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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.

Now, I’m 16, and I’ve been able to reflect on how I got sucked into that void—and how others do, too. My brief infatuation with the alt-right has helped me understand the ways big tech companies and their algorithms are contributing to the problem of radicalization—and why it’s so important to be skeptical of what you read online.

while a quick burst of radiation probably won’t give you cancer, prolonged exposure is far more dangerous. The same is true for the alt-right. I knew that the messages I was seeing were wrong, but the more I saw them, the more curious I became. I was unfamiliar with most of the popular discussion topics on Reddit. And when you want to know more about something, what do you do? You probably don’t think to go to the library and check out a book on that subject, and then fact check and cross reference what you find. If you just google what you want to know, you can get the information you want within seconds.

I started googling things like “Illegal immigration,” “Sandy Hook actors,” and “Black crime rate.” And I found exactly what I was looking for.

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.

The Information World War has already been going on for several years. We called the opening skirmishes “media manipulation” and “hoaxes”, assuming that we were dealing with ideological pranksters doing it for the lulz (and that lulz were harmless). In reality, the combatants are professional, state-employed cyberwarriors and seasoned amateur guerrillas pursuing very well-defined objectives with military precision and specialized tools. Each type of combatant brings a different mental model to the conflict, but uses the same set of tools.

There are also small but highly-skilled cadres of ideologically-motivated shitposters whose skill at information warfare is matched only by their fundamental incomprehension of the real damage they’re unleashing for lulz. A subset of these are conspiratorial — committed truthers who were previously limited to chatter on obscure message boards until social platform scaffolding and inadvertently-sociopathic algorithms facilitated their evolution into leaderless cults able to spread a gospel with ease.

There’s very little incentive not to try everything: this is a revolution that is being A/B tested.

There is probably no technology more beaten down, more discarded by “innovators,” and yet more irreplaceable and urgent today than RSS.

In an age of user feeds, everyone insist on becoming the one channel to rule your life, into a tyranny of algorithmic centralization. In a crafty and much needed mesh of open source standards and open-mindedness, RSS understood the human spirit will seek after freedom and choice at every turn.

democratized syndication

Wrongful arrests, an expanding surveillance dragnet, defamation and deep-fake pornography are all actually existing dangers of so-called “artificial intelligence” tools currently on the market. That, and not the imagined potential to wipe out humanity, is the real threat from artificial intelligence.

Beneath the hype from many AI firms, their technology already enables routine discrimination in housing, criminal justice and health care, as well as the spread of hate speech and misinformation in non-English languages. Already, algorithmic management programs subject workers to run-of-the-mill wage theft, and these programs are becoming more prevalent.

Corporate AI labs justify this posturing with pseudoscientific research reports that misdirect regulatory attention to such imaginary scenarios using fear-mongering terminology, such as “existential risk.”

How and why do well-educated, well-intentioned scientists produce biased AI systems? Sociological theories of privilege provide one useful lens.

Their training data is biased. They are designed by an unrepresentative group. They face the mathematical impossibility of treating all categories equally. They must somehow trade accuracy for fairness. And their biases are hiding behind millions of inscrutable numerical parameters.

fairness can still be the victim of competitive pressures in academia and industry. The flawed Bard and Bing chatbots from Google and Microsoft are recent evidence of this grim reality. The commercial necessity of building market share led to the premature release of these systems.

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.

Here’s a thought experiment: where do you end? Not your body, but you, the nebulous identity you think of as your “self”. Does it end at the limits of your physical form? Or does it include your voice, which can now be heard as far as outer space; your personal and behavioral data, which is spread out across the impossibly broad plane known as digital space; and your active online personas, which probably encompass dozens of different social media networks, text message conversations, and email exchanges? This is a question with no clear answer, and, as the smartphone grows ever more essential to our daily lives, that border’s only getting blurrier.

our minds have become even more radically extended than ever before

one of the essential differences between a smartphone and a piece of paper, which is that our relationship with our phones is reciprocal: we not only put information into the device, we also receive information from it, and, in that sense, it shapes our lives far more actively than would, say, a shopping list. The shopping list isn’t suggesting to us, based on algorithmic responses to our past and current shopping behavior, what we should buy; the phone is

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

expanding this system to a wider group of people would be hard. When a population reaches a certain scale, the system is likely to encounter people with similar eyes.This might be why most commercial facial recognition systems that can identify masked faces seem limited to small-scale applications

Many residential communities, especially in areas hit hardest by the virus, have been limiting entry to residents only. Minivision introduced the new algorithm to its facial recognition gate lock systems in communities in Nanjing to quickly recognize residents without the need to take off masks.

SenseTime, which announced the rollout of its face mask-busting tech last week, explained that its algorithm is designed to read 240 facial feature key points around the eyes, mouth and nose. It can make a match using just the parts of the face that are visible.

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?

for a great many people, the permanent memory bank of the Web increasingly means there are no second chances — no opportunities to escape a scarlet letter in your digital past. Now the worst thing you’ve done is often the first thing everyone knows about you.

a collective identity crisis. For most of human history, the idea of reinventing yourself or freely shaping your identity — of presenting different selves in different contexts (at home, at work, at play) — was hard to fathom, because people’s identities were fixed by their roles in a rigid social hierarchy. With little geographic or social mobility, you were defined not as an individual but by your village, your class, your job or your guild. But that started to change in the late Middle Ages and the Renaissance, with a growing individualism that came to redefine human identity. As people perceived themselves increasingly as individuals, their status became a function not of inherited categories but of their own efforts and achievements. This new conception of malleable and fluid identity found its fullest and purest expression in the American ideal of the self-made man, a term popularized by Henry Clay in 1832.

the dawning of the Internet age promised to resurrect the ideal of what the psychiatrist Robert Jay Lifton has called the “protean self.” If you couldn’t flee to Texas, you could always seek out a new chat room and create a new screen name. For some technology enthusiasts, the Web was supposed to be the second flowering of the open frontier, and the ability to segment our identities with an endless supply of pseudonyms, avatars and categories of friendship was supposed to let people present different sides of their personalities in different contexts. What seemed within our grasp was a power that only Proteus possessed: namely, perfect control over our shifting identities. But the hope that we could carefully control how others view us in different contexts has proved to be another myth. As social-networking sites expanded, it was no longer quite so easy to have segmented identities: now that so many people use a single platform to post constant status updates and photos about their private and public activities, the idea of a home self, a work self, a family self and a high-school-friends self has become increasingly untenable. In fact, the attempt to maintain different selves often arouses suspicion.

Over the past two years, RealNetworks has developed a facial recognition tool that it hopes will help schools more accurately monitor who gets past their front doors. Today, the company launched a website where school administrators can download the tool, called SAFR, for free and integrate it with their own camera systems

how to balance privacy and security in a world that is starting to feel like a scene out of Minority Report

facial recognition technology often misidentifies black people and women at higher rates than white men

The effectiveness of psychographic targeting is one bet being made by an increasing number of media companies when it comes to interrupting your viewing experience with advertising messages.

“Across the board, articles that were in top emotional categories, such as love, sadness and fear, performed significantly better than articles that were not.”

ESPN and USA Today are also using psychographic rather than demographic targeting to sell to advertisers, including in ESPN’s case, the decision to not show you advertising at all if your team is losing.