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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

DeepMind Ethics and Society hallmark of a change in attitude

The unit, called DeepMind Ethics and Society, is not the AI Ethics Board that DeepMind was promised when it agreed to be acquired by Google in 2014. That board, which was convened by January 2016, was supposed to oversee all of the company’s AI research, but nothing has been heard of it in the three-and-a-half years since the acquisition. It remains a mystery who is on it, what they discuss, or even whether it has officially met.

DeepMind Ethics and Society is also not the same as DeepMind Health’s Independent Review Panel, a third body set up by the company to provide ethical oversight – in this case, of its specific operations in healthcare.

Nor is the new research unit the Partnership on Artificial Intelligence to Benefit People and Society, an external group founded in part by DeepMind and chaired by the company’s co-founder Mustafa Suleyman. That partnership, which was also co-founded by Facebook, Amazon, IBM and Microsoft, exists to “conduct research, recommend best practices, and publish research under an open licence in areas such as ethics, fairness and inclusivity”.

Nonetheless, its creation is the hallmark of a change in attitude from DeepMind over the past year, which has seen the company reassess its previously closed and secretive outlook. It is still battling a wave of bad publicity started when it partnered with the Royal Free in secret, bringing the app Streams to active use in the London hospital without being open to the public about what data was being shared and how.

The research unit also reflects an urgency on the part of many AI practitioners to get ahead of growing concerns on the part of the public about how the new technology will shape the world around us.

Source: The Guardian



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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


Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Intelligent Machines Forget Killer Robots—Bias Is the Real AI Danger

John Giannandrea – GETTY

John Giannandrea, who leads AI at Google, is worried about intelligent systems learning human prejudices.

… concerned about the danger that may be lurking inside the machine-learning algorithms used to make millions of decisions every minute.

The real safety question, if you want to call it that, is that if we give these systems biased data, they will be biased

The problem of bias in machine learning is likely to become more significant as the technology spreads to critical areas like medicine and law, and as more people without a deep technical understanding are tasked with deploying it. Some experts warn that algorithmic bias is already pervasive in many industries, and that almost no one is making an effort to identify or correct it.

Karrie Karahalios, a professor of computer science at the University of Illinois, presented research highlighting how tricky it can be to spot bias in even the most commonplace algorithms. Karahalios showed that users don’t generally understand how Facebook filters the posts shown in their news feed. While this might seem innocuous, it is a neat illustration of how difficult it is to interrogate an algorithm.

Facebook’s news feed algorithm can certainly shape the public perception of social interactions and even major news events. Other algorithms may already be subtly distorting the kinds of medical care a person receives, or how they get treated in the criminal justice system.

This is surely a lot more important than killer robots, at least for now.

Source: MIT Technology Review



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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


Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

The Growing #AI Emotion Reading Tech Challenge

PL – The challenge of an AI using Emotion Reading Tech just got dramatically more difficult.

A new study identifies 27 categories of emotion and shows how they blend together in our everyday experience.

Psychology once assumed that most human emotions fall within the universal categories of happiness, sadness, anger, surprise, fear, and disgust. But a new study from Greater Good Science Center faculty director Dacher Keltner suggests that there are at least 27 distinct emotions—and they are intimately connected with each other.

“We found that 27 distinct dimensions, not six, were necessary to account for the way hundreds of people reliably reported feeling in response to each video”

Moreover, in contrast to the notion that each emotional state is an island, the study found that “there are smooth gradients of emotion between, say, awe and peacefulness, horror and sadness, and amusement and adoration,” Keltner said.

“We don’t get finite clusters of emotions in the map because everything is interconnected,” said study lead author Alan Cowen, a doctoral student in neuroscience at UC Berkeley.

“Emotional experiences are so much richer and more nuanced than previously thought.”

Source: Mindful

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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)



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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.

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Artificial intelligence ethics the same as other new technology – #AI

AI gives us the power to solve problems more efficiently and effectively.

Just as a calculator is more efficient at math than a human, various forms of AI might be better than humans at other tasks. For example, most car accidents are caused by human error – what if driving could be automated and human error thus removed? Tens of thousands of lives might be saved every year, and huge sums of money saved in healthcare costs and property damage averted.

