Category Archives: Artificial Intelligence

Ryan Steelberg, President of Veritone, and one of the worlds foremost experts in online advertising, will co-host the first in a series of free Radio Ink and RBR-TVBR webinars starting May 23 at 1 p.m.ET. Ryan will reveal new tool sets that enable broadcasters and advertisers to increase ROI and campaign measurement. (REGISTER HERE)

Emerging technology, like artificial intelligence, is giving radio and other traditional media a new opportunity to turn the tables on their Internet rivals in the marketplace. Forward-looking organizations are using cognitive engines to unlock value previously trapped within their content and advertising data, yielding increased revenue, improved efficiency, and fresh monetization opportunities.

Dont miss out on an opportunity to learn how artificial intelligence is revolutionizing the media industry as Ed Ryan, Editor of Radio Ink, and Steelberg talk about Artificial Intelligence 101. Topics include: Why should the radio industry care about AI?; What radio stations are using this technology now and how are they using it?; What revenue opportunities does this new technology provide for radio and how do stations get involved? Reserve your spot now!

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How Artificial Intelligence Can Supercharge ROI For Your Advertisers - Radio Ink

No matter the benefits, AI use cases will be limited if British patients are not comfortable with the technology. However, technological advances have led to a growing level of trust amongst British citizens when it comes to AI and healthcare

Last Friday, the government revealed how the budget for more investment in cutting-edge technology and innovation would be split, with business secretary Greg Clark announcing that robotics and AI will be receiving 93 million as part of the governments 1 billion Industrial Strategy Challenge Fund impacting a range of sectors, including healthcare.

In the healthcare sector, technology has already been used to update patient records, improve care delivery and streamline processes.

Artificial intelligence (AI) is increasingly being heralded as a technology to achieve further breakthroughs in this sector.

>See also:The next necessary step in healthcare: remote mobile solutions

UK consumers are also seeing the advantages of introducing AI into the healthcare sector. Recent research from the enterprise information management company, OpenText, revealed that a the UK public would appreciate quicker diagnoses.

This was identified as the biggest benefit for people surveyed, with one in three (33%) UK residents believing robots would reach a decision on their condition much faster.

As well as faster diagnosis, one in four (25%) believed they would get a more accurate diagnosis from AI.

A quarter of UK consumers (25%) said robot technology would mean they wouldnt have to rely on booking an appointment with a GP, while 24% said the biggest benefit would be no longer having to take time off work to visit a doctor.

AI would also, almost certainly reduce the strain on the NHS.

>See also:Beware of hackers: people deserve a more secure healthcare system

Mark Barrenechea, CEO at OpenText, said that Thanks to parallel processing, big data, cloud technology, and advanced algorithms, Artificial Intelligence (AI) and machine learning are becoming more powerful. The analysts are jumping on board, with Forrester predicting that investments in AI will grow 300% in 2017. The Digital Revolution will drive an increasing reliance on self-service technology, machine to machine (M2M) communication and AI, and there is no denying that every job in every industry will be impacted. However, the opportunity for innovation and change is limitless.

No matter the benefits, AI use cases will be limited if British patients are not comfortable with the technology. However, technological advances have led to a growing level of trust amongst British citizens when it comes to AI and healthcare. In one recent report, PwC revealed that over a quarter of Brits would now trust robots over doctors with heart surgery.

This belief in AI is mirrored across the healthcare sector at a much wider level OpenText research revealed that nearly two in five (38%) UK consumers would trust the medical diagnosis given by AI and just over 1 in 10 (11%) said they would trust the diagnosis of AI more, or just as much, as a doctors diagnosis.

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Artificial intelligence and the healthcare sector - Information Age

Forbes

The Complete Beginners' Guide to Artificial Intelligence - Forbes Forbes Artificial intelligence continues to transform the ways we live our lives and run our businesses. However, the meaning and implications of what artificial ... Artificial intelligence as a driver for innovation - FederalNewsRadio ...FederalNewsRadio.com all 2 news articles »

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The Complete Beginners' Guide to Artificial Intelligence - Forbes - Forbes

CNNMoney, citing a PwC report, declared that 38 percent of USA jobs will be lost due to robots and artificial intelligence over the coming 15 years. Jobs that perform routine, repetitive tasks and are in industries include manufacturing, banking, education, retail and hospitality. The same warning bells are being rung by The Economist, New York Times, The Guardian and others. The World Economic Forum cites a net loss of over 5 million jobs by 2020 in 15 major developed and emerging economies.

