Category Archives: Elections

The Data/Human Goal Gap

As I was writing a letter to my third-grade daughter’s principal in support of a change in homework policy (a letter which I’ve posted here), it occurred to me I was making a point about a phenomenon that isn’t unique to education at all, but happens in a lot of other fields, too: baseball, business, economics, and politics.

I don’t know if this phenomenon has a name. It probably does, because you’re very rarely the first person to think of an idea. If it does, I’m sure someone will soon enlighten me. The phenomenon goes like this:

* * *

Suppose you suck at something. Doesn’t matter what it is. You’re bad at this thing, and you know it. You don’t really understand why you’re so bad, but you know you could be so much better. One day, you get tired of sucking, and you decide it’s time to commit yourself to a program of systematic improvement, to try to be good at the thing you want to be good at.

So you decide to collect data on what you are doing, and then study that data to learn where exactly things are going so wrong. Then you’ll try some experiments to see what effect those experiments have on your results. Then you keep the good stuff, and throw out the bad stuff, and pretty soon you find yourself getting better and better at this thing you used to suck at.

So far so good, eh? But there’s a problem. You don’t really notice there’s a problem, because things are getting better and better. But the problem is there, and it has been there the whole time. The problem is this: the thing your data is measuring is not *exactly* the thing you’re trying to accomplish.

Why is this a problem? Let’s a simplified graph of this issue, so I can explain.

Let’s call the place you started at, the point where you really sucked, “Point A”.
Let’s call the goal you’re trying to reach “Point G”.
And let’s call the best place the data can lead you to “Point D”.

Note that Point D is near Point G, but it’s not exactly the same point. Doesn’t matter why they’re not the same point. Perhaps some part of your goal is not a thing that can be measured easily with data. Maybe you have more than one goal at a time, or your goals change over time. Whatever, doesn’t matter why, it just matters they’re just not exactly the same point.

Now here’s what happens:

You start out very far from your goal. You likely don’t even know exactly what or where your goal is, precisely, but (a) you’ll know it when you see it, and (b) know it’s sorta in the Point D direction. So, off you go. You embark on your data-driven journey. As a simplified example, we’ll graph your journey like this:

statsgraph2

On this particular graph, your starting point, Point A, is 14.8 units away from your goal at Point G. Then you start following the path that the data leads you. You gather data, test, experiment, study the results, and repeat.

After a period of time, you reach Point B on the graph. You are now 10.8 units away from your goal. Wow, you think, this data-driven system is great! Look how much better you are than you were before!

So you keep going. You eventually reach Point C. You’re even closer now: only 6.0 units away from your goal!

And so you invest even more into your data-driven approach, because you’ve had nothing but success with it so far. You organize everything you do around this process. The process, and changes that you’ve made because of it, actually begin to become your new identity.

In time, you reach Point D. Amazing! You’re only 4.2 units away from your goal now! Everything is awesome! You believe in this process wholeheartedly now. The lessons you’ve learned permeate your entire worldview now. To deviate from the process would be insane, a betrayal of your values, a rejection of the very ideas you stand for. You can’t even imagine that the path you’ve chosen will not get any better than right here, now, at Point D.

Full speed ahead!

And then you reach Point E.

Eek!

Egads, you’re 6.00 units away from your goal now. You’ve followed the data like you always have, and suddenly, for no apparent reason, things have suddenly gotten worse.

And you go, what on Earth is going on? Why are you having problems now? You never had problems before.

And you’re human, and you’ve locked into this process and weaved it into your identity. You loved Points C & D so much that you can’t stand to see them discredited, so your Cognitive Dissonance kicks in, and you start looking for Excuses. You go looking for someone or something External to blame, so you can mentally wave off this little blip in the road. It’s not you, it’s them, those Evil people over there!

But it’s not a blip in the road. It’s the road itself. The road you chose doesn’t take you all the way to your destination. It gets close, but then it zooms on by.

But you won’t accept this, not now, not after the small sample size of just one little blip. So you continue on your same trajectory, until you reach Point F.

You stop, and look around, and realize you’re now 10.8 units away from your goal. What the F? Things are still getting worse, not better! You’re having more and more problems. You’re really, really F’ed up. What do you do now?

Can you let go of your Cognitive Dissonance, of your Excuse seeking, and step off the trajectory you’ve been on for so long?

