Being 50 minutes late for his first meeting with Pope Francis was nothing unusual for Russian President Vladimir Putin. That’s just the way he is — a character trait that provides some insight into his attitude toward power.
When Putin arrived on time to an audience with Pope John Paul II in 2003, the punctuality was considered a newsworthy aberration: “The President Was Not Even a Second Late,” read the headline in the newspaper Izvestia. He had been 15 minutes late for a similar audience in 2000.
The waits other leaders have had to endure in order to see Putin range from 14 minutes for the Queen of England to three hours for Yulia Tymoshenko, the former Ukrainian prime minister. Few people are as important in terms of protocol as the queen or the pope, and there is no country Putin likes to humiliate as much as Ukraine.
The typical delay seems to be about 30 minutes. Half an hour is enough in some cultures to make people mad. Koreans saw Putin’s 30-minute lateness for a meeting with their President Park Geun Hye as a sign of disrespect.
Everybody endures the wait, though.
Jason Kottke suggests:
I could imagine Glass Concierge becoming a future job title, basically a personal assistant who looks in on your Google Glass video feed to make helpful suggestions and advice, basically a rally co-driver for your life.
Most of the post is about using Google Glass to cheat at poker. In response to inquiries, I will review the product once I can get one.
After six games, Carlsen leads by two points, with four draws added to the tally. Anand seems hell bent on founding a campaign to abolish the advantages of playing with the white pieces.
I find two aspects of the match notable so far. First, in the last two endgames Carlsen has been outplaying the computer programs (and Anand), sometimes for dozens of moves in a row. That isn’t easy, to say the least. And kudos to Alan Turing for realizing early on, in his 1953 paper, that chess-playing computer programs would face special difficulties in understanding some endgames. The sequences required to establish the importance (or not) of a measurable material advantage can stretch beyond the time horizon of the program, for instance, and the endgame tablebases take us only so far.
Second, Carlsen is demonstrating one of his most feared qualities, namely his “nettlesomeness,” to use a term coined for this purpose by Ken Regan. Using computer analysis, you can measure which players do the most to cause their opponents to make mistakes. Carlsen has the highest nettlesomeness score by this metric, because his creative moves pressure the other player and open up a lot of room for mistakes. In contrast, a player such as Kramnik plays a high percentage of very accurate moves, and of course he is very strong, but those moves are in some way calmer and they are less likely to induce mistakes in response.
Nettlesomeness is an underrated concept in our world, and kudos to Ken for bringing it to our attention. It should play a larger role in formal game theory than it does currently. It’s already playing a decisive role in the world of chess.
Addendum: Here are some of Ken’s metrics for “nettlesomeness.”
Companies, academics and individual software developers will be able to use it at a small fraction of the previous cost, drawing on IBM’s specialists in fields like computational linguistics to build machines that can interpret complex data and better interact with humans.
That is a big deal, obviously. The story is here.
But is that claim true? It depends on the margin. Let’s say the standard tip is a dollar, and price inflation lowers the real value of that dollar. A lot of customers won’t substitute into stuffing $1.43 into the stripper’s garments. They might do two or three singles, but strippers will be shortchanged at various points going up the price pole. There is something about handing out a single bill that is easier and more transparent, or so it seems.
Say inflation gets high, or runs on for a long time for a large cumulative effect. At some point the customers switch to giving $5 bills.
Does it help strippers if the Fed issues lots of $2 bills? Well, the leap up to the larger tip comes more quickly, but the customers also stay at the $2 tip level a long time before moving up to $5.
At some margins inflation is bad for current strippers, but good for some set of future strippers. If the economy is close to the margin where individuals upgrade from a $1 tip to a $5 tip, then inflation is good for current strippers but bad for future strippers (for a while).
The answer also may depend on whether the Fed adjusts the ratio of $5 to $1 bills to keep in proper synch with the stripper customers. If the Fed doesn’t increase the supply of fivers rapidly enough, future strippers may not get their deserved payoffs for a long time.
Let’s explore this assumption that handing out a single bill of a given kind is easier (admittedly there may be other ways to specify the assumptions). And let’s assume that overpaying some strippers and underpaying others is less efficient for some reason, whether Benthamite or having to do with the unevenness of medium-run supply elasticities.
