to privacy is no different from that of the right to freedom of movement, of association, and of work that citizens have already been suffering for several weeks, for the - at least allegedly - superior good of public health. It is obvious that the compression can only be justified to the extent that the health emergency actually exists, and that the two opposing demands must be constantly balanced, also from an evolutionary point of view. When the threat is greatest, more invasive measures can be justified; when the threat is least, these measures can become illegitimate. It is equally obvious that it will be necessary to ensure adequate control of the choices that in these days are made by governments, regional governors, other administrative authorities, with little or no involvement of Parliament and in the paralysis of the judicial system. Both these aspects must be rapidly restored, on pain of upsetting the fundamental characteristics of our society. It will be interesting to see what decisions will be taken by Italy and the other EU Member States. In fact, it is to be expected that the latter will undertake their own paths to implement AI systems in the medical field to counter the spread of COVID-19.

And here comes to light the second issue mentioned above, namely the disruptive effect that the COVID - 19 emergency is having on all the structures and principles of the European Union. Member States soon suspended some of these principles, first of all that of free movement of people and goods, blocking borders, deliveries of goods considered essential, and sometimes seizing such goods in transit to supply their own facilities. Also in the field of IA and apps for health control it is foreseeable that each Member State will move autonomously, with good peace of mind of the initiatives undertaken by the Community bodies, and highlighting how the whole system must now be rethought.

A fundamental question therefore remains to be asked: will the fundamental pillars - also in terms of AI - developed by the European Union stand up to the challenge of the health emergency that has upset Europe?

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Artificial intelligence, European Union in balance between common approach and nationalism - Lexology

On April 1, nearly 30 artificial intelligence (AI) researchers and experts met virtually to discuss ways AI can help understand COVID-19 and potentially mitigate the disease and developing public health crisis.

COVID-19 and AI: A Virtual Conference, hosted by the Stanford Institute for Human-Centered Artificial Intelligence, brought together Stanford faculty across medicine, computer science, and humanities; politicians, startup founders, and researchers from universities across the United States.

In these trying times, I am especially inspired by the eagerness and diligence of scientists, clinicians, mathematicians, engineers, and social scientists around the world that are coming together to combat this pandemic, Fei-Fei Li, Denning Family Co-Director of Stanford HAI, told the live audience.

COVID-19: What is Working?

As the virus envelops the world, South Korea, China, Hong Kong, and Singapore have been able to drastically flatten their curves, says Michele Barry, Stanford University professor of medicine. To begin, these countries were quick to enact strong containment, social-distancing or quarantine rules, rigorous and free testing and tracking, and far-reaching communication strategies. Why else were they so successful? All were highly prepared to meet this health crisis as a result of prior experience confronting the 2002 SARS epidemic, she notes.

Jason Wang, director of Stanfords Center for Policy, Outcomes, and Prevention, pointed to Taiwan as another leader in this space. Taiwan focused on tracking health supplies, coordinating government agencies, regulating transportation, and amending laws for violating quarantine. Both Taiwan and South Korea implemented aggressive technologies, including thermal imaging. If your temperature reading was too high, for example, you were denied entry to an office building or restaurant.

In the United States, early focus has shifted from containment to quarantine and testing. Were paying attention to Korea, China, and Singapore and other places that are a month ahead of us, says U.S. Rep. Ami Bera. Serological testing used to diagnose the presence of antibodies in the blood will help us understand who has immunity and when we can reopen parts of the community, he adds.

The Fight Against Misinformation

Managing the scope of this global pandemic has been made more difficult and complicated by the spread of disinformation, misinformation, and conspiracy theories.

In times of crisis, University of Washington associate professor Kate Starbird explains, people come together to seek information and take psychological comfort. But sensemaking can also lead to false rumors. Disinformation false information thats spread intentionally causes confusion and even panic and can divert resources to the wrong areas, says Stanford Health Communication Initiative director Seema Yasmin. Both disinformation and misinformation (any information thats inaccurate) can breed xenophobia. Eram Alam, Harvard University assistant professor, notes a recent uptick in hate crimes and racist incidents as references to the Chinese virus or Wuhan virus peppered articles and government news conferences.

To maintain trust, says Starbird, political leaders must be mindful that their statements not contribute to the spread of misinformation or cast doubt on science; crisis communicators must be transparent about the rationale for their actions (while acknowledging that facts may change as we learn more).