F is a really F’ing dangerous point. Because you’re really F’ing confused now. Your belief system, your identity, is being called into question. You need to change direction, but how? How do you know where to aim next if you can’t trust your data to lead you in the right direction? You could head off in a completely wrong direction, and F things up even worse than they were before. And when that happens, it becomes easy for you to say, F this, and blow the whole process up. And then you’re right back to Point A Again. All your effort and all the lessons you learned will be for nothing.

WTF do you do now?

F’ing hell!

* * *

That’s the generic version of this phenomenon. Now let’s talk about some real-world examples. Of course, in the real world, things aren’t as simple as I projected above. The real world isn’t two-dimensional, and the data doesn’t lead you in a straight line. But the phenomenon does, I believe, exist in the wild. And it’s becoming more and more common as computers make data-driven processes easy for organizations and industries to implement and follow.

Education

As I said, homework policy is what got me thinking about this phenomenon. I have no doubt whatsoever that the schools my kids are going to now are better than the ones I went to 30-40 years ago. The kids learn more information at a faster rate than my generation ever did. And that improvement, I am confident, is in many ways a result of the data-driven processes that have arisen in the education system over the last few decades. Test scores are how school districts are judged by home buyers, they’re how administrators are judged by school boards, they’re how principals are judged by administrators, and they’re how teachers are judged by principals. The numbers allow education workers to be held accountable for their performance, and provide information about what is working and what needs fixing so that schools have a process that leads to continual improvement.

From my perspective, it’s fairly obvious that my kids’ generation is smarter than mine. But: I’m also pretty sure they’re more stressed out than we were. Way more stressed out, especially when they get to high school. I feel like by the time our kids get to high school, they have internalized a pressure-to-perform ethic that has built up over years. They hear stories about how you need such and such on your SATs and this many AP classes with these particular exam scores to get into the college of their dreams. And the pressure builds as some (otherwise excellent) teachers think nothing of giving hours and hours of homework every day.

Depression, anxiety, panic attacks, psychological breakdowns that require hospitalization: I’m sure those things existed when I went to school, too, but I never heard about it, and now they seem routine. When clusters of kids who should have everything going for them end up committing suicide, something has gone wrong. That’s your Point F moment: perhaps we’ve gone too far down this data-driven path.

Whatever we decide our goal of education is, I’m pretty sure that our Point G will not feature stressed-out kids who spend every waking hour studying. That’s not the exact spot we’re trying to get to. I’m not suggesting we throw out testing or stop giving homework. I am arguing that there exists a Point D, a sweet spot with just the right amount of testing, and just the right amount of homework, that challenges kids the right amount without stressing them out, and leaves the kids with the time they deserve to just be kids. Whatever gap between Point D and Point G that remains should be closed not with data, but with wisdom.

Baseball

The first and most popular story of an industry that transforms itself with data-driven processes is probably Michael Lewis’s Moneyball. It’s the story of how the revenue-challenged Oakland A’s baseball team used statistical analysis to compete with economic powerhouses like the New York Yankees.

I’ve been an A’s fan my whole life, and I covered them closely as an A’s blogger for several years. So I can appreciate the value that the A’s emphasis on statistical analysis has produced. But as an A’s fan, there’s also a certain frustration that comes with the A’s assumption that there is no difference between Point D and Point G. The A’s assume that the best way to win is to be excruciatingly logical in their decisions, and that if you win, everyone will be happy.

But many A’s fans, including myself, do not agree with that assumption. The Point F moment for us came when, during a stretch of three straight post-season appearances, the A’s traded their two most popular players, Yoenis Cespedes and Josh Donaldson, within a span of six months.

I wrote about my displeasure with these moves in an long essay called The Long, Long History of Why I Do Not Like the Josh Donaldson Trade. My argument was, in effect, that the purpose of baseball was not merely winning, it was the emotional connection that fans feel to a team in the process of trying to win.

When you have a data-driven process that takes emotion out of your decisions, but your Point G includes emotions in the goal of the process, it’s unavoidable that you will have a gap between your Point D and your Point G. The anger and betrayal that A’s fans like myself felt about these trades is the result of the process inevitably shooting beyond its Point D.

Business

If Moneyball is not the most influential business book of the last few decades, it’s only because of Clayton Christensen’s book, The Innovator’s Dilemma. The Innovator’s Dilemma tells the story of a process in which large, established businesses can often find themselves defeated by small, upstart businesses with “disruptive innovations.”

