The Foundation we’ve built for AI- Human Collaboration.
AI and the future
The Deadly Recklessness of the Self-Driving Industry
“Tesla,” Stilgoe tells me, “is turning a blind eye to their drivers’ own experiments with Autopilot. People are using Autopilot irresponsibly, and Tesla are overlooking it because they are gathering data.” #ai #aiethics
The Deadly Recklessness ofhttps://t.co/wLcaqqn00h— Phil & Pam Lawson (@SocializingAI) December 14, 2018
Let’s be clear about this, because it seems to me that these companies have gotten a bit of a pass for undertaking a difficult, potentially ‘revolutionary’ technology, and because blame can appear nebulous in car crashes, or in these cases can be directed toward the humans who were supposed to be watching the road. These companies’ actions (or sometimes, lack of action) have led to loss of life and limb. In the process, they have darkened the outlook for the field in general, sapping public trust in self-driving cars and delaying the rollout of what many hope will be a life-saving technology.
- According to an email recently obtained by the Information, Uber’s self-driving car division may not only be reckless, but outright negligent. The company’s executive staff reportedly ignored detailed calls from its own safety team and continued unsafe practices and a pedestrian died. Before that, a host of accidents and near-misses had gone unheeded.
- At least one major executive in Google’s autonomous car division reportedly exempted himself from test program protocol, directly caused a serious crash, injured his passenger, and never informed police that it was caused by a self-driving car. Waymo, now a subsidiary of Google, has been involved, by my count, in 21 reported crashes this year, according to California DMV records, though it was at fault in one.
But the fact is, those of us already on the road in our not-so-autonomous cars have little to no say over how we coexist with self-driving ones.
Over whether or not we’re sharing the streets with AVs running on shoddy software or overseen by less-than-alert human drivers because executives don’t want to lag in their quest to vacuum up road data or miss a sales opportunity.
Source: Gizmodo – Brian Merchant
The AI Cold War That Could Doom Us All
… as Beijing began to build up speed, the United States government was slowing to a walk. After President Trump took office, the Obama-era reports on AI were relegated to an archived website.
In March 2017, Treasury secretary Steven Mnuchin said that the idea of humans losing jobs because of AI “is not even on our radar screen.” It might be a threat, he added, in “50 to 100 more years.” That same year, China committed itself to building a $150 billion AI industry by 2030.
And what’s at stake is not just the technological dominance of the United States. At a moment of great anxiety about the state of modern liberal democracy, AI in China appears to be an incredibly powerful enabler of authoritarian rule. Is the arc of the digital revolution bending toward tyranny, and is there any way to stop it?
AFTER THE END of the Cold War, conventional wisdom in the West came to be guided by two articles of faith: that liberal democracy was destined to spread across the planet, and that digital technology would be the wind at its back.
As the era of social media kicked in, the techno-optimists’ twin articles of faith looked unassailable. In 2009, during Iran’s Green Revolution, outsiders marveled at how protest organizers on Twitter circumvented the state’s media blackout. A year later, the Arab Spring toppled regimes in Tunisia and Egypt and sparked protests across the Middle East, spreading with all the virality of a social media phenomenon—because, in large part, that’s what it was.
“If you want to liberate a society, all you need is the internet,” said Wael Ghonim, an Egyptian Google executive who set up the primary Facebook group that helped galvanize dissenters in Cairo.
It didn’t take long, however, for the Arab Spring to turn into winter
…. in 2013 the military staged a successful coup. Soon thereafter, Ghonim moved to California, where he tried to set up a social media platform that would favor reason over outrage. But it was too hard to peel users away from Twitter and Facebook, and the project didn’t last long. Egypt’s military government, meanwhile, recently passed a law that allows it to wipe its critics off social media.
Of course, it’s not just in Egypt and the Middle East that things have gone sour. In a remarkably short time, the exuberance surrounding the spread of liberalism and technology has turned into a crisis of faith in both. Overall, the number of liberal democracies in the world has been in steady decline for a decade. According to Freedom House, 71 countries last year saw declines in their political rights and freedoms; only 35 saw improvements.
While the crisis of democracy has many causes, social media platforms have come to seem like a prime culprit.
Which leaves us where we are now: Rather than cheering for the way social platforms spread democracy, we are busy assessing the extent to which they corrode it.
VLADIMIR PUTIN IS a technological pioneer when it comes to cyberwarfare and disinformation. And he has an opinion about what happens next with AI: “The one who becomes the leader in this sphere will be the ruler of the world.”
It’s not hard to see the appeal for much of the world of hitching their future to China. Today, as the West grapples with stagnant wage growth and declining trust in core institutions, more Chinese people live in cities, work in middle-class jobs, drive cars, and take vacations than ever before. China’s plans for a tech-driven, privacy-invading social credit system may sound dystopian to Western ears, but it hasn’t raised much protest there.
In a recent survey by the public relations consultancy Edelman, 84 percent of Chinese respondents said they had trust in their government. In the US, only a third of people felt that way.
… for now, at least, conflicting goals, mutual suspicion, and a growing conviction that AI and other advanced technologies are a winner-take-all game are pushing the two countries’ tech sectors further apart.
A permanent cleavage will come at a steep cost and will only give techno-authoritarianism more room to grow.
Source: Wired (click to read the full article)
Making AI Safe May be an Impossible Task
When it comes to creating safe AI and regulating this technology, these great minds have little clue what they’re doing. They don’t even know where to begin.
I met with Michael Page, the Policy and Ethics Advisor at OpenAI.
Beneath the glittering skyscrapers of the self-proclaimed “city of the future,” he told me of the uncertainty that he faces. He spoke of the questions that don’t have answers, and the fantastically high price we’ll pay if we don’t find them.
The conversation began when I asked Page about his role at OpenAI. He responded that his job is to “look at the long-term policy implications of advanced AI.” If you think that this seems a little intangible and poorly defined, you aren’t the only one. I asked Page what that means, practically speaking. He was frank in his answer: “I’m still trying to figure that out.”
Page attempted to paint a better picture of the current state of affairs by noting that, since true artificial intelligence doesn’t actually exist yet, his job is a little more difficult than ordinary.
He noted that, when policy experts consider how to protect the world from AI, they are really trying to predict the future.
They are trying to, as he put it, “find the failure modes … find if there are courses that we could take today that might put us in a position that we can’t get out of.” In short, these policy experts are trying to safeguard the world of tomorrow by anticipating issues and acting today.
The problem is that they may be faced with an impossible task.
Page is fully aware of this uncomfortable possibility, and readily admits it. “I want to figure out what can we do today, if anything. It could be that the future is so uncertain there’s nothing we can do,” he said.
asked for a concrete prediction of where humanity and AI will together be in a year, or in five years, Page didn’t offer false hope: “I have no idea,”
However, Page and OpenAI aren’t alone in working on finding the solutions. He therefore hopes such solutions may be forthcoming: “Hopefully, in a year, I’ll have an answer. Hopefully, in five years, there will be thousands of people thinking about this,” Page said.
