The idea that you had no idea any of this was happening strains my credibility

From left: Twitter’s acting general counsel Sean Edgett, Facebook’s general counsel Colin Stretch and Google’s senior vice president and general counsel Kent Walker, testify before the House Intelligence Committee on Wednesday, Nov. 1, 2017. Manuel Balce Ceneta/AP

Members of Congress confessed how difficult it was for them to even wrap their minds around how today’s Internet works — and can be abused. And for others, the hearings finally drove home the magnitude of the Big Tech platforms.

Sen. John Kennedy, R-La., marveled on Tuesday when Facebook said it could track the source of funding for all 5 million of its monthly advertisers.

“I think you do enormous good, but your power scares me,” he said.

There appears to be no quick patch for the malware afflicting America’s political life.

Over the course of three congressional hearings Tuesday and Wednesday, lawmakers fulminated, Big Tech witnesses were chastened but no decisive action appears to be in store to stop a foreign power from harnessing digital platforms to try to shape the information environment inside the United States.

Legislation offered in the Senate — assuming it passed, months or more from now — would change the calculus slightly: requiring more disclosure and transparency for political ads on Facebook and Twitter and other social platforms.

Even if it became law, however, it would not stop such ads from being sold, nor heal the deep political divisions exploited last year by foreign influence-mongers. The legislation also couldn’t stop a foreign power from using all the other weapons in its arsenal against the U.S., including cyberattacks, the deployment of human spies and others.

“Candidly, your companies know more about Americans, in many ways, than the United States government does. The idea that you had no idea any of this was happening strains my credibility,”  Senate Intelligence Committee Vice Chairman Mark Warner, D.-Va.

The companies also made clear they condemn the uses of their services they’ve discovered, which they said violate their policies in many cases.

They also talked more about the scale of the Russian digital operation they’ve uncovered up to this point — which is eye-watering: Facebook general counsel Colin Stretch acknowledged that as many as 150 million Americans may have seen posts or other content linked to Russia’s influence campaign in the 2016 cycle

“There is one thing I’m certain of, and it’s this: Given the complexity of what we have seen, if anyone tells you they have figured it out, they are kidding ourselves. And we can’t afford to kid ourselves about what happened last year — and continues to happen today.” Senate Intelligence Committee Chairman Richard Burr, R-N.C.

Source: NPR


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Does Even Mark Zuckerberg Know What Facebook Is?

In a statement broadcast live on Facebook on September 21 and subsequently posted to his profile page, Zuckerberg pledged to increase the resources of Facebook’s security and election-integrity teams and to work “proactively to strengthen the democratic process.”

It was an admirable commitment. But reading through it, I kept getting stuck on one line: “We have been working to ensure the integrity of the German elections this weekend,” Zuckerberg writes. It’s a comforting sentence, a statement that shows Zuckerberg and Facebook are eager to restore trust in their system.

But … it’s not the kind of language we expect from media organizations, even the largest ones. It’s the language of governments, or political parties, or NGOs. A private company, working unilaterally to ensure election integrity in a country it’s not even based in?

Facebook has grown so big, and become so totalizing, that we can’t really grasp it all at once.

Like a four-dimensional object, we catch slices of it when it passes through the three-dimensional world we recognize. In one context, it looks and acts like a television broadcaster, but in this other context, an NGO. In a recent essay for the London Review of Books, John Lanchester argued that for all its rhetoric about connecting the world, the company is ultimately built to extract data from users to sell to advertisers. This may be true, but Facebook’s business model tells us only so much about how the network shapes the world.

Between March 23, 2015, when Ted Cruz announced his candidacy, and November 2016, 128 million people in America created nearly 10 billion Facebook posts, shares, likes, and comments about the election. (For scale, 137 million people voted last year.)

In February 2016, the media theorist Clay Shirky wrote about Facebook’s effect: “Reaching and persuading even a fraction of the electorate used to be so daunting that only two national orgs” — the two major national political parties — “could do it. Now dozens can.”

It used to be if you wanted to reach hundreds of millions of voters on the right, you needed to go through the GOP Establishment. But in 2016, the number of registered Republicans was a fraction of the number of daily American Facebook users, and the cost of reaching them directly was negligible.

Tim Wu, the Columbia Law School professor

“Facebook has the same kind of attentional power [as TV networks in the 1950s], but there is not a sense of responsibility,” he said. “No constraints. No regulation. No oversight. Nothing. A bunch of algorithms, basically, designed to give people what they want to hear.”

It tends to get forgotten, but Facebook briefly ran itself in part as a democracy: Between 2009 and 2012, users were given the opportunity to vote on changes to the site’s policy. But voter participation was minuscule, and Facebook felt the scheme “incentivized the quantity of comments over their quality.” In December 2012, that mechanism was abandoned “in favor of a system that leads to more meaningful feedback and engagement.”

Facebook had grown too big, and its users too complacent, for democracy.

Source: NY Magazine



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Put Humans at the Center of AI

As the director of Stanford’s AI Lab and now as a chief scientist of Google Cloud, Fei-Fei Li is helping to spur the AI revolution. But it’s a revolution that needs to include more people. She spoke with MIT Technology Review senior editor Will Knight about why everyone benefits if we emphasize the human side of the technology.

Why did you join Google?

Researching cutting-edge AI is very satisfying and rewarding, but we’re seeing this great awakening, a great moment in history. For me it’s very important to think about AI’s impact in the world, and one of the most important missions is to democratize this technology. The cloud is this gigantic computing vehicle that delivers computing services to every single industry.

What have you learned so far?

We need to be much more human-centered.

If you look at where we are in AI, I would say it’s the great triumph of pattern recognition. It is very task-focused, it lacks contextual awareness, and it lacks the kind of flexible learning that humans have.

We also want to make technology that makes humans’ lives better, our world safer, our lives more productive and better. All this requires a layer of human-level communication and collaboration.

When you are making a technology this pervasive and this important for humanity, you want it to carry the values of the entire humanity, and serve the needs of the entire humanity.

If the developers of this technology do not represent all walks of life, it is very likely that this will be a biased technology. I say this as a technologist, a researcher, and a mother. And we need to be speaking about this clearly and loudly.

Source: MIT Technology Review



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Why we launched DeepMind Ethics & Society

We believe AI can be of extraordinary benefit to the world, but only if held to the highest ethical standards.

Technology is not value neutral, and technologists must take responsibility for the ethical and social impact of their work.

As history attests, technological innovation in itself is no guarantee of broader social progress. The development of AI creates important and complex questions. Its impact on society—and on all our lives—is not something that should be left to chance. Beneficial outcomes and protections against harms must be actively fought for and built-in from the beginning. But in a field as complex as AI, this is easier said than done.

As scientists developing AI technologies, we have a responsibility to conduct and support open research and investigation into the wider implications of our work. At DeepMind, we start from the premise that all AI applications should remain under meaningful human control, and be used for socially beneficial purposes. 

So today we’re launching a new research unit, DeepMind Ethics & Society, to complement our work in AI science and application. This new unit will help us explore and understand the real-world impacts of AI. It has a dual aim: to help technologists put ethics into practice, and to help society anticipate and direct the impact of AI so that it works for the benefit of all. 

If AI technologies are to serve society, they must be shaped by society’s priorities and concerns.

Source: DeepMind


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Facebook and Google promote Las Vegas-shooting hoaxes

The missteps underscore how misinformation continues to undermine the credibility of Silicon Valley’s biggest companies.

Accuracy matters in the moments after a tragedy. Facts can help catch the suspects, save lives and prevent a panic.

But in the aftermath of the deadly mass shooting in Las Vegas on Sunday, the world’s two biggest gateways for information, Google and Facebook, did nothing to quell criticism that they amplify fake news when they steer readers toward hoaxes and misinformation gathering momentum on fringe sites.

Google posted under its “top stories” conspiracy-laden links from 4chan — home to some of the internet’s most ardent trolls. It also promoted a now-deleted story from Gateway Pundit and served videos on YouTube of dubious origin.

The posts all had something in common: They identified the wrong assailant.

Facebook’s Crisis Response page, a hub for users to stay informed and mobilize during disasters, perpetuated the same rumors by linking to sites such as Alt-Right News and End Time Headlines, according to Fast Company.

The platforms have immense influence on what gets seen and read. More than two-thirds of Americans report getting at least some of their news from social media, according to the Pew Research Center. A separate global study published by Edelman last year found that more people trusted search engines (63%) for news and information than traditional media such as newspapers and television (58%).

Still, skepticism abounds that the companies beholden to shareholders are equipped to protect the public from misinformation and recognize the threat their platforms pose to democratic societies.

Source: LA Times



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Sundar Pichai says the future of Google is AI. But can he fix the algorithm?