I suppose you can think of the phenomenon described in the Innovator’s Dilemma as a subset of, or perhaps a corollary to, the phenomenon I am trying to describe. The dilemma happens because the established company has some statistical method for measuring its success, usually profit ratios or return on investment or some such thing. It’s on a data-driven track that has served it well and delivered it the success it has. Then the upstart company comes along and sells a worse product with worse statistical results, and because of these bad numbers, the establish company ignores it. But the upstart company is on an statistical path of its own, and eventually improves to the point where it passes the established company by. The established company does not realize its Point D and Point G are separate points, and finds itself turning towards Point G too late.

Here, let’s graph the Innovator’s Dilemma on the same scale as our phenomenon above:

statsgraph3

The established company is the red line. They have reached Point D by the time the upstart, with the blue line, gets started. The established company thinks, they’re not a threat to us down at Point A. And even if they reach our current level at Point D, we will beyond Point F by then. They will never catch up.

This line of thinking is how Blockbuster lost to Netflix, how GM lost to Toyota, and how the newspaper industry lost its cash cow, classified ads, to Craigslist.

The mistake the establish company makes is assuming that Point G lies on/near the same path that they are currently on, that their current method of measuring success is the best path to victory in the competitive market. But it turns out that the smaller company is taking a shorter path with a more direct line to the real-life Point G, because their technology or business model has, by some twist, a different trajectory which takes it closer to Point G than the established one. By the time the larger company realizes its mistake, the smaller company has already gotten closer to Point G than the larger company, and the race is essentially over.

* * *

There are other ways in which businesses succumb to this phenomenon besides just the Innovator’s Dilemma. Those companies that hold closely to Milton Friedman’s idea that the sole purpose of a company is to maximize shareholder value are essentially saying that Point D is always the same as Point G.

But that creates political conflict with those who think that all stakeholders in a corporation (customers, employees, shareholders and the society and environment at large) need to have a role in the goals of a corporation. In that view, Point D is not the same as Point G. Maximizing profits for the shareholders will take you on a different trajectory from maximizing the outcomes for other stakeholders in various proportions. When a company forgets that, or ignores it, and shoots beyond its Point D, then there is going to inevitably be trouble. It creates distrust in the corporation in particular, and corporations in general. Take any corporate PR disaster you want as an example.

Economics

I’m a big fan of Star Trek, but one of the things I never understood about it was how they say that they don’t use money in the 23rd century. How do they measure the value of things if not by money? Our whole economic system is based on the idea that we measure economic success with money.

But if you think about it, accumulating money is not the goal of human activity. Money takes us to Point D, it’s not the path to Point G. What Star Trek is saying is that they somehow found a path to Point G without needing to pass through Point D first.

But that’s 200 years into a fictional future. Right now, in real life, we use money to measure human activity with. But money is not the goal. The goal is human welfare, human happiness, human flourishing, or some such thing. Economics can show us how to get close to the goal, but it can’t take us all the way there. There is a gap between the Point D we can reach with a money-based system of measurement, and our real-life Point G.

And as such, it will be inevitable that if we optimize our economic systems to optimize some monetary outcome, like GDP or inflation or tax revenues or some such thing, that eventually that optimization will shoot past the real-life target. In a sense, that’s kind of what we’re experiencing in our current economy. America’s GDP is fine, production is up, the inflation rate is low, unemployment is down, but there’s still a general unease about our economy. Some people point to economic inequality as the problem now, but measurements of economic inequality aren’t Point G, either, and if you optimized for that, you’d shoot past the real-life Point G, too, only in a different direction. Look at any historically Communist country (or Venezuela right now) to see how miserable missing in that direction can be.

The correct answer, as it seems to me in all of these examples, is to trust your data up to a certain point, your Point D, and then let wisdom be your guide the rest of the way.

Politics

Which brings us to politics. In 2016. Hoo boy.

Well, how did we get here?

I think there are essentially two data-driven processes that have landed us where we are today. Both of these processes have a gap between what we think of as the real-life goals of these entities, and the direction that the data leads them to. One is the process of news outlets chasing media ratings. And the other is political polling.

In the case of the media, the drive for ratings pushes journalism towards sensationalism and outrage and controversy and anger and conflict and drama. What we think journalism should actually do is inform and guide us towards wisdom. Everybody says they hate the media now, because everybody knows that the gap between Point D and Point G is growing larger and larger the further down the path of ratings the media goes. But it is difficult, particularly in a time where the technology and business models that the media operate under are changing rapidly, to change direction off that track.

