Daily Archives: October 31, 2019

Photo: Joe McKendrick

Artificial intelligence is a must-have in todays economy. However, for the most part, its still not delivering business value in a profound way. Yet, everyone has high hopes.

Thats the word from a survey of 2,555 executives published by MIT Sloan Management Review and Boston Consulting Group, which finds those companies achieving success with AI are those that pay close attention extremely close attention to organizational factors.

A growing number of leaders view AI as not just an opportunity but also a strategic risk, the studys co-authors, led by Sam Ransbotham of Boston College, report. What if competitors, particularly unencumbered new entrants, figure out AI before we do? In 2019, 45% perceived this risk in their markets, up from 37% in 2017.

The path to AI-driven success is not a smooth one, however. Many AI initiatives have been falling flat when it comes to business impact. Seven out of 10 companies surveyed report minimal or no impact from AI so far, the survey shows.

Even among organizations leading the way with AI with significant investments, only about three in five report some business impact from AI. This means 40% of organizations making significant investments in AI do not report business gains from AI, Ransbotham and his team points out.

Whats the problem? Organizational issues bog down AI initiatives, the survey shows. Companies that focus solely on the production of AI data, technology, tools are less likely to derive value than those companies that actively align business owners, process owners, and AI owners, the survey authors state. Leaders enable their organizations to consume AI as much as to produce AI.

Ransbotham and his co-authors identified five common traits that the AI winners exhibit:

While the AI leaders have these commonalities, there is no step-by-step process for achieving a sustainable and profitable AI initiative, the researchers caution. The key is to elevate AI efforts out of the labs and into the business mainstream where everyone can see and experience it.

Executives must act strategically, they advise. Acting strategically means deciding what not to do. AI projects that focus on targeted solutions create a positive pressure for organizational integration on two levels: by forcing a level of data hygiene that yields greater integration across functions, and by revealing exciting opportunities for innovation that organizations can only realize if many disparate parts of the organization pull together.

Originally posted here:

Five Traits Of Artificial Intelligence Trailblazers - Forbes

Artificial Intelligence Use Expected to Increase in Risk and Compliance Efforts | 2019-10-30 | Security Magazine This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more. This Website Uses CookiesBy closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.

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Artificial Intelligence Use Expected to Increase in Risk and Compliance Efforts - Security Magazine

NEW DELHI: Germany and India are likely to sign agreements including a partnership on the use of artificial intelligence in farming during a three-day visit to New Delhi by Chancellor Angela Merkel that begins on Thursday, the German ambassador said.

Merkel will be accompanied by several cabinet colleagues and a business delegation, ambassador Walter J. Lindner told reporters.

Merkel and Indian Prime Minister Narendra Modi are expected to discuss trade, investment, regional security and climate change.

Both countries could sign agreements in areas such as artificial intelligence and green urban mobility, Lindner said.

"This time, the focus will be on economic and trade relations, innovation and digitalisation, and climate protection and sustainable development," Merkel said in a message ahead of the visit released by the Indian embassy in Berlin.

Bilateral trade between the two countries rose to $24.06 billion in the 2018/19 fiscal year ending in March from $22 billion the previous year, while German companies have invested nearly $12 billion in India since 2000.

Germany is India's largest trading partner in Europe and more than 1,700 German companies are operating in India.

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India and Germany likely to sign agreement on artificial intelligence - Economic Times

Updated: May 25, 2018:

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Is the Use of Artificial Intelligence in the Employee Application Process Worth the Risk? - JD Supra

Updated: May 25, 2018:

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This Privacy Policy describes how JD Supra, LLC ("JD Supra" or "we," "us," or "our") collects, uses and shares personal data collected from visitors to our website (located at http://www.jdsupra.com) (our "Website") who view only publicly-available content as well as subscribers to our services (such as our email digests or author tools)(our "Services"). By using our Website and registering for one of our Services, you are agreeing to the terms of this Privacy Policy.

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Our Website and Services are not directed at children under the age of 16 and we do not knowingly collect personal information from children under the age of 16 through our Website and/or Services. If you have reason to believe that a child under the age of 16 has provided personal information to us, please contact us, and we will endeavor to delete that information from our databases.

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Some browsers have incorporated a Do Not Track (DNT) feature. These features, when turned on, send a signal that you prefer that the website you are visiting not collect and use data regarding your online searching and browsing activities. As there is not yet a common understanding on how to interpret the DNT signal, we currently do not respond to DNT signals on our site.

