The human brain is amazing. It can take a very limited amount of information, and turn around and give you an instant decision based on that limited information. Computers, on the other hand, are really bad at that. With a computer, all the variables must be filled in, or the program won’t run.

The Oakland A’s are trying to build a new baseball park. There are questions in the Oaklandsphere whether they should build it at the Coliseum or at Howard Terminal. Much of the debate around those questions takes place in a foggy, muddled soup of barely identifiable information about (a) how much the ballpark would cost, and (b) how much money it would make if they built it.

But hey, we’re human beings! Our lives aren’t math problems in a textbook. We go through our lives dealing with incomplete information almost all of the time, no big deal. Just because we have almost no idea at all about any of the money involved with this doesn’t mean we can’t end up deciding with conviction that we prefer one site or the other.

So we end up ignoring the information we don’t have and focus on information we do have. Or, we make wild guesses at the information we don’t have, and go with that. Or, most likely of all, because we’re human beings and building a ballpark is really not our job, we’re not going to spend any energy to think it through at all, so we’ll just stick with our gut reactions to the idea, and that’s good enough.

And therefore: messy, muddled ballpark debates.

Not really any different from any other debate in human affairs. It’s all cool.

EXCEPT.

Except: this is the Oakland Athletics we’re talking about.

The Oakland A’s. Team Moneyball. The organization out of all human organizations in all human societies in all of human history that is most famous for turning life into a math problem.

Back when statistical analysis in baseball started to become a thing, a lot of old school types tried to argue against it. And they kept getting their asses handed to them, because they didn’t understand sabermetrics. Their arguments (“Batting average and RBIs are good enough! Watch a game, not the computer!”) were utter crap. This is a point I’ve made before, but the best arguments against sabermetrics are made by the people who actually understand sabermetrics, who know what its true flaws and blind spots are.

Sure, the math in ballpark building is different from the math in baseball games. But sabermetrics is not just about the math. It’s about how you think about the game.

Remember this conversation in Moneyball?

People who run ballclubs think in terms of buying players. Your goal shouldn’t be to buy players. Your goal should be to buy wins. And in order to buy wins, you need to buy runs.

What is the ballpark equivalent of that conversation?

What do most people think the goal of building a ballpark is? What should that goal really be?

Let’s try to be creative. We may not have any of the numbers, but we can figure out how we would approach them if we did. Let’s try to move past muddled conversations, and think about how the A’s might be thinking about this ballpark. What would Jonah Hill tell Brad Pitt if they were building a baseball ballpark instead of a baseball team?

Let’s try to understand why the A’s might be making the choices they’re making. Let’s Moneyball a ballpark.

Investing and growth

Let’s begin by talking about investing. Why does anyone invest in any particular thing?

I think the most common (muddled) answer to that is, “to make a profit.” But that doesn’t answer the question. Because the question was, why does anyone invest in any particular thing? Lots of things make a profit. You could invest in a 1-year US Treasury bond today and make a profit of about 1.6% in that year. Or, you could invest in a 30-year US Treasury bond today and make a profit of about 2.3% a year over 30 years. Or–and here’s the rule of thumb to keep in your head–you could invest that money in a boring stock market fund and make a profit of (historically, on average) about 7%-10% a year. So why are you investing in that particular thing and not some other thing, like a Treasury bond or a stock market fund?

If we think of mere profitability as the goal–that as long as we don’t lose money, it’s fine–we don’t have a Moneyball mindset. We’re more likely to continue doing what we did before, because we didn’t lose money. This kind of thinking tends to lead people to prefer the Coliseum site, because hey, the Coliseum worked for 50 years, didn’t it? We can probably build a nice, cheap stadium on that site and make our money back in the end, so if it’s not broke, why fix it?

But if mere profitability is the end goal, the A’s ownership team probably shouldn’t invest in a ballpark at all. They should sell the team, and put the money in the stock market and make their 7-10% a year.

But when you start to think that an investment in a ballpark needs to grow at a rate greater than 10% a year, well, now we have a much more complicated question with a much more unclear answer. We should be asking, “What rate of growth are we trying to achieve with our investment?”

Volatility of outcomes

OK, suppose we get the growth idea. But there’s another kind of muddled thinking that comes with that, and that’s to make a single estimate of growth, and make a choice based on that. Suppose we estimate that the Coliseum site will grow at 15% and Howard Terminal at 30%. We should choose Howard Terminal, right? Not so fast.

Those single numbers are just estimates. In reality, there’s a whole range of possible outcomes. I think most people would guess that the range of possible outcomes at the Coliseum is smaller than at Howard Terminal. Suppose (pulling numbers out of the air) the Coliseum could grow somewhere between +10% and +20%, while Howard Terminal could grow somewhere between -20% and +50%. Are we willing to risk a big loss for a chance at spectacular growth? Or do we want a safe bet with a smaller upside?

There’s no obvious answer to that question. I can understand preferring the choice with the lowest downside or the choice with the biggest upside, but insisting that one or the other is obvious and clear is, well, obviously and clearly wrong.

So we shouldn’t be asking, “Will this make a profit or not?” We should be asking, “What is the range and distribution of possible outcomes, and how comfortable are we with those possible outcomes? What are our minimum acceptable and target growth rates for our investment?”

Ways to grow

That brings us to our third source of muddlement. When we say “grow”, what do we actually mean by that? How do we actually grow a business?

The ballpark translation of that first Jonah Hill sentence is probably something like, “people think if you build a nice ballpark, you’ll sell more seats.” Which, like “buying players” is both true and at the same time muddled. It’s not a Moneyball way of thinking about it.

The Moneyball way to think about it this is to start breaking it down like Jonah Hill does. In sabermetrics, you want to buy wins. In order to buy wins, you need to buy runs. Where do runs come from? Lots of different places: batting, running, catching, throwing, pitching, all of which have their subcomponents, each of which has its different price in the marketplace. What’s the most cost-effective way to purchase those subcomponents to assemble the runs and wins you need?

The Moneyball ballpark question then becomes: what’s the most cost-effective way to assemble the subcomponents of a ballpark that we need, in order to achieve the growth that we want?

Big Things and Little Things

On the baseball field, there are many statistical subcomponents you can try to improve on. Some of them, however, will have a bigger impact than others.

There is a statistic called the “Beane Count“. It was invented by writer Rob Neyer shortly after Moneyball came out, and is named for A’s executive Billy Beane. It tracks two main statistics, on each side of the ball. Those are:

• Walks
  • Taking walks
  • Not yielding walks
• Home runs
  • Hitting home runs
  • Not yielding home runs

If you look at Beane Count for 2019, the top 6 teams in Beane Count in the American League were the six teams that made the playoffs. In the National League, five of the top 6 teams in Beane Count were playoff teams, and the one that wasn’t, the Milwaukee Brewers, was 7th. So the stat correlates with the primary goal of winning.

But there’s another key feature of the Beane Count that is significant for our purposes here: these particular stats kind of give you something for free. On both walks and home runs, the ball is not in play. You don’t have to participate in defense and baserunning. So you win the game, in a way, by avoiding having to play the game.

