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Kosinski, a computational psychologist and professor of organizational behavior at Stanford Graduate School of Business, says the pace of AI development is accelerating beyond researchers’ ability to keep up (never mind policymakers and ordinary users).

We’re talking two weeks after OpenAI released GPT-4, the latest version of its large language model, grabbing headlines and making an unpublished paper Kosinski had written about GPT-3 all but irrelevant. “The difference between GPT-3 and GPT-4 is like the difference between a horse cart and a 737 — and it happened in a year,” he says.

he’s found that facial recognition software could be used to predict your political leaning and sexual orientation.

Powerful artificial intelligence systems threaten social stability and AI companies must be made liable for harms caused by their products, a group of senior experts including two “godfathers” of the technology has warned.

A co-author of the policy proposals from 23 experts said it was “utterly reckless” to pursue ever more powerful AI systems before understanding how to make them safe.

“It’s time to get serious about advanced AI systems,” said Stuart Russell, professor of computer science at the University of California, Berkeley. “These are not toys. Increasing their capabilities before we understand how to make them safe is utterly reckless.”

Large language models are drafting screenplays and writing code and cracking jokes. Image generators, such as Midjourney and DALL-E 2, are winning art prizes and democratizing interior design and producing dangerously convincing fabrications. They feel like magic. Meanwhile, the world’s most advanced robots are still struggling to open different kinds of doors

the cognitive psychologist Steven Pinker offered a pithier formulation: “The main lesson of thirty-five years of AI research,” he wrote, “is that the hard problems are easy and the easy problems are hard.” This lesson is now known as “Moravec’s paradox.”

The paradox has grown only more apparent in the past few years: AI research races forward; robotics research stumbles. In part that’s because the two disciplines are not equally resourced. Fewer people work on robotics than on AI.

the technological accomplishment of Bitcoin is that it invented a decentralized way to create scarcity on computers. Bitcoin demonstrated a way for me to send you a computer message so that you’d have it and I wouldn’t, to move items of computer information between us in a way that limited their supply and transferred possession.

The wild thing about Bitcoin is not that Satoshi invented a particular way for people to send numbers to one another and call them payments. It’s that people accepted the numbers as payments.

That social fact, that Bitcoin was accepted by many millions of people as having a lot of value, might be the most impressive thing about Bitcoin, much more than the stuff about hashing.

some eye-popping new realities about what’s really eating away at U.S.-China relations.

The new, new thing has a lot to do with the increasingly important role that trust, and its absence, plays in international relations, now that so many goods and services that the United States and China sell to one another are digital, and therefore dual use — meaning they can be both a weapon and a tool.

In the last 23 years America has built exactly one sort-of-high-speed rail line, the Acela, serving 15 stops between Washington, D.C., and Boston. Think about that: 900 to 15.

Lee Saedol was the finest Go player of his generation when he suffered a decisive loss, defeated not by a human opponent but by artificial intelligence.

The stunning upset, in 2016, made headlines around the world and looked like a clear sign that artificial intelligence was entering a new, profoundly unsettling era.

By besting Mr. Lee, an 18-time world champion revered for his intuitive and creative style of play, AlphaGo had solved one of computer science’s greatest challenges: teaching itself the abstract strategy needed to win at Go, widely considered the world’s most complex board game.

The Phaethon myth and Goethe’s poem fail to provide useful advice because they misconstrue the way humans gain power. In both fables, a single human acquires enormous power, but is then corrupted by hubris and greed. The conclusion is that our flawed individual psychology makes us abuse power.

What this crude analysis misses is that human power is never the outcome of individual initiative. Power always stems from cooperation between large numbers of humans. Accordingly, it isn’t our individual psychology that causes us to abuse power.

