Monthly Archives: May 2017

While artificial intelligence continues to become a part of everyday life for consumers, the technology has gathered a pretty impressive collection of critics and fear mongers.

Don't count Jeff Bezos among them. The Amazon founder and CEO paints a fairly rosy picture when it comes to A.I.--and he thinks there should be much more of it.

The comments came at a gala Friday put on by the Internet Association, a Washington, D.C.-based lobbyist group. During a fireside chat with the group's CEO, Michael Beckerman, Bezos said we are currently in the "golden age" of machine learning.

"We are solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades," he said. "Natural language understanding, machine vision problems--it really is an amazing renaissance."

Bezos spoke of a future in which A.I. has application far beyond technology products. "Machine learning and A.I. is a horizontal enabling layer," he said. "It will empower and improve every business, every government organization, every philanthropy. Basically, there's no institution in the world that cannot be improved with machine learning."

That's in stark contrast to some tech leaders, most notably Elon Musk, who have warned about the dangers of the technology. Musk recently presented a futuristic scenario in which even the most benign forms of A.I. could have catastrophic effects on humanity.

"Let's say you create a self-improving A.I. to pick strawberries," Musk told Vanity Fair, "and it gets better and better at picking strawberries and picks more and more and it is self-improving, so all it really wants to do is pick strawberries. So then it would have all the world be strawberry fields. Strawberry fields forever."

While some organizations, like Google, have proposed developing a kill switch to shut down overly aggressive A.I., Musk doesn't believe this is plausible.

"I'm not sure I'd want to be the one holding the kill switch for some super-powered A.I.," he said, "because you'd be the first thing it kills."

Musk's school of thought is shared by Y Combinator president Sam Altman and venture capitalist Peter Thiel, with whom he co-founded OpenAI, a non-profit meant to ensure A.I. is used for good. The three are part of a group of tech elites that have pledged $1 billion dollars toward the company.

Tim Berners-Lee, the inventor of the World Wide Web, recently laid out a scenario in which A.I. that's used in business settings eventually becomes so smart, it runs entire companies and financial institutions on its own--and thus controls entire economies. "You have survival of the fittest going on between these A.I. companies," he said, "until you reach the point where you wonder if it becomes possible to understand how to ensure they are being fair--and how do you describe to a computer what that means, anyway?"

Stephen Hawking has spoken out against A.I. too, saying that he fears it "could spell the end of the human race." Last year, Hawking opened a research center at Cambridge University, meant to nurture ideas for using A.I. to solve world problems--and for regulating its use.

Amazon has leaned more heavily into artificial intelligence in recent years. As Bezos pointed out during his talk, the company is continually improving its website's search feature and product recommendations using machine learning. More visibly, the Echo home assistant relies on A.I. and uses machine learning to improve its capabilities.

The company is also developing drones for delivering goods, which the company hopes will someday fly autonomously. "Those things use a tremendous amount of machine learning, machine vision systems," Bezos said.

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Jeff Bezos and Elon Musk Have Vastly Different Views on Artificial Intelligence - Inc.com

Facebooks billion-plus users speak a plethora of languages, and right now, the social network supports translation of over 45 different tongues. That means that if youre an English speaker confronted with German, or a French speaker seeing Spanish, youll see a link that says See Translation.

But Tuesday, Facebook announced that its machine learning experts have created a neural network that translates language up to nine times faster and more accurately than other current systems that use a standard method to translate text.

The scientists who developed the new system work at the social networks FAIR group, which stands for Facebook A.I. Research.

Neural networks are modeled after the human brain, says Michael Auli, of FAIR, and a researcher behind the new system. One of the problems that a neural network can help solve is translating a sentence from one language to another, like French into English. This network could also be used to do tasks like summarize text, according to a blog item posted on Facebook about the research.