Source: Futurism
The reckoning over social media has transformed SXSW
“Fifteen years ago, when we were coming here to Austin to talk about the internet, it was this magical place that was different from the rest of the world,” said Ev Williams, now the CEO of Medium, at a panel over the weekend.
“It was a subset” of the general population, he said, “and everyone was cool. There were some spammers, but that was kind of it. And now it just reflects the world.” He continued: “When we built Twitter, we weren’t thinking about these things. We laid down fundamental architectures that had assumptions that didn’t account for bad behavior. And now we’re catching on to that.”
Questions about the unintended consequences of social networks pervaded this year’s event. Academics, business leaders, and Facebook executives weighed in on how social platforms spread misinformation, encourage polarization, and promote hate speech.
The idea that the architects of our social networks would face their comeuppance in Austin was once all but unimaginable at SXSW, which is credited with launching Twitter, Foursquare, and Meerkat to prominence.
But this year, the festival’s focus turned to what social apps had wrought — to what Chris Zappone, a who covers Russian influence campaigns at Australian newspaper The Age, called at his panel “essentially a national emergency.”
Steve Huffman, the CEO of Reddit discouraged strong intervention from the government. “The foundation of the United States and the First Amendment is really solid,” Huffman said. “We’re going through a very difficult time. And as I mentioned before, our values are being tested. But that’s how you know they’re values. It’s very important that we stand by our values and don’t try to overcorrect.”
Sen. Mark Warner (D-VA), vice chairman of the Senate Select Committee on intelligence, echoed that sentiment. “We’re going to need their cooperation because if not, and you simply leave this to Washington, we’ll probably mess it up,” he said at a panel that, he noted with great disappointment, took place in a room that was more than half empty. “It needs to be more of a collaborative process. But the notion that this is going to go away just isn’t accurate.”
Nearly everyone I heard speak on the subject of propaganda this week said something like “there are no easy answers” to the information crisis.
And if there is one thing that hasn’t changed about SXSW, it was that: a sense that tech would prevail in the end.
“It would also be naive to say we can’t do anything about it,” Ev Williams said. “We’re just in the early days of trying to do something about it.”
Source: The Verge – Casey Newton
Stephen Hawking’s Haunting Last Reddit Posts on AI Are Going Viral
GETTY IMAGES
In the hours since the news of his death broke, fans have been resurfacing some of their favorite quotes of his, including those from his Reddit AMA two years ago.
He wrote confidently about the imminent development of human-level AI and warned people to prepare for its consequences:
“When it eventually does occur, it’s likely to be either the best or worst thing ever to happen to humanity, so there’s huge value in getting it right.”
When asked if human-created AI could exceed our own intelligence, he replied:
It’s clearly possible for a something to acquire higher intelligence than its ancestors: we evolved to be smarter than our ape-like ancestors, and Einstein was smarter than his parents. The line you ask about is where an AI becomes better than humans at AI design, so that it can recursively improve itself without human help. If this happens, we may face an intelligence explosion that ultimately results in machines whose intelligence exceeds ours by more than ours exceeds that of snails.
As for whether that same AI could potentially be a threat to humans one day?
“AI will probably develop a drive to survive and acquire more resources as a step toward accomplishing whatever goal it has, because surviving and having more resources will increase its chances of accomplishing that other goal,” he wrote. “This can cause problems for humans whose resources get taken away.”
Source: Cosmopolitan
A Hippocratic Oath for artificial intelligence practitioners
Getty Images
In the forward to Microsoft’s recent book, The Future Computed, executives Brad Smith and Harry Shum proposed that Artificial Intelligence (AI) practitioners highlight their ethical commitments by taking an oath analogous to the Hippocratic Oath sworn by doctors for generations.
In the past, much power and responsibility over life and death was concentrated in the hands of doctors.
Now, this ethical burden is increasingly shared by the builders of AI software.
Future AI advances in medicine, transportation, manufacturing, robotics, simulation, augmented reality, virtual reality, military applications, dictate that AI be developed from a higher moral ground today.
In response, I (Oren Etzioni) edited the modern version of the medical oath to address the key ethical challenges that AI researchers and engineers face …
The oath is as follows:
I swear to fulfill, to the best of my ability and judgment, this covenant:
I will respect the hard-won scientific gains of those scientists and engineers in whose steps I walk, and gladly share such knowledge as is mine with those who are to follow.
I will apply, for the benefit of the humanity, all measures required, avoiding those twin traps of over-optimism and uniformed pessimism.
I will remember that there is an art to AI as well as science, and that human concerns outweigh technological ones.
Most especially must I tread with care in matters of life and death. If it is given me to save a life using AI, all thanks. But it may also be within AI’s power to take a life; this awesome responsibility must be faced with great humbleness and awareness of my own frailty and the limitations of AI. Above all, I must not play at God nor let my technology do so.
I will respect the privacy of humans for their personal data are not disclosed to AI systems so that the world may know.
I will consider the impact of my work on fairness both in perpetuating historical biases, which is caused by the blind extrapolation from past data to future predictions, and in creating new conditions that increase economic or other inequality.
My AI will prevent harm whenever it can, for prevention is preferable to cure.
My AI will seek to collaborate with people for the greater good, rather than usurp the human role and supplant them.
I will remember that I am not encountering dry data, mere zeros and ones, but human beings, whose interactions with my AI software may affect the person’s freedom, family, or economic stability. My responsibility includes these related problems.
I will remember that I remain a member of society, with special obligations to all my fellow human beings.
Source: TechCrunch – Oren Etzioni
How to Make A.I. That’s Good for People
Credit Elisa Macellari
For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast.
Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis. If our era is the next Industrial Revolution, as many claim, A.I. is surely one of its driving forces.
I worry, however, that enthusiasm for A.I. is preventing us from reckoning with its looming effects on society. Despite its name, there is nothing “artificial” about this technology — it is made by humans, intended to behave like humans and affects humans. So if we want it to play a positive role in tomorrow’s world, it must be guided by human concerns.
I call this approach “human-centered A.I.” It consists of three goals that can help responsibly guide the development of intelligent machines.
- First, A.I. needs to reflect more of the depth that characterizes our own intelligence.
- the second goal of human-centered A.I.: enhancing us, not replacing us.
- the third goal of human-centered A.I.: ensuring that the development of this technology is guided, at each step, by concern for its effect on humans.
No technology is more reflective of its creators than A.I. It has been said that there are no “machine” values at all, in fact; machine values are human values.
A human-centered approach to A.I. means these machines don’t have to be our competitors, but partners in securing our well-being. However autonomous our technology becomes, its impact on the world — for better or worse — will always be our responsibility.
Fei-Fei Li is a professor of computer science at Stanford, where she directs the Stanford Artificial Intelligence Lab, and the chief scientist for A.I. research at Google Cloud.
Source: NYT
The Mueller indictment exposes the danger of Facebook’s focus on Groups
Illustration by Alex Castro / The Verge
A year ago this past Friday, Mark Zuckerberg published a lengthy post titled “Building a Global Community.” It offered a comprehensive statement from the Facebook CEO on how he planned to move the company away from its longtime mission of making the world “more open and connected” to instead create “the social infrastructure … to build a global community.”