Our tendency to summon powers we cannot control stems not from individual psychology but from the unique way our species cooperates in large numbers. Humankind gains enormous power by building large networks of cooperation, but the way our networks are built predisposes us to use power unwisely

Strategists affiliated with the Obama and Romney campaigns say they have access to information about the personal lives of voters at a scale never before imagined. And they are using that data to try to influence voting habits — in effect, to train voters to go to the polls through subtle cues, rewards and threats in a manner akin to the marketing efforts of credit card companies and big-box retailers.

In the weeks before Election Day, millions of voters will hear from callers with surprisingly detailed knowledge of their lives. These callers — friends of friends or long-lost work colleagues — will identify themselves as volunteers for the campaigns or independent political groups. The callers will be guided by scripts and call lists compiled by people — or computers — with access to details like whether voters may have visited pornography Web sites, have homes in foreclosure, are more prone to drink Michelob Ultra than Corona or have gay friends or enjoy expensive vacations.

“You don’t want your analytical efforts to be obvious because voters get creeped out,” said a Romney campaign official who was not authorized to speak to a reporter. “A lot of what we’re doing is behind the scenes.”

So you’re happily tweeting away as your Google self-driving car crosses a bridge, its speed precisely synced to the 50 m.p.h. limit. A group of frisky schoolchildren is also heading across the bridge, on the pedestrian walkway. Suddenly, there’s a tussle, and three of the kids are pushed into the road, right in your vehicle’s path. Your self-driving car has a fraction of a second to make a choice: Either it swerves off the bridge, possibly killing you, or it runs over the children. What does the Google algorithm tell it to do?

As we begin to have computer-controlled cars, robots, and other machines operating autonomously out in the chaotic human world, situations will inevitably arise in which the software has to choose between a set of bad, even horrible, alternatives. How do you program a computer to choose the lesser of two evils? What are the criteria, and how do you weigh them?

Since we humans aren’t very good at codifying responses to moral dilemmas ourselves, particularly when the precise contours of a dilemma can’t be predicted ahead of its occurrence, programmers will find themselves in an extraordinarily difficult situation. And one assumes that they will carry a moral, not to mention a legal, burden for the code they write.

In case you needed further evidence that the White Hats are losing the war on cybercrime, a six-year-old so-called Trojan horse program that drains bank accounts is alive and well on Facebook. Zeus is a particularly nasty Trojan horse that has infected millions of computers, most of them in the United States. Once Zeus has compromised a computer, it stays dormant until a victim logs into a bank site, and then it steals the victim’s passwords and drains the victim’s accounts

Fifty minutes.That’s the average amount of time, the company said, that users spend each day on its Facebook, Instagram and Messenger platforms

there are only 24 hours in a day, and the average person sleeps for 8.8 of them. That means more than one-sixteenth of the average user’s waking time is spent on Facebook.

That’s more than any other leisure activity surveyed by the Bureau of Labor Statistics, with the exception of watching television programs and movies (an average per day of 2.8 hours)

Professor Winner coined the term “mythinformation,” the wishful thinking that with open access to technology, the world will become a better place. He has written of “computer enthusiasts,” that they feel there is “no need to try and shape the institutions of the information age in ways that maximize human freedom while placing limits upon concentrations of power.” The deletion of Mr. Cooper’s blog is, perhaps, evidence of what happens when we don’t try to limit concentrations of power.

The idea of a cloud benevolently storing our personal information, our work, our photos, our music, so much of our lives, is also really nice, but as users, we have no control over the cloud.

We surrender that control each time we write a blog post or log in to an email account or upload an image. The allure of all this technology is hard to resist.

have we run out of things to say and write that actually are about technology and the companies behind them? Or do we feel compelled to fill the white space between what matters? Sort of like talk radio?