In that case tips may be more efficient, with ongoing inflation, at the $5 level than the $1 level. Given that two dollar notes are rare, the step up from a one to a five involves a fivefold increase. But the step up from a five to a ten is only a twofold increase, as is the step up from a ten to a twenty. Even the switch from twenties to fifties involves a smaller multiple than from a one to a five. So there are fewer problems with the non-convexities within the 5-10-20-50 range than within the 1-5 range.
Perhaps the sooner we get the strippers away from “the ones” the better — who needs those non-convexities? Strippers sure don’t.
On the whole, therefore, strippers may prefer price inflation. Of course once the $100 bill is the standard tip, the next notch upwards is again hard to come by, outside of the eurozone that is.
This is a fascinating article by Ben Lindbergh, and it does not require interest in baseball, here is one bit:
“The goal, of course, is no error, or as close to that ideal as we can possibly come. And so the best solution might be a hybrid approach that combines tradition with technology. Not robot umps, but regular umps with input from robot brains.”
Here is another good bit of many:
Over time, players have internalized some of the idiosyncrasies of the strike zone as it’s currently called. The zone called against left-handed hitters is shifted a couple inches away relative to righties. The size of the zone fluctuates depending on the count — expanding dramatically on 3-0 and shrinking severely on 0-2 — and according to the base-out state, velocity of the pitch, and many other factors. Yes, these are all arguments in support of standardizing the strike zone, assuming you like to see pitches called according to code. They’re also reasons to exercise caution. “Because it’s always worked this way” isn’t a good reason not to do something different, but it is a reason to think through the possible ramifications before making a major change that could upset the delicate batter-pitcher balance. Players will adjust to whatever the zone looks like, but it’s in baseball’s best interests to make those adjustments smooth.
McKean cautions that instituting an automatic zone “would ruin the game,” which makes him the latest in a long line of thus-far-incorrect critics who’ve warned that something would be the end of baseball. “If you told the pitchers to try and throw that ball with an automatic strike zone, which means it has to hit some part of that plate or be in some part of that strike zone, heck, the games would go on for five, six hours,” he says. My guess is that he has the direction of the effect right, but the magnitude wrong. Automating the strike zone would probably make it slightly smaller, on the whole, and more predictable for the hitter. That could increase scoring and perhaps lead to longer games, but not to such an extent that the sport would be broken.
However, standardizing the zone would remove a level of interplay between batter, pitcher, catcher, and umpire that many fans find compelling.
Interesting throughout, and for the pointer I thank Hamp Nettles.
They start playing Saturday, with a 12-game format. Originally I had been picking Anand, on the grounds of superior match experience and better opening preparation. But Carlsen’s results have simply been too strong lately, including in St. Louis. Tarjei Svensen puts it well:
Or if we judge the match by numerical rating, Carlsen again is a strong favorite.
The Chennai venue may help Anand, as Carlsen will be bringing a Norwegian chef to convert the local ingredients into…what…a $35 dollar small pizza? Still, being surrounded by your friends, entire family, and numerous well-wishers is not always a net advantage in a competition. Carlsen may find it easier to concentrate on the chess. And Anand is 43 years old, which puts him as one of the oldest players in the top 100. Carlsen is 22 and it feels like it is his time.
Some of you will know that Average is Over contains an extensive discussion of “freestyle chess,” where humans can use any and all tools available — most of all computers and computer programs — to play the best chess game possible. The book also notes that “man plus computer” is a stronger player than “computer alone,” at least provided the human knows what he is doing. You will find a similar claim from Brynjolfsson and McAfee.
Computer chess expert Kenneth W. Regan has compiled extensive data on this question, and you will see that a striking percentage of the best or most accurate chess games of all time have been played by man-machine pairs. Ken’s explanations are a bit dense for those who don’t already know chess, computer chess, Freestyle and its lingo, but yes that is what he finds, click on the links in his link for confirmation. In this list for instance the Freestyle teams do very very well.
Average is Over also raised the possibility that, fairly soon, the computer programs might be good enough that adding the human to the computer doesn’t bring any advantage. (That’s been the case in checkers for some while, as that game is fully solved.) I therefore was very interested in this discussion at RybkaForum suggesting that already might be the case, although only recently.