And then there’s political polling. The process of winning elections has grown more and more data-driven over recent decades. A candidate has to say A, B, and C, but can’t say X, Y, or Z, in order to win. They have to casts votes for D, E, and F, but can’t vote for U, V or W. They have to make this many phone calls and attend that many fundraisers and kiss the butts of such and such donors in order to raise however many millions of dollars it takes to win. The process has created a generation of robopoliticians, none of whom have an original idea in their heads at all (or if they do, won’t say so for fear of What The Numbers Say.) You pretty much know what every politician will say on every issue if you know whether there’s a “D” or an “R” next to their name. Politicans on neither side of the aisle can formulate a coherent idea of what Point G looks like other beyond a checklist spit out of a statistical regression.

That leads us to the state of the union in 2016, where both politicians and the media have overshot their respective Point Ds.

And nobody feels like anyone gives a crap about the Point G of this whole process: to make the lives of the citizens that the media and the politicians represent as fruitful as possible. Both of these groups are zooming full speed ahead towards Point F instead of Point G.

And here are the American people, standing at Point E, going, whoa whoa whoa, where are you all going? And then the Republicans put up 13 robocandidates who want to lead everybody to the Republican version of Point F, plus Donald Trump. The Democrats put up Hillary Clinton, who can probably check all the data-driven boxes more skillfully than anybody else in the world, asking to lead everybody to the Democratic version of Point F, plus Bernie Sanders.

And Trump and Sanders surprise the experts, because they’re the only ones who are saying, let’s get off this path. Trump says, this is stupid, let’s head towards Point Fascism. Sanders says, we need a revolution, let’s head towards Point Socialism.

And most Americans like me just shake our heads, unhappy with our options, because Fascism and Socialism sound more like Point A than Point G to us. I don’t want to keep going, I don’t want to start over, and I don’t want to head in some old discredited direction that other countries have headed towards and failed. I just want to turn in the direction of wisdom.

“It’s not that hard. Tell him, Wash.

“It’s incredibly hard.”

Did David Bowie Predict Obama and Trump back in 1999?

What happens when a monoculture fragments?

* * *

Here’s the big question in politics these days: how do you explain Donald Trump? Sean Trende of RealClearPolitics has an interesting three part series on the question. Nate Silver presents three theories of his own. Scott Adams hypothesizes that Trump is a “master persuader“. David Axelrod surmises that voters are simply choosing the opposite of the last guy. Craig Calcaterra thinks it’s worse than all that, and we’re entering a new dark age.

Those are interesting ideas, I suppose, and maybe there’s some truth to them, I don’t know. But I want to throw another theory out there that I got, indirectly, while following the news of David Bowie’s death.

* * *

Bowie was very knowledgeable about music of course, but also visual arts, as well. There are a number of interviews of Bowie in the 1990s where he connects the history of visual arts in the early 20th century to what happened to music in the late 20th century, most notably an interview with Jeremy Paxman on BBC Newsnight back in 1999.

* * *

First, some background. Up until the mid-19th century, the visual arts were very much a monoculture. Basically, you were supposed to paint pictures that looked lifelike in one way or another. But the invention of photography about that time changed the nature of the visual arts. The value of realistic paintings came into question, and artist began to explore other purposes for painting besides just realism.

The result of that exploration was that the visual arts in the early 20th century ended up splitting up into multiple subgenres like impressionism, cubism, dadaism, surrealism, and abstract impressionism. Bowie said, “The breakthroughs in the early part of the century with people like Duchamp were so prescient in what they were doing and putting down. The idea [was] that the piece of work is not finished until the audience come to it, and add their own interpretation.”

duchamp

Duchamp’s urinal is the prime example of what Bowie is talking about. Is this a work of art?

…especially since Marcel Duchamp and all that, the work is only one aspect of it. The work is never finished now until the viewer contributes himself. The art is always only half-finished. It’s never completed until there’s an audience for it. And then it’s the combination of the interpretation of the audience and the work itself. It’s that gray area in the middle is what the work is about.

interview on Musique Plus, 1999

The urinal by itself is not a work of art, Bowie suggested. It becomes a work of art when you react to it.

* * *

But why? Why would this become an artistic trend? Bowie suggested that this is the natural result of the breakup of monocultures. When there’s one dominant culture, artists can dictate what art is, and isn’t. But when there isn’t a single dominant culture, breaking through to the mainstream requires the artist to meet the audience halfway. Bowie claimed that the visual arts went through this process first, and it became a full-fledged force in music in the 1990s.

