Households making $25,000-$35,000 a year spend ninety-two more minutes a week online than households making $100,000 or more a year in income, and differences vary monotonically over intermediate income levels.

That is from a new NBER paper by Boik, Greenstein, and Prince.  Do note that the authors adjust for age and other demographic variables.

The upshot is that the real “undervalued” services from the internet come from its risk-sharing properties, not from the supposed lack of pricing of internet services.  If something bad happens to you, well…there is always the internet to fall back upon, at least provided you still can afford the connection.  This also means that business cycles are not quite as painful as before, but also that labor markets will be slower to adjust.

Some also may find in this fact an optimistic statement that “real life” (ha ha) has more to offer than the internet, with the caveat that real life is expensive.

The data in this very interesting paper also indicate that Chat has largely collapsed since 2008 as a way of spending time on the internet, internet time devoted to news sites has fallen from 10% to 5%, and social media and video are on the rise.

Here is my previous post “Let them eat ideology!”

Here is Erik Hurst, from an excellent piece profiling Erik Hurst:

Right now, I’m gathering facts about the possible mechanisms at play, beginning with a hard look at time-use by young men with less than a four-year degree. In the 2000s, employment rates for this group dropped sharply – more than in any other group. We have determined that, in general, they are not going back to school or switching careers, so what are they doing with their time? The hours that they are not working have been replaced almost one for one with leisure time. Seventy-five percent of this new leisure time falls into one category: video games. The average low-skilled, unemployed man in this group plays video games an average of 12, and sometimes upwards of 30 hours per week. This change marks a relatively major shift that makes me question its effect on their attachment to the labor market.

To answer that question, I researched what fraction of these unemployed gamers from 2000 were also idle the previous year. A staggering 22% – almost one quarter – of unemployed young men did not work the previous year either. These individuals are living with parents or relatives, and happiness surveys actually indicate that they quite content compared to their peers, making it hard to argue that some sort of constraint, like they are miserable because they can’t find a job, is causing them to play video games.

This problem, if that is the right word for it, will not be easily solved.

From Istanbul, follow him here.  Here is my 2010 post “Why Timur Kuran is one of our most important thinkers.”  Timur’s work has held up very well since then, to say the least.

Addendum: Here are remarks from Turkish economist Dani Rodrik.

For some time now I have had mixed feelings about the move to electronic medical records, here is another reason why:

On the dark web, medical records draw a far higher price than credit cards. Hackers are well aware that it’s simple enough to cancel a credit card, but to change a social security number is no easy feat. Banks have taken some major steps to crack down on identity theft. But hospitals, which have only transitioned en masse from paper-based to digital systems in the past decade, have far fewer security protections in place.

…These records can sell for as much as (the bitcoin equivalent) of $60 apiece, whereas social security numbers are a mere $15. Stolen credit cards sell for just $1 to $3. During the tour, we spotted one hacker who claimed to have a treasure trove of just shy of 1 million full health records up for grabs.

As IBM’s Kuhn explained in a follow-up interview, these medical records can be leveraged for a wide variety of nefarious purposes. In some cases, it’s about stealing a person’s identity and billing them for a surgery or a prescription, and in others it’s about opening a new line of credit. Security researcher Avi Rubin told Fast Company in an recent interview that he suspects hacked medical records are often routinely used for blackmail and extortion.

Such hacking is indeed a trend:

More than 113 million medical records were hacked in 2015 alone, according to data compiled by the Health and Human Services. A newly released report from the Institute for Critical Infrastructure Technology, a cybersecurity think tank, found that some 47% of Americans have had their medical record hacked in the past 12 months.

That is from Christina Farr.

“The definition of an anchor has changed,” said Stephen Lebovitz, the chief executive of mall owner CBL & Associates Properties Inc. “Cheesecake Factory does as much business as Sears used to do.”

That is from Suzanne Kapner at the WSJ, on the decline of traditional anchor stores.  Yet not all of the new service sector jobs will be there forever:

“Right now we’re doing a couple hundred videos a day,” he said. “We think we need to be doing 2,000 videos a day.”

Mr. Ferro’s comments added to mounting confusion over his embattled company’s sudden rebranding. How could a newspaper publisher create nearly three-quarters of a million videos a year?

But as jarring as Tronc’s goals may sound, the company’s plan is far from novel. In pursuit of more lucrative video advertising and success on dominant social platforms like Facebook, a growing number of publishers have turned to technology that promises to streamline video production, sometimes to the point of near-full automation.

That is John Herrman from the NYT.  File under Marginal Revolution Robot University.  And if you are wondering how it works, here is a snippet:

The two services’ automation features work in similar ways. They analyze, and may summarize, text, be it a script or a traditional news article, and then automatically find photographs and video clips to go with it. The services typically get the videos and images from sources like The Associated Press and Getty Images.