Researchers Roles in Fighting COVID-19

Across disciplines, researchers are finding ways to fight COVID-19, by sharing data and building new tools. Infectious diseases data scientist Lucy Li of the Chan Zuckerberg Biohub says her organization is developing a tool to estimate unreported infections. At Stanford, associate professor of medicine Nigam Shah and colleagues are honing in on ways data science can respond both operationally (How many patients will our region have? How many ICU beds do we need?) and clinically (Whom do we test?), while pointing to critical areas for further research (What drugs can help us?). Harvard Medical School pediatrician John Brownstein and his team are tracking all coronavirus infections worldwide and partnering with organizations designing tools around the information together with the CDC, for example, they are working to analyze the efficacy of various social-distancing policies.

At Carnegie Mellon, statistics and machine learning associate professor Ryan Tibshiranis epidemiological forecasting team has shifted from studying flu to COVID-19 to predict short-term forecasts that will inform public health officials in making policy decisions. Meanwhile, Tina White, a Stanford mechanical engineering PhD candidate, designed an open-source app to track the spread of COVID-19, using anonymized Bluetooth data. HAI co-director Fei-Fei Lis research offers an AI approach to helping senior citizens stay in their homes: sensors and cameras could send valuable information about sleep or dietary patterns, for instance, to clinicians in a secure and ethical way.

Meanwhile, startups are playing a role. Curai co-founder Xavier Amatriain says his companys machine learning tools create personalized diagnostic assessments, while Anthony Goldblooms company, Kaggle, offers the machine-learning community ways to share data and review each others work.

Finding a Cure

Tools are essential weapons for tracking and better understanding the disease, but vaccines and drugs are the pathway to an eventual cure. Binbin Chen, Stanford genetics MD and PhD student, says vaccines are among the most powerful ways to curb a pandemic and prevent its recurrence. His team uses artificial intelligence to examine fragments of SARS-CoV-2 to determine how they might apply to COVID-19 vaccines. These tools, says Chen, can give us a better educated guess and increase our chances of finding an effective vaccine. Meanwhile, Stanford bioengineering research engineer Stefano Rensi is examining existing drugs that can be repurposed to combat the disease. He and his team use natural language processing, protein structure prediction, and biophysics to identify potential drugs. According to preliminary results, the team has classified several candidates, including one undergoing clinical testing in Japan.

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Artificial Intelligence and COVID-19: How Technology Can Understand, Track, and Improve Health Outcomes - Stanford University News

Proficient Market announces that it has a new study on Global Artificial Intelligence in Security Market. The 2020 study has 211 pages, 74 tables and 102 figures.

According to the report, global artificial intelligence in security market in 2018 stood at USD 5.08 billion and is expected to reach USD 15.9 billion by 2027 growing at a CAGR of 26.3% from 2019 to 2026.

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Artificial intelligence is basically a result of a software that tries to create a decision mechanism similar to human brains decision mechanism. AI in security generally provides an enticing proposition with its proactive threat mitigation capabilities which is required for constant supervision and adaptation to the multifaceted security vulnerabilities faced by modern digitalized economy. Also, artificial intelligence is playing a important role in cyber security by identifying threats as well as protecting organizations data from lethal cyber-attacks. It speeds up the process of noticing attacks and enables organizations to adopt predictive measures in combating cyber-crimes. Moreover, AI can be utilized to fight against various cyber threats including spear phishing, watering hole attack, webshell, ransomware, DDoS attacks, and remote exploitation, by identifying and preventing them from proliferating into the systems. Apart from that, AI based security systems can analyze even those threats that have not occurred in the past unlike traditional based security systems.

Global Artificial Intelligence in Security Market Key Players: The research study includes profiles of leading companies operating in the global artificial intelligence in security market. Key players profiled in the report include:BAE SystemsCiscoFortinetFireEyeCheck PointIBMRSA SecuritySymantecJuniper NetworkPalo Alto Networks

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Drivers for the Global Artificial Intelligence in Security Market: According to current market condition, one of the major factors that is helping the artificial intelligence-based security market to grow is the surge in number of connected devices across the world. Artificial Intelligence in a security solution is expected to increase precision and efficiency of the system to notice any potential threat in system. Surge in number of mobile devices has significantly caused the networks to become more vulnerable to cyberattacks, thus increasing the demand for AI based security solutions. Moreover, growing inclination of government to adopt smart city concept is expected to bolster the artificial intelligence-based security market growth. Also, growing awareness regarding various types of cyber threats such as phising, malware, denial, and password breaches are dissuading individuals to connect to any public Wi-Fi. This is increasing the uptake of personal Wi-Fi, which directly increases the demand for AI based security solutions. Growing number of e-commerce websites, mobile application, and payment getaways which accepts store credit card, debit card, and online transactions are likely to increase the demand for artificial intelligence-based security market.

