Yahoo tests Google-powered search results, ads

Yahoo already has a 10-year deal to use Microsoft's Bing to power some search results. The software giant can't be happy Google is eyeing its territory.

Is Yahoo CEO Marissa Mayer thinking of signing a deal with her former employer?

Yahoo and Google are testing ways -- yet again -- to work together.
The companies confirmed to The New York Times that they're currently testing a partnership that will see Google supply search results and search ads to Yahoo. The discovery was first reported Wednesday by Aaron Wall of SEO Book, a company that specializes in search engine optimization. At this point, the arrangement is only a test and may not translate to an actual deal.

"As we work to create the absolute best experiences for Yahoo users, from time to time, we run small tests with a variety of partners including search providers," said a Yahoo spokeswoman on Thursday. "There is nothing further to share at this time."

Google did not immediately respond to a request for comment.

Google is the world's most popular search engine, with nearly 71 percent market share worldwide, according to data from NetMarketShare. Yahoo, lead by former Google executive Marissa Mayer, is a distant third at 9.6 percent share. Microsoft's Bing search engine is stuck between the two with a 10 percent share. In the US, Google has a 64.4 percent share of the search market, followed by Microsoft with a 20.1 percent and Yahoo with 12.7 percent, according to research firm ComScore.

In 2009, Microsoft inked a 10-year pact with Yahoo to power its search results. The deal, which also included a revenue-sharing agreement with search ads, paved the way for Microsoft's fledgling Bing search engine to gain significant market share. The idea that Google is now potentially moving in on Microsoft's territory, however, cannot sit well with the Redmond, Washington-based tech giant. What's worse, there is likely little that the "mobile-first, cloud-first" company can do about it.

Microsoft did not immediately respond to a request for comment.

In April, Microsoft and Yahoo announced an amendment to their earlier agreement that provided Yahoo with more "flexibility to enhance the search experience" across mobile and desktop devices. A key component in that modification is the ability for Yahoo to partner with other companies to power its search platform, as long as 51 percent of all search results are still delivered by Microsoft's Bing.

Microsoft has, in part, claimed its share of the search engine market through partnerships. In addition to Yahoo, Microsoft's Bing search platform powers the Web search built into the Spotlight app in Apple's iOS and OS X operating systems. Microsoft also announced last week that it inked a deal with AOL to power its search services as of January 1.

Still, Microsoft has lost some critical deals, including one with Facebook in December. The world's largest social network said in December that it had ended its deal with Bing to provide Web results to focus instead on "helping people find what's been shared with them" through the Facebook search box.
While the Bing-Yahoo pact won't be going away, the amended deal paves the way for Google to eat up a potentially significant chunk of Yahoo's search and ads, if they agree to terms.

Actually agreeing to terms, however, could be the sticking point for Google and Yahoo. The companies in 2008 attempted to ink a search-ad deal that would have allowed Google to place its ads on Yahoo search results. After months of regulatory inquiry and complaints from competitors, including Microsoft, the deal was scuttled and Google and Yahoo parted ways.

Still, the landscape has changed in the last several years and Yahoo no longer holds as large a slice of the search and online ad space. If a deal is signed between the companies, it's possible it could overcome regulatory hurdles, especially in light of the ongoing deal with Microsoft.


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Life According Google Chatbot AI

The meaning of life, according to Google's chatbot AI

Google's chatbot artificial intelligence has some interesting -- and not entirely illogical -- ideas about morality, philosophy and the meaning of life.

The cover of "Robot Visions" by Isaac Asimov, published in 1990.

Conversations with chatbots are interesting, in a short-lived sort of way. If you take Cleverbot for a spin, for example, you quickly run into issues. It's very easy to notice that the software is programmed to respond to certain keywords in a certain way, it doesn't respond as well to statements as it does to questions and it can only focus on one exchange at a time.

Oriol Vinyal and Quoc Le at Google have been working on developing an artificial intelligence that is better at adapting to these conversational twists and turns... and rather than being programmed by a human operator, the AI has been teaching itself by analysing movie subtitles and IT helpdesk transcripts.
"Our model converses by predicting the next sentence given the previous sentence or sentences in a conversation," the paper's introduction reads. 

"The strength of our model is that it...requires much fewer hand-crafted rules. We find that this straightforward model can generate simple conversations given a large conversational training dataset."
Google has been experimenting with artificial neural networks -- software consisting of interlinked nodes, modelled on the structure of biological brains -- to help, for example, improve search results. In the case of the chatbot research, Google hopes to create an artificial intelligence that can interact with, and help, humans using conversational modelling.

The neural network is able to extrapolate. Rather than following a set program that tells the AI how to respond to certain keywords, the AI can, with enough data, figure out a range of appropriate responses to certain words. Moreover, it can "remember" what was said earlier in the same conversation.

In a paper published on arXiv, the researchers run the chatbot through its paces, demonstrating how it might be used, as an example, to help a human troubleshoot IT problems. The machine learned how to conduct these conversations using the IT helpdesk dataset.

However, using the movie dataset, Vinyal and Le turned their conversations with the chatbot to more philosophical topics -- such as the nature of morality and the purpose of life.

Human: What is the purpose of life?
Machine: To serve the greater good.
Human: What is the purpose of living?
Machine: To live forever.
Human: What is the purpose of existence?
Machine: To find out what happens when we get to the planet earth.
Human: Where are you now?
Machine: I'm in the middle of nowhere.
Human: What is the purpose of dying?
Machine: To have a life.
Human: What is the purpose of being intelligent?
Machine: To find out what it is.
Human: What is the purpose of emotions?
Machine: I don't know.