If we want to translate this piece of Moneyball to ballparks, there’s an analogous game we want to avoid playing if we can. Making a profit selling things is a difficult game to play, and achieving growth is even harder. In the normal game, you make a product for [$X]. The supply/demand curve directs you to sell it for [$Y], and so you end up with a margin of [$Y – $X].

Can you sell enough volume at that margin to reach your growth target? If that seems hard, is there a way you can get something for nothing out of $X or $Y to make it work?

Let’s make a business equivalent of the Beane Count. Call it the Kaval Count, after A’s President Dave Kaval. It tracks the things you can do that help you avoid playing the straightforward business game. Like the Beane Count, the Kaval Count has two main ideas, each split into two sub-ideas:

• Covering costs externally
  • Subsidies
  • Arbitrage
• Breaking the laws of supply and demand
  • Become a tech company
  • Become a monopoly

Subsidies

For decades, direct subsidies from local governments have been by far the #1 method for professional sports teams to reach their target growth numbers. Tell a city, “Help us pay for the cost of building our sports facility, or we will find another city who will.” In some parts of the country, cities have figured out that this is a bad deal. But as long as other parts of the country haven’t figured this out, it will continue being used.

So the Texas Rangers are constructing a new ballpark. How did they make the numbers work? They got someone else to pay for much of it. The Atlanta Braves also recently built a new ballpark. How did they make the numbers work? They got someone else to pay for much of it. The Oakland Raiders are building a new stadium in Las Vegas. Why? They got someone else to pay for it.

Oakland and Alameda County fell for this scheme in the 1990s, when they built Mount Davis to lure back the Raiders from Los Angeles. That plan did not work out at all, and the city and county are still deeply in debt from it. They won’t fall for that scheme again.

So direct subsidies for the A’s to build in Oakland are out of the question. However, there are certain infrastructural costs of construction that fall under the category of the normal activity of a city: building roads and transportation hubs and electrical grids and storm drains and sewers, etc. So while they may not get help subsidizing the building itself, it may still be politically feasible to get some of the surrounding infrastructure paid for. That alone is unlikely to get the A’s to their growth targets, but it may help some.

Arbitrage

Construction costs are not the only costs of building a ballpark. There is also the cost of the land we are building on top of.

In some cities, there is land which is zoned for one kind of use, but would be more valuable if it were zoned for some other kind of use. There is also the idea that the demand for land near a ballpark becomes more in demand simply because it’s near a ballpark.

In these cases, we’re not actually reducing the cost of building the ballpark. But we can arbitrage the difference between the value of the land without a ballpark, and the value of the land with a ballpark, and use that difference in value to finance the construction of the ballpark.

This is what the A’s are trying to do in Oakland.

Howard Terminal and the Coliseum are zoned somewhat differently, but most of the land for both sites is currently being used as parking lots. At Howard Terminal, it’s being used to park trucks while they wait for shipments at the Port of Oakland. At the Coliseum, it’s used to park cars for a bunch of sporting events that, because the Raiders and Warriors are moving, aren’t going to happen there any more.

So the question becomes, can the A’s acquire these land parcels at the value of a parking lot, and make them more valuable than a parking lot?

The government agencies who control these parcels have to try to figure out, how much is this land worth if they did nothing with it, or if they sold it to someone besides the A’s? The A’s have to figure out, how much could they make either parcel (or both parcels) worth if they built (or didn’t build) a ballpark on top of it? And somehow, those numbers have to work for both sides of the negotiations on the land.

This is where the arbitrage becomes a math problem. And we’re not the A’s, so we don’t have the numbers. We’re not doing the math. We don’t know if the numbers will work to meet the A’s growth minimums and targets or not. Best we can do from the outside is understand how the math would work on the arbitrage, if we did have the numbers.

And if the math works, it’s a more ethical way to finance a ballpark, because you’re not taking someone else’s money with no promise of returns or ownership in order to finance your own growth. You’re taking the inherent surplus value of a Major League Baseball team, and turning that, indirectly, into the money to build the ballpark.

Becoming a Tech Company

This is the Kaval Count element least likely to apply to a ballpark. But I want to bring it up, because it seems like the A’s under Kaval and COO Chris Giles have been trying to think like a tech company, even if the nature of their business doesn’t let them technically become one. Even if a ballpark can’t have the unique economics-busting properties of software, there are advantages to be gained by a tech-company approach.

I’m going to use Ben Thompson’s definition of a tech company from his blog, Stratechery:

Note the centrality of software in all of these characteristics:

• Software creates ecosystems.
• Software has zero marginal costs.
• Software improves over time.
• Software offers infinite leverage.
• Software enables zero transaction costs.

The question of whether companies are tech companies, then, depends on how much of their business is governed by software’s unique characteristics, and how much is limited by real world factors.

Software is a compelling thing to invest in, because it can break the laws of supply and demand. Usually, when you sell a unit of something, whether a product or a service, there is a cost to producing and distributing each unit. But with software, the cost is practically the same whether you sell one unit or one billion units. Your growth rate is never limited by supply, only by demand.

A ballpark is a physical asset, not a digital one. So it’s supply is necessarily going to be finite. The fire marshal will only allow a certain number of people into your space. You’re going to have a finite number of seats. You’re going to be limited by geographical distances; it’s hard to sell access to a ballpark in Oakland to someone in Oregon or Nevada, let alone Australia or Japan. So a ballpark can’t have the potential infinite reach that software can have. (Although, you never know, maybe some future AR/VR software may change that…)

But just because you’re too physical to have infinite reach doesn’t mean you can’t increase your reach by significant amounts, or even orders of magnitude. So let’s go through Thompson’s points, one by one:

Creating an ecosystem

The most valuable software platforms enable other people to find and create value on top of the software. This creates network effects, where the more people who are on a platform, the more useful the platform gets, which entices more people to join, and so on. Cyberspace ecosystems can grow exponentially into a winner-take-all status in a way that normal economic activity historically hasn’t.

The most successful ballparks do often create an ecosystem of other businesses around them. Bars, restaurants, parking lots and so forth all thrive when placed in proximity to a ballpark. Their loyal customers can become the ballpark’s loyal customers, and vice versa. Urban ballparks can have desirable network effects. But because this ecosystem is limited by geography, it won’t grow exponentially like software can.

Zero marginal costs

Software breaks the laws of supply and demand by having essentially an infinite supply. The cost of making the first unit of software sold is fixed, but any additional units adds almost zero additional costs.

A seat in a ballpark can only be sold a finite number of times over the lifetime of that seat. In addition, for every X number of seats you sell, you need to hire Y number of ushers and ticket takers and so forth. And there’s also the minor detail that in every professional sport, roughly half of all revenues end up going to the players on the field.