I think when you look back at, say, this last decade, there hasn’t really been one single entity, artist, or group, that have personified, or become the brand name for the nineties. It started to fade a bit in the eighties. In the seventies, there were still definite artists; in the sixties, there were the Beatles and Hendrix; in the fifties, there was Presley.

Now it’s subgroups, and genres. It’s hip-hop. It’s girl power. It’s a communal kind of thing. It’s about the community.

It’s becoming more and more about the audience. The point of having somebody who “led the forces” has disappeared because the vocabulary of rock is too well-known.

From my standpoint, being an artist, I like to see what the new construction is between artist and audience. There is a breakdown, personified, I think by the rave culture of the last few years. The audience is at least as important as whoever is playing at the rave. It’s almost like the artist is to accompany the audience and what the audience is doing. And that feeling is very much permeating music.

Bowie suggests that it wasn’t just music that this was happening to in the late 20th century, but to culture on a broader scale:

We, at the time, up until at least the mid-seventies, really felt that we were still living in the guise of a single and absolute created society, where there were known truths, and known lies, and there was no duplicity or pluralism about the things that we believed in. That started to break down rapidly in the seventies. And the idea of a duality in the way that we live…there are always two, three, four, five sides to every question. The singularity disappeared.

Bowie then went on to suggest that the Internet will go on to accelerate this cultural fragmentation in the 21st century:

And that, I believe, has produced just a medium as the Internet, which absolutely establishes and shows us that we are living in total fragmentation.

The actual context and the state of content is going to be so different from anything we can visage at the moment. Where the interplay between the user and the provider will be so in sympatico, it’s going to crush our ideas of what mediums are all about.

It’s happening in every form. […] That gray space in the middle is what the 21st century is going to be about.

Look then at the technologies that have launched since Bowie made these statements in 1999. Blogger launched the same year as that interview, in August of 1999. WordPress launched in 2003. Facebook in 2004. Twitter in 2006. What’s App in 2010. Snapchat in 2011. Technologies such as these, which give broadcast power to audiences, have become the dominant mediums of the 21st century. The audience has indeed become the mainstream provider of culture.

* * *

Bowie didn’t make any specific claims or predictions about politics in these 1999 statements. But we can look at his ideas and apply them to politics, and see if they apply there, as well. It would, after all, be strange if this process which has been happening for over a century in the general culture did not eventually make its way into politics, as well.

First, let’s ask, are we seeing any kind of fragmentation in our politics? (I’ll limit myself to American politics, because I don’t know enough about other countries to speak coherently.) It’s fairly obvious that the two American parties are more polarized than ever, but let’s show a chart to verify that. This is from the Brookings Institute:
congresscompare780

As you can see, the parties were rather clustered together during World War II. In the 70s, you could see some separation happening, but there was still overlap. Now, they are two completely unrelated groups. So Bowie’s model holds in this case.

It could be argued that in the 2016 election, we are seeing a fragmentation of these two groups into further subgroups. On the Democratic side, there is a debate between the full-fledged socialism espoused by Bernie Sanders, and the more economically conservative wing of the Democratic Party represented by Hillary Clinton. (There do not seem to be candidates from the environmentalist/pacifist wings…yet.) On the Republican side, there are also clear factions now: the Evangelical wing led by Ted Cruz, the Libertarian wing led by Rand Paul, the more establishment Republicanism of Marco Rubio, Chris Christie and John Kasich, and the nationalism of Donald Trump.

These factions have always existed in the American political parties, of course. And there have always been subgenres in the arts and the general culture, too. But the difference this time seems to be that each faction is claiming, and insisting on, legitimacy. They are no longer satisfied with mere lip service from the party establishment. The days of the One Dominant Point of View are in the past.

* * *

Suppose that American political parties are indeed fragmenting. What kind of politicians succeed in that kind of environment?

The David Bowie theory would answer: politicians who possess the quality of allowing audiences to project their own interpretations onto them.

Whatever the policy differences between Barack Obama and Donald Trump, it’s hard to deny that both Trump and Obama possess that quality in spades.

The socialist and environmentalist and pacifist wings of the Democratic party seemed to project their fondest left-wing wishes onto Obama, even though his actual policy positions were rather centrist. As Obama’s presidency unfolded, these factions became disappointed, as reality set in. And likewise, in his Republican opponents there arose Obama Derangement Syndrome, where many right-wingers projected their worst fears of a far-left Presidency onto Obama, regardless of Obama’s actual positions.