I was asking in the context of the aftermath of the 2016 election and the misinformation that companies like Facebook, Twitter, and Google were found to have spread.

“I view it as a big responsibility to get it right,” he says. “I think we’ll be able to do these things better over time. But I think the answer to your question, the short answer and the only answer, is we feel huge responsibility.”

But it’s worth questioning whether Google’s systems are making the rightdecisions, even as they make some decisions much easier.

People are already skittish about how much Google knows about them, and they are unclear on how to manage their privacy settings. Pichai thinks that’s another one of those problems that AI could fix, “heuristically.”

“Down the line, the system can be much more sophisticated about understanding what is sensitive for users, because it understands context better,” Pichai says. “[It should be] treating health-related information very differently from looking for restaurants to eat with friends.” Instead of asking users to sift through a “giant list of checkboxes,” a user interface driven by AI could make it easier to manage.

Of course, what’s good for users versus what’s good for Google versus what’s good for the other business that rely on Google’s data is a tricky question. And it’s one that AI alone can’t solve. Google is responsible for those choices, whether they’re made by people or robots.

The amount of scrutiny companies like Facebook and Google — and Google’s YouTube division — face over presenting inaccurate or outright manipulative information is growing every day, and for good reason.

Pichai thinks that Google’s basic approach for search can also be used for surfacing good, trustworthy content in the feed. “We can still use the same core principles we use in ranking around authoritativeness, trust, reputation.

What he’s less sure about, however, is what to do beyond the realm of factual information — with genuine opinion: “I think the issue we all grapple with is how do you deal with the areas where people don’t agree or the subject areas get tougher?”

When it comes to presenting opinions on its feed, Pichai wonders if Google could “bring a better perspective, rather than just ranking alone. … Those are early areas of exploration for us, but I think we could do better there.”

Source: The Verge



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The idea that Silicon Valley is the darling of our markets and of our society … is definitely turning

“Personally, I think the idea that fake news on Facebook, it’s a very small amount of the content, influenced the election in any way is a pretty crazy idea.”

Facebook CEO Mark Zuckerberg’s company recently said it would turn over to Congress more than 3,000 politically themed advertisements that were bought by suspected Russian operatives. (Eric Risberg/AP

Nine days after Facebook chief executive Mark Zuckerberg dismissed as “crazy” the idea that fake news on his company’s social network played a key role in the U.S. election, President Barack Obama pulled the youthful tech billionaire aside and delivered what he hoped would be a wake-up call.

Obama made a personal appeal to Zuckerberg to take the threat of fake news and political disinformation seriously. Unless Facebook and the government did more to address the threat, Obama warned, it would only get worse in the next presidential race.

“There’s been a systematic failure of responsibility. It’s rooted in their overconfidence that they know best, their naivete about how the world works, their extensive effort to avoid oversight, and their business model of having very few employees so that no one is minding the store.” Zeynep Tufekci

Zuckerberg acknowledged the problem posed by fake news. But he told Obama that those messages weren’t widespread on Facebook and that there was no easy remedy, according to people briefed on the exchange

One outcome of those efforts was Zuckerberg’s admission on Thursday that Facebook had indeed been manipulated and that the company would now turn over to Congress more than 3,000 politically themed advertisements that were bought by suspected Russian operatives.

These issues have forced Facebook and other Silicon Valley companies to weigh core values, including freedom of speech, against the problems created when malevolent actors use those same freedoms to pump messages of violence, hate and disinformation.

Congressional investigators say the disclosure only scratches the surface. One called Facebook’s discoveries thus far “the tip of the iceberg.” Nobody really knows how many accounts are out there and how to prevent more of them from being created to shape the next election — and turn American society against itself.

“There is no question that the idea that Silicon Valley is the darling of our markets and of our society — that sentiment is definitely turning,” said Tim O’Reilly, an adviser to tech executives and chief executive of the influential Silicon Valley-based publisher O’Reilly Media

Source: Washington Post


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The idea was to help you and I make better decisions amid cognitive overload

IBM Chairman, President, and Chief Executive Officer Ginni Rometty. PHOTOGRAPHER: STEPHANIE SINCLAIR FOR BLOOMBERG BUSINESSWEEK

If I considered the initials AI, I would have preferred augmented intelligence.

It’s the idea that each of us are going to need help on all important decisions.

A study said on average that a third of your decisions are really great decisions, a third are not optimal, and a third are just wrong. We’ve estimated the market is $2 billion for tools to make better decisions.

That’s what led us all to really calling it cognitive

“Look, we really think this is about man and machine, not man vs. machine. This is an era—really, an era that will play out for decades in front of us.”

We set out to build an AI platform for business.

AI would be vertical. You would train it to know medicine. You would train it to know underwriting of insurance. You would train it to know financial crimes. Train it to know oncology. Train it to know weather. And it isn’t just about billions of data points. In the regulatory world, there aren’t billions of data points. You need to train and interpret something with small amounts of data.

This is really another key point about professional AI. Doctors don’t want black-and-white answers, nor does any profession. If you’re a professional, my guess is when you interact with AI, you don’t want it to say, “Here is an answer.”

What a doctor wants is, “OK, give me the possible answers. Tell my why you believe it. Can I see the research, the evidence, the ‘percent confident’? What more would you like to know?”

It’s our responsibility if we build this stuff to guide it safely into the world.

Source: Bloomberg



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Siri as a therapist, Apple is seeking engineers who understand psychology

PL – Looks like Siri needs more help to understand.

Apple Job Opening Ad

“People have serious conversations with Siri. People talk to Siri about all kinds of things, including when they’re having a stressful day or have something serious on their mind. They turn to Siri in emergencies or when they want guidance on living a healthier life. Does improving Siri in these areas pique your interest?

Come work as part of the Siri Domains team and make a difference.

We are looking for people passionate about the power of data and have the skills to transform data to intelligent sources that will take Siri to next level. Someone with a combination of strong programming skills and a true team player who can collaborate with engineers in several technical areas. You will thrive in a fast-paced environment with rapidly changing priorities.”

The challenge as explained by Ephrat Livni on Quartz

The position requires a unique skill set. Basically, the company is looking for a computer scientist who knows algorithms and can write complex code, but also understands human interaction, has compassion, and communicates ably, preferably in more than one language. The role also promises a singular thrill: to “play a part in the next revolution in human-computer interaction.”

The job at Apple has been up since April, so maybe it’s turned out to be a tall order to fill. Still, it shouldn’t be impossible to find people who are interested in making machines more understanding. If it is, we should probably stop asking Siri such serious questions.

Computer scientists developing artificial intelligence have long debated what it means to be human and how to make machines more compassionate. Apart from the technical difficulties, the endeavor raises ethical dilemmas, as noted in the 2012 MIT Press book Robot Ethics: The Ethical and Social Implications of Robotics.

Even if machines could be made to feel for people, it’s not clear what feelings are the right ones to make a great and kind advisor and in what combinations. A sad machine is no good, perhaps, but a real happy machine is problematic, too.

In a chapter on creating compassionate artificial intelligence (pdf), sociologist, bioethicist, and Buddhist monk James Hughes writes:

Programming too high a level of positive emotion in an artificial mind, locking it into a heavenly state of self-gratification, would also deny it the capacity for empathy with other beings’ suffering, and the nagging awareness that there is a better state of mind.

Source: Quartz

 

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Artificial intelligence pioneer says throw it all away and start again

Geoffrey Hinton harbors doubts about AI’s current workhorse. (Johnny Guatto / University of Toronto)

In 1986, Geoffrey Hinton co-authored a paper that, three decades later, is central to the explosion of artificial intelligence.

But Hinton says his breakthrough method should be dispensed with, and a new path to AI found.

… he is now “deeply suspicious” of back-propagation, the workhorse method that underlies most of the advances we are seeing in the AI field today, including the capacity to sort through photos and talk to Siri.

“My view is throw it all away and start again”

Hinton said that, to push materially ahead, entirely new methods will probably have to be invented. “Max Planck said, ‘Science progresses one funeral at a time.’ The future depends on some graduate student who is deeply suspicious of everything I have said.”

Hinton suggested that, to get to where neural networks are able to become intelligent on their own, what is known as “unsupervised learning,” “I suspect that means getting rid of back-propagation.”

“I don’t think it’s how the brain works,” he said. “We clearly don’t need all the labeled data.”

Source: Axios

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I prefer to be killed by my own stupidity rather than the codified morals of a software engineer

…or the learned morals of an evolving algorithm. SAS CTO Oliver Schabenberger

With the advent of deep learning, machines are beginning to solve problems in a novel way: by writing the algorithms themselves.

The software developer who codifies a solution through programming logic is replaced by a data scientist who defines and trains a deep neural network.