There have been three big innovation narratives in the last few years that complicate, but don't invalidate, my thesis. The first -- The Rise of the Cloud -- was essentially a rebranding of having data on the Internet, which is, well ... what the Internet has always been about. Though I think it has made the lives of some IT managers easier and I do like Rdio. The second, Big Data, has lots of potential applications. But, as Tim Berners-Lee noted today, the people benefiting from more sophisticated machine learning techniques are the people buying consumer data, not the consumers themselves. How many Big Data startups might help people see their lives in different ways? Perhaps the personal genomics companies, but so far, they've kept their efforts focused quite narrowly. And third, we have the daily deal phenomenon. Groupon and its 600 clones may or may not be good companies, but they are barely technology companies. Really, they look like retail sales operations with tons of sales people and marketing expenses.

we've reached a point in this technology cycle where the old thing has run its course. I think the hardware, cellular bandwidth, and the business model of this tottering tower of technology are pushing companies to play on one small corner of a huge field.

Now there's a new pattern created by two big ideas. First, for the first time ever, you have computer devices, mobile and tablet especially, in the hands of billions of people. Second is that we are moving all the social needs that we used to do face-to-face, and we're doing them on a computer.

Companies like Facebook for the first time can get total markets approaching the entire population.

Silicon Valley is screwed as we know it.  If I have a choice of investing in a blockbuster cancer drug that will pay me nothing for ten years,  at best, whereas social media will go big in two years, what do you think I'm going to pick? If you're a VC firm, you're tossing out your life science division. All of that stuff is hard and the returns take forever. Look at social media. It's not hard, because of the two forces I just described, and the returns are quick.

The drive to reinvent school has also set off an explosive clash with teachers unions and backers of more traditional education. Partly, it's a philosophical divide. Critics say that cyberschools turn education into a largely utilitarian pursuit: Learn content, click ahead. They mourn the lack of discussion, fear kids won't be challenged to take risks, and fret about devaluing the softer skills learned in classrooms. "Schools teach people the skills of citizenship—how to get along with others, how to reason and deliberate, how to tolerate differences,"

A teacher in a traditional high school might handle 150 students. An online teacher can supervise more than 250, since he or she doesn't have to write lesson plans and most grading is done by computer.

In Georgia, state and local taxpayers spend $7,650 a year to educate the average student in a traditional public school. They spend nearly 60% less—$3,200 a year—to educate a student in the statewide online Georgia Cyber Academy, saving state and local tax dollars. Florida saves $1,500 a year on every student enrolled online full time.

Nokia was a phone company in a world that had stopped buying phones. Instead, we buy small computers that can also make calls. 

The iPhone evolved differently. It was a mobile phone, yes, but it was a device created with the explicit intent of syncing with iTunes and other Apple computer apps. In spirit, its form and function descended as much from the iPod as much as any phone that preceded it. The thing had a hard drive. It could access actual web pages. And once the second generation 3G model debuted along with the Apple app store, owners suddenly found themselves with a seemingly limitless range of software a few finger swipes away.

Before Steve Jobs & Co. effectively rethought the industry, smartphones were still essentially communications devices. They could call. They could text. They could moonlight as "email machines

My theory is that tablet computers aren't the new mobile phone or personal computer, gadgets most American adults have, particularly well-off ones. Rather, iPads are the new bicycle.

in a general sense, the trajectory is clear: With enough time and enough prosperity, sooner or later every consumer-technology product achieves a near-universal level of adoption. 

the National Household Travel Survey found that there were 0.86 bikes per American household.

“Earlier it was because some students weren’t plugged in enough into any virtual communication.” Seven years later, she said she cannot remove the instruction because now students avoid e-mail because it is “too slow compared to texting.”

Just how little are students using e-mail these days? Six minutes a day, according to an experiment done earlier this year by Reynol Junco, an associate professor of library science at Purdue. With the promise of a $10 Amazon gift card, Dr. Junco persuaded students to download a program letting him track their computer habits. During the semester, they spent an average of 123 minutes a day on a computer, by far the biggest portion of it, 31 minutes, on social networking. The only thing they spent less time on than e-mail: hunting for content via search engines (four minutes).

“I never know what to say in the subject line and how to address the person,” Ms. Carver said. “Is it mister or professor and comma and return, and do I have to capitalize and use full sentences? By the time I do all that I could have an answer by text if I could text them.”