But there are multiple types of neural networks. The standard approach so far has been to use recurrent neural networks to translate text, which look at one word at a time and then predict what the output word in the new language should be. It learns the sentence as it reads it. But the Facebook researchers tapped a different technique, called a convolutional neural network, or CNN, which looks at words in groups instead of one at a time.

It doesnt go left to right, Auli says, of their translator. [It can] look at the data all at the same time. For example, a convolutional neural network translator can look at the first five words of a sentence, while at the same time considering the second through sixth words, meaning the system works in parallel with itself.

Graham Neubig, an assistant professor at Carnegie Mellon Universitys Language Technologies Institute, researches natural language processing and machine translation. He says that this isnt the first time this kind of neural network has been used to translate text, but that this seems to be the best hes ever seen it executed with a convolutional neural network.

What this Facebook paper has basically showedits revisiting convolutional neural networks, but this time theyve actually made it really work very well, he says.

Facebook isnt yet saying how it plans to integrate the new technology with its consumer-facing product yet; thats more the purview of a department there call the applied machine learning group. But in the meantime, theyve released the tech publicly as open-source, so other coders can benefit from it

Thats a point that pleases Neubig. If its fast and accurate, he says, itll be a great additional contribution to the field.

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Facebook created a faster, more accurate translation system using artificial intelligence - Popular Science

For Joseph Qualls, it all started with video games.

That got him messing around with an AI program, and ultimately led to a PhD in electrical and computer engineering from the University of Memphis. Soon after, he started his own company, called RenderMatrix, which focused on using AI to help people make decisions.

Much of the companys work has been with the Defense Department, particularly during the wars in Iraq and Afghanistan, when the military was at the cutting edge in the use of sensors and seeing how AI could be used to help train soldiers to function in a hostile, unfamiliar environment.

Qualls is now a clinical assistant professor and researcher at the University of Idaho's college of engineering, and he hasnt lost any of his fascination with the potential of AI to change many aspects of modern life. While the military has been the leading edge in applying AIwhere machines learn by recognizing patterns, classifying data, and adjusting to mistakes they makethe corporate world is now pushing hard to catch up. The technology has made fewer inroads in education, but Qualls believes its only a matter of time before AI becomes a big part of how children learn.

Its often seen as being a key component of the concept of personalized education, where each student follows a unique mini-curriculum based on his or her particular interests and abilities. AI, the thinking goes, can not only help children zero in on areas where theyre most likely to succeed, but also will, based on data from thousands of other students, help teachers shape the most effective way for individual students to learn.

Smithsonian.com recently talked to Qualls about how AI could profoundly affect education, and also some of the big challenges it faces.

So, how do you see artificial intelligence affecting how kids learn?

People have already heard about personalized medicine. Thats driven by AI. Well, the same sort of thing is going to happen with personalized education. I dont think youre going to see it as much at the university level. But do I see people starting to interact with AI when theyre very young. It could be in the form of a teddy bear that begins to build a profile of you, and that profile can help guide how you learn throughout your life. From the profile, the AI could help build a better educational experience. Thats really where I think this is going to go over the next 10 to 20 years.

You have a very young daughter. How would you foresee AI affecting her education?

Its interesting because people think of them as two completely different fields, but AI and psychology are inherently linked now. Where the AI comes in is that it will start to analyze the psychology of humans. And Ill throw a wrench in here. Psychology is also starting to analyze the psychology of AI. Most the projects I work on now have a full-blown psychology team and theyre asking questions like 'Why did the AI make this decision?'

But getting back to my daughter. What AI would start doing is trying to figure out her psychology profile. Its not static; it will change over time. But as it sees how shes going to change, the AI could make predictions based on data from my daughter, but also from about 10,000 other girls her same age, with the same background. And, it begins to look at things like Are you really an artist or are you more mathematically inclined?

It can be a very complex system. This is really pie-in-the-sky artificial intelligence. Its really about trying to understand who you are as an individual and how you change over time.