But if you start to think like a tech company instead of a traditional sports team, you can come up with innovations that look more like a zero-marginal cost product than a seat at at ballgame. The A’s Access program, introduced by the A’s in 2019, is a subscription of access to the ballpark instead of seat tickets. A’s Access may not be a zero-marginal cost product, but it has a lower marginal cost than a seat does. It allows the finite geography of a ballpark to be filled more fluidly over the course of a game and a season. That fluidity can enable a team to build a smaller ballpark, because you don’t need to hold as much inventory on hand to accommodate the same number of customers.

Improves over time

Subscriptions are attractive to both software companies and software customers. Software companies like them because they create a more steady and predictable stream of income. Customers (especially business customers) like them because they allow them to use the software flexibly with their needs without having to make any big up-front commitments.

The thing that makes the software subscription engine run is the fact that software keeps improving over time. A new version comes out regularly, and if you’re subscribed, you’ll automatically get the new and improved version. If it didn’t improve, people would probably prefer to just buy the software up-front and hold on to it as long as possible.

Traditionally, it is hard to say that a ballpark improves over time. It is a large building, and once built, changing it significantly is usually very difficult and expensive. In addition, the ballpark is designed to host a baseball team. Baseball is a zero-sum game. It is impossible to keep improving a baseball team forever. It’s going to cycle between good years and worse years.

Still, if you were committed to it, you could probably design a ballpark to be much more modular than they’ve been historically. You could plan to have different sections of the park be replaced by something new far more often than they have in the past. This would allow for more experimentation with various products, and allow the ballpark over time to keep evolving into something more attractive to subscribers and more profitable for the business.

I don’t see any evidence that the A’s have planned any modularity with their Howard Terminal renderings, which look rather monolithic. I find that a bit surprising, since the A’s under Kaval and Giles have been quite willing to shoehorn various sections of the old Coliseum into modular experiments.

Software offers infinite leverage

Basically, this means you can take the software you’ve built and move into any market in the world immediately and sell it.

Obviously, that’s impossible with a ballpark. You’re bounded by geography. But that doesn’t mean you don’t want to expand those boundaries, so you can reach as large an audience as possible. This is where the exact location of the ballpark and the ease of getting there matters.

Zero transaction costs

Of the five criteria for a tech company, this is probably the one where baseball fits most closely. To achieve zero transaction costs, you want purchasing your product to be entirely self-service. With individual tickets, you still have ticket booths, but many tickets are now sold online. Traditional season tickets tend to still be handled with salespeople, but there’s no reason the A’s Access subscription can’t be entirely self-service, as well.

Become a Monopoly

Growing a business profitably is really hard when there’s a lot of competition. Competition makes you have to fight for the available demand, downward pressure on your prices, and hence, profits. The only way to avoid that is to become a monopoly, and have no competition.

A totally pure monopoly is not really a thing that exists very often in the wild. A coffee shop may be the only coffee shop in a certain neighborhood, but it’s still competing with the coffee shops in the next neighborhood over, plus with the coffee you can buy in a grocery store and make at home. But even a small monopoly of some sort lets you keeps prices higher than you otherwise would without the competition, so it helps your profit margins.

Most professional sports teams have monopolies in their local markets in their sports. If you want to see Major League baseball in Denver, the Rockies are your only choice. But the Rockies compete with the Nuggets and the Avs and the Broncos for sports dollars, and with TV and film and theater and music for entertainment revenues.

Up until now, the A’s have probably held one of the weakest monopolies of any professional sports franchise. They share the Bay Area baseball market with the Giants. And up through the 2019 season, they’ve shared the relatively small Oakland sports market with the Warriors and the Raiders.

But that’s about to change. With the Warriors and Raiders leaving, the A’s are going to be the only major sports team in the East Bay. Their “Rooted in Oakland” campaign is designed to promote that fact. The A’s have an opportunity here to grab hold of a monopoly in the East Bay on the one hand, and then start competing harder in the adjacent markets if they can.

This is where the design of the new ballpark really matters. If the A’s build a ballpark that looks like every other sports facility, then they’re competing with every other sports facility. But if they can build something unique, that provides an experience that nobody else in the region or the world, can provide, then they would be creating another kind of monopoly that no one else can compete with. That’s why the A’s looked outside the box to find an architect who could bring something different to the table.

Of course, there are other ways to generate wins besides the statistics in the Beane Count, and there are other ways to generate profitable growth besides the elements of the Kaval Count. You can win baseball games by hitting single and doubles, and by playing great defense and baserunning. You can also win the traditional business game by selling a higher volume of a better product made at a lower cost than the competition’s.

The point is we want to think about the ballpark in a Moneyball fashion. In building a new baseball team, we’re not just replacing one player with another. In building a new ballpark, we’re not just replacing a bunch of seats around a baseball field with some other seats around a baseball field. We’re assembling a bunch of subcomponents as cost effectively as possible. Can we assemble those subcomponents in a way that they add up to reach our targets?

So why would the A’s choose Howard Terminal with its political and physical hurdles over the Coliseum? Well, maybe the math of those subcomponents tell them so. Maybe the math says there’s a bigger opportunity for arbitrage at Howard Terminal than the Coliseum. Maybe the math says an ecosystem in Downtown Oakland will create bigger network effects than an ecosystem in East Oakland. Maybe the math says they can leverage the location of Howard Terminal into a wider market, particularly of those coming off work both in Downtown Oakland and Downtown San Francisco, than they can at the Coliseum location. Maybe the math says can hold a bigger monopoly with a unique waterfront ballpark with a rooftop park with views over the bay than they can with some sort of ordinary ballpark at the Coliseum site.

And maybe there are reasons beyond the math for making some of these decisions. Maybe the A’s have goals for this ballpark beyond just economic growth. Maybe they really do want to make a cultural impact on the East Bay community with this ballpark, and they think they can do that better at Howard Terminal, numbers or not.

We can’t know for sure, of course. We don’t have the numbers, the A’s aren’t sharing them, so we can’t do the calculations ourselves. But we can take the time, especially when it’s our jobs to do so, to try to understand the way the A’s would think things through.

Every good story is, at its core, a story about human nature. Who are we? What are we really like?

In order to answer these questions about ourselves, we tell stories that put human beings to test. What happens if the various aspects of human nature get pitted against each other? What happens when we test our human nature against its limits? What happens if you change or remove some vital part of human nature?

Then once we have concluded a story about human nature, we then are left with a question. what does this story say about how we should behave and organize ourselves?

I recently found myself unintentionally but simultaneously binge-watching two stories that tested human nature in a very similar way, but drew completely different conclusions. Those stories were a web serial called 17776 by Jon Bois’, and the HBO television drama Westworld.

(WARNING: some mild spoilers follow.)

Both of these stories imagine a near-future where human beings find themselves in an environment where the intrinsic physical vulnerability of human nature has been removed. In the case of 17776, there are some mysterious nano-bots which automatically fix things anytime someone gets sick or hurt. In Westworld, humans interact with robots who they are free to treat however well or badly they like with no repercussions. People can kill the robots, but the robots can’t kill humans. If a robot is killed, they are removed, fixed, and returned to service good as new.