Moving into the future, AI might be able to better personalize education to individual students, just as adaptive testing evaluates students today. AI might help figure out how to increase energy efficiency and thus save money and protect the environment. It might increase efficiency and prediction in healthcare; improving health while saving money. Perhaps AI could even figure out how to improve law and government, or improve moral education. For every problem that needs a solution, AI might help us find it.

But as human beings, we should not be so much thinking about efficiency as morality.

Doing the right thing is sometimes “inefficient” (whatever efficiency might mean in a certain context). Respecting human dignity is sometimes inefficient. And yet we should do the right thing and respect human dignity anyway, because those moral values are higher than mere efficiency.

Ultimately, AI gives us just what all technology does – better tools for achieving what we want.

The deeper question then becomes “what do we want?” and even more so “what should we want?” If we want evil, then evil we shall have, with great efficiency and abundance. If instead we want goodness, then through diligent pursuit we might be able to achieve it.

Source: Crux

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

#AI data-monopoly risks to be probed by UK parliamentarians

Among the questions the House of Lords committee will consider as part of the enquiry are:

  • How can the data-based monopolies of some large corporations, and the ‘winner-takes-all’ economics associated with them, be addressed?
  • What are the ethical implications of the development and use of artificial intelligence?
  • In what situations is a relative lack of transparency in artificial intelligence systems (so-called ‘black boxing’) acceptable?
  • What role should the government take in the development and use of artificial intelligence in the UK?
  • Should artificial intelligence be regulated?

The Committee wants to use this inquiry to understand what opportunities exist for society in the development and use of artificial intelligence, as well as what risks there might be.

“We are looking to be pragmatic in our approach, and want to make sure our recommendations to government and others will be practical and sensible.

There are significant questions to address relevant to both the present and the future, and we want to help inform the answers to them. To do this, we need the help of the widest range of people and organisations.”

Source: Techcrunch

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Microsoft is forming a grand army of experts in the #AI wars with Google, Facebook, and Amazon

Microsoft announces the creation of Microsoft Research AI, a dedicated unit within its global Microsoft Research division that will focus exclusively on how to make the company’s software smarter, now and in the future.

The difference now, Microsoft Research Labs director Eric Horvitz tells Business Insider, is that this new organization will bring roughly 100 of those experts under one figurative roof. By bringing them together, Microsoft’s AI team can do more, faster.

Horvitz describes the formation of Microsoft Research AI as a “key strategic effort;’ a move that is “absolutely critical” as artificial intelligence becomes increasingly important to the future of technology.

Artificial intelligence carries a lot of power, and a lot of responsibility.

That’s why Microsoft has also announced the formation of Aether (AI and ethics in engineering and research), a board of executives drawn from across every division of the company, including lawyers. The idea, says Horvitz, is to spot issues and potential abuses of AI before they start.

Similarly, Microsoft’s AI design guide is designed to help engineers build systems that augment what humans can do, without making them feel obsolete. Otherwise, people might start to feel like machines are piloting them, rather than the other way around. That’s why it’s so key that apps like Cortana feel warm and relatable.

“Oh my goodness, those computers better talk to us in a way that’s friendly and approachable,” says Microsoft General Manager Emma Williams, in charge of the group behind the design guide. “As people, we have the control.”

Source: Business Insider

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Ethics And Artificial Intelligence With IBM Watson’s Rob High – #AI

In the future, chatbots should and will be able to go deeper to find the root of the problem.

For example, a person asking a chatbot what her bank balance is might be asking the question because she wants to invest money or make a big purchase—a futuristic chatbot could find the real reason she is asking and turn it into a more developed conversation.

In order to do that, chatbots will need to ask more questions and drill deeper, and humans need to feel comfortable providing their information to machines.

As chatbots perform various tasks and become a more integral part of our lives, the key to maintaining ethics is for chatbots to provide proof of why they are doing what they are doing. By showcasing proof or its method of calculations, humans can be confident that AI had reasoning behind its response instead of just making something up.

The future of technology is rooted in artificial intelligence. In order to stay ethical, transparency, proof, and trustworthiness need to be at the root of everything AI does for companies and customers. By staying honest and remembering the goals of AI, the technology can play a huge role in how we live and work.

Source: Forbes

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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 



Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Tech Reckons With the Problems It Helped Create

Festival goer is seen at the 2017 SXSW Conference and Festivals in Austin, Texas.