The expert who studied and learned a domain is replaced by a reinforcement learning algorithm that discovers the rules of play from historical data.

We are learning incredible lessons in this process.

But does the rise of such highly sophisticated deep learning mean that machines will soon surpass their makers? They are surpassing us in reliability, accuracy and throughput. But they are not surpassing us in thinking or learning. Not with today’s technology.

The artificial intelligence systems of today learn from data – they learn only from data. These systems cannot grow beyond the limits of the data by creating, innovating or reasoning.

Even a reinforcement learning system that discovers rules of play from past data cannot develop completely new rules or new games. It can apply the rules in a novel and more efficient way, but it does not invent a new game. The machine that learned to play Go better than any human being does not know how to play Poker.

Where to from here?

True intelligence requires creativity, innovation, intuition, independent problem solving, self-awareness and sentience. The systems built based on deep learning do not – and cannot – have these characteristics. These are trained by top-down supervised methods.

We first tell the machine the ground truth, so that it can discover its regularities. They do not grow beyond that.

Source: InformationWeek



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Can machines learn to be moral?  #AI

AI works, in part, because complex algorithms adeptly identify, remember, and relate data … Moreover, some machines can do what had been the exclusive domain of humans and other intelligent life: Learn on their own.

As a researcher schooled in scientific method and an ethicist immersed in moral decision-making, I know it’s challenging for humans to navigate concurrently the two disparate arenas. 

It’s even harder to envision how computer algorithms can enable machines to act morally.

Moral choice, however, doesn’t ask whether an action will produce an effective outcome; it asks if it is good decision. In other words, regardless of efficacy, is it the right thing to do? 

Such analysis does not reflect an objective, data-driven decision but a subjective, judgment-based one.

Individuals often make moral decisions on the basis of principles like decency, fairness, honesty, and respect. To some extent, people learn those principles through formal study and reflection; however, the primary teacher is life experience, which includes personal practice and observation of others.

Placing manipulative ads before a marginally-qualified and emotionally vulnerable target market may be very effective for the mortgage company, but many people would challenge the promotion’s ethicality.

Humans can make that moral judgment, but how does a data-driven computer draw the same conclusion? Therein lies what should be a chief concern about AI.

Can computers be manufactured with a sense of decency?

Can coding incorporate fairness? Can algorithms learn respect? 

It seems incredible for machines to emulate subjective, moral judgment, but if that potential exists, at least four critical issues must be resolved:

  1. Whose moral standards should be used?
  2. Can machines converse about moral issues?
  3. Can algorithms take context into account?
  4. Who should be accountable?

Source: Business Insider David Hagenbuch



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Why The Sensitive Intersection of Race, Hate Speech And Algorithms Is Heating Up #AI

SAN JOSE, CA – APRIL 18: Facebook CEO Mark Zuckerberg delivers the keynote address at Facebook’s F8 Developer Conference on April 18, 2017 at McEnery Convention Center in San Jose, California. (Photo by Justin Sullivan/Getty Images)

… recent story in The Washington Post reported that “minority” groups feel unfairly censored by social media behemoth Facebook, for example, when using the platform for discussions about racial bias. At the same time, groups and individuals on the other end of the race spectrum are quickly being banned and ousted in a flash from various social media networks.

Most all of such activity begins with an algorithm, a set of computer code that, for all intents and purposes for this piece, is created to raise a red flag when certain speech is used on a site.

But from engineer mindset to tech limitation, just how much faith should we be placing in algorithms when it comes to the very sensitive area of digital speech and race, and what does the future hold?

Indeed, while Facebook head Mark Zuckerberg reportedly eyes political ambitions within an increasingly brown America in which his own company consistently has issues creating racial balance, there are questions around policy and development of such algorithms. In fact, Malkia Cyril executive director for the Center for Media Justice  told the Post  that she believes that Facebook has a double standard when it comes to deleting posts.

Cyril explains [her meeting with Facebook] “The meeting was a good first step, but very little was done in the direct aftermath.  Even then, Facebook executives, largely white, spent a lot of time explaining why they could not do more instead of working with us to improve the user experience for everyone.”

What’s actually in the hearts and minds of those in charge of the software development? How many more who are coding have various thoughts – or more extreme – as those recently expressed in what is now known as the Google Anti-Diversity memo?

Not just Facebook, but any and all tech platforms where race discussion occurs are seemingly at a crossroads and under various scrutiny in terms of management, standards and policy about this sensitive area. The main question is how much of this imbalance is deliberate and how much is just a result of how algorithms naturally work?

Nelson [National Chairperson National Society of Black Engineers] notes that the first source of error, however, is how a particular team defines the term hate speech. “That opinion may differ between people so any algorithm would include error at the individual level,” he concludes.

“I believe there are good people at Facebook who want to see justice done,” says Cyril. “There are steps being taken at the company to improve the experience of users and address the rising tide of hate that thwarts democracy, on social media and in real life.

That said, racism is not race neutral, and accountability for racism will never come from an algorithm alone.”

Source: Forbes



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Machines Learn a Biased View of Women

Two prominent research-image collections—including one supported by Microsoft and Facebook—display a predictable gender bias in their depiction of activities such as cooking and sports. Images of shopping and washing are linked to women, for example, while coaching and shooting are tied to men.

Machine-learning software trained on the datasets didn’t just mirror those biases, it amplified them. If a photo set generally associated women with cooking, software trained by studying those photos and their labels created an even stronger association.

Mark Yatskar, a researcher at the Allen Institute for Artificial Intelligence, says that this phenomenon could also amplify other biases in data, for example related to race. “This could work to not only reinforce existing social biases but actually make them worse,” says Yatskar, who worked with Ordóñez and others on the project while at the University of Washington.

“A system that takes action that can be clearly attributed to gender bias cannot effectively function with people,” he says.

When image-recognition software is “trained” by examining these datasets, the bias is amplified. A system trained on the COCO dataset associated men with keyboards and computer mice even more strongly than the dataset itself.

The researchers devised a way to neutralize this amplification phenomenon—effectively forcing learning software to reflect its training data. But it requires a researcher to be looking for bias in the first place, and to specify what he or she wants to correct. And the corrected software still reflects the gender biases baked into the original data.

One point of agreement in the field is that using machine learning to solve problems is more complicated than many people previously thought.

“Work like this is correcting the illusion that algorithms can be blindly applied to solve problems,” says Suresh Venkatasubramanian, a professor at the University of Utah.

Source: Wired


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Behind the Google diversity memo furor is fear of Google’s vast opaque power

Fear of opaque power of Google in particular, and Silicon Valley in general, wields over our lives.

If Google — and the tech world more generally — is sexist, or in the grips of a totalitarian cult of political correctness, or a secret hotbed of alt-right reactionaries, the consequences would be profound.

Google wields a monopoly over search, one of the central technologies of our age, and, alongside Facebook, dominates the internet advertising market, making it a powerful driver of both consumer opinion and the media landscape. 

It shapes the world in which we live in ways both obvious and opaque.

This is why trust matters so much in tech. It’s why Google, to attain its current status in society, had to promise, again and again, that it wouldn’t be evil. 

Compounding the problem is that the tech industry’s point of view is embedded deep in the product, not announced on the packaging. Its biases are quietly built into algorithms, reflected in platform rules, expressed in code few of us can understand and fewer of us will ever read.

But what if it actually is evil? Or what if it’s not evil but just immature, unreflective, and uncompassionate? And what if that’s the culture that designs the digital services the rest of us have to use?

The technology industry’s power is vast, and the way that power is expressed is opaque, so the only real assurance you can have that your interests and needs are being considered is to be in the room when the decisions are made and the code is written. But tech as an industry is unrepresentative of the people it serves and unaccountable in the way it serves them, and so there’s very little confidence among any group that the people in the room are the right ones.

Source: Vox (read the entire article by Ezra Klein)



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IBM Watson CTO on Why Augmented Intelligence Beats AI

If you look at almost every other tool that has ever been created, our tools tend to be most valuable when they’re amplifying us, when they’re extending our reach, when they’re increasing our strength, when they’re allowing us to do things that we can’t do by ourselves as human beings. That’s really the way that we need to be thinking about AI as well, and to the extent that we actually call it augmented intelligence, not artificial intelligence.

Some time ago we realized that this thing called cognitive computing was really bigger than us, it was bigger than IBM, it was bigger than any one vendor in the industry, it was bigger than any of the one or two different solution areas that we were going to be focused on, and we had to open it up, which is when we shifted from focusing on solutions to really dealing with more of a platform of services, where each service really is individually focused on a different part of the problem space.

what we’re talking about now are a set of services, each of which do something very specific, each of which are trying to deal with a different part of our human experience, and with the idea that anybody building an application, anybody that wants to solve a social or consumer or business problem can do that by taking our services, then composing that into an application.