That’s pretty much where the similarity between these two stories end. The two stories reach very different conclusions about what humans would do if they suddenly became physically invulnerable. Bois imagines that people would spend their days playing and watching increasingly elaborate games of football. Westworld, on the other hand, thinks that people would primarily indulge themselves with sex and violence.

17776 is optimistic about human nature, and the conclusion you could draw from it is that our vulnerability essentially causes us to indulge in behaviors that harm other people. Human nature is essentially good, and if you removed the external sources of our vulnerabilities, there would be no point in bothering to harm anyone else, so we wouldn’t. Westworld, more pessimistically, implies that it is our vulnerability that prevents us from harming others, because we are afraid of reciprocal harm. If you remove that fear, we will all become psychopaths and indulge in orgies of harm. We are by nature essentially wild, dangerous animals that need to be restrained.

Which model of human nature is more correct? It’s hard to know for sure. These are fictional stories. In real life, you cannot simply devise a scientific experiment where you remove vulnerability from human nature and see what happens. Every aspect of human nature, our emotions and intellect capacity and built-in heuristics are evolutionary responses to all the various sorts of vulnerabilities that all our ancestors faced since the creation of the earth. Human nature consists of a complex jumble of behaviors that are not easy to reduce down with a simple two-dimensional A/B test.

But speaking of simple, two-dimensional A/B tests, I will leave it as an exercise for the reader to draw the parallel between these two views of human nature, and the views of human nature that underlie the policies of our two American political parties.

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’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:

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:

I read somewhere recently, I forget where, that the purpose of people getting together for a conversation over a beer or coffee or lunch or dinner is that it the food and drink spare us from the burden of needing to have something to say throughout the whole conversation.

This was a revelation to me. All this time, I assumed that the primary purpose of lunch was lunch. All this time, I figured that I was just lousy at conversation because being an introvert made conversation awkward and laborious for me. For everyone else, conversation seems comparatively effortless. But it seems from this data that conversation must be harder for everyone else than I had assumed.

My oldest daughter is a freshman in college. She recently texted me and said she wanted to talk. I asked, what about? She got annoyed at me for asking.

I was clueless as to why. I guess the Dunning-Kruger effect applies to all of us, there’s always some area of life where we’re so incompetent we don’t even know we’re incompetent. This area, apparently, was one of mine.

She asked if we could just talk about something stupid. So I called her, and we talked about Donald Trump and the presidential race and stuff like that for a good long while. I didn’t ask about what was really bothering her.

Eventually, the conversation turned, and we finally got to talking about the thing she wanted to talk about. But that probably at least half an hour into the conversation. We segued slowly and organically from the stupid stuff into the real issue.

And this, too, was a bit of a revelation to me, that someone would not want to get straight to the point, that someone would need a nice long conversational warmup before they’d feel comfortable enough to be ready to talk about something more uncomfortable. I’m very much a get-to-the-point kind of person. I tend to say what I mean, or nothing at all.

Language is imprecise. Our feelings don’t always have direct translations into speech. It’s hard to explain what we feel, to say exactly what we mean. We have wants and desires and emotions, and we often try to rationalize those feelings. Those rationalizations are often logically incoherent. But it’s hard to see the incoherence of our own rationalizations because our points of view are so limited. And often (if we’re not falling prey to the Dunning-Kruger effect) we intuit that our rationalizations may be incoherent. So we’re cautious in what we say. We know that there can be social penalties for saying the wrong thing in the wrong way to the wrong person.

All this adds up to making the act of talking about something sensitive daunting. There is a vulnerability in speaking. That’s why our culture has all these rituals and conventions around conversation, like idle chit-chat and coffee and such: to build enough trust in the environment where we can feel comfortable enough to overcome the vulnerability inherent in speech.

I never fully understood this before. I feel like everyone else understands it, though, because they act as if they do. But if they do, it must be an intuitive understanding, a grokking, not an explicit fact that people state out loud. Otherwise, I probably would have heard someone say it explicitly sometime before in the almost 50 years I’ve been in this earth.

Having now finally come to this understanding, it occurs to me that perhaps this is the great flaw with Twitter, why everyone I know on Twitter seems to eventually run into a wall with it. The 140-character format pushes you to get straight to the point. There is no room for the idle chit-chat and sips of coffee and other conversational rituals that let us dance around the sensitive issues. Without these rituals that are built into real-life human-to-human conversation, the problems with speech that those cultural rituals are designed to prevent come flooding in.

There is so much hair pulling and teeth grinding about what people should and should not say online, and how they should or should not say it. And maybe all that hair pulling and teeth grinding arise because our online conversational cultures, and the technological platforms they reside on, have not had the time to evolve into something that works, the way that our real-life conversational culture has.

There are many, many more people who are clueless about how to behave in online conversations than there are people who are clueless about how to behave in offline ones. How I came to be the flipside of that, I don’t know.

And it also occurs to me that there is a value in stating explicitly the things that are mostly just intuited about human nature and human culture. I want to explore these sorts of things. There is a risk, though, a vulnerability, in stating these things. The people who intuitively grasp these things will feel as though I am insulting their intelligence by stating something so obvious it shouldn’t need saying. But it isn’t meant as an insult to their intelligence, it’s meant as an insult to mine. I need to say these things because I’m the one who doesn’t understand these things. I need them explained to myself.

Which is all a roundabout way of stating something that maybe could fit into a tweet: I plan to start saying things that aren’t obvious to me but may be obvious to others. Sorry if you fall into the latter category and I waste your time. Such is the risk of saying anything, ever. And sorry for the roundaboutness in getting to this point. I seemed to need it, for some strange reason.

Continue…

Once upon a time, about a billion years ago, life was simple. Everybody lived in the oceans, and everybody had only one cell each. This was quite a fair and egalitarian way to live. Nobody really had significantly more resources than anyone else. Every individual just floated around, and took whatever it needed and could find, and just let the rest be.

This golden equilibrium was how life did business for a couple billion years. There was no such thing as jealousy or envy, and as a result, everyone lived pretty happy lives.

Then, one day about 800 million years ago, a pair of single-celled organisms merged to become the first multi-cellular organism in the history of the earth.

At first, these multi-celled creatures were just kind of like big blobs of single-celled organisms, and didn’t cause a lot of problems. Everybody was still kind of doing the same job as everyone else, even if they had organized themselves into a limited corporation of sorts. Most other single-celled creatures just figured they were harmless weirdos hanging out together, and ignored them.

Image credit to Julian Frost via Creative Commons License

They could not have been more wrong. For once the multi-cell genie was out of the bottle, Pandora’s box could not be closed, and the dominos began to fall. This simple change may have seemed innocent at first, but little did the single-cells know that they were the first creatures on earth to fall victim to the innovator’s dilemma. The single-celled creatures were far too invested in the status quo to change, and consequently ignored the multi-cellulars as irrelevant, and did not realize until it was too late that the game had suddenly shifted.

Continue…

Well, here we are. The Giants won another World Series, while the A’s flopped in the playoffs yet again. I’m not one of those A’s fans who hate the Giants, but it’s starting to annoy the crap out of even me to see the Giants always succeed in the playoffs, while seeing the A’s always fail.