SXSW’s – this year, the conference itself feels a lot like a hangover.

It’s as if the coastal elites who attend each year finally woke up with a serious case of the Sunday scaries, realizing that the many apps, platforms, and doodads SXSW has launched and glorified over the years haven’t really made the world a better place. In fact, they’ve often come with wildly destructive and dangerous side effects. Sure, it all seemed like a good idea in 2013!

But now the party’s over. It’s time for the regret-filled cleanup.

speakers related how the very platforms that were meant to promote a marketplace of ideas online have become filthy junkyards of harassment and disinformation.

Yasmin Green, who leads an incubator within Alphabet called Jigsaw, focused her remarks on the rise of fake news, and even brought two propaganda publishers with her on stage to explain how, and why, they do what they do. For Jestin Coler, founder of the phony Denver Guardian, it was an all too easy way to turn a profit during the election.

“To be honest, my mortgage was due,” Coler said of what inspired him to write a bogus article claiming an FBI agent related to Hillary Clinton’s email investigation was found dead in a murder-suicide. That post was shared some 500,000 times just days before the election.

While prior years’ panels may have optimistically offered up more tech as the answer to what ails tech, this year was decidedly short on solutions.

There seemed to be, throughout the conference, a keen awareness of the limits human beings ought to place on the software that is very much eating the world.

Source: Wired

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

The last things that will make us uniquely human

What will be my grandson’s place in a world where machines trounce us in one area after another?

Some are worried that self-driving cars and trucks may displace millions of professional drivers (they are right), and disrupt entire industries (yup!). But I worry about my six-year-old son. What will his place be in a world where machines trounce us in one area after another? What will he do, and how will he relate to these ever-smarter machines? What will be his and his human peers’ contribution to the world he’ll live in?

He’ll never calculate faster, or solve a math equation quicker. He’ll never type faster, never drive better, or even fly more safely. He may continue to play chess with his friends, but because he’s a human he will no longer stand a chance to ever become the best chess player on the planet. He might still enjoy speaking multiple languages (as he does now), but in his professional life that may not be a competitive advantage anymore, given recent improvements in real-time machine translation.

So perhaps we might want to consider qualities at a different end of the spectrum: radical creativity, irrational originality, even a dose of plain illogical craziness, instead of hard-nosed logic. A bit of Kirk instead of Spock.

Actually, it all comes down to a fairly simple question: What’s so special about us, and what’s our lasting value? It can’t be skills like arithmetic or typing, which machines already excel in. Nor can it be rationality, because with all our biases and emotions we humans are lacking.

So far, machines have a pretty hard time emulating these qualities: the crazy leaps of faith, arbitrary enough to not be predicted by a bot, and yet more than simple randomness. Their struggle is our opportunity.

So we must aim our human contribution to this division of labour to complement the rationality of the machines, rather than to compete with it. Because that will sustainably differentiate us from them, and it is differentiation that creates value.

Source: BBC  Viktor Mayer-Schonberger is Professor of Internet Governance and Regulation at the Oxford Internet Institute, University of Oxford.

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

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

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

So long, banana-condom demos: Sex and drug education could soon come from chatbots

“Is it ok to get drunk while I’m high on ecstasy?” “How can I give oral sex without getting herpes?” Few teenagers would ask mom or dad these questions—even though their life could quite literally depend on it.

Talking to a chatbot is a different story. They never raise an eyebrow. They will never spill the beans to your parents. They have no opinion on your sex life or drug use. But that doesn’t mean they can’t take care of you.

Bots can be used as more than automated middlemen in business transactions: They can meet needs for emotional human intervention when there aren’t enough humans who are willing or able to go around.

In fact, there are times when the emotional support of a bot may even be preferable to that of a human.

In 2016, AI tech startup X2AI built a psychotherapy bot capable of adjusting its responses based on the emotional state of its patients. The bot, Karim, is designed to help grief- and PTSD-stricken Syrian refugees, for whom the demand (and price) of therapy vastly overwhelms the supply of qualified therapists.

From X2AI test runs using the bot with Syrians, they noticed that technologies like Karim offer something humans cannot:

For those in need of counseling but concerned with the social stigma of seeking help, a bot can be comfortingly objective and non-judgmental.

