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As information overload grows ever worse, computers may become our only hope for handling a growing deluge of documents. And it may become routine to rely on a machine to analyze and paraphrase articles, research papers, and other text for you.

Parsing language remains one of the grand challenges of artificial intelligence (see “AI’s Language Problem”). But it’s a challenge with enormous commercial potential. Even limited linguistic intelligence—the ability to parse spoken or written queries, and to respond in more sophisticated and coherent ways—could transform personal computing. In many specialist fields—like medicine, scientific research, and law—condensing information and extracting insights could have huge commercial benefits.

The system experiments in order to generate summaries of its own using a process called reinforcement learning. Inspired by the way animals seem to learn, this involves providing positive feedback for actions that lead toward a particular objective. Reinforcement learning has been used to train computers to do impressive new things, like playing complex games or controlling robots (see “10 Breakthrough Technologies 2017: Reinforcement Learning”). Those working on conversational interfaces are increasingly now looking at reinforcement learning as a way to improve their systems.

we need, first, to take charge of our own learning, and next, help others take charge of their own learning. We need to move beyond the idea that an education is something that is provided for us, and toward the idea that an education is something that we create for ourselves. It is time, in other words, that we change out attitude toward learning and the educational system in general. That is not to advocate throwing learners off the bus to fend for themselves. It is hard to be self-reliant, to take charge of one's own learning, and people shouldn't have to do it alone. It is instead to articulate a way we as a society approach education and learning, beginning with an attitude, though the development of supports and a system, through to the techniques and technologies that support that.

Harassment and misogyny had been problems in the community for years before this; the deep resentment and anger toward women that powered Gamergate percolated for years on internet forums. Robert Evans, a journalist who specializes in extremist communities and the host of the Behind the Bastards podcast, described Gamergate to me as partly organic and partly born out of decades-long campaigns by white supremacists and extremists to recruit heavily from online forums. “Part of why Gamergate happened in the first place was because you had these people online preaching to these groups of disaffected young men,” he said. But what Gamergate had that those previous movements didn’t was an organized strategy, made public, cloaking itself as a political movement with a flimsy philosophical stance, its goals and targets amplified by the power of Twitter and a hashtag.

The hate campaign, we would later learn, was the moment when our ability to repress toxic communities and write them off as just “trolls” began to crumble. Gamergate ultimately gave way to something deeper, more violent, and more uncontrollable.

Police have to learn how to keep the rest of us safe from internet mobs

My father would have been unable to “teach to the test.” He once complained about errors in a sixth-grade math textbook, so he had the class learn math by designing a spaceship. My father would have been spat out by today’s test-driven educational regime.

A career in computer science makes you see the world in its terms. You start to see money as a form of information display instead of as a store of value. Money flows are the computational output of a lot of people planning, promising, evaluating, hedging and scheming, and those behaviors start to look like a set of algorithms. You start to see the weather as a computer processing bits tweaked by the sun, and gravity as a cosmic calculation that keeps events in time and space consistent. This way of seeing is becoming ever more common as people have experiences with computers. While it has its glorious moments, the computational perspective can at times be uniquely unromantic. Nothing kills music for me as much as having some algorithm calculate what music I will want to hear. That seems to miss the whole point. Inventing your musical taste is the point, isn’t it? Bringing computers into the middle of that is like paying someone to program a robot to have sex on your behalf so you don’t have to. And yet it seems we benefit from shining an objectifying digital light to disinfect our funky, lying selves once in a while. It’s heartless to have music chosen by digital algorithms. But at least there are fewer people held hostage to the tastes of bad radio D.J.’s than there once were. The trick is being ambidextrous, holding one hand to the heart while counting on the digits of the other.

The future of education in the digital age will be determined by our judgment of which aspects of the information we pass between generations can be represented in computers at all. If we try to represent something digitally when we actually can’t, we kill the romance and make some aspect of the human condition newly bland and absurd. If we romanticize information that shouldn’t be shielded from harsh calculations, we’ll suffer bad teachers and D.J.’s and their wares.

If you want to learn something from Finland, it’s the implementation of ideas. It’s looking at education as nation-building. We have very carefully kept the business of education in the hands of educators. It’s practically impossible to become a superintendent without also being a former teacher. … If you have people [in leadership positions] with no background in teaching, they’ll never have the type of communication they need.