“Social media is a short-form medium where resonant messages get amplified many times,” Zuckerberg wrote. “This rewards simplicity and discourages nuance. At its best, this focuses messages and exposes people to different ideas. At its worst, it oversimplifies important topics and pushes us towards extremes.”
By that standard, Robert Mueller’s indictment of of a Russian troll farm last week showed social media at its worst.
Facebook has estimated that 126 million users saw Russian disinformation on the platform during the 2016 campaign. The effects of that disinformation went beyond likes, comments, and shares. Coordinating with unwitting Americans through social media platforms, Russians staged rallies and paid Americans to participate in them. In one case, they hired Americans to build a cage on a flatbed truck and dress up in a Hillary Clinton costume to promote the idea that she should be put in jail.
Russians spent thousands of dollars a month promoting those groups on Facebook and other sites, according to the indictment. They meticulously tracked the growth of their audience, creating and distributing reports on their growing influence. They worked to make their posts seem more authentically American, and to create posts more likely to spread virally through the mechanisms of the social networks.
the dark side of “developing the social infrastructure for community” is now all too visible.
The tools that are so useful for organizing a parenting group are just as effective at coercing large groups of Americans into yelling at each other. Facebook dreams of serving one global community, when in fact it serves — and enables —countless agitated tribes.
The more Facebook pushes us into groups, the more it risks encouraging the kind of polarization that Russia so eagerly exploited.
Source: The Verge
This is an opportunity for me to correct a wrong – Center for Humane Technology
Early Facebook and Google Employees Form Coalition to Fight What They Built
Jim Steyer, left, and Tristan Harris in Common Sense’s headquarters. Common Sense is helping fund the The Truth About Tech campaign. Peter Prato for The New York Times
A group of Silicon Valley technologists who were early employees at Facebook and Google, alarmed over the ill effects of social networks and smartphones, are banding togethe to challenge the companies they helped build.
The cohort is creating a union of concerned experts called the Center for Humane Technology. Along with the nonprofit media watchdog group Common Sense Media, it also plans an anti-tech addiction lobbying effort and an ad campaign at 55,000 public schools in the United States.
The campaign, titled The Truth About Tech
“We were on the inside,” said Tristan Harris, a former in-house ethicist at Google who is heading the new group. “We know what the companies measure. We know how they talk, and we know how the engineering works.”
An unprecedented alliance of former employees of some of today’s biggest tech companies. Apart from Mr. Harris, the center includes Sandy Parakilas, a former Facebook operations manager; Lynn Fox, a former Apple and Google communications executive; Dave Morin, a former Facebook executive; Justin Rosenstein, who created Facebook’s Like button and is a co-founder of Asana; Roger McNamee, an early investor in Facebook; and Renée DiResta, technologist who studies bots.
“Facebook appeals to your lizard brain — primarily fear and anger. And with smartphones, they’ve got you for every waking moment. This is an opportunity for me to correct a wrong.” Roger McNamee, an early investor in Facebook
Source: NYT
Life at the Intersection of AI and Society
Edits from a Microsoft podcast with Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research.
Ece Kamar Senior Researcher
I’m very interested in the complementarity between machine intelligence and human intelligence and what kind of value can be generated from using both of them to make daily life better.
We try to build systems that can interact with people, that can work with people and that can be beneficial for people. Our group has a big human component, so we care about modelling the human side. And we also work on machine-learning decision-making algorithms that can make decisions appropriately for the domain they were designed for.
My main area is the intersection between humans and AI.
we are actually at an important point in the history of AI where a lot of critical AI systems are entering the real world and starting to interact with people. So, we are at this inflection point where, whatever AI does, and the way we build AI, have consequences for the society we live in.
So, let’s look for what can augment human intelligence, what can make human intelligence better.” And that’s what my research focuses on. I really look for the complementarity in intelligences, and building these experience that can, in the future, hopefully, create super-human experiences.
So, a lot of the work I do focuses on two big parts: one is how we can build AI systems that can provide value for humans in their daily tasks and making them better. But also thinking about how humans may complement AI systems.
And when we look at our AI practices, it is actually very data-dependent these days … However, data collection is not a real science. We have our insights, we have our assumptions and we do data collection that way. And that data is not always the perfect representation of the world. This creates blind spots. When our data is not the right representation of the world and it’s not representing everything we care about, then our models cannot learn about some of the important things.
“AI is developed by people, with people, for people.”
And when I talk about building AI for people, a lot of the systems we care about are human-driven. We want to be useful for human.
We are thinking about AI algorithms that can bias their decisions based on race, gender, age. They can impact society and there are a lot of areas like judicial decision-making that touches law. And also, for every vertical, we are building these systems and I think we should be working with the domain experts from these verticals. We need to talk to educators. We need to talk to doctors. We need to talk to people who understand what that domain means and all the special considerations we should be careful about.
So, I think if we can understand what this complementary means, and then build AI that can use the power of AI to complement what humans are good at and support them in things that they want to spend time on, I think that is the beautiful future I foresee from the collaboration of humans and machines.
Source: Microsoft Research Podcast
AI poses one of the “greatest tests of leadership for our time”
Getty Images
“But it is a test that I am confident we can meet”
Thereas May, Prime Minister UK
The prime minister is to say she wants the UK to lead the world in deciding how artificial intelligence can be deployed in a safe and ethical manner.
Theresa May will say at the World Economic Forum in Davos that a new advisory body, previously announced in the Autumn Budget, will co-ordinate efforts with other countries.
In addition, she will confirm that the UK will join the Davos forum’s own council on artificial intelligence.
But others may have stronger claims.
Earlier this week, Google picked France as the base for a new research centre dedicated to exploring how AI can be applied to health and the environment.
Facebook also announced it was doubling the size of its existing AI lab in Paris, while software firm SAP committed itself to a 2bn euro ($2.5bn; £1.7bn) investment into the country that will include work on machine learning.
Meanwhile, a report released last month by the Eurasia Group consultancy suggested that the US and China are engaged in a “two-way race for AI dominance”.
It predicted Beijing would take the lead thanks to the “insurmountable” advantage of offering its companies more flexibility in how they use data about its citizens.
she is expected to say that the UK is recognised as first in the world for its preparedness to “bring artificial intelligence into government”.
Source: BBC
What’s Bigger Than Fire and Electricity? Artificial Intelligence – Google
Google CEO Sundar Pichai believes artificial intelligence could have “more profound” implications for humanity than electricity or fire, according to recent comments.
Pichai also warned that the development of artificial intelligence could pose as much risk as that of fire if its potential is not harnessed correctly.
“AI is one of the most important things humanity is working on” Pichai said in an interview with MSNBC and Recode
“My point is AI is really important, but we have to be concerned about it,” Pichai said. “It’s fair to be worried about it—I wouldn’t say we’re just being optimistic about it— we want to be thoughtful about it. AI holds the potential for some of the biggest advances we’re going to see.”
Source: Newsweek
wait … am I being manipulated on this topic by an Amazon-owned AI engine?
Image Credit: chombosan/Shutterstock
The other night, my nine-year-old daughter (who is, of course, the most tech-savvy person in the house), introduced me to a new Amazon Alexa skill.