Bzz is a Dutch chatbot created precisely to answer questions about drugs and sex. When surveyed teens were asked to compare Bzz to finding answers online or calling a hotline, Bzz won. Teens could get their answers faster with Bzz than searching on their own, and they saw their conversations with the bot as more confidential because no human was involved and no tell-tale evidence was left in a search history.

Because chatbots can efficiently gain trust and convince people to confide personal and illicit information in them, the ethical obligations of such bots are critical, but still ambiguous.

Source: Quartz

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Microsoft Ventures: Making the long bet on AI + people

Another significant commitment by Microsoft to democratize AI:

a new Microsoft Ventures fund for investment in AI companies focused on inclusive growth and positive impact on society.

Companies in this fund will help people and machines work together to increase access to education, teach new skills and create jobs, enhance the capabilities of existing workforces and improve the treatment of diseases, to name just a few examples.

CEO Satya Nadella outlined principles and goals for AI: AI must be designed to assist humanity; be transparent; maximize efficiency without destroying human dignity; provide intelligent privacy and accountability for the unexpected; and be guarded against biases. These principles guide us as we move forward with this fund.

Source: Microsoft blog

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Teaching an Algorithm to Understand Right and Wrong

hbr-ai-morals

Aristotle states that it is a fact that “all knowledge and every pursuit aims at some good,” but then continues, “What then do we mean by the good?” That, in essence, encapsulates the ethical dilemma.

We all agree that we should be good and just, but it’s much harder to decide what that entails.

“We need to decide to what extent the legal principles that we use to regulate humans can be used for machines. There is a great potential for machines to alert us to bias. We need to not only train our algorithms but also be open to the possibility that they can teach us about ourselves.” – Francesca Rossi, an AI researcher at IBM

Since Aristotle’s time, the questions he raised have been continually discussed and debated. 

Today, as we enter a “cognitive era” of thinking machines, the problem of what should guide our actions is gaining newfound importance. If we find it so difficult to denote the principles by which a person should act justly and wisely, then how are we to encode them within the artificial intelligences we are creating? It is a question that we need to come up with answers for soon.

Cultural Norms vs. Moral Values

Another issue that we will have to contend with is that we will have to decide not only what ethical principles to encode in artificial intelligences but also how they are coded. As noted above, for the most part, “Thou shalt not kill” is a strict principle. Other than a few rare cases, such as the Secret Service or a soldier, it’s more like a preference that is greatly affected by context.

What makes one thing a moral value and another a cultural norm? Well, that’s a tough question for even the most-lauded human ethicists, but we will need to code those decisions into our algorithms. In some cases, there will be strict principles; in others, merely preferences based on context. For some tasks, algorithms will need to be coded differently according to what jurisdiction they operate in.

Setting a Higher Standard

Most AI experts I’ve spoken to think that we will need to set higher moral standards for artificial intelligences than we do for humans.

Major industry players, such as Google, IBM, Amazon, and Facebook, recently set up a partnership to create an open platform between leading AI companies and stakeholders in academia, government, and industry to advance understanding and promote best practices. Yet that is merely a starting point.

Source: Harvard Business Review

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Microsoft is partnering with Elon Musk’s $1 billion #AI research company to help it battle Amazon and Google

elon-musk-robotsMicrosoft has announced a new partnership with OpenAI, the $1 billion artificial intelligence research nonprofit cofounded by Tesla CEO Elon Musk and Y Combinator President Sam Altman.

Artificial intelligence is going to be a big point of competition between Microsoft Azure, the leading Amazon Web Services, and the relative upstart Google Cloud over the months and years to come. As Guthrie says, “any application is ultimately going to weave in AI,” and Microsoft wants to be the company that helps developers do the weaving.

That’s where the OpenAI partnership becomes so important, Guthrie says.

Bscott-guthrie-photoecause we’re still in the earliest days of artificial intelligence, he says, the biggest challenge is figuring out what exactly can be done with artificial intelligence. Guthrie calls this “understanding the art of the possible.

Source: Business Insider

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Cambridge students build a ‘lawbot’ to advise sexual assault victims #AI

cambridge-law-bot

“Hi, I’m LawBot, a robot designed to help victims of crime in England.”