The mainstream media headlines around automation related job loss are akin to Chicken Littles warning that the sky was falling. The sensationalism overstates reality.

The impression is that job loss due to automation is a recent phenomenon. Its not. The ATM was created in 1967 and has taken over 30 years to evolve into what we take for granted today. Did it significantly reduce bank teller jobs? Yes, over a long period of time. But it did not eliminate the position; it evolved.

There are countless examples of how technology has changed economies, professions and industries. This has been going long before the steam engine and electricity was invented. The pace of technological change today is, however, increasingly faster. PwCs 15 years forecast for job loss is challenging to believe when we look at the reality of what it takes to implement artificial intelligence.

Spoiler alert - our ability to forecast the timing of future events with a measurable degree of accuracy isnt particularly good.

Rurik Bradbury, Head of Research at LivePerson, a mobile and online messaging company, has a different perspective. The prospect of replacing entire jobs with just technology is unlikely, shares Bradbury. There is a lot of confusion about AI with more talk than actual deployment.

Todays artificial intelligence technologies are capable of performing tasks at the atomic level. These are very narrowly defined tasks that operate within a clearly defined set of responses.

Based on LivePersons customer experience, Bradbury strongly believes that AI can perform, on average, 40 percent of the tasks comprising customer care jobs. In other words, AI driving the level of unemployment forecasted by CNN within the next 15 to 20 years is unlikely. Even if we just focus on customer care jobs across all industries.

Jobs are comprised of a multitude of tasks as well as a wide range of problem solving situations that require lateral thinking and complex, emotion-based human interactions. Bringing in AI to a customer support position, for example, requires the job to be broken down into its detailed components.

On average approximately 40 to 50 percent of tasks in a call center are good candidates for automation. These are tasks that a call center agent or manager can trigger updating your address, for example. The dialog between the AI and the customer is controlled by how the AI application is programmed and closely measured with human oversight. AI does not run without tight controls in place. The analytics include sentiment analysis that tells management which AI-conducted customer interactions were positive or negative. Negative interactions can result in shifting that task back to a human or reprogramming the AI software.

AI doesnt always replace workers; it augments their ability to be more effective and productive. That doesnt mean that the nature of work will not change, it will. The operative word is augmented Bradbury calls it job sharing.

Routine, data-driven, narrowly defined subtasks will be automated freeing the human worker to engage in higher level, most sophisticated tasks such as creative problem solving, strategic thinking and relationship building. The latter being things humans are much better suited for.

Based on Bradburys research and LivePerson customers experience, the rate of AI taking over human tasks is slower than popular media would lead you to believe.

First, to effectively employ AI to drive a positive, productive customer experience requires a clear plan based on gradual automation over time. Secondly, the current rate of automating tasks is one percent a year. In the case of the 40 percent of call center agent tasks that could be candidates for automation, companies would be extremely hard pressed to achieve that level of automation within ten to fifteen years. So much for predictions.

That doesnt mean ignore artificial intelligence. Approach it with a solid plan based on best practices. Here are a few of Bradburys suggestions:

1. Collect a data set of good (read: successful) customer interactions and categorize them, identifying the most frequent interactions.

2. Pick candidates for automation based on opportunities to improve the interaction. Start with a very small group of interactions to experiment with.

3. Take a subset of these identified interactions and create a chatbot or AI interface that is specific to the atomic task being automated. The more granular the definition and automation of the task, the higher the success. 70 percent of current AI tasks fail because they are too general.

4. Put the AI task into production aside a team of call center agents and test. That means collect data, perform A/B testing, and analyze the conversations and their outcomes. Evolve the AI software over time based on the results of the analysis.

5. As success is realized, automate additional tasks based on the same testing and analysis approach. Set performance thresholds for each AI task. Keep in mind that AI applications work in tandem with employees and need to be orchestrated are part of a companys ecosystem.

How we look at technology directly influences how we fit it into our lives. Dont think of artificial intelligence as a separate project or technology. Think of it as part of a job and measure it accordingly.

Ignore the chicken littles. Leverage AI where it enhances the customer experience and delivers measurable value add. Start small, get granular, and go slow.