“Alexa, start a conversation,” she said.
We were immediately drawn into an experience with new bot, or, as the technologists would say, “conversational user interface” (CUI). It was, we were told, the recent winner in an Amazon AI competition from the University of Washington.
At first, the experience was fun, but when we chose to explore a technology topic, the bot responded, “have you heard of Net Neutrality?” What we experienced thereafter was slightly discomforting.
The bot seemingly innocuously cited a number of articles that she “had read on the web” about the FCC, Ajit Pai, and the issue of net neutrality. But here’s the thing: All four articles she recommended had a distinct and clear anti-Ajit Pai bias.
Now, the topic of Net Neutrality is a heated one and many smart people make valid points on both sides, including Fred Wilson and Ben Thompson. That is how it should be.
But the experience of the Alexa CUI should give you pause, as it did me.
To someone with limited familiarity with the topic of net neutrality, the voice seemed soothing and the information unbiased. But if you have a familiarity with the topic, you might start to wonder, “wait … am I being manipulated on this topic by an Amazon-owned AI engine to help the company achieve its own policy objectives?”
The experience highlights some of the risks of the AI-powered future into which we are hurtling at warp speed.
If you are going to trust your decision-making to a centralized AI source, you need to have 100 percent confidence in:
- The integrity and security of the data (are the inputs accurate and reliable, and can they be manipulated or stolen?)
- The machine learning algorithms that inform the AI (are they prone to excessive error or bias, and can they be inspected?)
- The AI’s interface (does it reliably represent the output of the AI and effectively capture new data?)
In a centralized, closed model of AI, you are asked to implicitly trust in each layer without knowing what is going on behind the curtains.
Welcome to the world of Blockchain+AI.
3 blockchain projects tackling decentralized data and AI (click here to read the blockchain projects)
Source: Venture Beat
Montreal seeks to be world leader in AI research
Various computer scientists, researchers, lawyers and other techies have recently been attending bi-monthly meetings in Montreal to discuss life’s big questions — as they relate to our increasingly intelligent machines.
Should a computer give medical advice? Is it acceptable for the legal system to use algorithms in order to decide whether convicts get paroled? Can an artificial agent that spouts racial slurs be held culpable?
And perhaps most pressing for many people: Are Facebook and other social media applications capable of knowing when a user is depressed or suffering a manic episode — and are these people being targeted with online advertisements in order to exploit them at their most vulnerable?
Researchers such as Abhishek Gupta are trying to help Montreal lead the world in ensuring AI is developed responsibly.
“The spotlight of the world is on (Montreal),” said Gupta, an AI ethics researcher at McGill University who is also a software developer in cybersecurity at Ericsson.
His bi-monthly “AI ethics meet-up” brings together people from around the city who want to influence the way researchers are thinking about machine-learning.
“In the past two months we’ve had six new AI labs open in Montreal,” Gupta said. “It makes complete sense we would also be the ones who would help guide the discussion on how to do it ethically.”
In November, Gupta and Universite de Montreal researchers helped create the Montreal Declaration for a Responsible Development of Artificial Intelligence, which is a series of principles seeking to guide the evolution of AI in the city and across the planet.
Its principles are broken down into seven themes: well-being, autonomy, justice, privacy, knowledge, democracy and responsibility.
“How do we ensure that the benefits of AI are available to everyone?” Gupta asked his group. “What types of legal decisions can we delegate to AI?”
Doina Precup, a McGill University computer science professor and the Montreal head of DeepMind … said the global industry is starting to be preoccupied with the societal consequences of machine-learning, and Canadian values encourage the discussion.
“Montreal is a little ahead because we are in Canada,” Precup said. “Canada, compared to other parts of the world, has a different set of values that are more oriented towards ensuring everybody’s wellness. The background and culture of the country and the city matter a lot.”
Source: iPolitics
China’s artificial intelligence is catching criminals and advancing health care
Zhu Long, co-founder and CEO of Yitu Technology, has his identity checked at the company’s headquarters in the Hongqiao business district in Shanghai. Picture: Zigor Aldama
“Our machines can very easily recognise you among at least 2 billion people in a matter of seconds,” says chief executive and Yitu co-founder Zhu Long, “which would have been unbelievable just three years ago.”
Its platform is also in service with more than 20 provincial public security departments, and is used as part of more than 150 municipal public security systems across the country, and Dragonfly Eye has already proved its worth.
On its very first day of operation on the Shanghai Metro, in January, the system identified a wanted man when he entered a station. After matching his face against the database, Dragonfly Eye sent his photo to a policeman, who made an arrest.
In the following three months, 567 suspected lawbreakers were caught on the city’s underground network.
Whole cities in which the algorithms are working say they have seen a decrease in crime. According to Yitu, which says it gets its figures directly from the local authorities, since the system has been implemented, pickpocketing on Xiamen’s city buses has fallen by 30 per cent; 500 criminal cases have been resolved by AI in Suzhou since June 2015; and police arrested nine suspects identified by algorithms during the 2016 G20 summit in Hangzhou.
“Chinese authorities are collecting and centralising ever more information about hundreds of millions of ordinary people, identifying persons who deviate from what they determine to be ‘normal thought’ and then surveilling them,” says Sophie Richardson, China director at HRW.
Research and advocacy group Human Rights Watch (HRW) says security systems such as those being developed by Yitu “violate privacy and target dissent”.
The NGO calls it a “police cloud” system and believes “it is designed to track and predict the activities of activists, dissidents and ethnic minorities, including those authorities say have extreme thoughts, among others”.
Zhu says, “We all discuss AI as an opportunity for humanity to advance or as a threat to it. What I believe is that we will have to redefine what it is to be human. We will have to ask ourselves what the foundations of our species are.
“At the same time, AI will allow us to explore the boundaries of human intelligence, evaluate its performance and help us understand ourselves better.”
Source: South China Morning Post
Are there some things we just shouldn’t build? #AI
The prestigious Neural Information Processing Systems conference have a new topic on their agenda. Alongside the usual … concern about AI’s power.
Kate Crawford … urged attendees to start considering, and finding ways to mitigate, accidental or intentional harms caused by their creations. “
“Amongst the very real excitement about what we can do there are also some really concerning problems arising”
“In domains like medicine we can’t have these models just be a black box where something goes in and you get something out but don’t know why,” says Maithra Raghu, a machine-learning researcher at Google. On Monday, she presented open-source software developed with colleagues that can reveal what a machine-learning program is paying attention to in data. It may ultimately allow a doctor to see what part of a scan or patient history led an AI assistant to make a particular diagnosis.
“If you have a diversity of perspectives and background you might be more likely to check for bias against different groups” Hanna Wallach a researcher at Microsoft
Others in Long Beach hope to make the people building AI better reflect humanity. Like computer science as a whole, machine learning skews towards the white, male, and western. A parallel technical conference called Women in Machine Learning has run alongside NIPS for a decade. This Friday sees the first Black in AI workshop, intended to create a dedicated space for people of color in the field to present their work.