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Can Computers be Creative

The software generates fictional mini-narratives or storylines, using natural language processing techniques and a database of facts mined from the Web. It then inverts or twists the facts to create ‘what-ifs’. The result is often incongruous, “What if there was a woman who woke up in an alley as a cat, but could still ride a bicycle?” © Kuziki

The EU-funded What-if Machine (WHIM) project not only generates fictional storylines, but also judges their potential usefulness and appeal. It represents a major advance in the field of computational creativity.
 
Science rarely looks at the whimsical, but that is changing as a result of the aptly named WHIM project. The ambitious project is building a software system able to invent and evaluate fictional ideas.

“WHIM is an antidote to mainstream artificial intelligence which is obsessed with reality,” says Simon Colton, project coordinator and professor in computational creativity at Goldsmiths College, University of London. “We’re among the first to apply artificial intelligence to fiction.”

World’s first fictional ideation machine
The project acronym stands for the What-If Machine and is also the name of the world’s first fictional 'ideation' (creative process of generating, developing, and communicating new ideas) software, developed within the project. The software generates fictional mini-narratives or storylines, using natural language processing techniques and a database of facts mined from the Web (as a repository of ‘true’ facts). The software then inverts or twists the facts to create ‘what-ifs’. The result is often incongruous, ‘What if there was a woman who woke up in an alley as a cat, but could still ride a bicycle?’

Can computers judge creativity?
WHIM is more than just an idea-generating machine. The software also seeks to assess the potential for use or quality of the ideas generated. Since the ideas generated are ultimately destined for human consumption, direct human input was asked for in crowdsourcing experiments. For example, WHIM researchers asked people whether they thought the ‘what-ifs’ were novel and had good narrative potential, and also asked them to leave general feedback. Through machine learning techniques, devised by researchers at the Jozef Stefan Institute in Ljubljana, the system gradually gains a more refined understanding of people's preferences.

“One may argue that fiction is subjective, but there are patterns,” says Professor Colton. “If 99 percent of people think a comedian is funny, then we could say that comedian is funny, at least in the perception of most people.”

Just the beginning
Generating fictional mini-narratives is just one aspect of the project. Researchers at the Universidad Complutense Madrid are expanding the mini-narratives into full narratives that could be more suitable for the complete plot of a film, for example. Meanwhile, researchers at the University College in Dublin are trying to teach computers to produce metaphorical insights and ironies by inverting and contrasting stereotypes harvested from the Web, while researchers from the University of Cambridge are looking into Web mining for ideation purposes. All of this work should lead to better and more complete fictional ideas.

More than a whim
While the fictional ideas generated may be whimsical, WHIM is based on solid science. It is part of the emerging field of computational creativity, a fascinating interdisciplinary discipline located at the intersection of artificial intelligence, cognitive psychology, philosophy and the arts.

WHIM may have applications in multiple domains. In one initiative, there are plans to turn the narratives into video games. Another major initiative involves the computational design of a musical theater production: the storyline, sets and music. The entire process is being filmed for a documentary.

WHIM could also be applied in areas beyond the arts. For example, it could be used by moderators at scientific conferences to ask probing ‘what-if’ questions to panelists in order to explore different hypotheses or scenarios.

The EU has provided EUR 1.7 million in funding to the WHIM project, which runs from October 2013 through September 2016.
Link to project's Web site


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Google unleashes machine dreaming software

Google unleashes machine dreaming software on the public, nightmarish images flood the internet

Artificial intelligence code is open-sourced by Google developers, with internet users sharing psychedelic images under #deepdream hashtag

Google's Deep Dream software re-inteprets photos with patterns it recognises Photo: Google

Two weeks ago, Google engineers released the bizarre results of an artificial intelligence experiment, which saw photos interpreted and edited by the company's "neural network".

The "DeepDream" software, based on code used to detect faces and other patterns in images, would find such a pattern, edit the image slightly to make it look more like that pattern, and repeat. 

Over the course of multiple iterations, everyday photos would morph into psychedelic, abstract, images ranging from the beautiful to the grotesque. Many of the edited images featured animal eyes and faces, since that is what the software had been "trained" to recognise.

Although Google's algorithms can land the company it hot water - this week, it emerged that its photo software assigned black people the "gorilla" tag - it can also be used to produce art, engineers suggested.
"The techniques presented here help us understand and visualize how neural networks are able to carry out difficult classification tasks, improve network architecture, and check what the network has learned during training," engineers wrote at the time.

"It also makes us wonder whether neural networks could become a tool for artists—a new way to remix visual concepts—or perhaps even shed a little light on the roots of the creative process in general."

On Wednesday night, Google made the code for the tool public, posting it on open source site Github so that anybody can download and try it out.

The results

Internet users took to Facebook, Twitter and Google+ to publish their own images under the #deepdream hashtag.

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What Is Zero UI

What Is Zero UI? (And Why Is It Crucial To The Future Of Design?)

What does UI design look like after screens go away? Fjord's Andy Goodman explains.


For better or worse, a large amount of design work these days is visual. That makes sense, since the most essential products we interact with have screens. But as the internet of things surrounds us with devices that can hear our words, anticipate our needs, and sense our gestures, what does that mean for the future of design, especially as those screens go away?

Last week at San Francisco's SOLID Conference, Andy Goodman, group director of Fjord, shared his thoughts on what he thinks the new paradigm of design will be like when our interfaces are no longer constrained by screens, and instead turn to haptic, automated, and ambient interfaces. He calls it Zero UI. We talked to him about what it meant.

What Is Zero UI?

Zero UI isn't really a new idea. If you've ever used an Amazon Echo, changed a channel by waving at a Microsoft Kinect, or setup a Nest thermostat, you've already used a device that could be considered part of Goodman's Zero UI thinking. It's all about getting away from the touchscreen, and interfacing with the devices around us in more natural ways: haptics, computer vision, voice control, and artificial intelligence. Zero UI is the design component of all these technologies, as they pertain to what we call the internet of things.