While volunteering at a school sexual consent class, Ludwig Bull, a law student at the University of Cambridge, was inspired to build a chatbot that offers free legal advice to students. He enlisted the help of four coursemates, and Lawbot was designed and built in just six weeks.

The program is still in beta, but Bull hopes it will help victims of crime, at Cambridge and beyond, to get justice.

“A victim can talk to our artificially intelligent chatbot, receive a preliminary assessment of their situation, and then decide which available actions to pursue”

Source: The Gaurdian

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

The Christianizing of AI

Bloggers note: The following post illustrates the challenge in creating ethics for AI. There are many different faiths, with different belief systems. How would the AI be programmed to serve these diverse ethical needs? 

The ethics of artificial intelligence (AI) has drawn comments from the White House and British House of Commons in recent weeks, along with a nonprofit organization established by Amazon, Google, Facebook, IBM and Microsoft. Now, Baptist computer scientists have called Christians to join the discussion.

Louise Perkins, professor of computer science at California Baptist University, told Baptist Press she is “quite worried” at the lack of an ethical code related to AI. The Christian worldview, she added, has much to say about how automated devices should be programmed to safeguard human flourishing.

Individuals with a Christian worldview need to be involved in designing and programing AI systems, Perkins said, to help prevent those systems from behaving in ways that violate the Bible’s ethical standards.

Believers can thus employ “the mathematics or the logic we will be using to program these devices” to “infuse” a biblical worldview “into an [AI] system.” 

Perkins also noted that ethical standards will have to be programmed into AI systems involved in surgery and warfare among other applications. A robot performing surgery on a pregnant woman, for instance, could have to weigh the life of the baby relative to the life of the mother, and an AI weapon system could have to apply standards of just warfare.

Source: The Pathway

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

12 Observations About Artificial Intelligence From The O’Reilly AI Conference

12-observations-ai-forbesBloggers: Here’s a few excepts from a long but very informative review. (The best may be last.)

The conference was organized by Ben Lorica and Roger Chen with Peter Norvig and Tim O-Reilly acting as honorary program chairs.   

For a machine to act in an intelligent way, said [Yann] LeCun, it needs “to have a copy of the world and its objective function in such a way that it can roll out a sequence of actions and predict their impact on the world.” To do this, machines need to understand how the world works, learn a large amount of background knowledge, perceive the state of the world at any given moment, and be able to reason and plan.

Peter Norvig explained the reasons why machine learning is more difficult than traditional software: “Lack of clear abstraction barriers”—debugging is harder because it’s difficult to isolate a bug; “non-modularity”—if you change anything, you end up changing everything; “nonstationarity”—the need to account for new data; “whose data is this?”—issues around privacy, security, and fairness; lack of adequate tools and processes—exiting ones were developed for traditional software.

AI must consider culture and context—“training shapes learning”

“Many of the current algorithms have already built in them a country and a culture,” said Genevieve Bell, Intel Fellow and Director of Interaction and Experience Research at Intel. As today’s smart machines are (still) created and used only by humans, culture and context are important factors to consider in their development.

Both Rana El Kaliouby (CEO of Affectiva, a startup developing emotion-aware AI) and Aparna Chennapragada (Director of Product Management at Google) stressed the importance of using diverse training data—if you want your smart machine to work everywhere on the planet it must be attuned to cultural norms.

“Training shapes learning—the training data you put in determines what you get out,” said Chennapragada. And it’s not just culture that matters, but also context

The £10 million Leverhulme Centre for the Future of Intelligence will explore “the opportunities and challenges of this potentially epoch-making technological development,” namely AI. According to The Guardian, Stephen Hawking said at the opening of the Centre,

“We spend a great deal of time studying history, which, let’s face it, is mostly the history of stupidity. So it’s a welcome change that people are studying instead the future of intelligence.”

Gary Marcus, professor of psychology and neural science at New York University and cofounder and CEO of Geometric Intelligence,

 “a lot of smart people are convinced that deep learning is almost magical—I’m not one of them …  A better ladder does not necessarily get you to the moon.”

Tom Davenport added, at the conference: “Deep learning is not profound learning.”