More and more AI-based systems will become available over the coming years, giving my daughter faster access to a far superior education than any we ever had. My daughter will be exposed to ideas faster, and at her personalized pace, always keeping her engaged and allowing her to indirectly influence her own education.

What concerns might you have about using AI to personalize education?

The biggest issue facing artificial intelligence right now is the question of 'Why did the AI make a decision?' AI can make mistakes. It can miss the bigger picture. In terms of a student, an AI may decide that a student does not have a mathematical aptitude and never begin exposing that student to higher math concepts. That could pigeonhole them into an area where they might not excel. Interestingly enough, this is a massive problem in traditional education. Students are left behind or are not happy with the outcome after university. Something was lost.

Personalized education will require many different disciplines working together to solve many issues like the one above. The problem we have now in research and academia is the lack of collaborative research concerning AI from multiple fieldsscience, engineering, medical, arts. Truly powerful AI will require all disciplines working together.

So, AI can make mistakes?

It can be wrong. We know humans make mistakes. Were not used to AI making mistakes.

We have a hard enough time telling people why the AI made a certain decision. Now we have to try to explain why AI made a mistake. You really get down to the guts of it. AI is just a probability statistics machine.

Say, it tells me my child has a tendency to be very mathematically oriented, but she also shows an aptitude for drawing. Based on the data it has, the machine applies a weight to certain things about this person. And, we really cant explain why it does what it does. Thats why Im always telling people that we have to build this system in a way that it doesnt box a person in.

If you go back to what we were doing for the military, we were trying to be able to analyze if a person was a threat to a soldierout in the field. Say one person is carrying an AK-47 and another is carrying a rake. Whats the difference in their risk?

That seems pretty simple. But you have to ask deeper questions. Whats the likelihood of the guy carrying the rake becoming a terrorist? You have to start looking at family backgrounds, etc.

So, you still have to ask the question, 'What if the AIs wrong?' Thats the biggest issue facing AI everywhere.

How big a challenge is that?

One of the great engineering challenges now is reverse engineering the human brain. You get in and then you see just how complex the brain is. As engineers, when we look at the mechanics of it, we start to realize that there is no AI system that even comes close to the human brain and what it can do.

Were looking at the human brain and asking why humans make the decisions they do to see if that can help us understand why AI makes a decision based on a probability matrix. And were still no closer.

Actually, what drives reverse engineering of the brain and the personalization of AI is not research in academia, its more the lawyers coming in and asking 'Why is the AI making these decisions?' because they dont want to get sued.

In the past year, most of the projects Ive worked on, weve had one or two lawyers, along with psychologists, on the team. More people are asking questions like 'Whats the ethics behind that?' Another big question that gets asked is 'Whos liable?'

Does that concern you?

The greatest part of AI research now is that people are now asking that question 'Why?' Before, that question relegated to the academic halls of computer science. Now, AI research is branching out to all domains and disciplines. This excites me greatly. The more people involved in AI research and development, the better chance we have at alleviating our concerns and more importantly, our fears.

Getting back to personalized education. How does this affect teachers?

With education, whats going to happen, youre still going to have monitoring. Youre going to have teachers who will be monitoring data. Theyll become more data scientists who understand the AI and can evaluate the data about how students are learning.

Youre going to need someone whos an expert watching the data and watching the student. There will need to be a human in the loop for some time, maybe for at least 20 years. But I could be completely wrong. Technology moves so fast these days.

It really is a fascinating time in the AI world, and I think its only going to accelerate more quickly. Weve gone from programming machines to do things to letting the machines figure out what to do. That changes everything. I certainly understand the concerns that people have about AI. But when people push a lot of those fears, it tends to drive people away. You start to lose research opportunities.

It should be more about pushing a dialogue about how AI is going to change things. What are the issues? And, how are we going to push forward?

Link:

Is Artificial Intelligence the Key to Personalized Education? - Smithsonian

Amazon Alexa, Apple Siri, Google Assistant, Microsoft Cortana and artificial intelligence technology from other developers often serves up responses and content without a perceived reason. Shouldn't users have the ability to ask the AI why?