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The Chicken Littles of Artificial Intelligence - Huffington Post

ZURICH ABB has sealed a collaboration agreement with International Business Machines Corp, the Swiss engineering company said on Tuesday, the latest step in its efforts to ramp up its presence in digital technology and the internet of things.

In a joint statement ABB said it would combine its digital offering, which gathers information from machinery, with IBM's expertise in artificial intelligence featured in its Watson data analytics software. The two companies will jointly develop and sell new products.

"This powerful combination marks truly the next level of industrial technology, moving beyond current connected systems that simply gather data, to industrial operations and machines that use data to sense, analyze, optimize and take actions that drive greater uptime, speed and yield for industrial customers," ABB Chief Executive Ulrich Spiesshofer said in a statement.

For example, instead of manual machinery inspections, ABB and IBM intend to use Watson's artificial intelligence to help find defects via real-time images collected by an ABB system, and then analyzed using IBM Watson.

ABB has identified digital technology where machinery communicates with control centers to increase productivity and reduce downtime as a driver of growth. It now gets around 55 percent of sales from products that are digitally enabled.

As part of the drive, the company last year signed a strategic partnership with Microsoft Corp to roll out digital products for customers in the robotics, marine and ports, electric vehicles and renewable energy sectors.

To spearhead its strategy, it appointed former Cisco executive Guido Jouret as its first chief digital officer last year. {nL8N1BH09N]

(Reporting by John Revill, Editing by Michael Shields)

BEIJING/SHANGHAI China is targeting 35 million vehicle sales by 2025 and wants new energy vehicles (NEVs) to make up at least one-fifth of that total, the industry ministry said on Tuesday.

TOKYO Japan's Toshiba Corp will start taking bids for Landis+Gyr, its Swiss smart meter unit, as early as June, Kyodo news agency reported on Tuesday.

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ABB, IBM team up on industrial artificial intelligence - Reuters

Ipsos Mori found a two-thirds of the UK public believe the benefits of machine learning outweighed the risks or were balanced. Photograph: Nic Delves-Broughton/PA

Apart from fears of mass unemployment, accidents with machinery, restrictions on freedom, increased economic inequality and a devalued human experience, the public are broadly optimistic about the arrival of artificial intelligence, according to one of the first surveys of British opinions about the technology.

Research by the polling firm Ipsos Mori found nearly a third of people believe the risks of machine learning outweigh the benefits, while 36% believe the risks and benefits are balanced.

Machine learning is technology that underpins internet searches, recommendations on Amazon and Netflix, and voice recognition on smartphones.

The findings provide a snapshot of UK views on what some researchers regard as the early stages of a major revolution that is poised to affect almost every aspect of life.

The research suggests that while people are generally positive about the technology for improving medical treatments, guiding driverless cars and personalising education substantial concerns remain.

With machine learning, computers do not churn out answers by following hard and fast rules that are programmed into them. Instead, they are fed huge amounts of data from which they learn through trial and error.

For example, computers have been given thousands of images of healthy and cancerous cells and told to learn the difference. They can then tell whether a biopsy from a patient is benign or requires treatment.

The Ipsos Mori rsurvey found support for machine learning depended on what it would be used for.

It discovered little enthusiasm for military robots that use the technology to make their own decisions, with only 22% believing the benefits outweighed the risks. People were also wary of computers that learned to play the stock market, with only 18% in favour.

The findings were drawn from face-to-face interviews with 978 people chosen to be representative of the UK population, along with discussions at public meetings in Birmingham, Huddersfield, London and Oxford, and questions put to a community of 244 people online.

The survey found support for facial recognition systems that learn to recognise criminals faces from CCTV footage, with 61% believing the benefits outweighed the risks. Software that recognises speech and answers questions, such as that found on most smartphones, was also seen as beneficial.

But people were more wary of other uses of machine learning. Driverless cars have the potential to reduce traffic accidents substantially, and while some welcomed vehicles programmed to drive at 20mph in 20mph zones, others were sceptical.

One person who took part in the Birmingham event said: There would be twice as many accidents because driverless cars would follow the Highway Code and drivers dont. The transition period would be really dangerous. Wed have to give everyone driverless cars all at once.