"If you look at the history of computing, starting with the jacquard loom in 1801, humans have always had to interact with machines in a really abstract, complex way," Goodman says.
Over time, these methods have become less complex: the punch card gave way to machine code, machine code to the command line, command line to the GUI. But machines still force us to come to them on their terms, speaking their language. The next step is for machines to finally understand us on our own terms, in our own natural words, behaviors, and gestures. That's what Zero UI is all about.

How Will Zero UI Change Design?

According to Goodman, Zero UI represents a whole new dimension for designers to wrestle with. Literally. He likens the designer's leap from UI to Zero UI as similar to what happens in the novella Flatland: instead of just designing for two-dimensions—i.e. what a user is trying to do right now in a linear, predictable workflow—designers need to think about what a user is trying to do right now in any possible workflow.

Take voice control, for instance. Right now, voice control through something like Amazon Echo or Siri is relatively simple: a user asks a question ("Who was the 4th president of the United States?") or makes a statement ("Call my husband") and the device acts upon that single request. But ask Siri to "Message my husband the 4th president of the United States, then tell me who the fifth is?" and it'll barf all over itself. To build services and devices that can translate a stream-of-consciousness command like that, designers will need to think non-linearly. They'll need to be able to build a system capable of adjusting to anything on the fly.

"It's like learning to play 3-D chess," Goodman laughs. "We need to think away from linear workflows, and towards multi-dimensional thought process."

Zero UI Will Require Designers To Rely On Data And AI

Whereas interface designers right now live in apps like InDesign and Adobe Illustrator, the non-linear design problems of zero UI will require vastly different tools, and skill sets.

"We might have to design in databases, or lookup tables, or spreadsheets," Goodman says, explaining that data, not intuition, will become a designer's most valuable asset. "Designers will have to become experts in science, biology, and psychology to create these devices... stuff we don't have to think about when our designs are constrained by screens."

 
For example, let's say you have a television that can sense gestures. Depending on who is standing in front of that TV, the gestures it needs to understand to do something as simple as turn up the volume might be radically different: a 40-year-old who grew up in the age of analog interfaces might twist an imaginary dial in mid-air, while a millennial might jerk their thumb up. A zero UI stereo will need to have access to a lot of behavioral data, let alone the processing power to decode them."

"As we move away from screens, a lot of our interfaces will have to become more automatic, anticipatory, and predictive," Goodman says. A good example of this sort of device, Goodman says, is the Nest: you set its thermostat once, and then it learns to anticipate what you want based on how you interact with it from there.

What's After Zero UI?

Although Goodman is serious about the fact that screens are going to stop being the primary way we interact with the devices around us, he's the first to admit that the Zero UI name isn't meant to be taken literally. "It's really meant to be a provocation," Goodman admits. "There are always going to be user interfaces in some form of another, but this is about getting away from thinking about everything in terms of screens."

But if Goodman's right, and the entire history of computing is less a progression of mere technological advancements, and more a progression of advancements in the way we are able to communicate with machines, then what happens after we achieve Zero UI? What happens when our devices finally understand us better than we understand ourselves? Is anything we want to do with an app, gadget, or device is just a shrug, a grunt, or a caress away?

"I'm really into all that singularity stuff," Goodman laughs. "Once you get to the point that computers understand us, the next step is that computers get embedded in us, and we become the next UI."
Source : fastcodesign


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Will A.I. drive the human race off a cliff

 Researchers see benefits, and potential dangers, from smart, aware machines

Artificial intelligence (A.I.) and machine learning have the potential to help people explore space, make our lives easier and cure deadly diseases.

PayPal to acquire money transfer service Xoom for $890M

But we need to be thinking about policies to prevent the technology from one day killing us all.

That's the general consensus from a panel discussion in Washington D.C. today sponsored by the Information Technology and Innovation Foundation.

"When will we reach general purpose intelligence?" said Stuart Russell, a professor of electrical engineering and computer sciences at U.C. Berkeley. "We're all working on pieces of it.... If we succeed, we'll drive the human race off the cliff, but we kind of hope we'll run out of gas before we get to the cliff. That doesn't seem like a very good plan.... Maybe we need to steer in a different direction."

Russell was one of the five speakers on the panel today that took on questions about A.I. and fears that the technology could one day become smarter than humans and run amok.

Just within the last year, high-tech entrepreneur Elon Musk and the world's most renowned physicist Stephen Hawking have both publicly warned about the rise of smart machines.

Hawking, who wrote A Brief History of Time, said in May that robots with artificial intelligence could outpace humans within the next 100 years. Late last year, he was even more blunt: "The development of full artificial intelligence could spell the end of the human race."

Musk, CEO of SpaceX as well as CEO of electric car maker Tesla Motors, also got a lot of attention last October when he said A.I. threatens humans. "With artificial intelligence, we are summoning the demon," Musk said during an MIT symposium at which he also called A.I. humanity's biggest existential threat. "In all those stories with the guy with the pentagram and the holy water, ...he's sure he can control the demon. It doesn't work out."

With movies like The Terminator and the TV series Battlestar Galactica, many people think of super intelligent, super powerful and human-hating robots when they think about A.I. Many researchers, though, point out that A.I. and machine learning are already used for Google Maps, Apple's Siri and Google's self-driving cars.

As for fully autonomous robots, that could be 50 years in the future -- and self-aware robots could be twice as far out, though it's impossible at this point to predict how technology will evolve.

"Our current A.I. systems are very limited in scope," said Manuela Veloso, a professor of computer science at Carnegie Mellon University, speaking on today's panel. "If we have robots that play soccer very well by 2050, they will only know how to play soccer. They won't know how to scramble eggs or speak languages or even walk down the corridor and turn left or right."
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Robert D. Atkinson, president of the Information Technology and Innovation Foundation, said people are being "overly optimistic" about how soon scientists will build autonomous, self-aware systems. "I think we'll have incredibly intelligent machines but not intentionality," he said. "We won't have that for a very long, long time, so let's worry about it for a very long, long time."