Towards the end of her talk Tuesday, Crawford suggested civil disobedience could shape the uses of AI. She talked of French engineer Rene Carmille, who sabotaged tabulating machines used by the Nazis to track French Jews. And she told today’s AI engineers to consider the lines they don’t want their technology to cross. “Are there some things we just shouldn’t build?” she asked.
Source: Wired
Artificial intelligence doesn’t have to be evil. We just have to teach it to be good
Training an AI platform on social media data, with the intent to reproduce a “human” experience, is fraught with risk. You could liken it to raising a baby on a steady diet of Fox News or CNN, with no input from its parents or social institutions. In either case, you might be breeding a monster.
Ultimately, social data — alone — represents neither who we actually are nor who we should be. Deeper still, as useful as the social graph can be in providing a training set for AI, what’s missing is a sense of ethics or a moral framework to evaluate all this data. From the spectrum of human experience shared on Twitter, Facebook and other networks, which behaviors should be modeled and which should be avoided? Which actions are right and which are wrong? What’s good … and what’s evil?
Here’s where science comes up short. The answers can’t be gleaned from any social data set. The best analytical tools won’t surface them, no matter how large the sample size.
But they just might be found in the Bible. And the Koran, the Torah, the Bhagavad Gita and the Buddhist Sutras. They’re in the work of Aristotle, Plato, Confucius, Descartes and other philosophers both ancient and modern.
AI, to be effective, needs an ethical underpinning. Data alone isn’t enough. AI needs religion — a code that doesn’t change based on context or training set.
In place of parents and priests, responsibility for this ethical education will increasingly rest on frontline developers and scientists.
As emphasized by leading AI researcher Will Bridewell, it’s critical that future developers are “aware of the ethical status of their work and understand the social implications of what they develop.” He goes so far as to advocate study in Aristotle’s ethics and Buddhist ethics so they can “better track intuitions about moral and ethical behavior.”
On a deeper level, responsibility rests with the organizations that employ these developers, the industries they’re part of, the governments that regulate those industries and — in the end — us.
Source: Recode Ryan Holmes is the founder and CEO of Hootsuite.
How a half-educated tech elite delivered us into chaos
Donald Trump meeting PayPal co-founder Peter Thiel and Apple CEO Tim Cook in December last year. Photograph: Evan Vucci/AP
One of the biggest puzzles about our current predicament with fake news and the weaponisation of social media is why the folks who built this technology are so taken aback by what has happened.
We have a burgeoning genre of “OMG, what have we done?” angst coming from former Facebook and Google employees who have begun to realise that the cool stuff they worked on might have had, well, antisocial consequences.
Put simply, what Google and Facebook have built is a pair of amazingly sophisticated, computer-driven engines for extracting users’ personal information and data trails, refining them for sale to advertisers in high-speed data-trading auctions that are entirely unregulated and opaque to everyone except the companies themselves.
The purpose of this infrastructure was to enable companies to target people with carefully customised commercial messages and, as far as we know, they are pretty good at that.
It never seems to have occurred to them that their advertising engines could also be used to deliver precisely targeted ideological and political messages to voters. Hence the obvious question: how could such smart people be so stupid?
My hunch is it has something to do with their educational backgrounds. Take the Google co-founders. Sergey Brin studied mathematics and computer science. His partner, Larry Page, studied engineering and computer science. Zuckerberg dropped out of Harvard, where he was studying psychology and computer science, but seems to have been more interested in the latter.
Now mathematics, engineering and computer science are wonderful disciplines – intellectually demanding and fulfilling. And they are economically vital for any advanced society. But mastering them teaches students very little about society or history – or indeed about human nature.
As a consequence, the new masters of our universe are people who are essentially only half-educated. They have had no exposure to the humanities or the social sciences, the academic disciplines that aim to provide some understanding of how society works, of history and of the roles that beliefs, philosophies, laws, norms, religion and customs play in the evolution of human culture.
We are now beginning to see the consequences of the dominance of this half-educated elite.
Source: The Gaurdian – John Naughton is professor of the public understanding of technology at the Open University.
AI more than just another industrial revolution
This is more than just another industrial revolution. This is something new that transcends humankind and even biology. It is a privilege to witness its beginnings, and contribute something to it.
Source: Scientific American Blog Network
The idea that you had no idea any of this was happening strains my credibility
From left: Twitter’s acting general counsel Sean Edgett, Facebook’s general counsel Colin Stretch and Google’s senior vice president and general counsel Kent Walker, testify before the House Intelligence Committee on Wednesday, Nov. 1, 2017. Manuel Balce Ceneta/AP
Members of Congress confessed how difficult it was for them to even wrap their minds around how today’s Internet works — and can be abused. And for others, the hearings finally drove home the magnitude of the Big Tech platforms.
Sen. John Kennedy, R-La., marveled on Tuesday when Facebook said it could track the source of funding for all 5 million of its monthly advertisers.
“I think you do enormous good, but your power scares me,” he said.
There appears to be no quick patch for the malware afflicting America’s political life.
Over the course of three congressional hearings Tuesday and Wednesday, lawmakers fulminated, Big Tech witnesses were chastened but no decisive action appears to be in store to stop a foreign power from harnessing digital platforms to try to shape the information environment inside the United States.
Legislation offered in the Senate — assuming it passed, months or more from now — would change the calculus slightly: requiring more disclosure and transparency for political ads on Facebook and Twitter and other social platforms.
Even if it became law, however, it would not stop such ads from being sold, nor heal the deep political divisions exploited last year by foreign influence-mongers. The legislation also couldn’t stop a foreign power from using all the other weapons in its arsenal against the U.S., including cyberattacks, the deployment of human spies and others.
“Candidly, your companies know more about Americans, in many ways, than the United States government does. The idea that you had no idea any of this was happening strains my credibility,” Senate Intelligence Committee Vice Chairman Mark Warner, D.-Va.
The companies also made clear they condemn the uses of their services they’ve discovered, which they said violate their policies in many cases.
They also talked more about the scale of the Russian digital operation they’ve uncovered up to this point — which is eye-watering: Facebook general counsel Colin Stretch acknowledged that as many as 150 million Americans may have seen posts or other content linked to Russia’s influence campaign in the 2016 cycle
“There is one thing I’m certain of, and it’s this: Given the complexity of what we have seen, if anyone tells you they have figured it out, they are kidding ourselves. And we can’t afford to kid ourselves about what happened last year — and continues to happen today.” Senate Intelligence Committee Chairman Richard Burr, R-N.C.
Source: NPR
Does Even Mark Zuckerberg Know What Facebook Is?
In a statement broadcast live on Facebook on September 21 and subsequently posted to his profile page, Zuckerberg pledged to increase the resources of Facebook’s security and election-integrity teams and to work “proactively to strengthen the democratic process.”
It was an admirable commitment. But reading through it, I kept getting stuck on one line: “We have been working to ensure the integrity of the German elections this weekend,” Zuckerberg writes. It’s a comforting sentence, a statement that shows Zuckerberg and Facebook are eager to restore trust in their system.