For non-EU/Swiss residents, if you would like to know what personal information we have about you, you can send an e-mail to privacy@jdsupra.com. We will be in contact with you (by mail or otherwise) to verify your identity and provide you the information you request. We will respond within 30 days to your request for access to your personal information. In some cases, we may not be able to remove your personal information, in which case we will let you know if we are unable to do so and why. If you would like to correct or update your personal information, you can manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard. If you would like to delete your account or remove your information from our Website and Services, send an e-mail to privacy@jdsupra.com.

We reserve the right to change this Privacy Policy at any time. Please refer to the date at the top of this page to determine when this Policy was last revised. Any changes to our Privacy Policy will become effective upon posting of the revised policy on the Website. By continuing to use our Website and Services following such changes, you will be deemed to have agreed to such changes.

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There are different types of cookies and other technologies used our Website, notably:

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Five Questions With...Doug Smith, SVP at Tallan, on Artificial Intelligence and Analytics in the Workplace - JD Supra

For private companies and government agencies trying to track peoples' movements, technology is making the task increasingly easy.

Facial recognition and analysis are becoming increasingly popular surveillance tools the technology was rolled out in airports across the world this summer as a tool for verifying flyers' identity, and is widely used by police departments for tracking suspected criminals.

Privacy-minded activists and lawmakers are now hitting back at facial recognition. The technology has been banned for law-enforcement purposes across California, and a similar bill is being weighed in Massachusetts. Meanwhile, artists and researchers have begun to develop clothes designed to thwart algorithms that detect human faces.

But emerging technology presents alternate means of identifying and tracking humans beyond facial recognition. These methods, also driven by artificial intelligence, detect the presence of humans using devices ranging from lasers to WiFi networks.

The vast range of biometric data that technology can register makes regulation difficult. Meanwhile, some of the emerging surveillance technology is already being embraced by military powers like the US and China.

Here's a rundown of emerging technology that can detect humans and track their location.

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How AI is being trained to recognize humans beyond facial recognition - Business Insider

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence (AI) Hardware: Global Markets" report has been added to ResearchAndMarkets.com's offering.

The scope includes the analysis of the AI hardware market based on technology type, computation type, end use industries and regional markets. For each of these market segments, revenue forecasts for 2018 through 2024 are provided at the global level.

The AI hardware market is segmented into the following categories:

This report covers analyses of the global market trends, with data from 2018 to 2024 and projections of CAGR during 2019 to 2024 . The estimated values used are based on manufacturers' total revenues. Projected and forecasted revenue values are in constant U.S. dollars that have not been adjusted for inflation.

Report Includes:

Key Topics Covered:

Chapter 1 Introduction

Chapter 2 Summary and Highlights

Chapter 3 Market and Technology Background

Chapter 4 AI Hardware Market

Chapter 5 Competitive Landscape

Chapter 6 Company Profiles

For more information about this report visit https://www.researchandmarkets.com/r/2h9th9

Originally posted here:

Global Artificial Intelligence (AI) Hardware Markets, 2019-2024 - Start-Ups and Software Industry Giants Entering the AI Hardware Industry -...

Using a fluoroscopy system enabled with artificial intelligence (AI) during image-guided endoscopy can significantly reduce patients exposure to radiation and diminish the scatter effect to endoscopy personnel, according to late-breaking research presented at the American College of Gastroenterology (ACG) 2019 Annual Scientific Meeting and Postgraduate Course.

To reach this conclusion, Ji Young Bang, MD, from AdventHealth Orlando in Orlando, Florida, and colleagues conducted a prospective study of 100 consecutive patients who underwent endoscopy with either a conventional fluoroscopy system (n=50) or an AI-enabled fluoroscopy system (n=50).

The study outcome measures were to compare radiation exposure to patients via dose area product (DAP) and to measure radiation scatter to endoscopy personnel via a dosimeter.

The groups had no significant difference in demographics, body mass index, procedural type, or procedural/fluoroscopy time between the conventional and the AI-enabled fluoroscopy systems.

Radiation exposure to patients was lower with the AI-enabled fluoroscopy system compared with the conventional system (median DAP, 2178 mGym2 vs 5708 mGym2, respectively).

The scatter effect to endoscopy personnel was less with the AI-enabled fluoroscopy system compared with the conventional system (total deep-dose equivalent, 0.28 mSv vs 0.69 mSv, respectively), for a difference of 59.4%.