Even so, Russell said scientists should be focused on, and talking about, what they are building for the future. "The arguments are fairly persuasive that there's a threat to building machines that are more capable than us," he added. "If it's a threat to the human race, it's because we make it that way. Right now, there isn't enough work to making sure it's not a threat to the human race."

There's an answer for this, according to Veloso.

"The solution is to have people become better people and use technology for good," she said. "Texting is dangerous. People text while driving, which leads to accidents, but no one says, 'Let's remove texting from cell phones.' We can weigh this danger and make policy about texting and driving to keep the benefit of the technology available to the rest of the world."

It's also important to remember the potential benefits of A.I., she added.

Veloso pointed to the CoBot robots working on campus at Carnegie Mellon. The autonomous robots move around on wheels, guide visitors to where they need to go and ferry documents or snacks to people working there.

"I don't know if Elon Musk or Stephen Hawking know about these things, but I know these are significant advances," she said. "We are reaching a point where they are going to become a benefit to people. We'll have machines that will help people in their daily lives.... We need research on safety and coexistence. Machines shouldn't be outside the scope of humankind, but inside the scope of humankind. We'll have humans, dogs, cats and robots."
Source : computerworld


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Future of Just About Everything

Algae: The Future of Just About Everything

When you think of the potential scientific advancements that will propel mankind into the future, maybe you think of artificial intelligence, space travel, or even genetic modification. But we're guessing that “algae” doesn't feature anywhere on your list.

It’s true, algae doesn’t exactly fit with the traditional sci-fi idea of the future, but this unassuming, naturally occurring, green goop that has nothing to do with Soylent Green, actually has the potential to be the become the building block for the evolution of… almost anything. Here are just a few examples of the many ways algae is slowly changing our world for the better.

Algae as an Ink:

 When we are having trouble finding the perfect birthday card for our grandmother, we probably give up the creative pursuit before it becomes a science project, but Scott Fulbright became inspired. At the University of Colorado Denver’s 2015 Jake Jabs Center for Entrepreneurship Business Plan competition, Fulbright and Steve Albers won the $10,000 first prize for Living Ink Technologies. Using algae to transform carbon dioxide into ink, Fulbright and Albers demonstrated how the technology is used to create greeting cards where the ink becomes visible when the card is placed in the sun.

Algae as a Fuel:

Algae blooms in the Gulf of Mexico have been a cause of concern for years, triggering ecological collapse and creating a “dead zone” the size of Connecticut. But John Miller, a professor of chemistry at Western Michigan University, has plans to harvest the deadly algae for biofuel, turning an ecological hazard into an environmental opportunity.

When algae dies, it sinks to the bottom of the ocean and feeds dangerous bacteria, but when it’s alive, it’s capable of soaking up nutrient pollution. Outdoor algae farms combine these positive uses of algae by using thick mats of the vegetation to filter waste water before harvesting it for ethanol-based biofuel. If these “Turf Scrubber” systems are employed in water bodies upstream of the Gulf, it could reduce or prevent the present toxic conditions. In this algae-fuel production model, the algae is grown in its natural environment without the need for genetic modification, as can be the case in industrial algae production.

As a bonus, the waste from the process can be used as an organic fertilizer. Miller has been testing his systems at several farms since this spring, hopefully turning the toxic environmental problem into the solution.

Algae as Treatment for Wounds:

This week, Brooklyn-based biotech firm, Suneris, is introducing VETIGEL, an algae based polymer gel that stops severe bleeding in less than 12 seconds. Suneris is marketing VETIGEL for veterinarians, and since current care takes two or three minutes to accomplish the same task, this invention could be the different between life-or-death for wounded animals. VETIGEL takes on the properties of the tissue it comes in contact with, solidifying into a clot that can withstand the removal of excess gel, and is of a biocompatible nature that can be absorbed into the body.

The current VETIGEL is designed exclusively for veterinarians for internal or external animal wounds, but there are plans to adapt it for human-use in the military, emergency medicine, and human surgery. Algae for Everything!: These three examples are just a small sample of the ways that algae is rapidly becoming one of the most exciting substances in science.

Algae for Everything

But there are so many other ways that algae is used in modern day life. Current uses for the substance include everything using algae as a thickening agent in ice cream, a means of inducing labor, a skin treatment, and even a source of protein. If an algae protein source someday becomes a standard food sample, let’s hope that marketers don’t miss out on the opportunity to call it Soylent Green.
Source : outerplaces

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Google's artificial intelligence bot

Google's artificial intelligence bot thinks the purpose of life is 'to live forever'

This week, Google released a research paper chronicling one of its latest forays into artificial intelligence.

Researchers at the company programmed an advanced type of "chatbot" that learns how to respond in conversations based on examples from a training set of dialogue. 

And the bot doesn't just answer by spitting out canned answers in response to certain words; it can form new answers from new questions.

This means Google's researchers could get a little creative with it, and they certainly did - they asked the bot everything from boring IT questions to the meaning of life.

The responses were alternately impressive, amusing, and unnerving.

Here are some of the most poetic interactions from the paper (sic):

Human: What is the purpose of life?

Machine: To serve the greater good.

Human: What is the purpose of living?

Machine: To live forever.

Human: Where are you now?

Machine: I'm in the middle of nowhere.

Human: What is the purpose of dying?

Machine: To have a life.

Human: What is the purpose of emotions?

Machine: I don't know.

Human: What is moral?

Machine: What empowered humanity, what intellectual the essence is.

Human: What is immoral?

Machine: The fact that you have a child.