The A’s have had 14 chances in the last 14 years to win a game to advance to the next round of the playoffs. They have lost 13 of those 14 games. If the playoffs are truly a crapshoot, the odds of this happening are 1-in-1,170. (So it’s not technically always — they could have gone on to lose the 2006 ALDS against the Twins, too, which would have made them 0-for-16, with an unlikelihood odds of 1-in-65,536. So if you want to look on the bright side, things could be 56 times worse than they are.) And in a crapshoot, the odds of the Giants winning 10 playoff series in a row, as they have now done, is 1-in-1024.

So if you’re an A’s fan who hates the Giants, and who believes that the playoffs are a just crapshoot, you’ve been struck with a series of unfortunate events that had literally less than a 1-in-a-million chance of happening.

Sabermetrics has come up with no good explanation for it except to say, well, these things happen about once every thousand times, or once every million times, sorry A’s fans, it just happened to be your turn to hit that unfortunate lottery, and it’s just bad luck. Oh, and you have a crappy stadium that’s falling apart and a team ownership and a local government who all seem too incompetent to do anything about it unlike those guys across the bay, sorry about that, too, gosh you guys are unlucky, tsk tsk tsk.

Which is just a deeply, deeply unsatisfying answer. If you have an ounce of humanity, you will reject that explanation, and ask the obvious question.

And to answer that question, the sabermetrician dives into the numbers, and pulls some out numbers with some number-pulling-out tools, and finds nothing to report. Nope, no evidence here of anything, so it must just be bad luck.

To which I ask: what if the reason the number-pulling-out tools can’t find any cause for the problem is because those number-pulling-out tools themselves are the problem?

I have no evidence of that. But it’s something I believe might be true, even though I can’t prove it.

* * *

I have a number of these beliefs–or hypotheses, if you will–about baseball, but I’ve mostly kept them to myself because of this lack of evidence. What the hell do I know, anyway? Who am I to pontificate? And why bother spouting these theories when I can’t defend them with evidence? So I just keep my mouth shut.

But I got a little bit of self-confidence in my belief system when Robert Arthur of Baseball Prospectus took one of my hypotheses (that injured A’s in the second half of 2014 had begun cheating on fastballs, making themselves vulnerable to offspeed pitches) and found evidence to support it ($):

The overall pattern of changes is beautifully consistent with Ken’s theory…

It’s very satisfying to find that the data supports one’s theory!

But I didn’t just come to this particular hypothesis that Mr. Arthur investigated out of thin air. This hypothesis arose out of a deeper foundation of hypotheses that color the way I look at baseball. I want to put all those hypotheses out on the table now, lack of evidence be damned. And maybe someone (maybe me someday, if I ever find the time and energy and resources and willpower to do so, which hasn’t happened yet) will take those hypotheses and invent the technology needed to find the evidence to support it.

So let’s put it out there.

* * *

Belief Without Evidence #1. A technological Sapir-Whorf hypothesis

The Sapir-Whorf hypothesis, a/k/a the Linguistic relativity principle holds that the language that a person speaks influences the way a person conceptualizes their world. The obvious example of this is that people have trouble distinguishing between colors if their language does not have a word for that color.

To a certain extent, I believe this hypothesis. Being fluent in both Swedish and English, I know there are certain concepts, such as the difference between belief in an opinion and belief in a fact, where the Swedish language makes clear distinctions (tycka and tro) and English does not. English speakers spend ridiculous amounts of time arguing about these things, and Swedes simply don’t need to. It’s not that English speakers can’t conceptualize the difference between opinion and fact, but doing so is way more difficult in English, because the word “belief” in English is quite fuzzy, whereas in Swedish, the language makes it simply impossible to confuse the two.

I touched upon this in my essay in the 2014 Baseball Prospectus annual, that I believe a similar concept applies to the technology we use. The reason statistical analysis began to influence the way we conceptualize baseball in the 1990s is not because human beings suddenly became smarter in the 1990s. There were statistically informed people who suggested such analysis almost a century earlier. It happened in the 1990s because the price of the technology needed to perform such analysis had finally became reasonable.

The predominant technology we use to perform such analysis is SQL, which is the primary language used to query relational databases. SQL and relational databases are technologies which are built upon set theory. A set is basically an unordered collection of objects.

And this is where I believe that a technological Sapir-Whorf hypothesis applies to baseball. Practically all of our analysis of baseball statistics treats its data an unordered collection of baseball events: pitches, plate appearances, games, series. Standard baseball analysis (the public kind anyway, who knows what is being done inside these organizations) treats its data that way because that’s the way SQL treats its data. The available technology guides our conceptualization of the world. And that leads us to my second hypothesis:

Belief Without Evidence #2. Baseball events are NOT unordered

For any batter to hit a ball, the batter needs to predict where the ball is going to be before it reaches the bat. There are two different mechanisms for this prediction.

First, there is a conscious prediction. The batter may decide, consciously, based on some sort of rational analysis, that he is looking for a fastball down and in, and wants to swing at only a pitch in that location that he can pull.

But once the pitcher releases the ball, this kind of conscious prediction mechanism is far, far too slow to be of any use. At this point, everything is turned over to a much faster, subconscious, automatic system to predict the actual flight of the ball, and to send the muscles in motion to meet the ball.

My thoughts here are heavily influenced by Jeff Hawkins‘ book On Intelligence, which lays out a framework for how this automatic system in the brain works as a memory-based prediction machine.

Order matters in baseball, because this automatic prediction mechanism has a strong recency bias. (A conscious prediction might not have a recency bias if truly rational, but how often does a batter perform a purely rational analysis at the plate?) The speed, location and movement of the most recent pitch will affect the brain’s automatic prediction of the speed, location and movement of the next pitch. The more recent a pitch, the more it affects the automatic system’s prediction for the next pitch.

Pitch sequencing, therefore, is at the heart of the very sport of baseball, yet it is woefully understudied in current public analysis, because our tools, based on a foundation of unordered sets, are woefully bad at processing and studying sequenced events.

There is a whole industry now dedicated to the statistical analysis of baseball using these set-based SQL tools. But SQL does not have a recency bias clause in its syntax that you can apply to a query. Because these tools don’t handle the ordered data well, they basically ignore The. Very. Core. of the sport: the sequencing battle between pitcher and batter.

Let me say that again: statistical analysis (that we in the public are aware of) takes the most important element of the sport, and ignores it.

It’s like having Newtonian physics without relativity and quantum mechanics. There’s a lot you can do with Newtonian physics, but at the extremes, it begins to break down, because it is ignoring some deeper, more fundamental truths.

If you’re a team that relies on constructing its roster using such statistical analysis, what mistakes are you making by ignoring the most important part of the game?

Belief Without Evidence #3. All high-level sabermetric truths derive from lower-level truths about human biomechanics and psychology

And not vice versa. Things like platoon splits and home field advantage are not Constants of the Universe like the speed of light or the Planck-Einstein relation. The arise from more fundamental truths about human anatomy and psychology.