Think about why such a flip might be in the works, even though chess is far from fully solved. The “human plus computer” can add value to “the computer alone” in a few ways:
1. The human may in selective cases prune variations better than the computer alone, and thus improve where the computer searches for better moves and how the computer uses its time.
2. The human can see where different chess-playing programs disagree, and then ask the programs to look more closely at those variations, to get a leg up against the computer playing alone (of course this is a subset of #1). This is a biggie, and it is also a profound way of thinking about how humans will add insight to computer programs for a long time to come, usually overlooked by those who think all jobs will disappear.
3. The human may be better at time management, and can tell the program when to spend more or less time on a move. “Come on, Rybka, just recapture the damned knight!” Haven’t we all said that at some point or another? I’ve never regretted pressing the “Move Now” button on my program.
4. The human knows the “opening book” of the computer program he/she is playing against, and can prepare a trap in advance for the computer to walk into, although of course advanced programs can to some extent “randomize” at the opening level of the game.
Insofar as the above RybkaForum thread has a consensus, it is that most of these advantages have not gone away. But the “human plus computer” needs time to improve on the computer alone, and at sufficiently fast time controls the human attempts to improve on the computer may simply amount to noise or may even be harmful, given the possibility of human error. Some commentators suggest that at ninety minutes per game the humans are no longer adding value to the human-computer team, whereas they do add value when the time frame is say one day per move (“correspondence chess,” as it is called in this context.) Circa 2008, at ninety minutes per game, the best human-computer teams were better than the computer programs alone. But 2013 or 2014 may be another story. And clearly at, say, thirty or sixty seconds a game the human hasn’t been able to add value to the computer for some time now.
Note that as the computer programs get better, some of these potential listed advantages, such as #1, #3, and #4 become harder to exploit. #2 — seeing where different programs disagree — does not necessarily become harder to exploit for advantage, although the human (often, not always) has to look deeper and deeper to find serious disagreement among the best programs. Furthermore the ultimate human sense of “in the final analysis, which program to trust” is harder to intuit, the closer the different programs are to perfection. (In contrast, the human sense of which program to trust is more acute when different programs have more readily recognizable stylistic flaws, as was the case in the past: “Oh, Deep Blue doesn’t always understand blocked pawn formations very well.” Or “Fritz is better in the endgame.” And so on.)
These propositions all require more systematic testing, of course. In any case it is interesting to observe an approach to the flip point, where even the most talented humans move from being very real contributors to being strictly zero marginal product. Or negative marginal product, as the case may be.
And of course this has implications for more traditional labor markets as well. You might train to help a computer program read medical scans, and for thirteen years add real value with your intuition and your ability to revise the computer’s mistakes or at least to get the doctor to take a closer look. But it takes more and more time for you to improve on the computer each year. And then one day…poof! ZMP for you.
Addendum: Here is an article on computer dominance in rock-paper-scissors. This source claims freestyle does not beat the machine in poker.
Allison Schrager writes:
This year, Americans on Eastern Standard Time should set their clocks back one hour (like normal), Americans on Central and Rocky Mountain time do nothing, and Americans on Pacific time should set their clocks forward one hour. After that we won’t change our clocks again—no more daylight saving. This will result in just two time zones for the continental United States. The east and west coasts will only be one hour apart. Anyone who lives on one coast and does business with the other can imagine the uncountable benefits of living in a two-time-zone nation (excluding Alaska and Hawaii).
It sounds radical, but it really isn’t. The purpose of uniform time measures is coordination. How we measure time has always evolved with the needs of commerce. According to Time and Date, a Norwegian Newsletter dedicated to time zone information, America started using four time zones in 1883. Before that, each city had its own time standard based on its calculation of apparent solar time (when the sun is directly over-head at noon) using sundials. That led to more than 300 different American time zones. This made operations very difficult for the telegraph and burgeoning railroad industry. Railroads operated with 100 different time zones before America moved to four, which was consistent with Britain’s push for a global time standard. The following year, at the International Meridian Conference, it was decided that the entire world could coordinate time keeping based on the British Prime Meridian (except for France, which claimed the Prime Median ran through Paris until 1911). There are now 24 (or 25, depending on your existential view of the international date line) time zones, each taking about 15 degrees of longitude.