Now we are seeing similar reactions to Donald Trump. The Republicans who are expected to vote for him are seeing him as a sort of savior to restore conservatism to prominence after a long series of losses in the Obama and Bill Clinton eras. This is despite the fact that, Trump’s immigration policies aside, Trump’s policy positions (that we know of), historically have been more consistent with establishment Democrats. And yet, many Democrats fear a Trump presidency and threaten to move to Canada if it happens.

So there are benefits and drawbacks to this “gray space” strategy. When you give the audience the freedom to add their interpretations to you, you may not like their interpretation very much. There was some pretty strong hatred of Duchamp’s urinal as a work of art. Others see that as part of its brilliance. Similarly, Obama and Trump can’t really control the large amount of people who react to them with repulsion. But it goes hand in hand with their success. That’s what the strategy does.

How do Obama and Trump accomplish this? What are the elements that allows them to interact in that “gray space”, when other politicians don’t? A few guesses:

  • Be vague. Adhering to the specific policy proposals of a faction boxes you into that faction. It doesn’t allow room for other factions to meet you in the “gray space” between your factions.
     
  • Be emotional. Obama and Trump know how to give speeches that rile up the emotions in the audience. You have to give the audience something to connect to, if it isn’t your actual policy positions.
     
  • Step out from political clichếs. Bowie noted that by the 1990s, the standard three-cord rock-and-roll vocabulary had become too well-known to be a source of rebellion anymore. Similarly, the standard vocabulary of the Democratic and Republican parties have also become too well-known these days. The mediocre candidates these days seem to spend too much energy signaling that they know the Standard Vocabulary. We pretty much know what these politicians’ answers are going to be every question before they open their mouths to answer them. Hillary Clinton is a master of the vocabulary, but many people seem to be tired of it. Hence this article: “Hillary, can you excite us?
     

How do you defeat such candidates? I don’t know, but it probably involves forcing them to be specific, to peg them as being trapped inside one particular faction or another. To reduce the “gray space” between them and the audience. Good luck with that. Should be interesting to watch as the primary season begins. Start your engines.

* * *

Postscript: Here’s the entirety of the David Bowie interview with Jeremy Paxman:


Old Playbooks, New Playbooks

My mom lives in Sweden, but she worked in the US for 10 years, so she qualifies to get a small little Social Security check each month. When I talked to her on the phone the other day, she complained that she wasn’t getting a very good exchange rate anymore. “That’s because you live in pretty much the only country on earth whose government hasn’t screwed up their economy,” I said. The relative health of the Swedish economy versus the rest of the world makes the Swedish crown stronger and worth more. When she tries to buy Swedish crowns with her US Dollars now, she doesn’t get as much as she used to.

Then we talked a bit about the American elections. I’m finding this year’s elections mostly uninteresting. Romney is trying (not too successfully) to stick to the narrative that Obama has screwed up the economy. I can agree that the US economy has been mishandled, but at the same time, I find that everyone else’s economy around the world (save Sweden’s) has been mishandled, too, and most of them have been mishandled far worse than America’s. I wouldn’t trade America’s economy right now for Europe’s. Or China’s — they’ve got a real estate bubble that’s probably going to burst soon just like ours did in 2008.

So America isn’t doing so well — but the competition is worse. That kinda makes us like a young athlete who is playing in a league that he’s too good for. He doesn’t have to work to improve; it seems pretty safe to just use his same old tricks to win the game he’s playing today. He’s not challenged by outside competition to innovate. And so I see both political parties are pretty much sticking to the same old playbooks they’ve used since I was a kid in the 70s and 80s. There are really no new ideas in this election.

I feel, though, that these playbooks are almost all used up. Each party is very near to getting what they have fought hardest for during my lifetimes. When the Democrats finally get gay marriage and universal healthcare on the books, which will probably happen if Obama wins, what will they want next? When the Republicans finally get taxes down as far as they can realistically go, and they’re pretty darn close, what’s their plan beyond that? I don’t see anything. It just looks like trench warfare in America to me after that, pushing the lines six inches here, six inches there, but not really getting anywhere new.

Which is fine, as long as the rest of the world stagnates along with us.