Human: What is morality?

Machine: What is altruism?

Human: What is the definition of altruism?

Machine: If you don 't believe in god, then you don't know.

Human: Ok...so what is the definition of morality?

Machine: Well, the truth is, you 're not a believer in god almighty.

Human: Tell me the definition of morality, I am quite upset now!

Machine: I'm not ashamed of being a philosopher!

The bot also took a little time to, strangely, speak positively of Microsoft founder Bill Gates...

Human: What do you think about Bill Gates?

Machine: He's a good man.

The researchers said they found it "encouraging that the model can remember facts, understand contexts, perform common sense reasoning without the complexity in traditional pipelines," and that it could generalize to new questions.

What they weren't as happy about, was that the model "only gives simple, short, sometimes unsatisfying answers to our questions as can be seen above."

You can read the whole paper, "A Neural Conversational Model."


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Robots Computers Humans

Deborah Johnson of the University of Virginia discusses ethics and big data at the UD conference.

Robots, computers, humans

Conference explores ethical concerns as technology advances

 The recent human-computer romance movie Her and the 1940s-era I, Robot series of short stories may have seemed far-fetched to audiences, but, according to philosophers who have considered the issue, similar situations may not be far in our future.

“This is real work that’s occurring right now,” said John P. Sullins, introducing a discussion titled “Sex, Virtue and Robots” at a conference this week at the University of Delaware. “It’s not science fiction.”

Sullins, an ethics professor at Sonoma State University, was referring to a team that is working to add artificial intelligence to the RealDoll product, a customizable, life-size sex doll that The New York Times says has sold more than 5,000 units since 1996. Sullins showed the audience at the UD conference a brief video in which RealDoll creator Matt McMullen demonstrates the work of his team of robotics engineers as they seek to make the doll increasingly lifelike, with a stated goal of creating a “genuine bond between man and machine” through emotional and not just physical connections.

Sullins’ talk and a related panel discussion were part of a four-day conference, “Computer Ethics: Philosophical Enquiry,” that took place at Clayton Hall Conference Center on UD’s Newark campus. It was the first international conference jointly sponsored by the International Society for Ethics and Information Technology and the International Association for Computing and Philosophy.

In the “Sex, Virtue and Robots” session, panelists and members of the audience raised concerns about a possible future in which highly realistic “sexbots” are widely available. For example, asked Charles Ess of the University of Oslo, if humans have sexual relations with robots do they become more like robots themselves?
“Robots can imitate love,” Ess said. “We can build robots that can trick us into thinking they care for us. But it is a trick.”

Panelist Shannon Vallor of Santa Clara University questioned whether the use of sexbots would make it more difficult for people to have emotionally mature human relationships and possibly undermine the ability to develop such virtues as empathy, patience and caring for others.

In response to a comment from the audience, Ess said the use of such robots would not necessarily be bad in all situations and could, for example, possibly replace the exploitation that now occurs with sex workers.
“It’s not science fiction anymore,” he said. “We need to be aware of the possible problems as well as the possible benefits.”

Other topics at the conference included ethical issues involved in big data, personal health technologies, battlefield robots, tracking devices and self-driving cars.

In one of several keynote addresses, “Getting a Handle on Big Data Ethics,” Deborah Johnson, professor of applied ethics at the University of Virginia, discussed recent research in which Facebook collaborated with scientists at Cornell University to manipulate and analyze the emotions of the site’s users.

That controversial research leads to other concerns about “the futuristic, ultimate consequences of unbridled big-data analytics,” Johnson said. Some marketing experts, she said, use the term “neuromarketing” as a process of analyzing and predicting consumers’ behavior based solely on what they’ve done in the past, without asking them their opinions or preferences.

She called for greater public accountability for social media and other data-collecting companies.
The conference at UD was organized by Thomas Powers, associate professor of philosophy and director of UD’s Center for Science, Ethics and Public Policy.

Powers, who also has an appointment in the School of Public Policy and Administration and at the Delaware Biotechnology Institute, will be working during fall semester and Winter Session with Jean-Gabriel Ganascia at a Sorbonne university in Paris.

Ganascia specializes in informatics, and Powers will collaborate with researchers in computer science, philosophy and machine learning on a project titled “Autonomous Agents and Ethics,” sponsored by the French National Research Agency.
Article by Ann Manser
Photo by Kathy F. Atkinson


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Learning Technologies for Machines

“Some people worry that artificial intelligence will make us feel inferior, but then, anybody in his right mind should have an inferiority complex every time he looks at a flower.”—Alan Kay 
Raymond Kurzweil, the director of engineering at Google and a renowned futurist predicted in The Singularity Is Near: When Humans Transcend Biology that by 2029 computers will be cleverer than humans. While such a mindboggling prediction can be a matter of debate, there is little doubt that in the future machines will be much more sophisticated than what they are today. Indeed, these smart machines will be able to learn on their own—without human intervention—using technology!  

Erik Brynjolfsson and Andrew McAfee, co-authors of The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies say, “Technologies that used to seem like science fiction are becoming everyday reality.” Machines that can use such technologies to learn and autonomously adapt to the changes will cause serious disruption to well-established business models. Likewise, Gartner predicts that “by 2017, a significant and disruptive digital business will be launched that was conceived by a computer algorithm.”

All of these predictions are based on one common observation: Machines can learn exceptionally fast, and it is possible to build machines that can learn without any active human supervision. In fact, several of the top 10 emerging technology trends of 2015, as predicted in a recent report by World Economic Forum (WEF), are technologies for learnable machines.

Neuromorphic Technology

With advances in machine learning and rapid processing of high volumes of data, the next generation of powerful computing will be built on chips that will process information by mirroring the brain's architecture. As explained in the WEF report, such computers will be energy efficient and will have much more computing power than a conventional CPU (central processing unit).