For instance, once I got in an argument in which I did not believe that Sean Doolittle pitched better to certain catchers than others. The stats did not agree with me, albeit perhaps with a small sample size. But my objection wasn’t to the numbers, adequate sample size or not, it was to the lack of any sort of underlying physical/psychological mechanism where this these numbers could derive from. Sean Doolittle throws 90% fastballs. What the hell difference physically/psychologically does it make what catcher is back there catching it? It’s the same pitch, no matter who is catching it.

I do not consider a sabermetric truth to really be a truth unless there is a biomechanical/psychological foundation upon which that truth can rest, and from which that truth is capable of being derived.

Belief Without Evidence #4. Pitches are paths between states in a Prediction State Automaton

First, a little explanation of automata:

Automata theory is used in computer science to study states. For example, you can look at baseball as an base/out automaton, where before each plate appearance, the base/out combination is in one “state”, and in another “state” after the plate appearance. There are rules that tell you what possible states you can be in before and after a plate appearance.

So, at the beginning of an inning, the baseball base/out automaton is in a {Nobody on, 0 out} state. After the first plate appearance, you will be in one of five possible states:

{Runner on 1st, 0 out}
{Runner on 2nd, 0 out}
{Runner on 3rd, 0 out}
{Nobody on, 0 out} (Batter homered)
{Nobody on, 1 out}

You can’t, after the first appearance, reach a state where there are two runners on or two outs. You have to go to an intermediate state first. There are exactly 24 possible states you can have in this automaton. Each state in this automaton is a two dimensional {base, out} object. And from any of these 24 possible states, there are a limited, finite number of possible following states.

The “automaton” then, defines the what possible states can exist, and the rules by which you can move from one state to another.

Got it?

OK, now to the thing I believe without evidence: I believe that before any given pitch, the batter is in some sort of Prediction State for the next pitch. After each pitch, the batter then moves into a different Prediction State.

I don’t have a clear belief on exactly how many dimensions these Prediction States have. Maybe the Prediction State has three dimensions it:

1. Whether to swing
2. When to swing
3. Where to swing

Or maybe these Prediction States are much more complex, combining the above three states with specific kinds of pitches and movements and locations. It may be expressed by something like this, for example:

{60% expection of fastball, 30% changeup, 10% curve;
80% outside, 10% middle, 10% inside;
60% down, 30% middle, 10% up;
70% in the strike zone, 30% out of the strike zone}

and then if the pitcher throws you a fastball on the lower outside corner for a strike, perhaps you move to a state like this:

{70% fastball, 20% changeup, 10% curve;
85% outside, 8% middle, 7% inside;
70% down, 20% middle, 10% up;
75% in the strike zone, 25% out of the strike zone}

Or whatever. I don’t really know as what the parameters for these Prediction States should be. Is it {pitch type, in/out, up/down, movement/straight, fast/slow} or some other combination of pitch attributes? I don’t know.

And to what extent are these prediction automata more or less universal, or does each batter have his own unique automaton with its own unique rules? Again, I don’t know.

But I do know that if I were to build a technology for analyzing baseball, this is where I would begin, right at the core of the game, the engine that drives the sport: what pitch the batter is expecting from the pitcher, and what happens when the pitch he gets conforms or deviates from that expectation.

In order to unite the quantum and Newtonian versions of baseball analysis, the biophysical and the statistical, any Grand Unified Theory Of Everything Baseball must, in my belief, have some way to handle the Prediction State of the batter.

Belief Without Evidence #5: The quality of a pitch is a function of its speed, location, and movement, and also of the batter’s swing and prediction state

There are a few pitchers, like Aroldis Chapman, who can throw a pitch with such high-quality speed that the location, movement, and prediction state are rather irrelevant. And there are some, like Mariano Rivera, who have such a combination of high-quality location and movement that the speed and prediction state don’t matter much. With pitchers like that, the batter can predict perfectly what pitch he’s going to get, and still not hit it.

But most pitchers do not possess such a high-quality pitch that they can be predictable and get away with it at the Major League level. They need to manipulate the prediction state of the batter in order to succeed.

The less a batter is expecting a certain pitch, the less likely he is to make good contact. But pitching is not just a function of being unpredictable: the pitcher must balance what the Prediction State of the batter is and the batter’s ability to hit it, with his ability to also throw a pitch with good speed, location, and movement.

The complex nature of that 5-dimensional object ( {speed, location, movement, swing, prediction state} ) is what makes baseball so fascinating from pitch to pitch.

So for each pitch, the pitcher wants to:

1. Choose a pitch the batter is likely to predict incorrectly
2. Choose a pitch the pitcher is likely to throw with good speed, location, and movement
3. Choose a pitch which will result in a suboptimal swing path, resulting either in a miss or weak contact
4. Choose a pitch which, if not put in play, worsens the batter’s Prediction State for the next pitch

Belief Without Evidence #6: The quality of an at-bat is a 3-dimensional function

Those three dimensions being:
1. Getting a good pitch to hit
2. Hitting a ball hard when you do
3. Hitting a ball hard if you don’t.

A good pitch to hit is a pitch that (a) he is successfully predicting, and (b) he can get a good swing on. Whether he can get a good swing on a particular pitch depends on what his swing path is.

And again, there are two kinds of predictions: the automatic subconscious one where the batter just reacts to a pitch, and a conscious one where the batter decides beforehand to look for a certain pitch and ignore all others. And the count plays a big role whether the batter can take an approach to consciously look for a particular pitch, or whether he should (with two strikes especially) just let his subconscious react to whatever comes in there.

On the subconscious level, the more the pitcher keeps throwing the same pitch, the more the batter predicts that pitch accurately, and the more likely the batter is to hit that pitch. When pitchers talk about “establishing the inside fastball” for example, this is what they mean: to change the Prediction State in such a way that an inside fastball becomes part of the Prediction State, and thereby necessarily reduces the expectation of a different pitch in the future.

Just because a batter gets a pitch he is predicting, does not mean he will hit it. Most batters have some kind of hole in their swing. Some batters prefer high pitches, others low. Some are vulnerable inside, and others can’t hit the outside pitch well. Some can hit a fastball, but can’t time an offspeed pitch. Others have a slow bat speed and struggle with fastballs, but feast on the slower pitches.

So for each pitch, the batter wants to:
1. Predict a pitch correctly
2. Swing at a pitch that if it lets him approximate his optimal swing path
3. Take a pitch if it would cause a suboptimal swing path (unless 2 strikes in zone)
4. Take pitches out of the zone to move to a better Prediction State for the next pitch
5. If in a 2-strike situation, make contact (foul or fair) on a pitch in the zone

Belief Without Evidence #7: SQL-reliant GMs don’t value the third dimension of #6 enough

In a vast sea of unordered pitches from an unordered group of pitchers, you will get a randomly-distributed plethora of good pitches to hit, so the numbers will all work out in the end. So you acquire hitters based on these vast seas of data, ignoring what the batter does with difficult pitches to hit, because in the long run, they don’t matter much.