Opportunities for the Global Artificial Intelligence in Security Market: AI and its applications allow the users to protect any system by providing alerts to them in real-time so that the risk can be mitigated. Also, with the data available within the organizations are being used to train these systems. With the implementation of machine learning with AI, the threats and malware can be proactively prevented rather than only be detected. This helps in creating a huge market opportunity for artificial intelligence in the security market during the forecasted period. Furthermore, increasing stringent laws and regulations imposed by the government on information and data security is anticipated to provide major growth opportunities for the market in the upcoming years.

Restrains for the Global Artificial Intelligence in Security Market: Due to the dearth of skilled AI professionals and lack of awareness is restraining about this field the market to grow during the forecast period.

Region Wise, Global Artificial Intelligence in Security Market Analysis: On the basis of region, global artificial intelligence in security market include North America, Europe, Asia Pacific, Latin America, Middle East and Africa. North America, held the leading position and is predicted to dominate in the upcoming years owing to surge in cyber-attack cases. Cyber-attacks particularly in the U.S. is considered to contribute the most. On the other hand, Asia Pacific is expected to exhibit a steady growth due to surge in adoption of machine learning in the region. North America region is followed by Asia pacific and Europe.

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Global Artificial Intelligence in Security Market: Product analysisMachine LearningNatural Language ProcessingOther

The Natural Language Processing segment holds the largest share in the artificial intelligence in security market. The deployment in technology has led NLP to play a significant role in facilitating text analytics and is also significantly contributing to the upgradation of progressive speech and text which will accelerate in the coming years.

Global Artificial Intelligence in Security Market: Application analysisBFSIGovernmentIT & TelecomHealthcareAerospace and DefenseOther

The IT & Telecommunication sector holds the largest market share for artificial intelligence in security market. The rising technological advancements such as the integration of machine learning, artificial intelligence, IoT and so on are highly enhancing the IT sector which is further leading to the rise of artificial intelligence in security market.

Global Artificial Intelligence in Security Market: Region analysisNorth America: U.S., Canada, MexicoEurope: U.K., France, Germany, Spain, Italy, Rest of EuropeAsia Pacific: China, Japan, South Korea, ASEAN, IndiaRest of Asia Pacific: Latin America, Brazil, Argentina, Colombia, Rest of L.A.Middle East and Africa: Turkey, GCC, UAE, South Africa, Rest of Middle East

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Global Artificial Intelligence in Security Market is Estimated to be Worth USD 5.08 billion in 2018 - PharmiWeb.com

LOS ANGELES, April 7, 2020 /PRNewswire/ -- Artificial Intelligence (AI) expert Neil Sahota says the COVID-19 pandemic is changing the way we live our lives, but AI can provide solutions in at least five key areas that will reduce the current impact from the disease and help prevent future disasters.

Business guru and master inventor Sahota, author of Own the AI Revolution (McGraw-Hill), says that with good data and careful modeling "AI actually can and is already helping reduce the impact from the disease on our lives."

Sahota says there are five key areas that the sophisticated computer solutions offered by AI should focus on:

"First, there is real concern that COVID-19 may return in upcoming Fall/Winter months or may even mutate and become a seasonal virus like influenza," Sahota says. "Thankfully, we can leverage artificial intelligence (AI) and generative design to help us. They can identify millions of potential COVID-19 mutations, and by applying environmental factors, can present healthcare researchers with the ten to twenty most likely mutations for the upcoming seasons. Armed with this knowledge (and virus genomics), the researchers could start identifying preventive measures, or perhaps even a 'flu shot,' before the viral outbreak occurs."

Second, AI can help manage the supply chain of equipment and people that have been disrupted by the virus. "Getting equipment and people to where they are needed the most has been such a challenge that reportedly the FDA has been leveraging Twitter to manage things," Sahota says. "We already have AI tools and deep analytic solutions that can be applied to predict COVID-19 hotspots, allowing us to route medical supplies, equipment and healthcare practitioners more effectively." Leveraging real-time micro-location technology like SmartPoint enables load balancing where people go for testing and treatment while minimizing wait times for test results.

Third, AI can help secure food production. "While we have a solid supply of food, there is concern about food production in just a few months. The FDA just released new guidelines on food production and safety to protect workers and people from COVID-19. However, there is real concern about the supply chain. Already, farmers are seeing challenges in getting enough workers to harvest food, and that's not something that can wait a week (or even a few days for certain fruits and vegetables.) Likewise, food handlers and distributors are worried about safety precautions to help them avoid disease, and everyone is concerned that food can get contaminated with COVID-19. Food exports from other countries are also a concern. Thankfully AI offers a host of agricultural technology solutions that can improve food production with fewer resources and people."