Now the world has evolved further—we are even more integrated and mobile, suggesting we’d benefit from fewer, more stable time zones. Why stick with a system designed for commerce in 1883? In reality, America already functions on fewer than four time zones. I spent the last three years commuting between New York and Austin, living on both Eastern and Central time. I found that in Austin, everyone did things at the same times they do them in New York, despite the difference in time zone. People got to work at 8 am instead of 9 am, restaurants were packed at 6 pm instead of 7 pm, and even the TV schedule was an hour earlier.
There is more here.
Here is one excerpt:
“If you’re not a good [chess] player,” Cowen writes, “the fact that you studied with a top teacher doesn’t mean a thing. … There is nothing [in chess] comparable to the glow resulting from a Harvard degree: Announcing ‘I studied with Rybka’ [a powerful chess engine] would bring gales of laughter, since anyone can do that. … The company selling Rybka tries to make its product replicable and universal, whereas Harvard tries to make its product as exclusive as possible. Now, which model do you think will spread and gain influence in the long run?”
Before you answer that, consider this: A year of tuition, room and board at Harvard will set you back more than $50,000. You can get a copy of Rybka for about $50.
The full piece is here.
From Aki Ito, here is a a good discussion of a new innovation, related to some trends I discussed in Average is Over:
To aid that search [for better workers], Juhl this month will begin using an online video game designed to track, record and analyze every millisecond of its players’ behavior. Developed by Knack in Palo Alto, California, Wasabi Waiter places job-seekers in the shoes of a sushi server who must identify the mood of his cartoon customers and bring them the dish labeled with the matching emotion. On a running clock, they must also clear empty dishes into the sink while tending to new customers who take a seat at the bar.
Using about a megabyte of data per candidate, Knack’s software measures a variety of attributes shown in academic studies to relate to job performance, including conscientiousness and the capacity to recognize others’ emotions. Knack’s clients will also see a score estimating each applicant’s likelihood of being a high performer.
As for another company:
…The patterns gleaned since the company’s founding in 2007 have debunked many of the common assumptions held by recruiters, Evolv executives say. For example, a history of job-hopping or long bouts of unemployment has little relationship with how long the candidate will stay at his or her next job, according to Evolv’s analysis of call center agents.
“As human beings, we’re actually pretty bad at evaluating other human beings,” said David Ostberg, vice president of workforce science at Evolv. “We’re making sure people are using the right data, instead of the traditional methods that were previously thought to be valid but big data’s showing are not.”
New York-based ConnectCubed has also developed software to determine the personality and cognitive abilities of job applicants that, at its largest clients, is tailored for that specific company. ConnectCubed has existing workers at those businesses complete its video games and questionnaires so the behavioral profiles of the star employees serve as a benchmark for who managers should hire in the future.
“When new people apply, you can say, wow this guy has all the makings of our top salesmen,” said Michael Tanenbaum, chief executive officer and co-founder of the service. “These are things that are impossible to measure from a resume, especially with educational backgrounds that are often more determined by socioeconomic status than your innate ability.”
To be sure, Knack and ConnectCubed, which say they can predict high-performers across a broad set of workers, haven’t been around for long enough to track, over time, whether their technologies actually are improving the quality of the employees their clients hire or those businesses’ bottom line.
The article is interesting throughout.
Here is a panoramic peek inside the offices of a number of Nobel prize winners, including Al Roth for economics. More interesting than it sounds with lots of Easter eggs.
Hat tip: Justin Wolfers.
I don’t think there should be a debt ceiling at all, and I also don’t favor conditionality on raising it, as I don’t think hostage-taking leads to better policy in the long run or even in the short run for that matter. Yet it seems to me this is an under-reported angle on the recent controversies:
Americans by a 2-to-1 ratio disagree with President Barack Obama’s contention that Congress should raise the U.S. debt limit without conditions.
Instead, 61 percent say that it’s “right to require spending cuts when the debt ceiling is raised even if it risks default,” because Congress lacks spending discipline, according to a Bloomberg National Poll conducted Sept. 20-23.
That sentiment is shared by almost three-quarters of Republicans, two-thirds of independents, and a plurality of Democrats. Just 28 percent of respondents backed Obama’s call for a clean bill that has no add-on provisions.
The Bloomberg article is here, and I would say this means the Republican strategy may be working somewhat better, and be less insane and out of touch, than its critics often suggest. (I do, by the way, understand that the framing of the initial question is going to influence the poll results significantly.)