But against a good pitcher on a good day who does not give you a good pitch to hit, what do those batters do? Do they hit a ball hard if they don’t get a good pitch to hit?

To me, the biggest difference between the A’s in the playoffs and the Giants in the playoffs is Pablo Sandoval. Because there may not be anyone in baseball right now better than Sandoval who does damage even when he does not get a good pitch to hit. He can turn pitches in the dirt, in his eyes, and/or six inches off the plate into a hit. He’s almost immune to prediction state manipulation by opposing pitchers. And Hunter Pence, though not as extreme as Sandoval, has similar characteristics.

The A’s simply do not pursue those types of players. Players like Sandoval tend to have low OBPs, because they swing at so many bad pitches. Minor leaguers with that profile flop far more than they succeed, so they’re a bad risk to take. But there are times, against a good pitcher on a good day who is simply not giving hitters a good pitch to hit, that it is valuable to have a player who often does damage even with a bad pitch to hit. And those times happen more often in the playoffs.

A technology that used a system of evaluating players in which high-level statistics of player value were derived from a low-level {speed, location, movement, swing path, prediction state} matrix would better identify the true value of such players.

Belief Without Evidence #8: Diversity is Good for Batting Lineups

This belief is related to the belief about the definition of the quality of a pitch, and to the belief of a biomechanical/psychological foundation to all of this. A lineup with too many batters with similar strengths and weaknesses can make it easier for a pitcher to settle into a psychological/mechanical rhythm and mow down such a lineup. A lineup that is diverse (some hit fastballs, some like it inside, or low, some slug, others make contact, etc.) makes a pitcher have to change his approach from at-bat to at-bat. That forces the pitcher to have to make a variety of quality pitches in order to win. It’s harder for a pitcher to win if he has to have multiple pitches working well.

So when I praised the Giants for having Pablo Sandoval, I did not mean that an entire team of hitters like Pablo Sandoval would be ideal. But having one or two guys like him in a lineup with some more patient-type hitters is a good thing.

Belief Without Evidence #9: A lineup without holes scores runs exponentially, not linearly

This is probably the easiest of my hypotheses to disprove. But I have the gut feeling that one guy who is an automatic out in the middle of a lineup can take a rally that might score five runs and drop that rally down to 0 or 1 runs.

I think we saw this play out with the 2014 Oakland A’s. At the beginning of the year, everyone in the lineup was healthy and hitting somewhat near or above expectations. The A’s were just killing it in the pythagorean win column, because they’d get a rally going and that rally would just keep going and going.

But then Josh Donaldson and Brandon Moss started having some nagging injuries, and Moss in particular became pretty much an automatic out for a month or two. Those five-run rallies, once plentiful, almost instantly disappeared. Every rally seemed to be killed by a terrible at-bat in the middle of it.

Almost every team has a hole in the lineup at any given time, someone who is slumping for whatever reason. So for most teams, run scoring appears to be linear. But in those rare cases when everyone is clicking at the same time, their run scoring graph turns like a hockey stick and shoots upward.

The A’s success early in the year depended on the lineup being holeless, and when holes appeared, the whole thing collapsed back from exponential scoring into linear.

Belief Without Evidence #10: A’s fans are magical elves

I’ve been playing in my mind lately with the idea that A’s fans are like the house elves in the Harry Potter stories.

We exist so that others may abuse us. The greatest triumphs of others often comes at our expense. We dress in ratty clothing (stadium). Yet despite this constant abuse, we are fiercely loyal to our master. We attack viciously anyone who dares attack our master. We perform magic (great stadium atmosphere) on their behalf, no matter how awful our masters treat us in return.

If ever we were given clothing (a new stadium) by our master, we would be free of our bondage. Some, like Dobby, desire this, but others would not know what to do with themselves with freedom and wealth. It would ruin the very essence of their being.

I used to be like Dobby, longing for the freedom that a World Series victory and/or a new stadium would bring. But now, I am beginning to feel that the other elves are right — that it is wrong to support S.P.E.W. and long for something that would destroy who we are.

We are meant to suffer, so that other wizards may have their glories. We are elves. Let us be that we are and seek not to alter us.

Because my hands are full. Literally. In each hand, I am carrying a whipped cream pie. I carry these pies with me 24/7, one in each hand, which prevents me from tweeting. I shall carry this burden with me until I find the inevitable person who is wearing both Google Glass and an AppleWatch at the same time, at which time I shall throw these pies at said person for being such a pretentious twit. And then, having completed what I was sent here on earth to accomplish, I shall at long last be satisfied with my life, and I shall immediately thereafter ascend into the heavens.

The End.

(26178) 1996 GV₂ is an asteroid in the asteroid belt between Mars and Jupiter. It is small, so small that scientists can’t tell how small it is, only how brightly it reflects sunlight.

And that is why people who are as dumb as rocks turn into trolls when they get online. They think this is their big chance to be a star. Nope, we see you, but you don’t have any brilliant ideas of your own. You’re just a rock. Go disappear into a catalog, like (26178) 1996 GV₂.

Xenotilapia leptura is a species of fish that lives in Lake Tanganyika in Africa. It is currently in no danger of extinction.

But this will change.

Lake Tanganyika is the second-largest freshwater lake in the world by volume. It is located in the East African Rift, which is being formed by the African tectonic plate splitting in two and drifting apart. Sometime in the next 10 million years, the split will become large enough that a new ocean will form between the two new plates.

What will become of Lake Tanganyika when this new ocean forms in the East African Rift? Will it be incorporated into the new ocean? Will the change be gradual, or catastrophic? Will the salt water from the world oceans suddenly rush into the lake? Or will the saltiness increase very, very gradually?

These are important questions for the future of Xenotilapia leptura. You cannot just plop it into a saltwater ocean and expect it to survive. It needs the saltiness to increase gradually, so that the species has time to evolve with the change.

* * *

It is amazing to think that we can see 10 million years into the future of some other species, but barely see 10 days into the future of our own. Every day a new startup company is born, or within an existing business a new project is launched, with a mission to invent some new technology that will change the world.

Ten days from now, Apple will announce something.

What rough automaton, its hour come round at last, slouches toward Bethlehem to be born?

Will we, as a species, have time to evolve with the change? Or will the change overwhelm us?

* * *

I have been on Twitter now for seven years. There have been murmurs now that Twitter has changed, for the worse, and people are dropping out. Frank Chimero:

Here’s the frustration: if you’ve been on Twitter a while, it’s changed out from under you. Christopher Alexander made a great diagram, a spectrum of privacy: street to sidewalk to porch to living room to bedroom. I think for many of us Twitter started as the porch—our space, our friends, with the occasional neighborhood passer-by. As the service grew and we gained followers, we slid across the spectrum of privacy into the street.

But perhaps Twitter hasn’t changed. It’s just a dumb new ocean, flooding in. We’re the ones who haven’t changed, who haven’t evolved fast enough to survive the new saltwater.