AI changes how we interact with computers—and it needs a dose of empathy

AI continues to be possibly hampered by a futile search for human-level intelligence while locked into a materialist paradigm

Maybe, just maybe, our minds are not computers and computers do not resemble our brains?  And maybe, just maybe, if we finally abandon the futile pursuit of replicating “human-level AI” in computers, we will find many additional–albeit “narrow”–applications of computers to enrich and improve our lives?

Gary Marcus complained about research papers presented at the Neural Information Processing Systems (NIPS) conference, saying that they are like alchemy, adding a layer or two to a neural network, “a little fiddle here or there.” Instead, he suggested “a richer base of instruction set of basic computations,” arguing that “it’s time for genuinely new ideas.”

Is it possible that this paradigm—and the driving ambition at its core to play God and develop human-like machines—has led to the infamous “AI Winter”? And that continuing to adhere to it and refusing to consider “genuinely new ideas,” out-of-the-dominant-paradigm ideas, will lead to yet another AI Winter?

 Source: Forbes

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

MIT makes breakthrough in morality-proofing artificial intelligence

mit-morality-breakthroughResearchers at MIT are investigating ways of making artificial neural networks more transparent in their decision-making.

As they stand now, artificial neural networks are a wonderful tool for discerning patterns and making predictions. But they also have the drawback of not being terribly transparent. The beauty of an artificial neural network is its ability to sift through heaps of data and find structure within the noise.

This is not dissimilar from the way we might look up at clouds and see faces amidst their patterns. And just as we might have trouble explaining to someone why a face jumped out at us from the wispy trails of a cirrus cloud formation, artificial neural networks are not explicitly designed to reveal what particular elements of the data prompted them to decide a certain pattern was at work and make predictions based upon it.

We tend to want a little more explanation when human lives hang in the balance — for instance, if an artificial neural net has just diagnosed someone with a life-threatening form of cancer and recommends a dangerous procedure. At that point, we would likely want to know what features of the person’s medical workup tipped the algorithm in favor of its diagnosis.

MIT researchers Lei, Barzilay, and Jaakkola designed a neural network that would be forced to provide explanations for why it reached a certain conclusion.

Source: Extremetech

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

China’s plan to organize its society relies on ‘big data’ to rate everyone

china-social-credits-scoreImagine a world where an authoritarian government monitors everything you do, amasses huge amounts of data on almost every interaction you make, and awards you a single score that measures how “trustworthy” you are.

In this world, anything from defaulting on a loan to criticizing the ruling party, from running a red light to failing to care for your parents properly, could cause you to lose points. 

This is not the dystopian superstate of Steven Spielberg’s “Minority Report,” in which all-knowing police stop crime before it happens. But it could be China by 2020.

And in this world, your score becomes the ultimate truth of who you are — determining whether you can borrow money, get your children into the best schools or travel abroad; whether you get a room in a fancy hotel, a seat in a top restaurant — or even just get a date.

It is the scenario contained in China’s ambitious plans to develop a far-reaching social credit system, a plan that the Communist Party hopes will build a culture of “sincerity” and a “harmonious socialist society” where “keeping trust is glorious.”

The ambition is to collect every scrap of information available online about China’s companies and citizens in a single place — and then assign each of them a score based on their political, commercial, social and legal “credit.”

Mobile device usage and e-commerce are in wide use in China, and now the Communist Party wants to compile a “social credit” score based on citizens’ every activity. (Michael Robinson Chavez/The Washington Post)

Mobile device usage and e-commerce are in wide use in China, and now the Communist Party wants to compile a “social credit” score based on citizens’ every activity. (Michael Robinson Chavez/The Washington Post)

Source: The Washington Post

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

New Research Center to Explore Ethics of Artificial Intelligence

carnegie-mellon-ethics

The Chimp robot, built by a Carnegie Mellon team, took third place in a competition held by DARPA last year. The school is starting a research center focused on the ethics of artificial intelligence. Credit Chip Somodevilla/Getty Images

Carnegie Mellon University plans to announce on Wednesday that it will create a research center that focuses on the ethics of artificial intelligence.

The ethics center, called the K&L Gates Endowment for Ethics and Computational Technologies, is being established at a time of growing international concern about the impact of A.I. technologies.

“We are at a unique point in time where the technology is far ahead of society’s ability to restrain it”
Subra Suresh, Carnegie Mellon’s president

The new center is being created with a $10 million gift from K&L Gates, an international law firm headquartered in Pittsburgh.