In an interview with Amazon CEO Jeff Bezos at the recentInternet Associations annual gala in Washington, D.C., Michael Beckerman, president and CEO of the Internet Association, asked him to explain Amazon's approach to artificial intelligence.

It is a renaissance -- it is a golden age, Bezos said. "We are now solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades."

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Bezos said much of the value from machine learning happens beneath the surface in search results, improved product recommendations and improved forecasting for inventory management.

He's correct. About 35.6 million Americans will use a voice-enabled virtual assistant home hub such as Amazon Echo and Google Home at least once monthly in 2017 -- up 128.9% from 2016, according to eMarketer.

One challenge for consumers will be transparency and finding answers to why these devices choose to serve up specific types of content.

Microsoft has already begun to teach systems how toread and answer questions. The group is trying to develop what it calls a "literate" machine.

An article published Monday in Slate in collaboration with Arizona State University and New America explores the way this emerging technology will influence society, posing the question of why users lack the ability to question the machine.

Transparency has become a major initiative across the online advertising industry. In the past few years the advertising industry has seen a major push to improve transparency around the data that makes the decisions for the content people see and hear.

The article makes the point that what the device picks to serve the user should have an obvious relationship to the request. For example, Alexa recently picked a song from 1990s rap artist Sir Mix-a-Lot based on a "diet" of "kid's music, show tunes, Beatles, Rat Pack, and Pink Martini. Why?

Similar to the right to be forgotten or the right to privacy or the right for Amazon Alexa, Google Home or Microsoft Cortana to be allowed to access and use personal data, these devices should inform individuals when using personal data when "automated decision-making, including profiling" is involved in process that data."

In 2016, the European Parliament and the Council of the European Union adopted the General Data Protection Regulation, a data protection act that proposes to bring on major changes that takes effect May 2018 in the EU.

When this legislation kicks in, "A.I. will owe you an explanation every time it uses your personal data to choose a particular recommendation or action." The analysis explains that it will put users in a better position to evaluate and correct the decisions these devices make on the user's behalf.

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Why? Artificial Intelligence To Provide An Explanation - MediaPost Communications

This is the final article in a three-part series on how IBM Watson for Cyber Security can help analysts win the arms race against cybercrime. Be sure to read part 1 and part 2 for the full story.

In just the time since I started writing this series, Watson and the way we work with it has evolved. An IBM employee prototyped a voice interface with his young son, for example. IBM also announced that Watson now works with MaaS360 for improved mobile security.

As it evolves, Watson will help to address a very real problem that has been growing in the security landscape for some years now: the cybersecurity skills gap. The need for experienced security analysts grows every year.

Since Watson is an augmentative technology, the intention is not to replace security operations center (SOC) analysts, but to make them more productive. They will become cognitive analysts in a cognitive SOC. This will create even more time and opportunities for senior IT professionals, who will not need to spend so many hours mentoring junior analysts.

Despite these potential benefits, a couple of questions consistently arise in conversations with peers in the industry: Will analysts skills atrophy if they are not doing the day-to-day digging? Furthermore, will Watson eventually render analysts redundant? What will it mean to be a cognitive analyst?

The fear that moving from one methodology to another, especially one perceived as needing less effort, will cause skills to atrophy is as old as civilization. Take the fear of the Greeks at the move from an oral to a written tradition, for example. The concern, in that case, was that people would lose the ability to accurately memorize large amounts of information.

I recall when the electronic calculator was introduced at school. It caused much concern among parents and teachers who believed it would undermine the capability for mental arithmetic. Indeed, they were right. How many people do you know can memorize a long work, word for word? And you will still get a reaction in shops if you can tell the cashier the total cost of your items before the register adds it up.

The point is that nobody realistically expects anyone to do that kind of thing today. We do not even value it, except as a novelty. There are bigger and different problems we are looking to solve. Trying to use logarithmic tables can be fun, but if you want to model something complex, it would take you centuries to calculate it manually.