But … it’s not the kind of language we expect from media organizations, even the largest ones. It’s the language of governments, or political parties, or NGOs. A private company, working unilaterally to ensure election integrity in a country it’s not even based in?
Facebook has grown so big, and become so totalizing, that we can’t really grasp it all at once.
Like a four-dimensional object, we catch slices of it when it passes through the three-dimensional world we recognize. In one context, it looks and acts like a television broadcaster, but in this other context, an NGO. In a recent essay for the London Review of Books, John Lanchester argued that for all its rhetoric about connecting the world, the company is ultimately built to extract data from users to sell to advertisers. This may be true, but Facebook’s business model tells us only so much about how the network shapes the world.
Between March 23, 2015, when Ted Cruz announced his candidacy, and November 2016, 128 million people in America created nearly 10 billion Facebook posts, shares, likes, and comments about the election. (For scale, 137 million people voted last year.)
In February 2016, the media theorist Clay Shirky wrote about Facebook’s effect: “Reaching and persuading even a fraction of the electorate used to be so daunting that only two national orgs” — the two major national political parties — “could do it. Now dozens can.”
It used to be if you wanted to reach hundreds of millions of voters on the right, you needed to go through the GOP Establishment. But in 2016, the number of registered Republicans was a fraction of the number of daily American Facebook users, and the cost of reaching them directly was negligible.
Tim Wu, the Columbia Law School professor
“Facebook has the same kind of attentional power [as TV networks in the 1950s], but there is not a sense of responsibility,” he said. “No constraints. No regulation. No oversight. Nothing. A bunch of algorithms, basically, designed to give people what they want to hear.”
It tends to get forgotten, but Facebook briefly ran itself in part as a democracy: Between 2009 and 2012, users were given the opportunity to vote on changes to the site’s policy. But voter participation was minuscule, and Facebook felt the scheme “incentivized the quantity of comments over their quality.” In December 2012, that mechanism was abandoned “in favor of a system that leads to more meaningful feedback and engagement.”
Facebook had grown too big, and its users too complacent, for democracy.
Source: NY Magazine
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
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
Siri as a therapist, Apple is seeking engineers who understand psychology
PL – Looks like Siri needs more help to understand.
“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
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
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 a 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:
- Whose moral standards should be used?
- Can machines converse about moral issues?
- Can algorithms take context into account?
- Who should be accountable?
Source: Business Insider David Hagenbuch
Putin: Leader in artificial intelligence will rule world
Putin, speaking Friday at a meeting with students, said the development of AI raises “colossal opportunities and threats that are difficult to predict now.”
[He] warned that “it would be strongly undesirable if someone wins a monopolist position” and promised that Russia would be ready to share its know-how in artificial intelligence with other nations.
The Russian leader predicted that future wars will be fought by drones, and “when one party’s drones are destroyed by drones of another, it will have no other choice but to surrender.”
Source: Washington Post
IBM Watson CTO on Why Augmented Intelligence Beats AI
If you look at almost every other tool that has ever been created, our tools tend to be most valuable when they’re amplifying us, when they’re extending our reach, when they’re increasing our strength, when they’re allowing us to do things that we can’t do by ourselves as human beings. That’s really the way that we need to be thinking about AI as well, and to the extent that we actually call it augmented intelligence, not artificial intelligence.
Some time ago we realized that this thing called cognitive computing was really bigger than us, it was bigger than IBM, it was bigger than any one vendor in the industry, it was bigger than any of the one or two different solution areas that we were going to be focused on, and we had to open it up, which is when we shifted from focusing on solutions to really dealing with more of a platform of services, where each service really is individually focused on a different part of the problem space.
… what we’re talking about now are a set of services, each of which do something very specific, each of which are trying to deal with a different part of our human experience, and with the idea that anybody building an application, anybody that wants to solve a social or consumer or business problem can do that by taking our services, then composing that into an application.
… If the doctor can now make decisions that are more informed, that are based on real evidence, that are supported by the latest facts in science, that are more tailored and specific to the individual patient, it allows them to actually do their job better. For radiologists, it may allow them to see things in the image that they might otherwise miss or get overwhelmed by. It’s not about replacing them. It’s about helping them do their job better.
That’s really the way to think about this stuff, is that it will have its greatest utility when it is allowing us to do what we do better than we could by ourselves, when the combination of the human and the tool together are greater than either one of them would’ve been by theirselves. That’s really the way we think about it. That’s how we’re evolving the technology. That’s where the economic utility is going to be.
There are lots of things that we as human beings are good at. There’s also a lot of things that we’re not very good, and that’s I think where cognitive computing really starts to make a huge difference, is when it’s able to bridge that distance to make up that gap
A way I like to say it is it doesn’t do our thinking for us, it does our research for us so we can do our thinking better, and that’s true of us as end users and it’s true of advisors.
Source: PCMag
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
We should not talk about jobs being lost but people suffering #AI
How can humans stay ahead of an ever growing machine intelligence? “I think the challenge for us is to always be creative,” says former world chess champion Garry Kasparov
He also discussed the threat that increasingly capable AI poses to (human) jobs, arguing that we should not try to predict what will happen in the future but rather look at immediate problems.
“We make predictions and most are wrong because we’re trying to base it on our past experience,” he argued. “I think the problem is not that AI is exceeding our level. It’s another cycle.
Machines have been constantly replacing all sorts of jobs… We should not talk about jobs being lost but people suffering.
“AI is just another challenge. The difference is that now intelligence machines are coming after people with a college degree or with social media and Twitter accounts,” he added.
Source: Tech Crunch
The true secret of copying life lies in movement #AI
Random International’s Zoological, part of Wayne McGregor’s +/- Human Photograph: Ravi Deepres/Alicia Clarke
Random International’s installation, Zoological, features a flock of airborne spheres that glide and swoop and dance and swarm above and among us. What a mind-boggling show.
In the darkened heights of the Roundhouse in north London, a flying flock of white spheres that uncannily resemble Magritte’s dream objects float intelligently and curiously, checking out the humans below, hovering downward to see us better. They are the most convincing embodiment of artificial intelligence I have ever seen. For these responsive, even sensitive machines truly create a sense of encounter with a digital life form that mirrors, or mocks, human free will.
Nobody is hidden behind a screen piloting this robotic airborne dance troupe. Each sphere has its own decision-making electronic brain. They fly in elegant unison yet also break ranks as they check their positions against the images recorded by infra-red cameras surrounding the circular space where they float and their human visitors walk.
Yet the crucial fact that they guide themselves, mimicking conscious choice in their unplanned and to all intents and purposes spontaneous actions, is apparent without knowing anything about their design. You can tell by the way they move that they are free entities.
Looked at coldly, these devices are just inflated plastic balls whose movements are guided by rotors, like a toy drone. Their behaviour is by turns entrancing and mildly menacing. They rise one after another from their resting positions in an upper gallery and calmly hover out into the open domed arena where their human guests are waiting. They are never at rest. As they glide in formation one or another is always changing its position, approaching the people below with what seems like curiosity. Then they all follow. It is when the entire swarm gathers directly above you that it suddenly becomes a threatening, sinister presence.
This artwork that opens visions of a future in which life evolves beyond biology itself.