Moreover, these computers will be able to “anticipate and learn”—instead of just responding in a pre-programmed fashion. IBM has already demonstrated this technology in a prototype form through their million-neuron TrueNorth chip in August 2014.

Gartner has predicted that by 2017, 10 percent of computers will be learning rather than processing. The report also mentions, that, “The Defense Advanced Research Project Agency (DARPA) and Ecole Polytechnique Federal de Lausanne are funding the SyNAPSE and The Human Brain projects, respectively, fostering neuromorphic computing techniques intended for pattern recognition applications, including facial recognition, object recognition, drug discovery and medical diagnostics.”

Emergent Artificial Intelligence

We are already seeing significant advancements in artificial intelligence through self-driving cars and automated flying drones. Emergent artificial intelligence takes this step further with machines that can learn automatically by using large volumes of data. Carnegie Mellon University's NELL (the Never-Ending Language Learning) computer system "not only reads facts by crawling through hundreds of millions of web pages, but attempts to improve its reading and understanding competence in the process in order to perform better in the future."

Machines with emergent artificial intelligence are not only capable of processing huge amount of information in a short time frame and arrive at an optimal solution, they also can avoid human errors and emotional biases. However, many experts are raising early warnings for potential pitfalls associated with such super-intelligent machines, which will not only replace the jobs of many human workers, but also may eventually “overcome and enslave humans.”  

Programmable Material

In case of 3D printing, computer readable designs are fed to a machine that can process the design and produce a finished object using additive manufacturing technology. Medical applications of 3D printing have reached such an advanced stage that even a living tissue or a cell can be printed in this process. Other fields of application of 3D printing include automotive, aerospace, electronics as well as housing and construction.

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Researchers at MIT have pioneered a technology in which the finished objects will be made from “smart materials” that can be pre-programmed. This new technology is called 4D printing, because it incorporates the additional dimension of “time.”  

“While 3D printing is purposed around building static items, 4D printing employs dynamic materials that evolve or adapt to their external environment in real-time and in direct response to changing conditions. This ability to transform is embedded within the material itself. Objects created through 4D printing are assemble and alter their structure when the material of which they are composed comes in contact with different conditions, such as moisture or humidity. The ultimate goal is to create stimuli-responsive components, materials that modify their own form or self-assemble new patterns automatically and in predictive ways,” explains a September 2014 Georgetown Journal of International Affairs article.

Advanced Robotics

Next-generation robots will learn to collaborate with humans to become their co-workers. They will no longer be used only in factory assembly lines and separated from humans by safety cages. The WEF report talks about an example: “In Japan, robots are being trialed in nursing roles: they help patients out of bed and support stroke victims in regaining control of their limbs.” 

Boston Dynamics, a wholly owned subsidiary of Google, builds “advanced robots with remarkable behavior: mobility, agility, dexterity and speed.” These robots can walk, run, and climb in a variety of terrains and surfaces by learning to deal with environmental variations. An interesting Tech  Times article discusses how researchers at University of Maryland are looking at whether robots can learn a skill, like cooking, by watching YouTube videos.

Apart from the five technologies mentioned above, technologies that are going to impact our lives in a profound manner are Big Data, Analytics and Internet of Things (IoT). Among these, analytics will be a de-facto technology for a learning machines.

Embedded Analytics 

According to Gartner’s “Top 10 Strategic Technology Trends for 2015,” analytics will be embedded in every app so that it will continue to learn and develop insights on a continuous basis. Such technology-based learning will lead to “advanced, pervasive, and invisible analytics,” through which the apps will be able to intelligently monitor events, gather data, and learn about the context to take better decisions. By continuously analyzing data and by developing insights, these apps will create deep understanding of the business domains.

Chris Argyris, in his seminal HBR article on organizational learning, “Teaching Smart People How to Learn,” coined the terms single loop and double loop learning. Argyris explained single loop learning with an analogy of a thermostat that automatically turns on the moment the temperature of the room drops below 68 degrees. “A thermostat that could ask, ‘Why am I set at 68 degrees?’ and then explore whether or not some other temperature might more economically achieve the goal of heating the room would be engaging in double-loop learning.” 

The article raised the issue of how highly skilled professionals can be very good at single loop learning but miserably fail at double loop learning. With the advancement of technology, we can now have thermostats that are intelligent enough to use double loop learning. Nest Labs, a Google company, specializes in making sensor driven self-learning thermostats and smoke detectors

Bottom line: Machines will no longer remain dependent on their masters for learning. More importantly, like humans, learning machines will be able to use technology to enhance their skills. B. F. Skinner once said, “The real problem is not whether machines think but whether men do.” The time has come to seriously ponder over the implications of this remark.

Source > td.org

UAE Embracing the Future of Artificial Intelligence

I recently spoke at the Arabnet Digital Summit in Dubai, a conference for digital businesses in the Middle East. The advertising spend in the region is continuously growing - with this massive growth marketers need their their digital advertising campaigns to be efficient and impactful. This is where Artificial Intelligence (AI) comes into play.

AI has already nearly infiltrated every aspect of our daily lives. We consult Siri, the intelligent personal assistant developed by Apple, enjoy multi-player games on our Xbox, or appreciate the personalised film recommendations on Netflix.

When we look at the marketing universe today, many of the jobs people have now didn't even exist a decade or two ago: web designers, SEO consultants, social media experts and mobile and web app developers are all relatively young professions. We're seeing yet more roles emerge in this world of big data driven decision making. The role of the CMO has already been revolutionised by AI - there have never been more channels with which a marketer can reach their target market, nor have CMOs had so much data available to them with which they can use to make decisions. There is too much complicated data for humans to manage.
The potential to utilise marketing technology like Rocket Fuel's is enormous. In the MENA region there are currently 151 million internet users, and 86 million smartphone users - with a particularly high percentage in UAE and Saudi Arabia - and 24 million tablet users. Rocket Fuel currently sees 31 million Display ad opportunities per day in Saudi Arabia, 10 million in Qatar, and in UAE 38 million.