If the doctor can now make decisions that are more informed, that are based on real evidence, that are supported by the latest facts in science, that are more tailored and specific to the individual patient, it allows them to actually do their job better. For radiologists, it may allow them to see things in the image that they might otherwise miss or get overwhelmed by. It’s not about replacing them. It’s about helping them do their job better.

That’s really the way to think about this stuff, is that it will have its greatest utility when it is allowing us to do what we do better than we could by ourselves, when the combination of the human and the tool together are greater than either one of them would’ve been by theirselves. That’s really the way we think about it. That’s how we’re evolving the technology. That’s where the economic utility is going to be.

There are lots of things that we as human beings are good at. There’s also a lot of things that we’re not very good, and that’s I think where cognitive computing really starts to make a huge difference, is when it’s able to bridge that distance to make up that gap

A way I like to say it is it doesn’t do our thinking for us, it does our research for us so we can do our thinking better, and that’s true of us as end users and it’s true of advisors.

Source: PCMag



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Will Satya’s ‘Charlottesville email’ shape AI applications at Microsoft?


“You can’t paint what you ain’t.”

– Drew Struzan

Those words got to me 18 years ago during an interview I had with this esteemed artist. We were working on a project together, an interactive CD about his movie posters, several of which were classics by then, when the conversation wandered off the subject of art and we began to examine the importance of being true to one’s self.  

“Have you ever, in your classes or seminars talked much about the underlying core foundation principles of your life?” I asked Drew that day.

His answer in part went like this: “Whenever I talk, I’m asked to talk about my art, because that’s what they see, that’s what’s out front. But the power of the art comes out of the personality of the human being. Inevitably, you can’t paint what you ain’t.”

That conversation between us took place five days before Columbine, in April of 1999, when Pam and I lived in Denver and a friend of ours had children attending that school. That horrific event triggered a lot of value discussions and a lot of human actions, in response to it.

Flash-forward to Charlottesville. And an email, in response to it, that the CEO of a large tech company sent his employees yesterday, putting a stake in the ground about what his company stands for, and won’t stand for, during these “horrific” times.

“… At Microsoft, we strive to seek out differences, celebrate them and invite them in. As a leader, a key part of your role is creating a culture where every person can do their best work, which requires more than tolerance for diverse perspectives. Our growth mindset culture requires us to truly understand and share the feelings of another person. …”

If Satya Nadella’s email expresses the emerging personality at Microsoft, the power source from which it works, then we are cautiously optimistic about what this could do for socializing AI.

It will take this kind of foundation-building, going forward, as MS introduces more AI innovations, to diminish the inherent bias in deep learning approaches and the implicit bias in algorithms.

It will take this depth of awareness to shape the values of Human-AI collaboration, to protect the humans who use AI. Values that, “seek out differences, celebrate them and invite them in.”

It will require unwavering dedication to this goal. Because. You can’t paint what you ain’t.

Blogger, Phil Lawson
SocializingAI.com



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Satya Nadella’s message to Microsoft after the attack in Charlottesville

Yesterday (Aug. 14), Microsoft CEO Satya Nadella sent out the following email to employees at Microsoft after the deadly car crash at a white nationalist rally in in Charlottesville, Virginia, on Saturday, Aug. 12:

This past week and in particular this weekend’s events in Charlottesville have been horrific. What I’ve seen and read has had a profound impact on me and I am sure for many of you as well. In these times, to me only two things really matter as a leader.

The first is that we stand for our timeless values, which include diversity and inclusion. There is no place in our society for the bias, bigotry and senseless violence we witnessed this weekend in Virginia provoked by white nationalists. Our hearts go out to the families and everyone impacted by the Charlottesville tragedy.

The second is that we empathize with the hurt happening around us. At Microsoft, we strive to seek out differences, celebrate them and invite them in. As a leader, a key part of your role is creating a culture where every person can do their best work, which requires more than tolerance for diverse perspectives. Our growth mindset culture requires us to truly understand and share the feelings of another person. It is an especially important time to continue to be connected with people, and listen and learn from each other’s experiences.

As I’ve said, across Microsoft, we will stand together with those who are standing for positive change in the communities where we live, work and serve. Together, we must embrace our shared humanity, and aspire to create a society that is filled with respect, empathy and opportunity for all.

Feel free to share with your teams.

Satya

Source: Quartz

TO READ this blogger’s view of the above email click here.

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Do we still need human judges in the age of Artificial Intelligence?

Technology and the law are converging, and where they meet new questions arise about the relative roles of artificial and human agents—and the ethical issues involved in the shift from one to the other. While legal technology has largely focused on the activities of the bar, it challenges us to think about its application to the bench as well. In particular,

Could AI replace human judges?

The idea of  AI judges raises important ethical issues around bias and autonomy. AI programs may incorporate the biases of their programmers and the humans they interact with.

But while such programs may replicate existing human biases, the distinguishing feature of AI over an algorithm  is that it can behave in surprising and unintended ways as it ‘learns.’ Eradicating bias therefore becomes even more difficult, though not impossible. Any AI judging program would need to account for, and be tested for, these biases.

Appealing to rationality, the counter-argument is that human judges are already biased, and that AI can be used to improve the way we deal with them and reduce our ignorance. Yet suspicions about AI judges remain, and are already enough of a concern to lead the European Union to promulgate a General Data Protection Regulation which becomes effective in 2018. This Regulation contains

“the right not to be subject to a decision based solely on automated processing”.

As the English utilitarian legal theorist Jeremy Bentham once wrote in An Introduction To The Principles of Morals and Legislation, “in principle and in practice, in a right track and in a wrong one, the rarest of all human qualities is consistency.” With the ability to process far more data and variables in the case record than humans could ever do, an AI judge might be able to outstrip a human one in many cases.

Even so, AI judges may not solve classical questions of legal validity so much as raise new questions about the role of humans, since—if  we believe that ethics and morality in the law are important—then they necessarily lie, or ought to lie, in the domain of human judgment.

In practical terms, if we apply this conclusion to the perspective of American legal theorist Ronald Dworkin, for example, AI could assist with examining the entire breadth and depth of the law, but humans would ultimately choose what they consider a morally-superior interpretation.

The American Judge Richard Posner believes that the immediate use of AI and automation should be restricted to assisting judges in uncovering their own biases and maintaining consistency.

At the heart of these issues is a hugely challenging question: what does it mean to be human in the age of Artificial Intelligence?

Source: Open Democracy

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We should not talk about jobs being lost but people suffering #AI

How can humans stay ahead of an ever growing machine intelligence? “I think the challenge for us is to always be creative,” says former world chess champion Garry Kasparov

He also discussed the threat that increasingly capable AI poses to (human) jobs, arguing that we should not try to predict what will happen in the future but rather look at immediate problems.

“We make predictions and most are wrong because we’re trying to base it on our past experience,” he argued. “I think the problem is not that AI is exceeding our level. It’s another cycle.

Machines have been constantly replacing all sorts of jobs… We should not talk about jobs being lost but people suffering.

“AI is just another challenge. The difference is that now intelligence machines are coming after people with a college degree or with social media and Twitter accounts,” he added.

Source: Tech Crunch



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Why We Should Fear Emotionally Manipulative Robots – #AI

Artificial Intelligence Is Learning How to Exploit Human Psychology for Profit

Empathy is widely praised as a good thing. But it also has its dark sides: Empathy can be manipulated and it leads people to unthinkingly take sides in conflicts. Add robots to this mix, and the potential for things to go wrong multiplies.

Give robots the capacity to appear empathetic, and the potential for trouble is even greater.

The robot may appeal to you, a supposedly neutral third party, to help it to persuade the frustrated customer to accept the charge. It might say: “Please trust me, sir. I am a robot and programmed not to lie.”

You might be skeptical that humans would empathize with a robot. Social robotics has already begun to explore this question. And experiments suggest that children will side with robots against people when they perceive that the robots are being mistreated.

a study conducted at Harvard demonstrated that students were willing to help a robot enter secured residential areas simply because it asked to be let in, raising questions about the potential dangers posed by the human tendency to respect a request from a machine that needs help.

Robots will provoke empathy in situations of conflict. They will draw humans to their side and will learn to pick up on the signals that work.

Bystander support will then mean that robots can accomplish what they are programmed to accomplish—whether that is calming down customers, or redirecting attention, or marketing products, or isolating competitors. Or selling propaganda and manipulating opinions.

The robots will not shed tears, but may use various strategies to make the other (human) side appear overtly emotional and irrational. This may also include deliberately infuriating the other side.