Finns don’t believe you can reliably measure the essence of learning. You know, one big difference in thinking about education and the whole discourse is that in the U.S. it’s based on a belief in competition. In my country, we are in education because we believe in cooperation and sharing. Cooperation is a core starting point for growth.

machine learning research mirrors the way cryptography research developed around the middle of the 20th century. Much of the cutting edge research was done in secret, and we're only finding out now, 40 or 50 years later, what GCHQ or the NSA was doing back then. I'm hopeful that it won't take quite that long for Amazon or Google to tell us what they're thinking about today

All the components of the system are thought of as agents — effectively "smart" pieces of software

increased adaptability in the face of asynchronously arriving data

rather than making us smarter, mobile devices reduce our cognitive ability in measurable ways

“There’s lots of evidence showing that the information you learn on a digital device, doesn’t get retained very well and isn’t transferred across to the real world,”

“You’re also quickly conditioned to attend to lots of attention-grabbing signals, beeps and buzzes, so you jump from one task to the other and you don’t concentrate.”

We also need to distinguish what scientists know about human neurophysiology from our all-too-human discomfort with cultural and social change.  I've been an English professor for over twenty years and have heard how students don't pay attention, can't read a long novel anymore, and are in decline against some unspecified norm of an idealized past quite literally every year that I have been in this profession. In fact, how we educators should address this dire problem was the focus of the very first faculty meeting I ever attended.

Whenever I hear about attentional issues in debased contemporary society, whether blamed on television, VCR's, rock music, or the desktop, I assume that the critic was probably, like me, the one student who actually read Moby Dick and who had little awareness that no one else did.

This is not really a discussion about the biology of attention; it is about the sociology of change.

UW researchers hypothesized that babies would be more likely to view the robot as a psychological being if they saw other friendly human beings socially interacting with it. “Babies look to us for guidance in how to interpret things, and if we treat something as a psychological agent, they will, too,” Meltzoff said. “Even more remarkably, they will learn from it, because social interaction unlocks the key to early learning.”

“The study suggests that if you want to build a companion robot, it is not sufficient to make it look human,” said Rao. “The robot must also be able to interact socially with humans, an interesting challenge for robotics.”

such attitudes among students can develop from the notion that all of education can be distilled into performance on a test -- which today's college students have absorbed from years of schooling under No Child Left Behind -- and not that education is a process in which one grapples with difficult material.

A significant difficulty that learning analytics needs to address is the possible return to behaviourism where we make decisions about learning only on observable behaviours of learners. Nonetheless, algorithms define our lives and how organizations interact with us. It’s a data-driven world, and the algorithm reigns supreme.

So, this moldy jail I was in was this old dot-com McMansion, out in the Permanent Foreclosure Zone in the dead suburbs. That's where they cooped us up. This gated community was built for some vanished rich people. That was their low-intensity prison for us rehab detainees.

This place outside was a Beltway suburb before Washington was abandoned. The big hurricane ran right over it, and crushed it down pretty good, so now it was a big green hippie jungle. Our prison McMansion had termites, roaches, mold and fleas, but once it was a nice house. This rambling wreck of a town was half storm-debris. All the lawns were replaced with wet, weedy, towering patches of bamboo, or marijuana -- or hops, or kenaf, whatever (I never could tell those farm crops apart). The same goes for the "garden roofs," which were dirt piled on top of the dirty houses. There were smelly goats running loose, chickens cackling. Salvaged umbrellas and chairs toppled in the empty streets. No traffic signs, because there were no cars.

The rich elite just blew it totally. They dropped their globalized ball. They panicked. So they're in jail, like I was. Or they're in exile somewhere, or else they jumped out of penthouses screaming when the hyperinflation ate them alive.

A book is more like the score of a piece of music than it is like a painting. No great musician confuses a symphony with the printed sheets of music. Arturo Toscanini reveres Brahms, but Toscanini's score of the G minor Symphony is so thoroughly marked up that no one but the maestro himself can read it. The reason why a great conductor makes notations on his musical scores -- marks them up again and again each time he returns to study them--is the reason why you should mark your books.

the physical act of writing, with your own hand, brings words and sentences more sharply before your mind and preserves them better in your memory. To set down your reaction to important words and sentences you have read, and the questions they have raised in your mind, is to preserve those reactions and sharpen those questions.

that is exactly what reading a book should be: a conversation between you and the author. Presumably he knows more about the subject than you do; naturally, you'll have the proper humility as you approach him. But don't let anybody tell you that a reader is supposed to be solely on the receiving end. Understanding is a two-way operation; learning doesn't consist in being an empty receptacle. The learner has to question himself and question the teacher. He even has to argue with the teacher, once he understands what the teacher is saying. And marking a book is literally an expression of differences, or agreements of opinion, with the author

experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities

most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.