Peter J. Kalis, chairman of the law firm, said the potential impact of A.I. technology on the economy and culture made it essential that as a society we make thoughtful, ethical choices about how the software and machines are used.

“Carnegie Mellon resides at the intersection of many disciplines,” he said. “It will take a synthesis of the best thinking of all of these disciplines for society to define the ethical constraints on the emerging A.I. technologies.”

Source: NY Times

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Genetically engineered humans will arrive sooner than you think. And we’re not ready

vox-geneticaly-engineered-humansMichael Bess is a historian of science at Vanderbilt University and the author of a fascinating new book, Our Grandchildren Redesigned: Life in a Bioengineered Society. Bess’s book offers a sweeping look at our genetically modified future, a future as terrifying as it is promising.

“What’s happening is bigger than any one of us”

We single out the industrial revolutions of the past as major turning points in human history because they marked major ways in which we changed our surroundings to make our lives easier, better, longer, healthier.

So these are just great landmarks, and I’m comparing this to those big turning points because now the technology, instead of being applied to our surroundings — how we get food for ourselves, how we transport things, how we shelter ourselves, how we communicate with each other — now those technologies are being turned directly on our own biology, on our own bodies and minds.

And so, instead of transforming the world around ourselves to make it more what we wanted it to be, now it’s becoming possible to transform ourselves into whatever it is that we want to be. And there’s both power and danger in that, because people can make terrible miscalculations, and they can alter themselves, maybe in ways that are irreversible, that do irreversible harm to the things that really make their lives worth living.

“We’re going to give ourselves a power that we may not have the wisdom to control very well”

I think most historians of technology … see technology and society as co-constructing each other over time, which gives human beings a much greater space for having a say in which technologies will be pursued and what direction we will take, and how much we choose to have them come into our lives and in what ways.

 Source: Vox

vox-genetically-enginnered-humans

 

vox-genetically-enginnered-humans

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Artificial Intelligence’s White Guy Problem

nyt-white-guy-problem

Credit Bianca Bagnarelli

Warnings by luminaries like Elon Musk and Nick Bostrom about “the singularity” — when machines become smarter than humans — have attracted millions of dollars and spawned a multitude of conferences.

But this hand-wringing is a distraction from the very real problems with artificial intelligence today, which may already be exacerbating inequality in the workplace, at home and in our legal and judicial systems.

Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many “intelligent” systems that shape how we are categorized and advertised to.

A very serious example was revealed in an investigation published last month by ProPublica. It found that widely used software that assessed the risk of recidivism in criminals was twice as likely to mistakenly flag black defendants as being at a higher risk of committing future crimes. It was also twice as likely to incorrectly flag white defendants as low risk.

The reason those predictions are so skewed is still unknown, because the company responsible for these algorithms keeps its formulas secret — it’s proprietary information. Judges do rely on machine-driven risk assessments in different ways — some may even discount them entirely — but there is little they can do to understand the logic behind them.

Histories of discrimination can live on in digital platforms, and if they go unquestioned, they become part of the logic of everyday algorithmic systems.

Another scandal emerged recently when it was revealed that Amazon’s same-day delivery service was unavailable for ZIP codes in predominantly black neighborhoods. The areas overlooked were remarkably similar to those affected by mortgage redlining in the mid-20th century. Amazon promised to redress the gaps, but it reminds us how systemic inequality can haunt machine intelligence.

And then there’s gender discrimination. Last July, computer scientists at Carnegie Mellon University found that women were less likely than men to be shown ads on Google for highly paid jobs. The complexity of how search engines show ads to internet users makes it hard to say why this happened — whether the advertisers preferred showing the ads to men, or the outcome was an unintended consequence of the algorithms involved.

Regardless, algorithmic flaws aren’t easily discoverable: How would a woman know to apply for a job she never saw advertised? How might a black community learn that it were being overpoliced by software?

Like all technologies before it, artificial intelligence will reflect the values of its creators.