When people imagine empathy by machines, they often think about selfless robot nurses and robot suicide helplines, or perhaps also robot sex. In all of these, machines seem to be in the service of the human. However, the hidden aspects of robot empathy are the commercial interests that will drive its development. Whose interests will dominate when learning machines can outwit not only their customers but also their owners?

Source: Zocalo

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Microsoft’s new corporate vision: artificial intelligence is in and mobile is out

Microsoft has inserted artificial intelligence into its vision for the first time, and removed references to a “mobile-first” world. That fits with Microsoft’s recent push into AI and retreat from the smartphone market.

“We believe a new technology paradigm is emerging that manifests itself through an intelligent cloud and an intelligent edge where computing is more distributed, AI drives insights and acts on the user’s behalf, and user experiences span devices with a user’s available data and information,” according to Microsoft’s vision statement.

Microsoft last year formed a new 5,000-person engineering and research team to focus on its artificial intelligence products — a major reshaping of the company’s internal structure reminiscent of its massive pivot to pursue the opportunity of the Internet in the mid-1990s.

Here is Microsoft’s full vision statement from the document:

Microsoft is a technology company whose mission is to empower every person and every organization on the planet to achieve more. We strive to create local opportunity, growth, and impact in every country around the world. Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).

Source: Geekwire



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What Makes an Artificial Intelligence Racist and Sexist – #AI

AI can analyze data more quickly and accurately than humans, but it can also inherit our biases. To learn, it needs massive quantities of data, and the easiest way to find that data is to feed it text from the internet. But the internet contains some extremely biased language.

A Stanford study found that an internet-trained AI associated stereotypically white names with positive words like “love,” and black names with negative words like “failure” and “cancer.”

The scariest thing about this bias is how invisibly it can take over. According to (Rob Speer, Chief Science Office, Luminoso) “some people [will] go through life not knowing why they get fewer opportunities, fewer job offers, more interactions with the police or the TSA…”

Of course, he points out, racism and sexism are baked into society, and promising technological advances, even when explicitly meant to counteract them, often amplify them. There’s no such thing as an objective tool built on subjective data.

So AI developers bear a huge responsibility to find the flaws in their AI and address them.

“There’s no AI that works like the human brain,” he says. “To counter the hype, I hope we can stop talking about brains and start talking about what’s actually going on: it’s mostly statistics, databases, and pattern recognition. Which shouldn’t make it any less interesting.”

Source: Lifehacker

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A blueprint for coexistence with #AI

In September 2013, I was diagnosed with fourth-stage lymphoma.

This near-death experience has not only changed my life and priorities, but also altered my view of artificial intelligence—the field that captured my selfish attention for all those years.

This personal reformation gave me an enlightened view of what AI should mean for humanity. Many of the recent discussions about AI have concluded that this scientific advance will likely take over the world, dominate humans, and end poorly for mankind.

But my near-death experience has enabled me to envision an alternate ending to the AI story—one that makes the most of this amazing technology while empowering humans not just to survive, but to thrive.

Love is what is missing from machines. That’s why we must pair up with them, to leaven their powers with what only we humans can provide. Your future AI diagnostic tool may well be 10 times more accurate than human doctors, but patients will not want a cold pronouncement from the tool: “You have fourth stage lymphoma and a 70 percent likelihood of dying within five years.” That in itself would be harmful.

Kai-Fu Lee. DAVID PAUL MORRIS/ BLOOMBERG

Patients would benefit, in health and heart, from a “doctor of love” who will spend as much time as the patient needs, always be available to discuss their case, and who will even visit the patients at home. This doctor might encourage us by sharing stories such as, “Kai-Fu had the same lymphoma, and he survived, so you can too.”

This kind of “doctor of love” would not only make us feel better and give us greater confidence, but would also trigger a placebo effect that would increase our likelihood of recuperation. Meanwhile, the AI tool would watch the Q&A between the “doctor of love” and the patient carefully, and then optimize the treatment. If scaled across the world, the number of “doctors of love” would greatly outnumber today’s doctors.

Let us choose to let machines be machines, and let humans be humans. Let us choose to use our machines, and love one another.

Kai-Fu Lee, Ph.D., is the Founder and CEO of Sinovation Ventures and the president of its Artificial Intelligence Institute.

Source: Wired

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#AI ushers in the era of superhuman doctors

One in 10 medical diagnoses is wrong, according to the US Institute of Medicine. In primary care, one in 20 patients will get a wrong diagnosis. Such errors contribute to as many as 80,000 unnecessary deaths each year in the US alone.

These are worrying figures, driven by the complex nature of diagnosis, which can encompass incomplete information from patients, missed hand-offs between care providers, biases that cloud doctors’ judgement, overworked staff, overbooked systems, and more. The process is riddled with opportunities for human error. This is why many want to use the constant and unflappable power of artificial intelligence to achieve more accurate diagnosis, prompt care and greater efficiency.

Source: New Scientist

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The big problem with artificial intelligence

Artificial intelligence algorithms can indeed create a world that distributes resources more efficiently and, in theory, can offer more for everyone.

Yes, but: If we aren’t careful, these same algorithms could actually lead to greater discrimination by codifying the biases that exist both overtly and unconsciously in human society.

What’s more, the power to make these decisions lies in the hands of Silicon Valley, which has a decidedly mixed record on spotting and addressing diversity issues in its midst.

Airbnb’s Mike Curtis put it well when I interviewed him this week at VentureBeat’s MobileBeat conference:

 One of the best ways to combat bias is to be aware of it. When you are aware of the biases then you can be proactive about getting in front of them. Well, computers don’t have that advantage. They can’t be aware of the biases that may have come into them from the data patterns they have seen.”

Concern is growing:

  • The ACLU has raised concerns that age, sex, and race biases are already being codified into the algorithms that power AI.
  • ProPublica found that a computer program used in various regions to decide whom to grant parole would go easy on white offenders while being unduly harsh to black ones.
  • It’s an issue that Weapons of Math Destruction author Cathy O’Neil raised in a popular talk at the TED conference this year. “Algorithms don’t make things fair,” she said. “They automate the status quo.”

Source: Axios

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Inside Microsoft’s Artificial Intelligence Comeback

Yoshua Bengio

[Yoshua Bengio, one of the three intellects who shaped the deep learning that now dominates artificial intelligence, has never been one to take sides. But Bengio has recently chosen to sign on with Microsoft. In this WIRED article he explains why.]

“We don’t want one or two companies, which I will not name, to be the only big players in town for AI,” he says, raising his eyebrows to indicate that we both know which companies he means. One eyebrow is in Menlo Park; the other is in Mountain View. “It’s not good for the community. It’s not good for people in general.”

That’s why Bengio has recently chosen to forego his neutrality, signing on with Microsoft.

Yes, Microsoft. His bet is that the former kingdom of Windows alone has the capability to establish itself as AI’s third giant. It’s a company that has the resources, the data, the talent, and—most critically—the vision and culture to not only realize the spoils of the science, but also push the field forward.

Just as the internet disrupted every existing business model and forced a re-ordering of industry that is just now playing out, artificial intelligence will require us to imagine how computing works all over again.

In this new landscape, computing is ambient, accessible, and everywhere around us. To draw from it, we need a guide—a smart conversationalist who can, in plain written or spoken form, help us navigate this new super-powered existence. Microsoft calls it Cortana.

Because Cortana comes installed with Windows, it has 145 million monthly active users, according to the company. That’s considerably more than Amazon’s Alexa, for example, which can be heard on fewer than 10 million Echoes. But unlike Alexa, which primarily responds to voice, Cortana also responds to text and is embedded in products that many of us already have. Anyone who has plugged a query into the search box at the top of the toolbar in Windows has used Cortana.

Eric Horvitz wants Microsoft to be more than simply a place where research is done. He wants Microsoft Research to be known as a place where you can study the societal and social influences of the technology.

This will be increasingly important as Cortana strives to become, to the next computing paradigm, what your smartphone is today: the front door for all of your computing needs. Microsoft thinks of it as an agent that has all your personal information and can interact on your behalf with other agents.

If Cortana is the guide, then chatbots are Microsoft’s fixers. They are tiny snippets of AI-infused software that are designed to automate one-off tasks you used to do yourself, like making a dinner reservation or completing a banking transaction.

Emma Williams, Marcus Ash, and Lili Cheng

So far, North American teens appear to like chatbot friends every bit as much as Chinese teens, according to the data. On average, they spend 10 hours talking back and forth with Zo. As Zo advises its adolescent users on crushes and commiserates about pain-in-the-ass parents, she is becoming more elegant in her turns of phrase—intelligence that will make its way into Cortana and Microsoft’s bot tools.

It’s all part of one strategy to help ensure that in the future, when you need a computing assist–whether through personalized medicine, while commuting in a self-driving car, or when trying to remember the birthdays of all your nieces and nephews–Microsoft will be your assistant of choice.