Additionally, the tools offer the option to quickly put large animated captions over the videos, in a format that has become popular on Facebook, where videos begin playing automatically and are often watched with the sound off. Each can also supply, through a third party, on-demand human narration; Wibbitz offers computerized voice-overs as well.

What does this say about the media sector more generally?

A neural network can be designed to provide a measure of its own confidence in a categorization, but the complexity of the mathematical calculations involved means it’s not straightforward to take the network apart to understand how it makes its decisions. This can make unintended behavior hard to predict; and if failure does occur, it can be difficult to explain why. If a system misrecognizes an object in a photo, for instance, it may be hard (though not impossible) to know what feature of the image led to the error. Similar challenges exist with other machine learning techniques.

That is from Will Knight.  This reminds me of computer chess, especially in its earlier days but still today as well.  The evaluation functions are not transparent, to say the least, and they were not designed by the conscious planning of humans.  (In the case of chess, it was a common tactic to let varied program options play millions of games against each other and simply see which evaluation functions won the most.)  So when people debate “Will you buy the Peter Singer utilitarian driverless car?” or “Will you buy the Kant categorical imperative driverless car?”, and the like, they are not paying sufficient heed to this point.  A lot of the real “action” with driverless cars will be determined by the non-transparent features of their programs.

How will regulatory systems — which typically look for some measure of verifiable ex ante safety — handle this reality?  Or might this non-transparency be precisely what enables the vehicles to be put on the road, because it will be harder to object to them?  What will happen when there is a call to “fix the software so this doesn’t happen any more”?  To be sure, adjustments will be made.

More and more of our world is becoming this way, albeit slowly.

For the pointer I thank Michelle Dawson.

Popular Science: A pilot A.I. developed by a doctoral graduate from the University of Cincinnati has shown that it can not only beat other A.I.s, but also a professional fighter pilot with decades of experience. In a series of flight combat simulations, the A.I. successfully evaded retired U.S. Air Force Colonel Gene “Geno” Lee, and shot him down every time. In a statement, Lee called it “the most aggressive, responsive, dynamic and credible A.I. I’ve seen to date.”

What’s the most important part of this paragraph? The fact that an AI downed a professional fighter pilot? Or the fact that the AI was developed by a graduate student?

In the research paper the article is based on the authors note:

…given an average human visual reaction time of 0.15 to 0.30 seconds, and an even longer time to think of optimal plans and coordinate them with friendly forces, there is a huge window of improvement that an Artificial Intelligence (AI) can capitalize upon.

The AI was running on a $35 Raspberry Pi.

AI pilots can plan and react far quicker than human pilots but that is only half the story. Once we have AI pilots, the entire plane can be redesigned. We can build planes today that are much faster and more powerful than anything that exists now but the pilots can’t take the G-forces even with g-suits, AIs can. Moreover, AI driven planes don’t need ejector seats, life-support, canopies or as much space as humans.

The military won’t hesitate to deploy these systems for battlefield dominance so now seems like a good time to recommend Concrete Problems in AI Safety, a very important paper written by some of the world’s leading researchers in artificial intelligence. The paper examines practical ways to design AI systems so they don’t run off the rails. In the Terminator movie, for example, Skynet goes wrong because it concludes that the best way to fulfill its function to safeguard the world is to eliminate all humans–this is an extreme example of one type of problem, reward hacking.

Imagine that an agent discovers a buffer overflow in its reward function: it may then use this to get extremely high reward in an unintended way. From the agent’s point of view, this is not a bug, but simply how the environment works, and is thus a valid strategy like any other for achieving reward. For example, if our cleaning robot is set up to earn reward for not seeing any messes, it might simply close its eyes rather than ever cleaning anything up. Or if the robot is rewarded for cleaning messes, it may intentionally create work so it can earn more reward. More broadly, formal rewards or objective functions are an attempt to capture the designer’s informal intent, and sometimes these objective functions, or their implementation, can be “gamed” by solutions that are valid in some literal sense but don’t meet the designer’s intent. Pursuit of these “reward hacks” can lead to coherent but unanticipated behavior, and has the potential for harmful impacts in real-world systems. For example, it has been shown that genetic algorithms can often output unexpected but formally correct solutions to problems [155, 22], such as a circuit tasked to keep time which instead developed into a radio that picked up the regular RF emissions of a nearby PC.

Concrete Problems in AI Safety asks what kind of general solutions might exist to prevent or ameliorate reward hacking when we can never know all the variables that might be hacked? (The paper looks at many other issues as well.)

Competitive pressures on the battlefield and in the market mean that AI adoption will be rapid and AIs will be placed in greater and greater positions of responsibility. Firms and governments, however, have an incentive to write piecemeal solutions to AI control for each new domain but that is unlikely to be optimal. We need general solutions so that every AI benefits from the best thinking across a wide range of domains. Incentive design is hard enough when applied to humans. It will take a significant research effort combining ideas from computer science, mathematics and economics to design the right kind of incentive and learning structures for super-human AIs.

Soon I will be recording a podcast-only, no live attendance, no live video Conversations with Tyler with Michael Orthofer.  Michael runs the site Literary Saloon and is perhaps the world’s most productive book reviewer and book review blogger, with a focus on foreign fiction translated into English.  Michael is a deeply devoted infovore, and I expect this to be one of the most interesting conversations in the series.

Here is my short review of Michael’s big book on world literature: “If you measure book quality by the actual marginal product of the text, this is one of the best books written, ever.  Reading the manuscript in draft form induced me to a) write an enthusiastic blurb, and b) order about forty items through Amazon, mostly used of course.  The book is basically a comprehensive guide to what is valuable and interesting in recently translated world literature, a meta-book so to speak, with extensive coverage of most of the countries you might want.”

Here is the New Yorker profile of Orthofer:

“I can’t imagine not doing it,” Orthofer told me. “A day in which I don’t read or write, I have trouble falling asleep.” His goal is to read a book a day, though he confesses that this is “unrealistic.” He works on weekends, too, and has written four novels that are in the drawer. His main interests, according to the site, are inline roller-skating in Central Park and building snow sculptures, some of which are big enough that he carves staircases inside them to get to the top. When he tires of working, he steps out to a library or bookstore, “to see, be around books.” Last year, and this year, he worked through Christmas.

OK, so what should I ask Michael?  Comments are open.

Addendum: Here are previous installments of Conversations with Tyler.

It can be incredibly frustrating when a virtual assistant repeatedly misunderstands what you’re saying. Soon, though, some of them might at least be able to hear the irritation in your voice, and offer an apology.

Amazon is working on significant updates to Alexa, the virtual helper that lives inside the company’s voice-controlled home appliance, called Amazon Echo. These will include better language skills and perhaps the ability to recognize the emotional tenor of your voice.

Researchers have long predicted that emotional cues could make machine interfaces much smarter, but so far such technology has not been incorporated into any consumer technology.

Rosalind Picard, a professor at MIT’s Media Lab, says adding emotion sensing to personal electronics could improve them: “Yes, definitely, this is spot on.” In a 1997 book, Affective Computing, Picard first mentioned the idea of changing the voice of a virtual helper in response to a user’s emotional state. She notes that research has shown how matching a computer’s voice to that of a person can make communication more efficient and effective. “There are lots of ways it could help,” she says.

The software needed to detect the emotional state in a person’s voice exists already. For some time, telephone support companies have used such technology to detect when a customer is becoming irritated while dealing with an automated system. In recent years, new machine-learning techniques have improved the state of the art, making it possible to detect more emotional states with greater accuracy, although the approach is far from perfect.

Here is the full story.  Here is my recent New Yorker piece on how talking bots will affect us.

The robot administers a small pin prick at random to certain people of its choosing.

The tiny injury pierces the flesh and draws blood.

Mr Reben has nicknamed it ‘The First Law’ after a set of rules devised by sci-fi author Isaac Asimov.

He created it to generate discussion around our fear of man made machines. He says his latest device shows we need to prepare for the worst

‘Obviously, a needle is a minimum amount of injury, however – now that this class of robot exists, it will have to be confronted,’ Mr Reben said on his website.

Here is more, with pictures of (slightly) injured humans, via the excellent Mark Thorson.

A reader has been asking me this question, and my answer is…no!

Don’t get me wrong, I still think it is a stimulating and wonderful book.  And if you don’t believe me, here is The Wall Street Journal:

Mr. Hanson’s book is comprehensive and not put-downable.

But it is best not read as a predictive text, much as Robin might disagree with that assessment.  Why not?  I have three main reasons, all of which are a sort of punting, nonetheless on topics outside one’s areas of expertise deference is very often the correct response.  Here goes:

1. I know a few people who have expertise in neuroscience, and they have never mentioned to me that things might turn out this way (brain scans uploaded into computers to create actual beings and furthermore as the dominant form of civilization).  Maybe they’re just holding back, but I don’t think so.  The neuroscience profession as a whole seems to be unconvinced and for the most part not even pondering this scenario.

2. The people who predict “the age of Em” claim expertise in a variety of fields surrounding neuroscience, including computer science and physics, and thus they might believe they are broader and thus superior experts.  But in general claiming expertise in “more” fields is not correlated with finding the truth, unless you can convince people in the connected specialized fields you are writing about.  I don’t see this happening, nor do I believe that neuroscience is somehow hopelessly corrupt or politicized.  What I do see the “Em partisans” sharing is an early love of science fiction, a very valuable enterprise I might add.

3. Robin seems to think the age of Em could come about reasonably soon (sorry, I am in Geneva and don’t have the book with me for an exact quotation).  Yet I don’t see any sign of such a radical transformation in market prices.  Even with positive discounting, I would expect backwards induction to mean that an eventual “Em scenario” would affect lots of prices now.  There are for instance a variety of 100-year bonds, but Em scenarios do not seem to be a factor in their pricing.

Robin himself believes that market prices are the best arbiter of truth.  But which market prices today show a realistic probability for an “Age of Em”?  Are there pending price bubbles in Em-producing firms, or energy companies, just as internet grocery delivery was the object of lots of speculation in 1999-2000?  I don’t see it.

The one market price that has changed is the “shadow value of Robin Hanson,” because he has finished and published a very good and very successful book.  And that pleases me greatly, no matter which version of Robin is hanging around fifty years hence.

Addendum: Robin Hanson responds.  I enjoyed this line: “Tyler has spent too much time around media pundits if he thinks he should be hearing a buzz about anything big that might happen in the next few centuries!”

Looking for something to do this weekend in New York? Story, a concept shop that completely changes theme every few months, has relaunched this week as a Mr. Robot-themed space. In addition to being a retail shop selling an assortment of gadgets, accessories, and Mr. Robot-themed wares, there’s an “Evil Corp” ATM at the front of the store that will dispense real money (up to $50) if you figure out the four-digit code. The clues are hidden around the store, and we’re told they’ll probably change often.

Here is the full story, with many photos and an address.  To think that they closed Tower Records and Borders for this…sigh.

I found this discussion of interest:

I believe I’ve sketched out an idea that enables all transfers to verify the recipient is not a prohibited person without communicating any distinguishing information to the government while optionally leaving an audit trail useful for prosecution.

  • When an individual applies for state-issued identification, let them choose a public-private key pair. Make the public key part of their identification card, and the private key remain private. Not even the issuing state would know it. Add their public key to a whitelist.

  • At the same time, perform a background check to determine if the individual is a prohibited person. If so, add their public key to a blacklist.

  • Publish the blacklist in bulk and make updates available daily. We all have access to the Internet. We can do this. Regularly update the blacklist according to adjudicating events associated with the definition of “prohibited person.” For example, at the time of conviction of a felony, and individual’s public key gets added to the blacklist.

  • Firearms sellers, private and commercial, must maintain a copy of the blacklist up-to-date at the time of sale. Perhaps use a blockchain of sorts and/or share via BitTorrent or some other distributed service.

  • At the time of sale, the recipient provides their public key to the seller. Seller verifies the public key is not on the blacklist. The seller constructs a secret cryptographic nonce and encrypts it with the recipient’s public key. Recipient decrypts with their private key and returns the nonce in plaintext to the seller to confirm their public-private key pair is valid. This form of handshaking is common place and may be automated.

  • If the recipient is on the whitelist and not on the blacklist, the transfer may proceed.

  • Optionally, the seller may record a log of the recipient’s public key, perhaps encrypted with their private key. On the event of a warranted search, the seller may choose to decrypt their log entry to reveal the identify of the recipient.This leaves the audit trail which we may be legislatively require.

Thus, no direct communication with the state on the event of a transfer is needed which prevents the creation of a registry. Prohibited persons cannot acquire firearms without unlawful behavior from the seller which satisfies the aims of universal background checks. We already have all the cryptographic primitives and communications infrastructure needed to implement this and verify its integrity.


That is from kermudgeon on Reddit, via N.  Some of the comments are quite good as well.

An all-cash deal where the combined entity is trading down on the news is basically the exact opposite of bubble behavior.

That is from Conor SenGrodaeu remarked:

Microsoft had to move quickly before the ECB bought it

Increasingly, says Professor Crystal, whose books include Making a Point: The Persnickety Story of English Punctuation,” the period is being deployed as a weapon to show irony, syntactic snark, insincerity, even aggression

If the love of your life just canceled the candlelit, six-course, home-cooked dinner you have prepared, you are best advised to include a period when you respond “Fine.” to show annoyance

“Fine” or “Fine!,” in contrast, could denote acquiescence or blithe acceptance

“The period now has an emotional charge and has become an emoticon of sorts,” Professor Crystal said

And this:

Researchers at Binghamton University in New York and Rutgers University in New Jersey have also recently noted the period’s new semantic force

They asked 126 undergraduate students to review 16 exchanges, some in text messages, some in handwritten notes, that had one-word affirmative responses (Okay, Sure, Yeah, Yup) Some had periods, while others did not

Those text message with periods were rated as less sincere, the study found, whereas it made no difference in the notes penned by hand

Here is the full Dan Bilefsky story (NYT).