The true secret of copying life, this installation shows, lies in movement. Dance, the oldest human art, turns out to be a key to comprehending life itself, and reproducing it. The orbs dance with you. They locate and follow members of the audience, not with mechanical inevitability but a complex, gracious harmony. Making and breaking patterns, coming together and loosely floating apart, they dance with each other, too.
Source: The Guardian
80% of what human physicians currently do will soon be done instead by technology, allowing physicians to
Data-driven AI technologies are well suited to address chronic inefficiencies in health markets, potentially lowering costs by hundreds of billions of dollars, while simultaneously reducing the time burden on physicians.
These technologies can be leveraged to capture the massive volume of data that describes a patient’s past and present state, project potential future states, analyze that data in real time, assist in reasoning about the best way to achieve patient and physician goals, and provide both patient and physician constant real-time support. Only AI can fulfill such a mission. There is no other solution.
Technologist and investor Vinod Khosla posited that 80 percent of what human physicians currently do will soon be done instead by technology, allowing physicians to focus their time on the really important elements of patient physician interaction.
Within five years, the healthcare sector has the potential to undergo a complete metamorphosis courtesy of breakthrough AI technologies. Here are just a few examples:
1. Physicians will practice with AI virtual assistants (using, for example, software tools similar to Apple’s Siri, but specialized to the specific healthcare application).
2. Physicians with AI virtual assistants will be able to treat 5X – 10X as many patients with chronic illnesses as they do today, with better outcomes than in the past.
Patients will have a constant “friend” providing a digital health conscience to advise, support, and even encourage them to make healthy choices and pursue a healthy lifestyle.
3. AI virtual assistants will support both patients and healthy individuals in health maintenance with ongoing and real-time intelligent advice.
Our greatest opportunity for AI-enhancement in the sector is keeping people healthy, rather than waiting to treat them when they are sick. AI virtual assistants will be able to acquire deep knowledge of diet, exercise, medications, emotional and mental state, and more.
4. Medical devices previously only available in hospitals will be available in the home, enabling much more precise and timely monitoring and leading to a healthier population.
5. Affordable new tools for diagnosis and treatment of illnesses will emerge based on data collected from extant and widely adopted digital devices such as smartphones.
6. Robotics and in-home AI systems will assist patients with independent living.
But don’t be misled — the best metaphor is that they are learning like humans learn and that they are in their infancy, just starting to crawl. Healthcare AI virtual assistants will soon be able to walk, and then run.
Many of today’s familiar AI engines, personified in Siri, Cortana, Alexa, Google Assistant or any of the hundreds of “intelligent chatbots,” are still immature and their capabilities are highly limited. Within the next few years they will be conversational, they will learn from the user, they will maintain context, and they will provide proactive assistance, just to name a few of their emerging capabilities.
And with these capabilities applied in the health sector, they will enable us to keep millions of citizens healthier, give physicians the support and time they need to practice, and save trillions of dollars in healthcare costs. Welcome to the age of AI.
Source: Venture Beat
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
Microsoft’s new corporate vision: artificial intelligence is in and mobile is out
Microsoft has inserted artificial intelligence into its vision for the first time, and removed references to a “mobile-first” world. That fits with Microsoft’s recent push into AI and retreat from the smartphone market.
“We believe a new technology paradigm is emerging that manifests itself through an intelligent cloud and an intelligent edge where computing is more distributed, AI drives insights and acts on the user’s behalf, and user experiences span devices with a user’s available data and information,” according to Microsoft’s vision statement.
Microsoft last year formed a new 5,000-person engineering and research team to focus on its artificial intelligence products — a major reshaping of the company’s internal structure reminiscent of its massive pivot to pursue the opportunity of the Internet in the mid-1990s.
Here is Microsoft’s full vision statement from the document:
Microsoft is a technology company whose mission is to empower every person and every organization on the planet to achieve more. We strive to create local opportunity, growth, and impact in every country around the world. Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).
Source: Geekwire
Google Has Started Adding Imagination to Its DeepMind #AI
Researchers have started developing artificial intelligence with imagination – AI that can reason through decisions and make plans for the future, without being bound by human instructions.
Another way to put it would be imagining the consequences of actions before taking them, something we take for granted but which is much harder for robots to do.
“When placing a glass on the edge of a table, for example, we will likely pause to consider how stable it is and whether it might fall,” explain the researchers in a blog post. “On the basis of that imagined consequence we might readjust the glass to prevent it from falling and breaking.”
The team working at Google-owned lab DeepMind says this ability is going to be crucial in developing AI algorithms for the future, allowing systems to better adapt to changing conditions that they haven’t been specifically programmed for. Insert your usual fears of a robot uprising here.
“If our algorithms are to develop equally sophisticated behaviours, they too must have the capability to ‘imagine’ and reason about the future. Beyond that they must be able to construct a plan using this knowledge.”
To do this, the researchers combined several existing AI approaches together, including reinforcement learning (learning through trial and error) and deep learning (learning through processing vast amounts of data in a similar way to the human brain).
What they ended up with is a system that mixes trial-and-error with simulation capabilities, so bots can learn about their environment then think before they act.
Source: Science Alert
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
Google Debuts PAIR Initiative to Humanize #AI
We’re announcing the People + AI Research initiative (PAIR) which brings together researchers across Google to study and redesign the ways people interact with AI systems.
The goal of PAIR is to focus on the “human side” of AI: the relationship between users and technology, the new applications it enables, and how to make it broadly inclusive.
PAIR’s research is divided into three areas, based on different user needs:
- Engineers and researchers: AI is built by people. How might we make it easier for engineers to build and understand machine learning systems? What educational materials and practical tools do they need?
- Domain experts: How can AI aid and augment professionals in their work? How might we support doctors, technicians, designers, farmers, and musicians as they increasingly use AI?
- Everyday users: How might we ensure machine learning is inclusive, so everyone can benefit from breakthroughs in AI? Can design thinking open up entirely new AI applications? Can we democratize the technology behind AI?
Many designers and academics have started exploring human/AI interaction. Their work inspires us; we see community-building and research support as an essential part of our mission.
Focusing on the human element in AI brings new possibilities into view. We’re excited to work together to invent and explore what’s possible.
Source: Google blog
In the #AI Age, “Being Smart” Will Mean Something Completely Different
What can we do to prepare for the new world of work? Because AI will be a far more formidable competitor than any human, we will be in a frantic race to stay relevant. That will require us to take our cognitive and emotional skills to a much higher level.
Many experts believe that human beings will still be needed to do the jobs that require higher-order critical, creative, and innovative thinking and the jobs that require high emotional engagement to meet the needs of other human beings.
The challenge for many of us is that we do not excel at those skills because of our natural cognitive and emotional proclivities: We are confirmation-seeking thinkers and ego-affirmation-seeking defensive reasoners. We will need to overcome those proclivities in order to take our thinking, listening, relating, and collaborating skills to a much higher level.
What is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement.
The new smart will be determined not by what or how you know but by the quality of your thinking, listening, relating, collaborating, and learning. Quantity is replaced by quality.