After adjusting for patient characteristics, procedural/fluoroscopy duration, and type of fluoroscopy system, only the AI-enabled fluoroscopy system and fluoroscopy duration were associated with radiation exposure.

Colleen Murphy

Reference:

Bang JY. Use of artificial intelligence to reduce radiation exposure at fluoroscopy-guided endoscopic procedures (late-breaking abstract) [abstract 73]. Presented at: ACG 2019Annual Scientific Meeting and Postgraduate Course; October 25-30, 2019; San Antonio, TX.

See the original post here:

Artificial Intelligence May Reduce Radiation Exposure in Fluoroscopy-Guided Endoscopy - Consultant360

In this version of the future, people will still have a role working alongside smart systems: either the technology will not be good enough to take over completely, or the decisions will have human consequences that are too important to hand over completely to a machine. Theres just one problem: when humans and semi-intelligent systems try to work together, things do not always turn out well. Like almost all of todays autonomous cars, a back-up driver was there to step in if the software failed. The so-called Level 3 system is designed to drive itself in most situations but hand control back to a human when confronted by situations it cannot handle.

If youre only needed for a minute a day, it wont work, says Stefan Heck, chief executive of Nauto, a US start-up whose technology is used to prevent professional drivers from becoming distracted. Without careful design, the intelligent systems making their way into the world could provoke a backlash against the technology. Preventing that will require more realistic expectations of the new autonomous systems, as well as careful design to make sure they mesh with the human world. Does the AI make us feel more involved or is it like dealing with an alien species?

Research from Stanford University has shown that it takes at least six seconds for a human driver to recover their awareness and take back control, says Mr Heck. But even when there is enough time for human attention to be restored, the person stepping into a situation may see things differently from the machine, making the handover far from seamless.

We need to work on a shared meaning between software systems and people this is a very difficult problem, says Mr Sikka. A second type of human/machine cooperation is designed to make sure that a sensitive task always depends on a person even in situations where an automated system has done all the preparatory work and would be quite capable of completing the task itself. Military drones, where human pilots, often based thousands of miles away, are called on to make the decision to fire at a target, are one example. Both show how AI can make humans far more effective without robbing them of control, says Mr Heck.

You cant say the technology itself can only be used in a defensive way and under human control. A final type of human in the loop system involves the use of AI that is not capable of handling a task entirely on its own but is used as an aid to human decision-making. Algorithms that crunch data and make recommendations, or direct people in which step to take next, are creeping into everyday life. The algorithms, though, are only as good as the data they are trained on and they are not good at dealing with new situations.

People required to trust these systems are often also required to take them on faith. The outcome of these computer-aided decisions may well end up being worse than those based on purely human analysis, he says. Sometimes people will blindly follow the machine, other times people will say: Hang on, that doesnt look right.

But what happens when the stakes are higher? IBM made medical diagnostics one of the main goals for Watson, the system first created to win a TV game show and then repurposed to become what it calls a more general cognitive system. Simply saying theyll still make the decisions doesnt make it so. Similar worries surfaced in the 1980s, when the field of AI was dominated by expert systems designed to guide their human users through a decision tree to reach the correct answer in any situation.

But the latest AI, based on machine learning, looks set to become far more widely adopted, and it may be harder to second-guess.

Non-experts may feel reluctant to second-guess a machine whose workings they do not understand. Technicians had no way of identifying the flaw and the machine stayed in use much longer as a result, says Mr Nourbakhsh.

Some experts, however, say headway is being made and that it will not be long before machine learning systems are able to point to the factors that led them to a particular decision. Like many working in the field, he expresses optimism that humans and machines, working together, will achieve far more than either could have done alone.

He had already founded and sold off several successful consumer technology companies, but as he grew older he wanted to do something more meaningful, that is, he wanted to build a product that would serve the people that technology startups had often ignored. Both my friend and I were entering the age at which our parents needed more help going about their daily lives, and he decided to design a product that would make life easier for the elderly.

It sounded like a wonderful product, one that would have a real market right now.

But once those material needs were taken care of, what these people wanted more than anything was true human contact, another person to trade stories with and relate to. If he had come to me just a few years earlier, I likely would have recommended some technical fix, maybe something like an AI chat bot that could simulate a basic conversation well enough to fool the human on the other end.

But there remains one thing that only human beings are able to create and share with one another: love.