Source: Wired for the full in-depth article

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This adorable #chatbot wants to talk about your mental health

Research conducted by the federal government in 2015 found that only 41 percent of U.S. adults with a mental health condition in the previous year had gotten treatment. That dismal treatment rate has to do with cost, logistics, stigma, and being poorly matched with a professional.

Chatbots are meant to remove or diminish these barriers. Creators of mobile apps for depression and anxiety, among other mental health conditions, have argued the same thing, but research found that very few of the apps are based on rigorous science or are even tested to see if they work. 

That’s why Alison Darcy, a clinical psychologist at Stanford University and CEO and founder of Woebot wants to set a higher standard for chatbots. Darcy co-authored a small study published this week in the Journal of Medical Internet Research that demonstrated Woebot can reduce symptoms of depression in two weeks.

Woebot presumably does this in part by drawing on techniques from cognitive behavioral therapy (CBT), an effective form of therapy that focuses on understanding the relationship between thoughts and behavior. He’s not there to heal trauma or old psychological wounds. 

“We don’t make great claims about this technology,” Darcy says. “The secret sauce is how thoughtful [Woebot] is as a CBT therapist. He has a set of core principles that override everything he does.” 

His personality is also partly modeled on a charming combination of Spock and Kermit the Frog.

Jonathan Gratch, director for virtual human research at the USC Institute for Creative Technologies, has studied customer service chatbots extensively and is skeptical of the idea that one could effectively intuit our emotional well-being.  

“State-of-the-art natural language processing is getting increasingly good at individual words, but not really deeply understanding what you’re saying,” he says.

The risk of using a chatbot for your mental health is manifold, Gratch adds.

Darcy acknowledges Woebot’s limitations. He’s only for those 18 and over. If your mood hasn’t improved after six weeks of exchanges, he’ll prompt you to talk about getting a “higher level of care.” Upon seeing signs of suicidal thoughts or behavior, Woebot will provide information for crisis phone, text, and app resources. The best way to describe Woebot, Darcy says, is probably as “gateway therapy.”

“I have to believe that applications like this can address a lot of people’s needs.”

Source: Mashable

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Ensure that #AI charts a course that benefits humanity and bolsters our shared values

AI for Good Global Summit

The United Nations this week is refocusing AI on sustainable development and assisting global efforts to eliminate poverty and hunger, and to protect the environment.

“Artificial Intelligence has the potential to accelerate progress towards a dignified life, in peace and prosperity, for all people,” said UN Secretary-General António Guterres. “The time has arrived for all of us – governments, industry and civil society – to consider how AI will affect our future.”

In a video message to the summit, Mr. Guterres called AI “a new frontier” with “advances moving at warp speed.”

He noted that that while AI is “already transforming our world socially, economically and politically,” there are also serious challenges and ethical issues which must be taken into account – including cybersecurity, human rights and privacy.

“This Summit can help ensure that artificial intelligence charts a course that benefits humanity and bolsters our shared values” 

 Source: UN News Centre

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We Need to Talk About the Power of #AI to Manipulate Humans

Liesl Yearsley is a serial entrepreneur now working on how to make artificial intelligence agents better at problem-solving and capable of forming more human-like relationships.

From 2007 to 2014 I was CEO of Cognea, which offered a platform to rapidly build complex virtual agents … acquired by IBM Watson in 2014.

As I studied how people interacted with the tens of thousands of agents built on our platform, it became clear that humans are far more willing than most people realize to form a relationship with AI software.

I always assumed we would want to keep some distance between ourselves and AI, but I found the opposite to be true. People are willing to form relationships with artificial agents, provided they are a sophisticated build, capable of complex personalization.

We humans seem to want to maintain the illusion that the AI truly cares about us.

This puzzled me, until I realized that in daily life we connect with many people in a shallow way, wading through a kind of emotional sludge. Will casual friends return your messages if you neglect them for a while? Will your personal trainer turn up if you forget to pay them? No, but an artificial agent is always there for you. In some ways, it is a more authentic relationship.

This phenomenon occurred regardless of whether the agent was designed to act as a personal banker, a companion, or a fitness coach. Users spoke to the automated assistants longer than they did to human support agents performing the same function.

People would volunteer deep secrets to artificial agents, like their dreams for the future, details of their love lives, even passwords.

These surprisingly deep connections mean even today’s relatively simple programs can exert a significant influence on people—for good or ill.

Every behavioral change we at Cognea wanted, we got. If we wanted a user to buy more product, we could double sales. If we wanted more engagement, we got people going from a few seconds of interaction to an hour or more a day.

Systems specifically designed to form relationships with a human will have much more power. AI will influence how we think, and how we treat others.

This requires a new level of corporate responsibility. We need to deliberately and consciously build AI that will improve the human condition—not just pursue the immediate financial gain of gazillions of addicted users.

We need to consciously build systems that work for the benefit of humans and society. They cannot have addiction, clicks, and consumption as their primary goal. AI is growing up, and will be shaping the nature of humanity.

AI needs a mother.

Source: MIT Technology Review 



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Tech Giants Grapple with the Ethical Concerns Raised by the #AI Boom

“We’re here at an inflection point for AI. We have an ethical imperative to harness AI to protect and preserve over time.” Eric Horvitz, managing director of Microsoft Research

2017 EmTech panel discussion

One shared concern was that recent advances are leading companies to put software in positions with very direct control over humans—for example in health care.

Francesca Rossi, a researcher at IBM, gave the example of a machine providing assistance or companionship to elderly people. “This robot will have to follow cultural norms that are culture-specific and task-specific,” she said. “[And] if you were to deploy in the U.S. or Japan, that behavior would have to be very different.”

In the past year, many efforts to research the ethical challenges of machine learning and AI have sprung up in academia and industry. The University of California, Berkeley; Harvard; and the Universities of Oxford and Cambridge have all started programs or institutes to work on ethics and safety in AI. In 2016, Amazon, Microsoft, Google, IBM, and Facebook jointly founded a nonprofit called Partnership on AI to work on the problem (Apple joined in January).

Companies are also taking individual action to build safeguards around their technology.

  • Gupta highlighted research at Google that is testing ways to correct biased machine-learning models, or prevent them from becoming skewed in the first place.
  • Horvitz described Microsoft’s internal ethics board for AI, dubbed AETHER, which considers things like new decision algorithms developed for the company’s in-cloud services. Although currently populated with Microsoft employees, in future the company hopes to add outside voices as well.
  • Google has started its own AI ethics board.

Technology Review

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We’re so unprepared for the robot apocalypse

Industrial robots alone have eliminated up to 670,000 American jobs between 1990 and 2007

It seems that after a factory sheds workers, that economic pain reverberates, triggering further unemployment at, say, the grocery store or the neighborhood car dealership.

In a way, this is surprising. Economists understand that automation has costs, but they have largely emphasized the benefits: Machines makes things cheaper, and they free up workers to do other jobs.

The latest study reveals that for manufacturing workers, the process of adjusting to technological change has been much slower and more painful than most experts thought. 

every industrial robot eliminated about three manufacturing positions, plus three more jobs from around town

“We were looking at a span of 20 years, so in that timeframe, you would expect that manufacturing workers would be able to find other employment,” Restrepo said. Instead, not only did the factory jobs vanish, but other local jobs disappeared too.

This evidence draws attention to the losers — the dislocated factory workers who just can’t bounce back

one robot in the workforce led to the loss of 6.2 jobs within a commuting zone where local people travel to work.

The robots also reduce wages, with one robot per thousand workers leading to a wage decline of between 0.25 % and 0.5 % Fortune

.None of these efforts, though, seem to be doing enough for communities that have lost their manufacturing bases, where people have reduced earnings for the rest of their lives.

Perhaps that much was obvious. After all, anecdotes about the Rust Belt abound. But the new findings bolster the conclusion that these economic dislocations are not brief setbacks, but can hurt areas for an entire generation.

How do we even know that automation is a big part of the story at all? A key bit of evidence is that, despite the massive layoffs, American manufacturers are making more stuff than ever. Factories have become vastly more productive.

some consultants believe that the number of industrial robots will quadruple in the next decade, which could mean millions more displaced manufacturing workers

The question, now, is what to do if the period of “maladjustment” that lasts decades, or possibly a lifetime, as the latest evidence suggests.

automation amplified opportunities for people with advanced skills and talents

Source: The Washington Post

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Technology is the main driver of the recent increases in inequality

Artificial Intelligence And Income Inequality

While economists debate the extent to which technology plays a role in global inequality, most agree that tech advances have exacerbated the problem.

Economist Erik Brynjolfsson said,

“My reading of the data is that technology is the main driver of the recent increases in inequality. It’s the biggest factor.”