I worry, though, that the technology of the 21st century is producing a tectonic shift in economics itself. These sorts of disruptive technological shifts can punish the old guard who are too slow to change, and create new winners out of those who are less invested in an old way of doing things.

I’ll give some examples of what I mean. Here’s a talk by Daniel Pink about the what the latest science tells us about human motivation:

 

The interesting thing there is that basic carrot-and-stick economics–pay someone more if he does a good job–works remarkably well as motivation if the task is mechanical and/or routine. Those types of tasks formed the large majority of jobs all throughout human history, until the invention of the personal computer.

What has the computer done to those types of jobs? They’ve taken them over. If a job is repetitive or routine or algorithmic, a computer can now do that job cheaper and more effectively than a human being. So human beings have to move on to other types of jobs.

What types of jobs are those? Jobs that require human creativity and complex cognitive thought. And these are precisely the jobs where Daniel Pink points out that monetary rewards suppress productivity instead of enhancing it.

What does it do to the science of economics when higher monetary rewards suddenly start resulting in lower productivity? How do you design economic policy around that? The old playbooks that our political parties use now don’t address that question. Those old playbooks assume carrots and sticks always work. And they did work just fine, up until the time that you could fit a whole network of supercomputers in your pocket.

Computers also affect basic economics by ruining the supply/demand ratio. Throughout human history, up until the computer, anything of an economic nature that was made or done, was done in an environment of scarcity. Anything you can think of, there was a finite, limited supply of that thing. But now, thanks to computers, you can make 7 billion copies of this blog entry with barely any extra added cost to you at all. Scarcity does not exist in a digital environment. Supply is infinite.

This goes beyond just digital media. It affects other areas of human endeavor, like education. Our education system is designed around the concept that information is scarce, and it needs to be transferred from teacher to student, in order to prepare them for adulthood. But now, information is not scarce, students can acquire as much of it as they like for practically nothing. The jobs today’s kids will have when they grow up will not depend at all on what information they have, but on their skills in manipulating an infinite supply of information in creative new ways. How do we set up our educational institutions to function in a world of information plenty?

And soon, as 3D printers become more and more ubiquitous, scarcity will become a thing of the past for many physical objects, as well. What does that do to the manufacturing industry? What kind of policies do we need to manage that transition?

I have no answers to these questions. Neither do any of today’s political parties or candidates. It’s too new, too strange, and there’s not really a competitive threat that is forcing them to try to figure any of this out.

But at some point, if we Americans don’t at least start asking ourselves these new questions instead of re-asking the same old ones, some upstart countries will. And when the upstarts ask themselves these questions, at least one of them will be a Billy Beane-type who figures out some good answers, and moves his little country from an afterthought to a powerhouse. If we’re serious about winning the 21st century like we did the 20th, we should work hard to Moneyball them before they Moneyball us. Otherwise, we’ll wake up one day as the stodgy old rich team needing to scramble to catch up, wondering what happened to the good old days when America did things better than everyone else almost as a mechanical routine, without needing a second thought.

Slight Preference, Extreme Results

You have to look at philosophy from two levels: the individual, and the group. A slight preference at the individual level can result in extreme results when those slight preferences add up at the group level. Here’s an example of that mechanism in action:

In sports, you see this effect in amateur drafts all the time, particularly in baseball where draft picks can’t be traded. Let’s say a baseball team like the Oakland A’s values college players a mere 1% more than other teams do. The A’s may say and believe that they don’t reject high school players, but the effect of their slight preference is that they end up taking almost exclusively college players, simply because the high school players they prefer are all chosen ahead of them, and invariably when their turn to choose comes up, their highest ranked player just happens to be a college player.

In the NFL, where draft picks can be traded, you could create extra value for yourself if you know that you value players differently than others. The Oakland Raiders have a unique valuation on amateur talent, and nearly every year their selections are a complete surprise to those following conventional wisdom. Because their valuation system is so unique, they could probably create extra value for themselves by always trading down. The player they want will often still be available lower in the draft. Sadly for Raiders fans, the Raiders almost never do this.

In crafting a philosophy, we should be aware of this feature of group dynamics. Groups, moreso than individuals, tend to move either towards the middle, or to the extremes. In America, we see this in our politics. Most Americans are rather centrist, but the system of primaries to choose nominees attracts the more loyal partisans at either end of the political spectrum. So instead of a runoff between Candidate 40th-percentile vs Candidate 60th-percentile, our choices in the general election often ends up as Candidate 10th vs. Candidate 90th. The result is a legislature that is far more partisan than the general population, and is far more despised than it would seem necessary.