Despite what science-fiction films like Her in which a man and his artificially intelligent computer operating system fall in love portray, AI has no ability or desire to love or be loved.

I firmly believe we must forge a new synergy between artificial intelligence and the human heart, and look for ways to use the forthcoming material abundance generated by artificial intelligence to foster love and compassion in our societies.

Excerpted with permission from The Tech Whisperer: On Digital Transformation and the Technologies that Enable It, Jaspreet Bindra, Penguin Portfolio.

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This chapter on the future of Artificial Intelligence was written by Artificial Intelligence - Scroll.in

It is common knowledge now that a homogenous and rote learning education system might suit some children but not all, thereby isolating many and preventing them from achieving their full potential. What we need to offer our children is a fun experience while learning. An experience that is immersive, experiential, self-paced, interactive and designed specifically for each child.

Fortunately, the global community has awakened to this crisis in education and has called for quality and inclusive education for all, which is the crux of the United Nations Sustainable Development Goal (SDG) 4. I perceive personalised learning as the foremost means of answering this global call and truly achieving this goal for all children across the world.

Social and institutional implications

The focus here, however, is not on highlighting the merits of personalised learning but to determine if the concept is feasible; if yes, what are the social and institutional implications?

The definite answer is Yes and information technology is the key to making it happen. Specifically, I am referring to the internet and the growth of Artificial Intelligence (AI), which offers the possibility of harnessing the collective wisdom of the many for the benefits of the individual.

The internet can be seen as offering two levels of information. The first is the actual content that is made available for learners to access lets call this the first order information. The second level of information is partially hidden it is not readily available to everyone and relates to the behavioural aspects of the users accessing and using content; this is the data that is harnessed by AI. Lets call this second order information.

An article in the May 17, 2017, issue of The Economist considers this second order information about users accessing and using information on the internet as new gold. Ben Rossi, in his article, Data revolution: the gold rush of the 21st century, estimates that the amount of data accumulated in 2011 and 2013 was more than nine times the data collected till 2011; this data is expected to reach 44 Zettabytes by 2020.

Personalised BOT

Such information has immense utility when it comes to education. Imagine a scenario where a child in rural India is having trouble with introductory algebra and the teachers limited knowledge base makes it hard for the child to find an answer. We can expect the teacher to only have a finite set of approaches to teaching algebra that is available as she or he is constrained by the human brain. Things will be very different, however, if the child is given access to an online system, which I will tentatively call Global Intelligent Education Platform (GIEP). As part of this system, the child is paired with a personalised BOT right after she/he enters school.

ABotcan be described as a computer program (a set of algorithms) that is able to support and provide guidance to a user or users in accomplishing a task or automatic repetitive tasksand may growits own intelligence after mining and analysing huge amounts of data. A Bot is a product of AI!

This BOT develops a keen understanding of the childs attributes and learning preferences by evaluating data about the childs ongoing learning experiences. It also has access to an infinite set of possible interventions arising from learner-centric data derived from the experiences of millions of other children learning algebra or any other topic worldwide to help the child overcome learning problems. Personalised learning, the holy grail of education, is a definite reality in this hypothetical scenario. As I perceive it, making this a reality for children today a distinct possibility.

Before that, however, we must overcome some ideological challenges related to the ownership of information that the BOT will access. As we have visualised it, the personalised BOTs capacity to impart learning and customise solutions will only be as strong as the amount of information that it can access. Therefore, the strength of the GIEP will depend on whether the information generated by learners all across the world is made accessible to every individual learner a pure social good.

Role of inter-governmental organisations

Who, then, should be the custodians or managers of this new gold? In many ways, the knowledge available can be considered as the global commons as described by the late Nobel Laureate Elinor Ostrom.

Who then can provide and manage this common? Can governments provide this service? The answer is both Yes and No. Yes, because governments do have the mandate to provide the social good; No, because in this case, the commons transcend national boundaries. If I need to find an analogous, I will use the global climate system as the global commons and if not managed properly can lead to climate change.

The unambiguous solution to this dilemma is that the responsibility be taken up by an inter-governmental organisation such as the United Nations or one or more of its specialised agencies such as the United Nations Education Science and Cultural Organisation (UNESCO).

To answer the two fundamental questions posed in the title of this article, I would say that the global community own the global knowledge commons and that this knowledge be managed by an inter-governmental agency such as the United Nations.

Original post:

Artificial Intelligence in education: Who should be the custodian of the new gold? - CNBCTV18