Fourth, AI can aid in generating jobs."About 10 million jobs were lost in just two weeks; worse, current estimates predict about 47 million jobs in the United States lost because of COVID-19, which is about 32% of the U.S. workforce.AI offers a short-term solution that can be scaled to a long-term fix, and, potentially, create better paying jobs for people. We have tools and infrastructure to teach people online the skills that they need to be community health workers, learn advanced skills and receive other training that would be a huge boon to getting jobs that would have immediate demand."

Fifth, AI can provide for mental health needs."COVID-19 has put a lot of stress on all of us," Sahota notes. "There's fear about getting ill, dying, losing jobs, not paying mortgages, cabin fever, and so forth. Even after we bounce back from COVID-19, there's real concern that many people will suffer from post-traumatic stress syndrome (PTSD), alcoholism, depression, etc. In a time of social distancing, we can't exactly see a therapist (at least in person). Thanks to the psychographic profiling capabilities of AI, we can create non-judgmental AI outlets to talk with and help maintain good mental health practices. Using AI solutions like Cyrano.ai and Woebot, people have these outlets to deal with their stress and get. Hopefully we will emerge from COVID-19 with more robust mental health and less addiction problems so that we can more effectively work on rebuilding our lives, jobs, businesses, and normal social interactions."

Story continues

AboutNeil Sahota:Neil Sahotais a futurist and leading expert on Artificial Intelligence (AI) and other next generation technologies. He is the author ofOwn the AI Revolution(McGraw Hill) and works with the United Nations on theAI for Goodinitiative. Sahota is also an IBM Master Inventor, former leader of the IBM Watson Group and professor at theUniversity of California/Irvine. His work spans multiple industries, including legal services, healthcare, life sciences, retail, travel, transportation, energy, utilities, automotive, telecommunications, media, and government.

View original content:http://www.prnewswire.com/news-releases/artificial-intelligence-expert-neil-sahota-says-ai-can-and-is-providing-solutions-to-covid-19-pandemic-in-five-key-areas-301036264.html

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Artificial Intelligence Expert Neil Sahota Says AI Can And Is Providing Solutions To COVID-19 Pandemic In Five Key Areas - Yahoo Finance

Increase in investment in AI technologies, rise in demand for analyzing and interpreting large amount of data, and surge in adoption of AI in emerging market are expected to propel the global AI market.

Rise in investment in AI technologies, increased demand for analyzing and interpreting large amount of data, and surge in customer satisfaction coupled with increase in adoption of reliable cloud application have boosted the growth of the global artificial intelligence (AI) market. However, dearth of trained and experienced staff hampers the market growth.

On the contrary, rise in adoption of AI in emerging markets and rapid development of smarter robots are expected to create lucrative opportunities in the near future.

The global artificial intelligence market was pegged at $4.06 billion in 2016 and is projected to reach $169.41 billion by 2025, registering a CAGR of 55.6% from 2016 to 2025.

The global AI market is divided on the basis of technology, industry vertical, and geography. Based on technology, the market is segmented into machine learning, natural language processing, image processing, and speech recognition.

The machine learning segment held the largest share in 2016, contributing more than half of the market and expected to maintain its dominance throughout the study period. Moreover, the segment is projected to register the fastest CAGR of 56.4% during the forecast period.

The market report provides an in-depth analysis of the major market players such asApple Inc., Alphabet (Google Inc.), IBM Corporation, Baidu, Microsoft Corporation, IPsoft, NVIDIA, MicroStrategy, Inc., Verint Systems Inc (Next IT Corp), and Qlik Technologies Inc.

Download Report:www.alliedmarketresearch.com/request-sample/1773

The global AI market is analyzed across various regions such as North America, Europe, Asia-Pacific, and LAMEA. The market across North America held the largest share in 2018, contributing nearly half of the market.

However, the market across Asia-Pacific is projected to manifest the fastest CAGR of 59.4% during the forecast period.

Based on industry vertical, the market is divided into media & advertising, BFSI, it & telecom, retail, healthcare, automotive & transportation, and others. The IT & telecom segment dominated the market in 2016, contributing more than one-fifth of the market.

Moreover, the segment is projected to register the fastest CAGR of 56.8% during the forecast period.

Report: http://www.alliedmarketresearch.com/1773

Top Impacting Factors Such as -

1.Increase in investment in AI technologies

2.Growth in demand for analyzing and interpreting large amounts of data

3.Increased customer satisfaction and increased adoption of reliable cloud applications

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Artificial Intelligence (AI) Market value is expected to hit $169411.8 million by 2025 according to a new research report - WhaTech Technology and...