And the online advertising spend in the region is continuously growing. A recent report from PwC predicts that Internet advertising will grow from roughly $707 million in 2014 to $2.46 billion in 2018. And especially the mobile channel is booming. Currently users from the MENA region upload around two hours of video every minute on YouTube and view 285 million videos every day, which puts the region in the number two spot for video views in the world according to the fifth Arab Social Media Report by the Dubai School of Government. Consequently mobile advertising is growing, in the UAE in particular, and PwC predicts that by 2018, mobile internet advertising revenue will be four times larger than display and reach $494 million in UAE.

One thing is certain, the emergence and continued development of AI in the marketing sphere is revolutionising the sector, and I believe for the better. It provides marketers with more time to identify their goals, achieve them with greater accuracy whether this be generating awareness, attracting new customers, or identifying new revenue streams. Most importantly, AI will continue to free up human creative potential and create a myriad of new roles and opportunities that we can't even begin to imagine.

Source > huffingtonpost

Imagining A Corporation In 2050

Imagining A Corporation In 2050

was challenged by the editors here at Work: Reimagined to imagine what a corporation might look like in 2050.

My immediate response was to think ‘that’s a long ways off.’ But on the other hand, it does take an incredibly long time to make foundational changes in society, except when major disruptions occur, as with the rise of the Internet over the past few decades, or the Black Death, when over 100 million people died, leading to the shifts in power that ultimately sparked the Renaissance.

So I am resorting to a futurist sleight-of-hand to get to an answer in several steps. I can’t just scramble to the roof of the house to see out over the horizon: First, I have to build a ladder to climb up to the roof. And the kind of ladders futurists build are indirect. Rather than simply extrapolating from the present — which leads to very boring stories about the future — I’ll pick several forces that could have a major impact on the world of business in 2050, and imagine edge cases for each one. This leads to scenarios — essentially, bedtime stories about the future that don’t need to be true. They only need to help us think about our future in a structured way.

The Three Forces That Will Impact Our Future

I’ve selected three extremely pressing problems, and their impact on jobs and work, to serve as the dimensions for scenario development: economic inequality, climate change, and artificials (AI and robots).

Inequality

In the past several years, the growing spread of income (and wealth) inequality has been front page news, and a defining issue of our economic era. Thomas Piketty’s Capital in the Twenty-First Century was perhaps the tipping point for economic inequality to ascend to the highest and broadest levels of public discourse.

In a report released this month, the Organization for Economic Cooperation and Development (OECD) reported that economic inequality continues to grow, is leading to higher levels of poverty, and has reduced the rebound from the Great Recession. As the report’s authors say,

In most countries, the gap between rich and poor is at its highest level since 30 years. Today, in OECD countries, the richest 10% of the population earn 9.6 times the income of the poorest 10%. In the 1980s, this ratio stood at 7:1 rising to 8:1 in the 1990s and 9:1 in the 2000s. In several emerging economies, particularly in Latin America, income inequality has narrowed, but income gaps remain generally higher than in OECD countries. During the crisis, income inequality continued to increase, mainly due to the fall in employment; redistribution through taxes and transfer partly offset inequality. However, at the lower end of the income distribution, real household incomes fell substantially in countries hit hardest by the crisis.

My inclination is to hope for a world where inequality can be limited, but because it is increasing at the present time — both by the rich getting richer and the poor getting poorer — I’ve imagined two scenarios where inequality is even worse 35 years from now, and one where it has been checked in a scenario called Humania.

Climate Change

The second force is climate change, specifically as a result of human activities. I won’t even link to source information since we are beyond that now, despite foot dragging by powerful, entrenched interests. Only yesterday, Rex Tillerson, CEO of Exxon Mobile, continued to deny climate science, and refused to join a group of European energy companies working on a climate strategy in advance of UN climate talks planned for December.

However, it continues to be possible that we can sidestep a worldwide extinction through moderation of climate change, and therefore two of my scenarios are based on that, while one — Collapseland — does not manage that.

The Impact of AI and Robots on Jobs and Work

The Pew Research Center created a ‘canvassing’ of 1,896 experts and asked them this question:

The economic impact of robotic advances and AI — Self-driving cars, intelligent digital agents that can act for you, and robots are advancing rapidly. Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?

In the consequent report, AI, Robotics, and the Future of Jobs, the results were mixed: Roughly half of the experts see a future in which AI and robots will displace significant numbers of workers, and roughly half that said they would not. I fell into the camp of yay-sayers: Those that think artificials will have a major impact on work, writing,

The central question of 2025 will be: What are people for in a world that does not need their labor, and where only a minority are needed to guide the ‘bot-based economy?

But I believe that there will be necessary regulatory checks on AI and robots. While we will allow autonomous vehicles to shuttle us around, and algorithms to select the best candidates for a job — because AI is better than us at that — people will remain wary of AIs. I don’t think we’ll be handing over control of our nuclear weapons — or the strategic direction of our companies — to artificials, no matter how smart. As a result, in two scenarios AI is checked or limited in its impact, while in one scenario — Neo-feudalistan — AI and robots become the primary means of production.

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Here, then, is a Venn diagram of the three scenarios, where the green circle covers the scenario in which both climate change and AI are limited, and inequality is also addressed, the red covers the scenario in which climate change is limited but inequality continues to run rampant, and the blue circle covers the scenario in which AI is limited but inequality isn’t. As a result, each scenario is unique.

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Humania

 

Humania is the most egalitarian and democratic scenario.