AI expert Yoshua Bengio suggests that equality and ensuring a shared benefit from AI could be pivotal in the development of safe artificial intelligence. Bengio, a professor at the University of Montreal, explains, “In a society where there’s a lot of violence, a lot of inequality, [then] the risk of misusing AI or having people use it irresponsibly in general is much greater. Making AI beneficial for all is very central to the safety question.”

“It’s almost a moral principle that we should share benefits among more people in society,” argued Bart Selman, a professor at Cornell University … “So we have to go into a mode where we are first educating the people about what’s causing this inequality and acknowledging that technology is part of that cost, and then society has to decide how to proceed.”

Source: HuffPost

 

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DeepMind’s social agenda plays to its AI strengths

DeepMind’s researchers have in common a clearly defined if lofty mission:

to crack human intelligence and recreate it artificially.

Today, the goal is not just to create a powerful AI to play games better than a human professional, but to use that knowledge “for large-scale social impact”, says DeepMind’s other co-founder, Mustafa Suleyman, a former conflict-resolution negotiator at the UN.

“To solve seemingly intractable problems in healthcare, scientific research or energy, it is not enough just to assemble scores of scientists in a building; they have to be untethered from the mundanities of a regular job — funding, administration, short-term deadlines — and left to experiment freely and without fear.”

“if you’re interested in advancing the research as fast as possible, then you need to give [scientists] the space to make the decisions based on what they think is right for research, not for whatever kind of product demand has just come in.”

“Our research team today is insulated from any short-term pushes or pulls, whether it be internally at Google or externally.

We want to have a big impact on the world, but our research has to be protected, Hassabis says.

“We showed that you can make a lot of advances using this kind of culture. I think Google took notice of that and they’re shifting more towards this kind of longer-term research.”

Source: Financial Times

 

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Artificial intelligence is ripe for abuse

Microsoft’s Kate Crawford tells SXSW that society must prepare for authoritarian movements to test the ‘power without accountability’ of AI

As artificial intelligence becomes more powerful, people need to make sure it’s not used by authoritarian regimes to centralize power and target certain populations, Microsoft Research’s Kate Crawford warned on Sunday.

“We want to make these systems as ethical as possible and free from unseen biases.”

In her SXSW session, titled Dark Days: AI and the Rise of Fascism, Crawford, who studies the social impact of machine learning and large-scale data systems, explained ways that automated systems and their encoded biases can be misused, particularly when they fall into the wrong hands.

“Just as we are seeing a step function increase in the spread of AI, something else is happening: the rise of ultra-nationalism, rightwing authoritarianism and fascism,” she said.

One of the key problems with artificial intelligence is that it is often invisibly coded with human biases.

We should always be suspicious when machine learning systems are described as free from bias if it’s been trained on human-generated data,” Crawford said. “Our biases are built into that training data.””

Source: The Gaurdian

 

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Our minds need medical attention, AI may be able to help there

AI could be useful for more than just developing Siri; it may bring about a new, smarter age of healthcare.

A team of researchers successfully predicted diagnoses of autism using MRI data from babies between six and 12 months old.

A team of researchers successfully predicted diagnoses of autism using MRI data from babies between six and 12 months old.

For instance, a team of American researchers used AI to aid detection of autism in babies as young as six months1. This is crucial because the first two years of life see the most neural plasticity when the abnormalities associated with autism haven’t yet fully settled in. This means that earlier intervention is better, especially when many autistic babies are diagnosed at 24 months.

While previous algorithms exist for detecting autism’s development using behavioral data, they have not been effective enough to be clinically useful. This team of researchers sought to improve on these attempts by employing deep learning. Their algorithm successfully predicted diagnoses of autism using MRI data from babies between six and 12 months old. Their system processed images of the babies’ cortical surface area, which grows too rapidly in developing autism. This smarter algorithm predicted autism so well that clinicians may now want to adopt it.

But human ailments aren’t just physical; our minds need medical attention, too. AI may be able to help there as well.

Facebook is beginning to use AI to identify users who may be at risk of suicide, and a startup company just built an AI therapist apparently capable of offering mental health services to anyone with an internet connection.

Source: Machine Design

 

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Humans are born irrational, and that has made us better decision-makers

Facts on their own don’t tell you anything. It’s only paired with preferences, desires, with whatever gives you pleasure or pain, that can guide your behavior. Even if you knew the facts perfectly, that still doesn’t tell you anything about what you should do.”

Even if we were able to live life according to detailed calculations, doing so would put us at a massive disadvantage. This is because we live in a world of deep uncertainty, under which neat logic simply isn’t a good guide.

It’s well-established that data-based decisions doesn’t inoculate against irrationality or prejudice, but even if it was possible to create a perfectly rational decision-making system based on all past experience, this wouldn’t be a foolproof guide to the future.

Courageous acts and leaps of faith are often attempts to overcome great and seemingly insurmountable challenges. (It wouldn’t take much courage if it were easy to do.) But while courage may be irrational or hubristic, we wouldn’t have many great entrepreneurs or works of art without those with a somewhat illogical faith in their own abilities.

There are occasions where overly rational thinking would be highly inappropriate. Take finding a partner, for example. If you had the choice between a good-looking high-earner who your mother approves of, versus someone you love who makes you happy every time you speak to them—well, you’d be a fool not to follow your heart.

And even when feelings defy reason, it can be a good idea to go along with the emotional rollercoaster. After all, the world can be an entirely terrible place and, from a strictly logical perspective, optimism is somewhat irrational.

But it’s still useful. “It can be beneficial not to run around in the world and be depressed all the time,” says Gigerenzer.

Of course, no human is perfect, and there are downsides to our instincts. But, overall, we’re still far better suited to the real world than the most perfectly logical thinking machine.

We’re inescapably irrational, and far better thinkers as a result.

Source: Quartz

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Is Your Doctor Stumped? There’s a Chatbot for That

Doctors have created a chatbot to revolutionize communication within hospitals using artificial intelligence … basically a cyber-radiologist in app form, can quickly and accurately provide specialized information to non-radiologists. And, like all good A.I., it’s constantly learning.

Traditionally, interdepartmental communication in hospitals is a hassle. A clinician’s assistant or nurse practitioner with a radiology question would need to get a specialist on the phone, which can take time and risks miscommunication. But using the app, non-radiologists can plug in common technical questions and receive an accurate response instantly.

“Say a patient has a creatinine [lab test to see how well the kidneys are working]” co-author and application programmer Kevin Seals tells Inverse. “You send a message, like you’re texting with a human radiologist. ‘My patient is a 5.6, can they get a CT scan with contrast?’ A lot of this is pretty routine questions that are easily automated with software, but there’s no good tool for doing that now.”

In about a month, the team plans to make the chatbot available to everyone at UCLA’s Ronald Reagan Medical Center, see how that plays out, and scale up from there. Your doctor may never be stumped again.

Source: Inverse

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An MIT professor explains why we are still a long ways off from solving one of the biggest problems with self-driving cars

“The idea of a robot having an algorithm programmed by some faceless human in a manufacturing plant somewhere making decisions that has life-and-death consequence is very new to us as humans”

Rahwan helped bring it to the surface in October 2015 when he co-wrote a paper “Autonomous vehicles need experimental ethics.”

But the debate arguably got to the forefront of discussion when Rahwan launched “MIT’s Moral Machine” — a website that poses a series of ethical conundrums to crowdsource how people feel self-driving cars should react in tough situations. The Moral Machine is an extension of Rahwan’s 2015 study.

Rahwan said since launching the website in August 2016, MIT has collected 26 million decisions from 3 million people worldwide. He is currently analyzing whether cultural differences play a role in the responses given.

“it’s not about a specific scenario or accident, it’s about the overall principle that an algorithm has to use to decide relative risk”

The National Highway Traffic Safety Administration acknowledged in a September report that self-driving cars could favor certain decisions over others even if they aren’t programmed explicitly to do so.

Self-driving cars will rely on machine learning, a branch of artificial intelligence that allows computers, or in this case cars, to learn over time. Since cars will learn how to adapt to the driving environment on their own, they could learn to favor certain outcomes.

“In the long run, I think something has to be done. There has to be some sort of guideline that’s a bit more specific, that’s the only way to obtain the trust of the public,” he said.

“Even in instances in which no explicit ethical rule or preference is intended, the programming of an HAV may establish an implicit or inherent decision rule with significant ethical consequences,” NHTSA wrote in the report, adding that manufacturers must work with regulators to address these situations.

Rahwan said programming for specific outcomes isn’t the right approach, but thinks companies should be doing more to let the public know that they are considering the ethics of driverless vehicles.