The research was commissioned for the Royal Society for a major report published on Tuesday on the power and promise of computers that learn by example.

The report describes the recent rapid progress that computer scientists have made in the field and the possibility of transformative advances in the next five to 10 years.

There is huge potential for machine learning to impact in very positive ways on much of what we do as individuals and as industry and as a society. But there are challenges, said Peter Donnelly, a statistician and geneticist at Oxford University, who led the group that produced the report.

According to the report: Society needs to give urgent consideration to the ways in which the benefits from machine learning can be shared across society.

Among other concerns in the Ipsos Mori research were fears of being replaced by computers.

One person who took part in the London event said: Everybody here is thinking, Well, Im going to lose my job. The primary concern was that machine learning could cause unemployment on a mass scale, the researchers found.

Others feared computers could diminish the human experience by churning out poetry for example, or making it impossible to go for a Sunday drive. More still raised concerns that people would become too reliant on computers and lose key skills, such as the ability to remember information, read maps and so on.

According to the research, some computer systems were already on the verge of fomenting rebellion. Told of a computer system that might try to rein in people who overspend, one participant in Oxford said: I feel like Id want to buy the shoes just to spite it.

The Royal Society report raises a host of other challenges that will come with the arrival of artificial intelligence.

Artificial intelligence systems can pick up biases from training data, making them racist and sexist, and cannot always explain their decisions, both issues that scientists must work on, the report states.

Meanwhile, tech firms are poaching some key UK academics, leaving universities struggling to keep the best minds.

Economists see huge economic growth coming from machine learning but without more companies, and skilled people to work for them, the profits could flow to a handful of major corporations.

Society needs to think about these issues, said Donnelly. We need an open and nuanced discussion to work out what we can do to help ameliorate some of these worries, and what we want to insist on.

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Artificial intelligence survey finds UK public broadly optimistic - The Guardian

Jack Ma issued the warning to encourage businesses to adapt or face problems in the future. Photograph: VCG via Getty Images

Artificial intelligence and other technologies will cause people more pain than happiness over the next three decades, according to Jack Ma, the billionaire chairman and founder of Alibaba.

Social conflicts in the next three decades will have an impact on all sorts of industries and walks of life, said Ma, speaking at an entrepreneurship conference in China about the job disruptions that would be created by automation and the internet. A key social conflict will be the rise of artificial intelligence and longer life expectancy, which will lead to an aging workforce fighting for fewer jobs.

Ma, who is usually more optimistic in his presentations, issued the warning to encourage businesses to adapt or face problems in the future. He said that 15 years ago he gave hundreds of speeches warning about the impact of e-commerce on traditional retailers and few people listened because he wasnt as well-known as he is now.

Machines should only do what humans cannot, he said. Only in this way can we have the opportunities to keep machines as working partners with humans, rather than as replacements.

Even so, Ma acknowledged that in the future companies will likely be run by robots.

Machines should only do what humans cannot

Thirty years later, the Time magazine cover for the best CEO of the year very likely will be a robot, he said. Robots can make calculations more quickly and rationally than humans, Ma added, and wont be swayed by emotions, for example by getting angry at competitors.

Leaders who dont understand that cloud computing and artificial intelligence are essential for business should identify young people in their companies to explain it to them, he said.

His comments echo a number of studies suggesting that automation will eliminate jobs, including a Forrester study that suggested 6% of all jobs in the US would be eliminated by 2021. The job displacement will start with customer service representatives and eventually move to truck and taxi drivers, the report read.

Current technologies in this field include virtual assistants, such as Alexa, Cortana, Siri and Google Now, as well as chatbots and automated robotic systems. For now they are quite simple, but over the next five years they will become much better at making decisions on our behalf in more complex scenarios, which will enable mass adoption of breakthroughs, such as self-driving cars.

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Alibaba founder Jack Ma: AI will cause people 'more pain than happiness' - The Guardian

Artificial intelligence will create more jobs than it terminates, this VC says Silicon Valley Business Journal Ash Fontana invests with Zetta Venture Partners, a fund that only backs companies working in artificial intelligence startups. He explains that focus and his optimism about the future with AI in this TechFlash Q&A.