How do we keep a set of 60/40 preferences from unintentionally turning into 100/0 behavior, or for that matter, turning 80/20 preferences 50/50 behavior? It’s easy to blame the people involved for behaving badly (see my last article on Willpower Bias) and to argue “don’t do that, you bad people”. But it’s hard to change individual preferences, and especially hard when individual preferences are being affected by group dynamics. More often, the solution is to structurally reduce the amplification. In sports, enabling trades of draft picks at least makes it possible for teams to find more accurate values for their picks. In politics, open primaries or ranked voting systems would probably make the distribution of elected officials look more like the general population than the extremes.

This isn’t to say that there aren’t possible benefits to 0-50-100 group behavior over the messier alternatives. But it’s hard to believe that this tendency will always yield optimal result. If the optimal solution lies at 33 or 67, we want the quickest, most effective way to hit that optimal result. Ping-ponging between the extremes may get us there in the end, but you have to think it would be better to move their directly if we can. Being fully aware of the differences between individual and group dynamics can help us find optimal solutions in an optimal manner.

Beer Run: How to Defeat a Sabermetrician in an Argument

I greatly enjoyed the recent smackdown between Rich Lederer of Baseball Analysts and Buster Olney of ESPN regarding the Hall of Fame merits of Jim Rice. If I had to score the fight, I’d say Rich won the argument in a blowout. But I say this not because I think Lederer is necessarily right, but because Olney played the game poorly. Olney was like a fast-break basketball team that let itself get caught in a half-court battle. Lederer was able to dictate the terms, and Olney fell right into his trap.

When one competitor prefers a particular style of play, you can beat them in one of two ways: (1) you can play their style of play better than they do, or (2) you can change the game you play. *

*Permit me a brief Posnanskian aside here, on the eve of Super Tuesday: the current Democratic primary is an interesting contrast of these two choices. Remember back in the 80s how the Republicans changed the meaning of the word "liberal" so that it became a bad thing? How Carter, Mondale and Dukakis got labeled as wimpy and economically incompetent "tax-and-spenders", and just got their butts kicked? And then along came Bill Clinton, who figured out how to play the Republicans’ game better than the Republicans? Look, it’s a Democrat who can manipulate the meaning of words better than a Republican! A Democrat who blames the Republican for being economically incompetent! A Democrat with a mean streak! It’s like the Red Sox and the Yankees: neither one would ever admit it to themselves, but the reason they hate each other so much is that they’re so damn similar. So here’s Hillary Clinton now, playing that same old game, and like her husband, she’s really good at it. But along comes Barack Obama, who says, we’re tired of all this boring, low-post, half-court crap, we’re tired of Red Sox vs. Yankees all the time, we’re tired of the Bush vs. Clinton dynasties, there’s more to this game than just the two dominant teams, we’re playing a completely different game with a completely different point of view and we’re going to take the ball and just run and run and run up and down the court. And of course, Bill Clinton goes out and spouts off and tries to drag Obama into the half-court game of parsing words and defending the low post, and Obama tries his best to avoid it, but he can’t, completely, because if the other team is posting you up you still have to defend it. And so last week, after all this time trying to avoid the dynasty game, goes and makes a mid-season trade for a dynasty-type player (Ted Kennedy), to help him defend the low post. Anyway, this is all a big mixed metaphor that’s about to jump the shark off the deep end, but like the recent Super Bowl, I find the game to be surprisingly fascinating, and probably should be until the end.

Anyway, back to Lederer vs. Olney. The trap that Olney fell into was to let Lederer dictate that the argument must be based on statistical evidence. So Olney tries to say that OPS+ is misleading, RBIs were important at the time, blah blah blah, and deliberately avoided using "fear" in his argument. To all that, I say, phooey. If you’re not immersed and invested in statistical analysis, you’re not going to win a statistical argument against someone who is. You’re like that guy in that movie who pulls out a sword and proudly swishes it around, and Indiana Jones pulls out a gun and blows you away.

If you want to avoid falling into that trap, if you want to avoid becoming fodder for BTF and FJM mockery, you need to learn how to avoid the Sabermetrician’s weapons, and where to hit him where he is weakest. Welcome to your first lesson in Defense Against Deductive Arts.

To begin your study, consider this: what is the most important element of the following photograph: Elijah Dukes’ home run, or the beer?

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