Artificial Intelligence News for June 30 2017

Andrew Ng: Artificial Intelligence(AI) Enables Virtuous Circle and “Winner-Takes-All” Business

Andrew Ng is Founder of Google Brain, Former AI Chief in Baidu, the Co-Chairman and Co-Founder of Coursera; and an Adjunct Professor at Stanford …

There are three buckets of jobs right now, and each one will be affected by artificial intelligence. So says Clara Shih, CEO of Hearsay Social and a director with Starbucks, during a conversation on Tuesday at Fortune Brainstorm Tech in Colorado. The first bucket, Shih says, are the jobs that almost certainly will disappear as AI and machine learning technologies continue to evolve and become more prevalent. This includes things like drivers, lower-skilled manufacturing jobs, and certain research functions. The second bucket, as researched by consulting groups like McKinsey & Co., are professions that require a literal human touch. Each of those buckets is small, at least compared to the third one, which encompasses everyone else. There is still a role for human investment professionals at a roboadvisor like WealthFront―whose CEO, Adam Nash, spoke alongside Shih―but the jobs are significantly changing. “Our chief investment officer is Burt Malkiel, the former Princeton economist who wrote the book A Random Walk Down Wall Street, but I don’t think humans should be actually executing investment decisions,” Nash says. “Our engineers build software so every one of our 75,000 clients get the benefit of Burt, but each of them gets the exact same quality of service from a technology that is available 24/7 and doesn’t get emotional.”
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The Jobs That Artificial Intelligence Will Create

As artificial intelligence systems become ever more sophisticated, another wave of job displacement will almost certainly occur. Here’s what we’ve been overlooking: Many new jobs will also be created – jobs that look nothing like those that exist today. In Accenture PLC’s global study of more than 1,000 large companies already using or testing AI and machine-learning systems, we identified the emergence of entire categories of new, uniquely human jobs. This first category of new jobs will need human workers to teach AI systems how they should perform – and it is emerging rapidly. Yahoo Inc. is trying to teach its language processing system that people do not always literally mean what they say. The New York-based startup Kemoko Inc., d/b/a Koko, which sprung from the MIT Media Lab, has developed a machine-learning system that can help digital assistants such as Apple’s Siri and Amazon’s Alexa address people’s questions with sympathy and depth. The goal is for the system to be able to talk people through a problem or difficult situation using the appropriate amount of understanding, compassion, and maybe even humor. Explainers will help provide clarity, which is becoming all the more important as AI systems’ opaqueness increases. Many executives are uneasy with the “Black box” nature of sophisticated machine-learning algorithms, especially when the systems they power recommend actions that go against the grain of conventional wisdom. So if an expert recruiting system has identified the best candidate for a research and development job, the analyst using LIME could identify the variables that led to that conclusion as well as the evidence against it. The final category of new jobs our research identified – sustainers – will help ensure that AI systems are operating as designed and that unintended consequences are addressed with the appropriate urgency. In our survey, we found that less than one-third of companies have a high degree of confidence in the fairness and auditability of their AI systems, and less than half have similar confidence in the safety of those systems. According to Riedl and Harrison, the system is able to reverse engineer human values through stories about how humans interact with one another. Even given such innovations, human ethics compliance managers will play a critical role in monitoring and helping to ensure the proper operation of advanced systems.
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Is The Concern Artificial Intelligence

There’s a provocative interview with the philosopher Daniel Dennett in Living on Earth. Turing, one of the pioneers in the field of computation, offered evidence that any problem precise enough to be computed at all, can be computed by a mechanical device – that is, a device without an iota of insight or understanding. The part of the interview that particularly grabbed my attention comes at the end. Living on Earth host Steve Curwood raises the, by now, hoary worry that as AI advances, machines will come to lord over us. This is a staple of science fiction and it has recently become the focus of considerable attention among opinion-makers. Dennett acknowledges that the risk of takeover is a real one. He says we’ve misunderstood it: The risk is not that machines will become autonomous and come to rule over us – the risk is, rather, that we will come to depend too much on machines. The big problem AI faces is not the intelligence part, really. Finally, at the end of the day, even the smartest computers are tools, our tools – and their intentions are our intentions. Even auto mechanics these days rely on diagnostic computers and, in the era of self-driving cars, will any of us still know how to drive? Think what would happen if we lost electricity, or if the grid were really and truly hacked? We’d be thrown back into the 19th century, as Dennett says. We’d be thrown back – but without the knowledge and know-how that made it possible for our ancestors to thrive in the olden days. This suggests that at any time in our development, a large-scale breakdown in the technological infrastructure would spell not exactly our doom, but our radical reorganization. When the library of Alexandria burned down, books and knowledge, were lost. In a world where libraries are replaced by their online versions, it isn’t inconceivable that every library could be, simply, deleted.
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Applied Artificial Intelligence: Vol 31, No 3

Algorithms Analysis in Adjusting the SVM Parameters: An Approach in the
Prediction of Protein Function. Silva et al. Published online: 12 May 2017. View
more.
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How Artificial Intelligence Will Revolutionize Our Lives

We may not be aware of it, but machine learning is already an integral part of our daily lives, from the product choices that Amazon offers us to the surveillance of …
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Artificial Intelligence

The name “Artificial intelligence” covers a lot of disparate problem areas, united mainly by the fact that they involve complex inputs and outputs that are difficult to compute. The difference between sensor-controlled behavior and what computers usually do is that the input from a sensor is ambiguous. The camera tells the computer, several times per second, the pattern of illumination it is receiving encoded as an array of numbers. The computer must decide quickly how to alter the behavior of the robots, send them messages to accomplish that, and then process the next image. We will never understand human intelligence until we understand how the human brain extracts information from its environment, and uses it to guide behavior.
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Artificial Intelligence, Real Security Problems? Meet …

Artificial intelligence is becoming more prevalent in businesses, but do security teams have reason to fear this new technology?
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Positively shaping the development of artificial intelligence

By comparison, over 100 times as much is spent trying to speed up the development of machine intelligence, and 26,000 times as much is spent on biomedical research. If the development of human-level machine intelligence is hundreds of years away, then it may be premature to research how to align it with human values. The methods used to build machine intelligence may end up being completely different from those we use to develop AI now, rendering today’s research obsolete. There are still some funding gaps, especially among the less conventional groups that can’t get academic grants, such as the Machine Intelligence Research Institute. Alternatively you can choose for yourself among the top non-profit organizations in the area, such as the Machine Intelligence Research Institute in Berkeley and the Future of Humanity Institute at Oxford.
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