And that shift will enable us to focus on the hard work of taking our cognitive and emotional skills to a much higher level.
Source: HBR
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
Ensure that #AI charts a course that benefits humanity and bolsters our shared values
AI for Good Global Summit
The United Nations this week is refocusing AI on sustainable development and assisting global efforts to eliminate poverty and hunger, and to protect the environment.
“Artificial Intelligence has the potential to accelerate progress towards a dignified life, in peace and prosperity, for all people,” said UN Secretary-General António Guterres. “The time has arrived for all of us – governments, industry and civil society – to consider how AI will affect our future.”
In a video message to the summit, Mr. Guterres called AI “a new frontier” with “advances moving at warp speed.”
He noted that that while AI is “already transforming our world socially, economically and politically,” there are also serious challenges and ethical issues which must be taken into account – including cybersecurity, human rights and privacy.
“This Summit can help ensure that artificial intelligence charts a course that benefits humanity and bolsters our shared values”
Source: UN News Centre
Will there be any jobs left as #AI advances?
A new report from the International Bar Association suggests machines will most likely replace humans in high-routine occupations.
The authors have suggested that governments introduce human quotas in some sectors in order to protect jobs.
We thought it’d just be an insight into the world of automation and blue collar sector. This topic has picked up speed tremendously and you can see it everywhere and read it every day. It’s a hot topic now.” – Gerlind Wisskirchen, a lawyer who coordinated the study
For business futurist Morris Miselowski, job shortages will be a reality in the future.
I’m not absolutely convinced we will have enough work for everybody on this planet within 30 years anyway. I’m not convinced that work as we understand it, this nine-to-five, Monday to Friday, is sustainable for many of us for the next couple of decades.”
“Even though automation begun 30 years ago in the blue-collar sector, the new development of artificial intelligence and robotics affects not just blue collar, but the white-collar sector,” Ms Wisskirchen. “You can see that when you see jobs that will be replaced by algorithms or robots depending on the sector.”
The report has recommended some methods to mitigate human job losses, including a type of ‘human quota’ in any sector, introducing ‘made by humans’ label or a tax for the use of machines.
But for Professor Miselowski, setting up human and computer ratios in the workplace would be impractical.
We want to maintain human employment for as long as possible, but I don’t see it as practical or pragmatic in the long-term,” he said. “I prefer what I call a trans-humanist world, where what we do is we learn to work alongside machines the same way we have with computers and calculators.
“It’s just something that is going to happen, or has already started to happen. And we need to make the best out of it, but we need to think ahead and be very thoughtful in how we shape society in the future — and that’s I think a challenge for everybody.” Ms Wisskirchen.
Source: ABC News
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
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
AI to become main way banks interact with customers within three years
Four in five bankers believe AI will “revolutionise” the way in which banks gather information as well as how they interact with their clients, said the Accenture Banking Technology Vision 2017 report
More than three quarters of respondents to the survey believed that AI would enable more simple user interfaces, which would help banks create a more human-like customer experience.
“(It) will give people the impression that the bank knows them a lot better, and in many ways it will take banking back to the feeling that people had when there were more human interactions.”
“The big paradox here is that people think technology will lead to banking becoming more and more automated and less and less personalized, but what we’ve seen coming through here is the view that technology will actually help banking become a lot more personalized,” said Alan McIntyre, head of the Accenture’s banking practice and co-author of the report.
The top reason for using AI for user interfaces, cited by 60 percent of the bankers surveyed, was “to gain data analysis and insights”.
Source: KFGO
Will Using AI To Make Loans Trade One Kind Of Bias For Another?
Digital lending is expected to double in size over the next three years, reaching nearly 10 percent of all loans in the U.S. and Europe.
Marc Stein, who runs Underwrite.AI, writes algorithms capable of teaching themselves.
The program learns from each correlation it finds, whether it’s determining someone’s favorite books or if they are lying about their income on a loan application. And using that information, it can predict whether the applicant is a good risk.
Digital lenders are pulling in all kinds of data, including purchases, SAT scores and public records like fishing licenses.
If we looked at the delta between what people said they made and what we could verify, that was highly predictive,” Stein says.
As part of the loan application process, some lenders have prospective borrowers download an app that uploads an extraordinary amount of information like daily location patterns, the punctuation of text messages or how many of their contacts have last names
“FICO and income, which are sort of the sweet spot of what every consumer lender in the United States uses, actually themselves are quite biased against people,” says Dave Girouard, the CEO of Upstart, an online lender.
Government research has found that FICO scores hurt younger borrowers and those from foreign counties because people with low incomes are targeted for higher-interest loans. Girouard argues that new, smarter data can make lending more fair.
Source: NPR
These chatbots may one day even replace your doctor
As artificial intelligence programs learn to better communicate with humans, they’ll soon encroach on careers once considered untouchable, like law and accounting.
These chatbots may one day even replace your doctor.
This January, the United Kingdom’s National Health Service launched a trial with Babylon Health, a startup developing an AI chatbot.
The bot’s goal is the same as the helpline, only without humans: to avoid unnecessary doctor appointments and help patients with over-the-counter remedies.
Using the system, patients chat with the bot about their symptoms, and the app determines whether they should see a doctor, go to a pharmacy, or stay home. It’s now available to about 1.2 million Londoners.
But the upcoming version of Babylon’s chatbot can do even more: In tests, it’s now dianosing patients faster human doctors can, says Dr. Ali Parsa, the company’s CEO. The technology can accurately diagnose about 80 percent of illnesses commonly seen by primary care doctors.
The reason these chatbots are increasingly important is cost: two-thirds of money moving through the U.K.’s health system goes to salaries.
“Human beings are very expensive,” Parsa says. “If we want to make healthcare affordable and accessible for everyone, we’ll need to attack the root causes.”
Globally, there are 5 million fewer doctors today than needed, so anything that lets a doctor do their jobs faster and more easily will be welcome, Parsa says.
Half the world’s population has little access to health care — but they have smartphones. Chatbots could get them the help they need.
Source: NBC News
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
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
DeepMind’s social agenda plays to its AI strengths
DeepMind’s researchers have in common a clearly defined if lofty mission:
to crack human intelligence and recreate it artificially.
Today, the goal is not just to create a powerful AI to play games better than a human professional, but to use that knowledge “for large-scale social impact”, says DeepMind’s other co-founder, Mustafa Suleyman, a former conflict-resolution negotiator at the UN.
“To solve seemingly intractable problems in healthcare, scientific research or energy, it is not enough just to assemble scores of scientists in a building; they have to be untethered from the mundanities of a regular job — funding, administration, short-term deadlines — and left to experiment freely and without fear.”
“if you’re interested in advancing the research as fast as possible, then you need to give [scientists] the space to make the decisions based on what they think is right for research, not for whatever kind of product demand has just come in.”
“Our research team today is insulated from any short-term pushes or pulls, whether it be internally at Google or externally.
We want to have a big impact on the world, but our research has to be protected, Hassabis says.
“We showed that you can make a lot of advances using this kind of culture. I think Google took notice of that and they’re shifting more towards this kind of longer-term research.”
Source: Financial Times
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