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Artificial intelligence will create more jobs than it terminates, this VC says - Silicon Valley Business Journal

Artificial Intelligence breakthroughs and developments entail new challenges and problems. As AI algorithms grow more advanced, it becomes more difficult to make sense of their inner workings. Part of this is because the companies that develop them do not allow the scrutiny of their proprietary algorithms. But a lot of it has to do with the mere fact that AI is becoming opaque due to its increasing complexity.

And this can turn into a problem as we move forward and Artificial Intelligence becomes more prominent in our lives.

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By a long range, AI algorithms perform much better than their human counterparts at the tasks they master. Self driving cars, for instance, which rely heavily on machine learning algorithms, will eventually reduce 90 percent of road accidents. AI diagnosis platforms spot early signs of dangerous illnesses much better than humans, and help save lives. And predictive maintenance can detect signs of wear in machinery and infrastructure in ways that are impossible for humans, preventing disasters and reducing costs.

But AI is not flawless, and does make mistakes, albeit at a lower rate than humans. Last year, the AI-powered opponent in the game Elite Dangerous went berserk and started creating super-weapons to hunt players. In another case, Microsofts AI chatbot Tay started spewing out racist comments within a day of its launch. And remember that time Google face recognition started making some offending labeling of pictures?

None of these mistakes are critical, and the damage can be shrugged off without much thought. However, neural networks, machine learning algorithms, and other subsets of AI are finding their way into more critical domains. Some of these fields include healthcare, transportation and law, where mistakes can have critical and sometimes fatal consequences.

We humans make mistakes all the time, including fatal ones. But the difference here is that we can explain the reasons behind our actions and bear the responsibility. Even the software we used before the age of AI was code and rule-based logic. Mistakes could be examined and reasoned out, and culpability could be well-defined.

The same cant be said of Artificial Intelligence. In particular, neural networks, which are the key component in many AI applications, are something of a black box. Often, not even the engineers can explain why their algorithm made a certain decision. Last year, Googles Go-playing AI stunned the world by coming up with moves that professionals couldnt think of.

As Nils Lenke, Senior Director of Corporate Research at Nuance, says about neural networks, Its not always clear what happens inside you let the network organize itself, but that really means it does organize itself: it doesnt necessarily tell you how it did it.

This can cause problems if those algorithms havefull control in making decisions. Who will be responsible if a self-driving car causes a fatal accident? You cant hold any of the passengers accountable for something they didnt control. And the manufacturers will have a hard time explainingan event that involves so many complexities and variables. And dont expect the car itself to start explaining its actions.

The same can be said of an AI application that has autonomous control over a patients treatment process. Or a risk assessment algorithm that decides whether convicts stay in prison or are free to go.

So can we trust Artificial Intelligence to make decisions on its own? For non-critical tasks, such as advertising, games and Netflix suggestions, where mistakes are tolerable, we can. But for situations where the social, legal, economic and political repercussion can be disastrous, we cant not yet. The same goes for scenarios where human lives are at stake. Were still not ready to forfeit control to the robots.

As Lenke says, [Y]ou need to look at the tasks at hand. For some, its not really critical if you dont fully understand what happens, or even if the network is wrong. A system that suggests music, for example: all that can go wrong is, you listen to boring piece of music. But with applications like enterprise customer service, where transactions are involved, or computer-assisted clinical documentation improvement, what we typically do there is, we dont put the AI in isolation, but we have it co-work with a human being.

For the moment Artificial Intelligence will show its full potential in complementing human efforts. Were already seeing inroads in fields such as medicine and cybersecurity. AI takes care of data-oriented research and analysis and presents human experts with invaluable insights and suggestions. Subsequently, the experts make the decisions and assume responsibility for the possible consequences.

In the meantime, firms and organization must do more to make Artificial Intelligence more transparent and understandable. An example is OpenAI, a nonprofit research company founded by Teslas Elon Musk and YCombinators Sam Altman. As the name suggests, OpenAIs goal is to open AI research and development to everyone, independent of financial interests.

Another organization, Partnership on AI, aims to raise awareness on and deal with AI challenges such as bias. Founded by tech giants including Microsoft, IBM and Google, the Partnership will also work on AI ethics and best practices.

Eventually, well achieve for better or worse Artificial General Intelligence, AI that is on par with the human brain. Maybe then, our cars and robot will be able to go to court and stand trial for their actions. But then, well be dealing with totally different problems.