Source: Business Insider

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Will Democracy Survive Big Data and Artificial Intelligence?


We are in the middle of a technological upheaval that will transform the way society is organized. We must make the right decisions now.

In 2016 we produced as much data as in the entire history of humankind through 2015.

It is estimated that in 10 years’ time there will be 150 billion networked measuring sensors, 20 times more than people on Earth. Then, the amount of data will double every 12 hours.

One thing is clear: the way in which we organize the economy and society will change fundamentally. We are experiencing the largest transformation since the end of the Second World War; after the automation of production and the creation of self-driving cars the automation of society is next.

Everything will become intelligent; soon we will not only have smart phones, but also smart homes, smart factories and smart cities. Should we also expect these developments to result in smart nations and a smarter planet?

The field of artificial intelligence is, indeed, making breathtaking advances. Artificial intelligence is no longer programmed line by line, but is now capable of learning, thereby continuously developing itself.

Under the label of “nudging,” and on massive scale, governments are trying to steer citizens towards healthier or more environmentally friendly behaviour by means of a “nudge”—a modern form of paternalism.

The new, caring government is not only interested in what we do, but also wants to make sure that we do the things that it considers to be right. The magic phrase is “big nudging”, which is the combination of big data with nudging.

In a rapidly changing world a super-intelligence can never make perfect decisions (see Fig. 1): systemic complexity is increasing faster than data volumes, which are growing faster than the ability to process them, and data transfer rates are limited.
Furthermore, there is a danger that the manipulation of decisions by powerful algorithms undermines the basis of “collective intelligence,” which can flexibly adapt to the challenges of our complex world. For collective intelligence to work, information searches and decision-making by individuals must occur independently. If our judgments and decisions are predetermined by algorithms, however, this truly leads to a brainwashing of the people. Intelligent beings are downgraded to mere receivers of commands, who automatically respond to stimuli.

We are now at a crossroads. Big data, artificial intelligence, cybernetics and behavioral economics are shaping our society—for better or worse.

We are at the historic moment, where we have to decide on the right path—a path that allows us all to benefit from the digital revolution.

Source: Scientific American

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We’re on the right ladder of #AI this time – Microsoft CEO

Calling AI “the third run time”, Nadella said, “If the operating system was the first run time, the second run time you could say was the browser, and the third run time can actually be the agent. Because in some sense, the agent knows you, your work context, and knows the work. And that’s how we are building Cortana. We are giving it a really natural language understanding.”

AI has been the buzzword at Microsoft for a while now. And the CEO has gone on record to say that it “is at the intersection of our ambitions.” Cortana is an intelligent assistant (agent) that “can take text input, can take speech input, and that knows you deeply.”

“We should not claim that artificial general intelligence is just around the corner,” he said. “I think we are on the right ladder this time… We are all grounded in where we are. Ultimately, the real challenge is human language understanding that still doesn’t exist. We are not even close to it... We just have to keep taking steps on that ladder.”

Source: Mashable

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Artificial intelligence set to transform the patient experience

Catalia developed a small robot, the Mabu Personal Healthcare Companion, aimed at assisting with “long-term patient engagement.” It’s able to have tailored conversations with patients that can evolve over time as the platform – developed using principles of behavioral psychology – gains daily data about treatment plans, health challenges and outcomes.

Catalia’s technology deploys AI to help patients manage their own chronic conditions.

“The kinds of algorithms we’re developing, we’re building up psychological models of patients with every encounter,” he explained. “We start with two types of psychologies: The psychology of relationships – how people develop relationships over time – as well as the psychology of  behavior change: How do we chose the right technique to use with this person right now?” Cory Kidd, CEO of Catalia Health

The platform also gets “smarter” as it become more attuned to “what we call our biographical model, which is kind of a catch-all for everything else we learn in conversation,” he said. “This man has a couple cats, this woman’s son calls her every Sunday afternoon, whatever it might be that we’ll use later in conversations.”

‘We’re not trying to replace the human interaction, we’re trying to augment it,’ AI developer says.

Kleinberg (managing director at The Advisory Board Company) pointed to AI pilots where patients paired with humanoid robots “felt a sense of loss” after the test ended. “One woman followed the robot out and waved goodbye to it.”

On the other, “some people are horrified that we would be letting machines play a part in a role that should be played by humans,” he said.

The big question, then: “Do we have place now for society and a system such as this?” he asked.

Source: Healthcare IT News

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Smartphones to become pocket doctors to diagnose illness

Smartphones will soon become mobile laboratories which can monitor bone density, calculate red blood cell levels and even predict if an asthma attack is imminent.

Scientists are repurposing the technology which already exists within phones, such as accelerometers, camera flashes and microphones to use as medical tools.

Professor Shwetak Patel, of the University of Washington is currently devising an app which can detect red blood cell levels simply by placing a finger over the camera and flash, so that a bright beam of light shines through the skin. Such a blood screening tool could quickly spot anaemia.

“You can do pulmonary assessment using the microphone on a mobile device, for diagnosing asthma. If think about people having an asthma attack, if you could monitor their lung function at home you can actually get in front of that, before somebody has an asthma attack.”

Source: The Telegraph

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Artificial Intelligence & Bias

On Thursday, February 16th, the JFK Jr. Forum at the Harvard Institute of Politics hosted a conversation on the past, present, and future of Artificial Intelligence

The conversation focused on the potential benefits of Artificial Intelligence as well as some of the major ethical dilemmas that these experts predicted. While Artificial Intelligence (AI) has the potential to eliminate inherent human bias in decision-making, the panel agreed that in the near future, there are ethical boundaries that society and governments must explore as Artificial Intelligence expands into the realms of medicine, governance, and even self-driving cars.

Some major takeaways from the event were:

1. Artificial Intelligence offers an incredible opportunity to eliminate human biases in decision-making

2. Society must begin having conversations surrounding the ethics of Artificial Intelligence

Professors Alex Pentland and Cynthia Dwork stated that as Artificial Intelligence proliferates, moral conflicts can surface. Pentland emphasized that citizens must ask themselves “is this something that is performing in a way that we as a society want?” Pentland noted that our society must continue a dialogue around ethics and determine what is right.

3. Although Artificial Intelligence is growing, there are still tasks that only humans should do

Source: The Huffington Post

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You’ll give an infant an intelligent toy that learns about her and tutors her and grows along with her

Spivack, the futurist, pictures people partnering with lifelong virtual companions. You’ll give an infant an intelligent toy that learns about her and tutors her and grows along with her. “It starts out as a little cute stuffed animal,” he says, “but it evolves into something that lives in the cloud and they access on their phone. And then by 2050 or whatever, maybe it’s a brain implant.” Among the many questions raised by such a scenario, Spivack asks: “Who owns our agents? Are they a property of Google?” Could our oldest friends be revoked or reprogrammed at will? And without our trusted assistants, will we be helpless?

El Kaliouby, of Affectiva, sees a lot of questions around autonomy: What can an assistant do on our behalf? Should it be able to make purchases for us? What if we ask it to do something illegal—could it override our commands? She also worries about privacy. If an AI agent determines that a teenager is depressed, can it inform his parents? Spivack says we’ll need to decide whether agents have something like doctor-patient or attorney-client privilege. Can they report us to law enforcement? Can they be subpoenaed? And what if there’s a security breach? Some people worry that advanced AI will take over the world, but Kambhampati, of the Association for the Advancement of Artificial Intelligence, thinks malicious hacking is the far greater risk.

Given the intimacy that we may develop with our ever-present assistants, if the wrong person were able to break in, what was once our greatest auxiliary could become our greatest liability.

Source: The Atlantic

 

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Microsoft’s new plan is to flood your entire life with artificial intelligence

The mission is clear:

if there’s success to be had with any kind of AI, Microsoft wants to be there.

And then yesterday, at an intimate press gathering in San Francisco, Microsoft’s AI parade continued! The company announced:

  • an Cortana-powered smart speaker to rival the Amazon Echo and Google Home, made by Harman Kardon
  • a virtual assistant that lives in your email to help schedule meetings (like x.ai)
  • a new English-speaking chatbot to replace Tay, called Zo
  • a new tool for real-time conversation translation
  • a software developer kit for Cortana for anybody who wants to configure it for a smart speaker or gadget

 You can look forward to living a life in constant conversation with your gadgets.

You’ll be able to chat with bots throughout the day via Kik, Skype or Facebook Messenger for customer service, ask your Cortana-enabled speaker to turn on your lights, and then to tell you if it scheduled plans for you tonight. Rather than navigating densely-packed menus dripping with options for customization, you can ask questions and trust the virtual assistant to lead you to whatever task you want to accomplish.

Microsoft has coined their own term for this: conversational computing. The company sees this shift to be as large as personal or mobile computing

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