As they sometimes say, it is time to elect a new people.
Bryan Caplan thinks that portfolios don’t reveal much about actual beliefs,. Here is one of his arguments:
Even prominent Nobel prize-winning economists admit they follow simple rules of thumb when they invest. So unless people’s beliefs are carved in stone, how could portfolios possibly reveal much about their beliefs? Tyler is a case in point: He changes his mind a hundred times a day, but he follows a simple financial strategy that hasn’t varied in years.
I view it differently. I don’t trade in public markets but I vary my allocations by changing how much money I spend and how to allocate my time. Perhaps not coincidentally, this puts me square into the world of classical finance theory as represented by “the mutual fund theorem,” with a static equity portfolio of fixed proportions and some unique covariances on my human capital. I call that rationality not inertia.
Bryan, you will note, is a founder of the theory of rational irrationality, which suggests you become more rational as the private stakes from your decisions go up. These days he is wishing to argue that the truly small stakes reflect what you really think, through the lens of mental accounting and compartmentalization. Of course that would undercut or at least drastically relativize his earlier theory. I say he has made a large and successful career bet — much bigger than any of his piddly ante monetary bets — on the theory of rational irrationality, so he must really agree with me after all.
It also happens that Bryan’s emphasis on simple rules of thumb will work against his interest in person-to-person bets as a metric of authenticity. If you don’t change or examine your overall portfolio very often, that means some reasonably wide range of portfolios is a matter of indifference or near indifference to you, if only because fine-tuned improvements are hard to find. (Do you really give matters a re-ponder when a firm in your portfolio pays dividends?) In that case, however, the small bets won’t be authentic either. One could compartmentalize one’s personal bets quite easily and say to oneself — whether consciously or not — “I can make this small bet: it still keeps my overall portfolio within that broad range of indifference.” Which indeed it does. The bet is then undertaken for expressive reasons, which is fine, nothing against that, but for me it is more fun to cheer for Tony Parker (without betting on him). I think of these small personal bets as akin to sports loyalties most of all and not as a unique window into our real beliefs.
The small person-to-person bets pay off (or not) in terms of pride, including for some people the pride in betting itself. One relevant substitute is to attempt to produce pride using your own internal mental accounting of your own predictions and so we must make the broader portfolio comparison. What the $$ betters are signaling is a lack of vividness for their own internal mental worlds. In my mind, I’m already betting an optimal amount of pride through my own mental accounting. Maybe some of us are already betting too much internal pride on external events; after all, the variance of pride introduces some new exogenous risk into life and perhaps we should be trying to move in the opposite direction toward greater pride indifference to external events. That is what the Stoics thought.
Most of all, I fear that Bryan’s results are coming from an asymmetric approach where he applies positive observation to large portfolios and normative recommendations to small bets. Bryan could go for a “positive vs. positive” comparison, in which case he would point out that people trade and adjust their large portfolios all the time, but don’t make small bets on public policy nearly as much. Alternatively, he could try a “normative vs. normative” comparison, in which case would you sooner recommend that people drop their inertia for their large portfolios or for their small ones? To even raise such a question is to answer it.
Do you want to find out “what a person really thinks”? Look at whom they married, how much money they spend, and how they devote their time. That is the most important portfolio of them all.
Just don’t bet that Bryan and I are going to agree anytime soon.
That query is from AskReddit, the link is here, and here are a few of the nominations:
It’s hard to explain puns to kleptomaniacs because they always take things literally.
Jean-Paul Sartre is sitting at a French cafe, revising his draft of Being and Nothingness. He says to the waitress, “I’d like a cup of coffee, please, with no cream.” The waitress replies, “I’m sorry, Monsieur, but we’re out of cream. How about with no milk?”
Werner Heisenberg, Kurt Gödel, and Noam Chomsky walk into a bar. Heisenberg turns to the other two and says, “Clearly this is a joke, but how can we figure out if it’s funny or not?” Gödel replies, “We can’t know that because we’re inside the joke.” Chomsky says, “Of course it’s funny. You’re just telling it wrong.”
I don’t find that latter one funny at all, as they are telling it wrong.
The pointer is from Jodi Ettenberg of Legal Nomads fame.
What are your picks? You get mine every day.