Source: New York Times – Kate Crawford is a principal researcher at Microsoft and co-chairwoman of a White House symposium on society and A.I.

test

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

AI is one of top 5 tools humanity has ever had

 A few highlights from AI panel at the White House Frontiers Conference

On the impact of AI

Andrew McAfee (MIT):

white-house-frontiers-ai-panel

To view video, click on pic, scroll down the page to Live Stream and click to start the video. It may take a min and then go to the time you want to watch.

(Begins @ 2:40:34)

We are at an inflection point … I think the development of these kinds of [AI] tools are going to rank among probably the top 5 tools humanity has ever had to take better care of each other and to tread more lightly on the planet … top 5 in our history. Like the book, maybe, the steam engine, maybe, written language — I might put the Internet there. We’ve all got our pet lists of the biggest inventions ever. AI needs to be on the very, very, short list.

On bias in AI

Fei-Fei Li, Professor of Computer Science, Stanford University:

(Begins @ 3:14:57)

Research repeatedly has shown that when people work in diverse groups there is increased creativity and innovation.

And interestingly, it is harder to work as a diverse group. I’m sure everybody here in the audience have had that experience. We have to listen to each other more. We have to understand the perspective more. But that also correlates well with innovation and creativity. … If we don’t have the inclusion of [diverse] people to think about the problems and the algorithms in AI, we might not only being missing the innovation boat we might actually create bias and create unfairness that are going to be detrimental to our society … 

What I have been advocating at Stanford, and with my colleagues in the community is, let’s bring the humanistic mission statement into the field of AI. Because AI is fundamentally an applied technology that’s going to serve our society. Humanistic AI not only raises the awareness and the importance of our technology, it’s actually a really, really important way to attract diverse students and technologists and innovators to participate in the technology of AI.

There has been a lot of research done to show that people with diverse background put more emphasis on humanistic mission in their work and in their life. So, if in our education, in our research, if we can accentuate or bring out this humanistic message of this technology, we are more likely to invite the diversity of students and young technologists to join us.

On lack of minorities in AI

Andrew Moore Dean, School of Computer Science, Carnegie Mellon University:

(Begins @ 3:19:10)

I so strongly applaud what you [Fei-Fei Li] are describing here because I think we are engaged in a fight here for how the 21st century pans out in terms of who’s running the world … 

The nightmare, the silly, silly thing we could do … would be if … the middle of the century is built by a bunch of non-minority guys from suburban moderately wealthy United States instead of the full population of the United States.

Source: Frontiers Conference
Click on the video that says Live Stream (event will start shortly)
it may take a minute to load

(Update 02/24/17: The original timelines listed above may be different when revisiting this video.)

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

How Deep Learning is making AI prejudiced

Bloggers note: The authors of this research paper show what they refer to as “machine prejudice” and how it derives so fundamentally from human culture. 

“Concerns about machine prejudice are now coming to the fore–concerns that our historic biases and prejudices are being reified in machines,” they write. “Documented cases of automated prejudice range from online advertising (Sweeney, 2013) to criminal sentencing (Angwin et al., 2016).”

Following are a few excerpts: 

machine-prejudiceAbstract

“Artificial intelligence and machine learning are in a period of astounding growth. However, there are concerns that these technologies may be used, either with or without intention, to perpetuate the prejudice and unfairness that unfortunately characterizes many human institutions. Here we show for the first time that human-like semantic biases result from the application of standard machine learning to ordinary language—the same sort of language humans are exposed to every day.

Discussion

“We show for the first time that if AI is to exploit via our language the vast knowledge that culture has compiled, it will inevitably inherit human-like prejudices. In other words, if AI learns enough about the properties of language to be able to understand and produce it, it also acquires cultural associations that can be offensive, objectionable, or harmful. These are much broader concerns than intentional discrimination, and possibly harder to address.

Awareness is better than blindness

“… where AI is partially constructed automatically by machine learning of human culture, we may also need an analog of human explicit memory and deliberate actions, that can be trained or programmed to avoid the expression of prejudice.

“Of course, such an approach doesn’t lend itself to a straightforward algorithmic formulation. Instead it requires a long-term, interdisciplinary research program that includes cognitive scientists and ethicists. …”

Click here to download the pdf of the report
Semantics derived automatically from language corpora necessarily contain human biases
Aylin Caliskan-Islam , Joanna J. Bryson, and Arvind Narayanan

1 Princeton University
2 University of Bath
Draft date August 31, 2016.

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwitter