The value of the internet, quantified

Measuring the economic impact of all the ways the internet has changed people’s lives is devilishly difficult because so much of it has no price. It is easier to quantify the losses Wikipedia has inflicted on encyclopedia publishers than the benefits it has generated for users like Ms Mollica. This problem is an old one in economics. GDP measures monetary transactions, not welfare. Consider someone who would pay $50 for the latest Harry Potter novel but only has to pay $20. The $30 difference represents a non-monetary benefit called “consumer surplus”. The amount of internet activity that actually shows up in GDP—Google’s ad sales, for example—significantly understates its contribution to welfare by excluding the consumer surplus that accrues to Google’s users. The hard question to answer is by how much.

The headline grabbing figure from this article on measuring the value of the Internet is $2,600. That's the consumer surplus per user per year of the Internet as measured by two researchers at MIT who looked at how much time the average American spent online and assumed that consumers valued that time online more than their alternatives.

​Does that figure sound right? I guess the easiest way to assess that is to ask yourself if you'd pay $2,600 a year for the Internet or not. That sounds like a lot of money, but I reluctantly concede that I probably would.

Maybe it could be included in Amazon Prime?​

The simulator

I think we all have a little built-in simulator in which we run miniature copies of all the people in our lives. These are the brain equivalents to computer games like The Sims. When you get to know someone, you put a copy of them in the simulator. This allows you to model their behavior, and thus to attempt to predict it. The simulator lets us guess which of our fellow humans is likely to be trustworthy, which ones might mate with us, which ones might beat us to a pulp if they get the chance.

That's Cory Doctorow on where fictional characters come from.

This, I think, is what happens when you write. You and your simulator collaborate to create your imaginary people. You start by telling your simulator that there’s a guy named Bob who’s on the run from the law, and the simulator dutifully creates a stick figure with a sign called ‘‘Bob’’ over his head and worried look on his face. You fill in the details as you write, dropping hints to your simulator about Bob, and so Bob gets more and more fleshed out. But the simulator isn’t just adding in the details you tell it about: it’s guessing about the details you haven’t yet supplied, so that when you go back to your imagination and ask it about Bob’s particulars, some of those answers come from the simulator – it’s a kind of prejudice that affects imaginary people, a magic trick where your conscious and subconscious minds vie to fool each other with compounded lies about fake people, each building on the last in a feedback loop that runs faster and faster as you go.

That’s why your characters eventually ‘‘come to life.’’ Eventually, your characters’ details contain so much data gleaned from things the simulator ‘‘knows’’ – because it has supplied them, after guessing about them – that they come to seem real to you, and to it (which is the same thing).

Purple Pricing

It shouldn't be surprising, perhaps, that one of the more innovative sports ticket pricing schemes to be put into practice comes out of Northwestern University, not traditionally a sports powerhouse. ​Last month, they launched Purple Pricing for select men's basketball games for the rest of this season.

Essentially, Purple Pricing is a form of Dutch Auction​, in which the prices of the item being sold are lowered until you hit the price at which all the items can be sold at that price. Then everyone who has bid above that price pays the lower price, the same as everyone else. The incentive, in the case of Northwestern men's basketball tickets, is to find that price at which they can sell out the game and also to capture some revenue back from the secondary market, from companies like Stubhub.

For the buyer, as soon as the price reaches one you're willing to pay, there's not reason to wait. The price can only go lower from there, it will never rise.​

Purple Pricing is a joint effort between the Northwestern athletic department and economists Jeff Ely and Sandeep Baliga. The experiment will provide Northwestern with a ton of data to maximize revenue.

Theirs is not a perfect Dutch Auction, however, as there is an artificial price floor. Northwestern will not let the Dutch Auction prices fall below the price that season ticket holders paid. In the future, they could do away with season tickets altogether and use Dutch Auctions to price every game.

The first two games Northwestern tried this with offered a good divergence in demand to test out the system: a desirable game against #16 ranked Ohio State, and a much less desirable game against Penn State. The attendance against Ohio State was 7,036, while against Penn State it was just 5,517. It would have been interesting to see where the price would have landed for the Penn State game had there been no price floor in effect.

Alas, Northwestern lost both games. Some problems can't be so easily solved with economics.​

Seeing at the Speed of Sound

That's the title of a lovely piece by Stanford graduate Rachel Kolb about what it's like for a deaf person to try to lipread.

Lipreading, on which I rely for most social interaction, is an inherently tenuous mode of communication. It's essentially a skill of trying to grasp with one sense the information that was intended for another. When I watch people's lips, I am trying to learn something about sound when the eyes were not meant to hear.

Spoken words occur in my blind spot, a vacancy of my perception. But if I watch a certain way, I can bring them into enough focus to guess what they are. The brain, crafty as it is, fills in the missing information from my store of knowledge.

The article gave me both a deep empathy for what it is like to try to lipread, how complex an art it is (at best, Kolb says she understands 30% of what she tries to lipread), and also a great appreciation for what it must be like when she is able to "see" the language come into sharp focus on another person's lips.

SOME PEOPLE ARE all but impossible for me to lipread. People with thin lips; people who mumble; people who speak from the back of their throats; people with dead-fish, unexpressive faces; people who talk too fast; people who laugh a lot; tired people who slur their words; children with high, babyish voices; men with moustaches or beards; people with any sort of accent.

Accents are a visible tang on people's lips. Witnessing someone with an accent is like taking a sip of clear water only to find it tainted with something else. I startle and leap to attention. As I explore the strange taste, my brain puzzles itself trying to pinpoint exactly what it is and how I should respond. I dive into the unfamiliar contortions of the lips, trying to push my way to some intelligible meaning. Accented words pull against the gravity of my experience; like slime-glossed fish, they wriggle and leap out of my hands. Staring down at my fingers' muddy residue, my only choice is to shrug and cast out my line again.

Some people, though not inherently difficult to understand, make themselves that way. By viewing lipreading as a mysterious and complicated thing, they make the process harder. They over-enunciate, which distorts the lips like a funhouse mirror. Lips are naturally beautiful, especially when words float from them without thought; they ought never be contorted in this way. There are other signs, too: nervous gestures and exaggerated expressions, improvised sign language, a tic-like degree of smiling and nodding.

The World's Top NBA Gambler

A fascinating profile in ESPN Magazine of Bob Voulgaris: Meet the world's top NBA gambler​. Together with a math, statistics, and programming prodigy Voulgaris simply calls the Whiz (he won't reveal the Whiz's real identity for fear of having him poached), Voulgaris built an NBA simulator named Ewing, after Bill Simmons' Ewing Theory.

If Ewing has a secret sauce, it’s just this sort of thing: Finding scraps of information, sliced and diced ever more finely, that reveal something about how a system -- in this case, a game of pro basketball -- will operate in the future. The key is to find those scraps that are more predictive than others. Case in point: One of Ewing’s most important functions is to assign values to players. Each player has two values -- on offense and as a defender -- and those values are constantly changing. Ewing will also automatically adjust the value depending on who’s guarding whom. Oklahoma City’s Kendrick Perkins “is more valuable guarding Dwight Howard than he is guarding Shane Battier,” Voulgaris says. Why? “Because Howard is a unique player, and you need a big to defend him.” Likewise, according to Voulgaris, Celtics seven-footer Jason Collins is “useless every game, except when he’s guarding Howard, which he does really, really well.” Player values also change across a season and a career. So Voulgaris and the Whiz created, for Ewing, an aging component. Further number-crunching revealed that different types of players, based on position and size, will reach their zeniths at different ages and on trajectories that are possible to predict. Ewing now grasps the curve of the lifespan of the point guard, the shooting guard, the forwards, the center -- and predicts the downslope and expiration date of every NBA career. 

When Ewing went live with actual betting for the first time toward the end of the 2008 season, Voulgaris was not yet sold on its powers. For one thing, his subjective-gambler side wasn’t ready to surrender control to a machine. For another, the model was performing unremarkably with their money on the line -- right above the break-even line. But Voulgaris had something in mind, “a long project, like a six-month-long project, to model a certain part of the game of basketball.” He and the Whiz spent the offseason pursuing this mysterious project, the precise nature of which Voulgaris will not discuss. “I don’t even want to allude to what it might be,” he says when I press him, “because I don’t think anyone else is doing anything like it.” 

By 2009, once they’d added this mysterious additional model to Ewing’s inner workings -- version 2.0 -- they started making bets based on the scores it produced after the All-Star break. “We just, like, crushed the second half of the season,” Voulgaris says. Since then, as each subsequent season has passed, Voulgaris’ confidence in Ewing has increased. So too has the frequency of his wagering. In a season, he now regularly puts down well over 1,000 individual bets. “I mean, I don’t want to sit here and brag,” he says. “But this is literally, like, the greatest thing ever when it comes to sports betting.” 

​More money is gambled on the NFL than any of the major US sports, but given how strong a role luck plays in NFL outcomes, it's surprising more people don't gamble on the NBA instead since skill plays a greater role in the NBA than in MLB, the NBA, or the NHL.