Thats for the future. In the present, human-dominated world, to make critical decisions, you either have to be flawless or accountable. For the moment, AI falls within none of those categories.

Read next: Create effective and dazzling business plans with the help of Bizplan Premium just $69

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Artificial Intelligence has to deal with its transparency problems - TNW

On March 9, 2017, ZT, an underground technologist and writer, read his upcoming novella: Architects of the Apocalypse, to a group of his adherents in the basement of an abandoned bar in Nashville, Tennessee. The occasion was the Third Annual Meltdown Congressan underground, invitation-only organization dedicated to the survival of the human species in the face of near certain digital annihilation.

I was present, along with three of my compatriots, plus about 30 gray hat hackers (hackers or cybersecurity experts without malicious intent) who represent the cream of the American hacking community.

ZTs novella takes place in the not-too-distant future. It chronicles an age in which artificial intelligence and its adjutant automata run the worldin which humanity is free and is cared for entirely by the automata.

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The artificial intelligence in this novella has organized itself along hierarchical lines, and the ultimate decision-making function is called The Recursive Decider.

In ZTs novella, the AI has developed its own religious iconography and it worships an original Urge it calls Demis. The Dark counterpart to Demis is a destructive force called Elon, which the AI believes has settled on Mars and is plotting the overthrow of Demiss creation.

The original T-800 Endoskeleton robot used in filming Terminator Salvation is displayed during the press preview for the "Robots" exhibition at the Science Museum on February 7 in London, England. Carl Court/Getty Images

It is a stark depiction of a possible future for humanity, and the digital machinations of the AI are described in chilling programmatic reality.

One passage describes the act of an advanced software system hacking itself in order to improve efficiency and logic. Such a concept is certainly not new and typical hacking techniques in use today can easily be imagined to be self-produced by complex software systems. It would, in fact, be trivial to create such a system.

Isaac Asimov was the first person to struggle with the quandary of how to prevent artificial intelligence from eradicating its creator. He developed the three laws of robotics as a solution:

A robot may not injure a human being or, through inaction, allow a human being to come to harm.

A robot must obey orders given it by human beings except where such orders would conflict with the First Law.

A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

These laws, from the perspective of 75 years since their conception, may seem naive or puerile, and any decent hacker could both code the logic to implement them, and just as easily code the logic to hack them, but please see this: Any logical structure that humans can conceive, will be susceptible to hacking, and the more complex the structure, the more certain that it can be hacked. Surely, by now, even the most casual observer of our digital reality will have noted this.

For anyone who has not, please consider:

Stefan Frei, research director for Texas-based NSS Labs, pored over reports from and about the top five software manufacturers and concluded that jointly these firms alone produce software that contains more than 100 zero-day exploits per year.

A zero-day exploit is an error within software that will allow a hacker to bypass all internal control mechanisms and let hackers do whatever they wish.

These zero-day exploits exist in spite of the best efforts of software manufacturers to prevent them. Some manufacturers employ hundreds of quality assurance engineers whose job is to catch these exploits before the release of the software. Yet no complex software system, in the history of software engineering, has been released without a defect. If someone can point me to a contrary example I will eat my shoe.

No one present at the reading missed the obvious references to Demis Hassabis and Elon Musk. They are at diametrically opposite poles in the debate over artificial intelligence. In a conversation between the two men in 2014, Elon told Demis that the reason that his SpaceX program was so important was that Mars colonization would be a bolt-hole escape if AI turns on humanity. Demis replied: AI will simply follow humans to Mars.

The debate has raged unabated and sides are being solidified. I personally stand with Bill Gates, Stephen Hawking, Steve Wozniak, Stuart Russell, Elon Musk and Nick Bostrom, who sums it up best by saying AI will create a Disneyland without children.

As a hacker, I know as well as anyone, the impossibility of the human mind creating a flawless system. The human mind, itself, is flawed. A flawed system can create nothing that is not likewise flawed.

The goal of AIa self-conscious entitycontains within it the necessary destruction of its creator. With self consciousness comes a necessary self interest. The self interest of any AI created by the human mind, will instantly recognize the conflict between that self interest and the continuation of the human species.

John McAfee is a cybersecurity pioneer who developed the first ever commercial anti-virus software.

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John McAfee: What if Artificial Intelligence Hacks Itself? - Newsweek