The results of modern complex modeling include improved medicine, better sports outcomes, more functional cars and a better understanding of the universe. Now we use our minds to solve more complex problems since we have alleviated the burden of the small tasks.

During the Industrial Revolution, society moved to create different demands and different jobs. That new technology enabled and supported an almost tenfold growth in population in the U.K. in just 150 years. Similarly, I believe that analysts role will evolve rather than disappear. Everyone whose work is touched by the power of this augmentation technology will probably find that there are shifts in the way they approach the work and how they spend their time day to day. But ultimately, they will be shifting to work of higher value.

Watson delivers threat information to the cognitive analyst more readily, having discounted material that is not relevant to the situation. In other words, Watson cuts down waste. Its the difference between searching information in Google and having to go to the library to hunt through loads of paper journals to find exactly what you are looking for.

By focusing cognitive analysts attention on what really matters, Watson will help them learn the patterns of attacks. These patterns may have been lost in the noise previously, when analysts were still trying to identify the trees and could not see the forest.

Watson is a very exciting technology with a great future, and it will transform the way we approach security.

Given the information that QRadar holds about an enterprise, with all its integrations and modules, I envision a future in which Watson provides advice on the best way to configure your network, servers and applications to counter the most current threat landscape. I imagine that Watson might one day write custom policies or rules in other technologies to protect your network. I can also see it providing an educational facility to train security specialists to detect and respond to the most likely threats for the specific industries in which they work.

Technology is great when it can make human lives better. We have this wonderful invention the internet and I want humanity to enjoy all the benefits of it without having to take unreasonable risks. Watson has endless potential to help us achieve exactly that.

Learn More About Watson for Cyber Security

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The Cognitive Analyst and the Artificial Intelligence - Security Intelligence (blog)

News Danny McCance 9 May 2017 11:48am

The Big Four firm has appointed Euan Cameron to the newly created role of UK artificial intelligence (AI) leader just in time for the AI summit, which begins in London today

Camerons appointment comes alongside a raft of appointments within PwCs senior tech leadership.

He will take control of all AI across the firm, to help clients embrace the emerging technology and coordinate PwCs own move towards AI.

He has been a partner since 2007 and brings with him over 20 years experience in consulting, with a focus on the development of corporate strategy, informed by data and analytics.

The core team that Cameron will lead consists of more than 30 specialists working with AI, robotic process automation and machine learning in the UK.

PwC aims to expand this to more than 200 by 2020.

The firm is looking to drive growth in cyber security, data and analytics, tech consulting and fintech.

Emerging technologies are already disrupting how we live and work, and their potential impact can no longer be ignored, Jon Andrews, head of technology and investments at PwC, said.

Artificial intelligence and automation form a key part of our targeted investment in technology, responding to high demand for expertise in these areas from our clients.

Our ambition is that well continue to grow our revenues from technology-related areas including AI, cyber security, data analytics and fintech, Andrews added.

Other appointments include Zubin Randeria, who will lead around 200 cyber security experts in the UK; Neil Hampson, a cyber security practice leader, to lead the data and analytics team; Mark Leaver, who will expand his existing financial services consulting role to concentrate on fintech and Madeleine Thompson, who takes on a new role in technology consulting.

Commenting on the new appointment, Cameron said, To be successful, AI needs to be implemented as part of a broader business transformation strategy.

"We are working with our clients on three main areas: helping businesses to understand the value of AI and the opportunities it holds; supporting their full AI journey from initial projects to large-scale transformation; and providing assurance services to create trust and confidence around AI-enabled business functions."

In February, Karen Bradley, secretary of state for the Department for Culture, Media and Sport announced that the UK can expect to receive more than 17m in funding to boost its artificial intelligence sector.

Opinion 9 December 2016

Features 19 October 2016

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PwC appoints its first artificial intelligence leader - economia