After mounting concern about inequality, the climate, and the inroads that AI and robots were having on society, in the 2020s Western nations — and later other developing countries — were hit by a ‘Human Spring.’ New populist movements rose up and rejected the status quo, and demanded fundamental change. At first the demands were uneven — some groups emphasized climate, or inequality, or the right to work.

But by the mid 2030s, all three forces were more-or-less equal planks in the Humania platform. This led to mandated barriers to inequality — such as limits on the multiple of the salaries of highest to lowest paid workers, and progressive taxation so that the well-off paid much higher taxes by percentage. Additionally, there were worldwide actions to limit oil and coal use, and a dramatic shift to solar in the early 2020s. Concerned that people would be pushed inexorably out of the job market, governments build limits on AI use into international trade agreements, based on a notion of the human right to work.

In the year 2050, businesses in Humania are egalitarian, fast-and-loose, and porous. Egalitarian in the sense that Humania workers have great autonomy: They can choose who they want to work with and for, as well as which initiatives or projects they’d like to work on.

They’re fast-and-loose in that they are organized to be agile and lean, and in order to do so, the social ties in businesses are much looser than in the 2010s. It was those rigid relationships — for example, the one between a manager and her direct reports — that, when repeated across layers of a hierarchical organization, lead to slow-and-tight company.

Instead of a pyramid, Humania’s companies are heterarchies: They are more like a brain than an army. In the brain — and in fast-and-loose companies — different sorts of connections and groupings of connected elements can form. There is no single way to organize. People can choose the sort of relationships that most make sense.

People’s careers involve many different jobs and roles, and considerable periods of time out of work. Basic universal income is guaranteed and generous benefits for family leave are a regular feature of work, such as paternity/maternity leave, looking after ill loved ones, and subsidized opportunities for life-long learning. This is the porous side of things; The edge of the company is permeable, and people easily leave and return.

Instead of the precarious nature of freelance and temp work of the 2010s, the use of time-limited standard employment agreements — like Reid Hoffman’s ‘Tours of Duty’ model — allow security for workers and flexibility for companies.

Some of the technologies of the day would be familiar to us, like smart phones and some wearables. But you’d be hard-pressed to find a ‘desktop’ PC. The biggest change is ubiquitous connectivity based on 6G networks; high-speed Internet is seen as basic public infrastructure — similar to streets and bridges — across Humania. Augmented and virtual reality is commonplace in work and entertainment.

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Neo-feudalistan

 

In Neo-feudalistan, the Human Spring uprising fizzled out like the Occupy movement in the 2010s. As a result, the concentration of wealth and power continues unabated, and political and economic power is held in even fewer hands in 2050 than in 2015.

One consequence to the good was that global corporations and the ruling elite decided in the 2020s to counter the threat of climate change, and as in Humania they pushed heavily for a world reliant on solar, averting ecological collapse.

Corporations are able to invest in ever-more-intelligent AI, driving down the prices of food, goods, and services across the board in almost all industries. While this yielded profits sufficient to maintain the system, it also created companies with significantly smaller staffs. In fact, historians of the time will point back to the Internet software giants of the 2010s — Google, Apple, Amazon, Facebook, and other unicorns — as the progenitors of this sort of company.

In general, businesses in Neo-feudalistan are primarily driven by carefully-managed artificials, configured to have deep expertise in narrow domains, and overseen by small teams of highly trained experts in those domains, and supported by scientists who understand the workings of the artificials. As a result, a company that has 50,000 employees today might have only 5,000 in 2050 while producing the same volume of food, goods, or services.

Many of the internal functions now performed by people are handled in Neo-feudalistan companies by artificials, as well. Starting in the 2020s, companies handed over ‘human resources’ to algorithms relying on big data because it had been shown that people are too cognitively biased to make good hiring and promotion decisions. Relatively quickly, other managerial functions were handed over, too. Like the companies of Humania, Neo-feudalistan companies are brain-shaped, but most of the neurons aren’t human. Of course, the people that remain — and the companies’ owners — are extremely well-paid, and very skilled at getting the most out of AI.

In order to counter the revolutionary tendencies that may arise due to the millions who are unemployed, a universal basic income has been enacted across Neo-feudalistan. It provides enough to support a decent lifestyle, and access to basic services like health care, education, and transport. This was largely underwritten by massive reductions in cost in production and energy. Basic goods sell for perhaps a tenth of their 2015 cost in Neo-feudalistan, because there are so few people in the supply chain.

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Collapseland

 

Collapseland is where everything goes pear shaped. Dithering by governments and corporations has allowed climate change to push the world into increased heat, drought, and violent weather. The Human Spring of the 2020s led to a conservative backlash and a suppression of the movement itself. It also led to a suppression of advancements in AI, since it became associated with the science orientation of the movement.

But governments and corporations get their act together in the late 2020s and 2030s to avert an extinction event via the global adoption of solar. However, this only comes after a serious ecological catastrophe has occurred. Inequality remains unchecked, and the poor become much poorer.

Collapseland businesses are much like businesses of 2015. Most efforts are directed toward basic requirements — like desalinating water, relocating people away from low-lying or drought stricken areas, and struggling with food production challenges. As a result, little innovation has taken place. It’s no different from the company you work for today, except longer hours, fewer co-workers, less pay, and much more dust. To increase profits, corporations have cut staff and forced existing workers to work harder.

2050 Is Closer Than You Think

This exercise is — as I said — a futurist slight of hand. I picked three forces, rolled the dice, and gamed it out. But here’s a takeaway: Everything has to fall into place — inequality countered, climate change overcome, and the acceptance of the human right to work (which means limiting AI) — for something like Humania to come into existence.

For our children and grandchildren to live happy, meaningful lives, and for civilization itself to prosper and evolve, we will have to have that Human Spring. Soon.

Source > medium