CONCERNS Human agency: Individuals are  experiencing a loss of control over their lives Decision-making on key aspects of digital life is automatically ceded to code-driven, "black box" tools. People lack input and do not learn the context about how the tools work. They sacrifice independence, privacy and power over choice; they have no control over these processes. This effect will deepen as automated systems become more prevalent and complex. Data abuse: Data use and surveillance in complex systems is designed for profit or for exercising power Most AI tools are and will be in the hands of companies striving for profits or governments striving for power. Values and ethics are often not baked into the digital systems making people's decisions for them. These systems are globally networked and not easy to regulate or rein in. Job loss: The AI takeover of jobs will widen economic divides, leading to social upheaval The efficiencies and other economic advantages of code-based machine intelligence will continue to disrupt all aspects of human work. While some expect new jobs will emerge, others worry about massive job losses, widening economic divides and social upheavals, including populist uprisings. Dependence lock-in: Reduction of individuals’ cognitive, social and survival skills Many see AI as augmenting human capacities but some predict the opposite - that people's deepening dependence on machine-driven networks will erode their abilities to think for themselves, take action independent of automated systems and interact effectively with others. Mayhem: Autonomous weapons, cybercrime and weaponized information Some predict further erosion of traditional sociopolitical structures and the possibility of great loss of lives due to accelerated growth of autonomous military applications and the use of weaponized information, lies and propaganda to dangerously destabilize human groups. Some also fear cybercriminals' reach into economic systems.

There is something thrilling about the intellectual audacity of thinking that you can explain ninety per cent of behavior in a society with one mental tool.

education, which they believe is a form of domestication

there is no moral dimension to this economic analysis: utility is a fundamentally amoral concept

I’ve spent my life writing science-fiction novels that try to convey some of the strangeness of the future. But I was still shocked by how much had changed, and how quickly.

the change that struck me seemed more abstract and internal. It was a change in the way we were looking at things, and it is still ongoing. The virus is rewriting our imaginations. What felt impossible has become thinkable. We’re getting a different sense of our place in history. We know we’re entering a new world, a new era. We seem to be learning our way into a new structure of feeling.

The Anthropocene, the Great Acceleration, the age of climate change—whatever you want to call it, we’ve been out of synch with the biosphere, wasting our children’s hopes for a normal life, burning our ecological capital as if it were disposable income, wrecking our one and only home in ways that soon will be beyond our descendants’ ability to repair. And yet we’ve been acting as though it were 2000, or 1990—as though the neoliberal arrangements built back then still made sense. We’ve been paralyzed, living in the world without feeling it.

The human capability for information processing is limited, yet there is an accelerating change in the development and deployment of new technology. This relentless wave upon wave of new information and technology causes an overload on the human mind by eventually flooding it. The resulting acopia -- inability to cope -- has to be solved by the use of ever more sophisticated information intelligence. Extrapolating these capabilities suggests the near-term emergence and visibility of self-improving neural networks, "artificial" intelligence, quantum algorithms, quantum computing and super-intelligence. This metamorphosis is so much beyond present human capabilities that it becomes impossible to understand it with the pre-conceptions and conditioning of the present mindset, societal make-up and existing technology

The Bio-Info-Nano Singularity is a transcendence to a wholly new regime of mind, society and technology, in which we have to learn to think in a new way in order to survive as a species.

What is globalized human society going to do with the mass of unemployed human beings that are rendered obsolete by the approaching super-intelligence of the Bio-Info-Nano Singularity?

not being trained in digital citizenship never caused a problem for me. I knew what was right and wrong, and I did the right thing. Why is this being treated so differently???‎"Nobody has come out and said, 'This is how it's supposed to be.'" This is part of my issue with "education". Students are learning that they only need to do what they are told. If there's isn't a rule, it must be OK. There's no thought, no critical evaluation, no drawing of parallels that if something is wrong in this circumstance, then it must also be in this other situation. People need to be allowed (forced? certainly encouraged) to think for themselves -- and to be responsible for their own actions!

"For the most part, kids who are in college today never received any form of digital citizenship or media training when they were in high school or middle school."