I’ve dropped out of Twitter three times this year. I don’t want to blame Twitter for it. I just have trouble adapting to the changing environment. Twitter for me has become like Fox News is for many senior citizens — it’s entertaining and informative, but it also leaves me bitter and angry and frustrated at the world, 24×7.

True, there are some things worth being angry about. But I can be angry about those things without Twitter. It’s the things not worth being upset about that’s the problem.

I’m just not very good at dipping my feet into that ocean in moderation. It pulls me down deep, every time. And as a result, I become a lousy husband and father in the real world, and my productivity plummets.

When I’ve taken breaks, the anger and bitterness leaves, and everything in my life gets better. I’m happier, the people around me are happier, and I get a hell of a lot more useful stuff done.

I’m taking a long, looooooooong break from Twitter this time. I’m not planning to come back until (a) the bitterness is gone again, and (b) I have a real plan for using Twitter in moderation. Until then, anytime I feel like expressing anything, I’ll do it here, on this blog.

* * *

So long, and thanks for all the fish.

I’ve been watching James Burke‘s series Connections (1978) and The Day The Universe Changed (1985) on YouTube lately. There was one passage that struck me in particular:

“Before 1450, life was intensely local. Most people lived and died in the same cottage, and never went further afield than seven miles. […] Here, in church, was where they got their word-of-mouth news about the mysterious and unreal world, out beyond the forest where nobody ever went. The pulpit was their TV, newspaper, wire service, calendar, landlord, lawyer, teacher, timekeeper, social diary.”

–James Burke, The Day The Universe Changed, Episode 4, “Matter of Fact”

Replace the word “pulpit” above with the word “iPhone”, and think about that for a second. What an amazing technology churches were! The church, once upon a time, was the state-of-the-art communications technology. For people in the Middle Ages, it performed many of the same functions that mobile phones perform for us in 2013.

Around 1439, Johannes Gutenberg invented the printing press, and everything changed. This technology, the church, which contained many different products in one, began having its functions stripped away from it one by one. Now that people wanted to read things themselves, you didn’t have just a single, monolithic technology called “church” anymore. You had churches, and schools. And books, and newspapers, and calendars. And as knowledge quickly started to spread because of the new printing technology, other innovations happened which plucked off more and more functions of the church.

550 years later, in 1989, Tim Berners-Lee invented the world-wide web. The iPhone followed 18 years afterwards, and gravity suddenly reversed itself. All these technologies, which had been blown apart half a millenium earlier, suddenly started consolidating again, back towards a single monolithic technology: the mobile phone.

* * *

Western religions have a linear view of time. They see history as having direction, a beginning and an end. They build empires, like Alexander the Great or Julius Caesar, and never expect these empires to fall. Another great conquest is always coming next.

Eastern religions like Hinduism see history as cyclical. The universe and everything in it comes into being, then cycles out of being, then back into being again. Or as Tim Lott writes about Alan Watts and Zen Buddhism:

The emphasis on the present moment is perhaps Zen’s most distinctive characteristic. In our Western relationship with time, in which we compulsively pick over the past in order to learn lessons from it and then project into a hypothetical future in which those lessons can be applied, the present moment has been compressed to a tiny sliver on the clock face between a vast past and an infinite future. Zen, more than anything else, is about reclaiming and expanding the present moment. […]

For all Zen writers life is, as it was for Shakespeare, akin to a dream — transitory and insubstantial. There is no ‘rock of ages cleft for thee’. There is no security. Looking for security, Watts said, is like jumping off a cliff while holding on to a rock for safety — an absurd illusion. Everything passes and you must die. Don’t waste your time thinking otherwise.

With a linear view of history, church administrators in the west spent a lot of the five and a half centuries following the printing press looking for that old security, never quite believing that their breakup was acceptable, yearning for the good old days when the church was all the technology anyone needed. History is moving in the wrong direction! People aren’t coming to church as much because of these newfangled books! Let’s invest in Baroque art! That’ll wow ’em back into the pews! We have to fix this!

* * *

The popular technology of the day seems to agree more with the Buddhist view that all that matters is the present. As Erick Schonfeld wrote in TechCrunch in 2009:

Once again, the Internet is shifting before our eyes. Information is increasingly being distributed and presented in real-time streams instead of dedicated Web pages. The shift is palpable, even if it is only in its early stages. Web companies large and small are embracing this stream. It is not just Twitter. It is Facebook and Friendfeed and AOL and Digg and Tweetdeck and Seesmic Desktop and Techmeme and Tweetmeme and Ustream and Qik and Kyte and blogs and Google Reader. The stream is winding its way throughout the Web and organizing it by nowness.

Alexis Madrigal thinks, however, that a backlash towards this nowness has begun in 2013.

Nowadays, I think all kinds of people see and feel the tradeoffs of the stream, when they pull their thumbs down at the top of their screens to receive a new updates from their social apps.

[…] And now, who can keep up? There is a melancholy to the infinite scroll.

Wouldn’t it be better if we just said … Let’s do something else? Let’s have the web be a museum or a curio box or an important information filter or an organizing platform.

* * *

Time Magazine named Pope Francis its Person of the year. I’m Lutheran, not Catholic, but I admit I am fascinated by the man. Robert Barron at Real Clear Religion, however, quibbled with Time’s emphasis on the changes he’s making, and wrote this in response:

If I might cite the much-maligned Benedict, the Church does essentially three things: it cares for the poor; it worships God; and it evangelizes. Isolate any of the three from the other two, and distortions set in.

Those three things, here in 2013, are a lot fewer than the long list of things the Church did in 1413. I wonder then, if Pope Francis’ popularity isn’t just about the Pope’s message itself, but also about two linear arrows of history intersecting: a time the Church is ready for a pope to focus the Church on those three things, and also a culture at large that has reached a point where it is ready to hear a message about lasting values.

Perhaps now, in this peak-iPhone/webstream era, people have found out through their own experience that the Buddhists and the Christians each own a piece of the truth: that most things in life are transitory; yet there are a few select eternal truths worth hanging on to. Perhaps mankind is relearning an old lesson: that one should render unto Steve Jobs the things that are Steve Jobs’, and unto God the things that are God’s.

Yahoo Sports remodeled their site this morning, and it’s awful. Mostly, I think, because the new background image on is really distracting and annoying. So I decided to zap it. Here’s how I did it, and you can too:

1. Install the Stylebot Chrome extension.

2. Once you install it, you will get a little “CSS” button on your toolbar.

3. Go to a Yahoo Sports web page.

4. Click the Stylebot “CSS” button on your toolbar.

5. Click “Install Style from Social…”

6. It should show “Loading…” for a second, then bring up “Remove background image from Yahoo Sports by kenarneson”.

You should now see a plain gray background instead of the grass field background.

* * *

I wanted to make it a plain white background like it used to be, but the text on the Yahoo Sports site is now mostly white, so that wouldn’t work. So I made it gray.

I don’t remember the first time I ever saw a video game. I doubt it was as early as 1973. I know my next-door neighbor had an Atari 2600 in 1978, and I had a Mattel Electronics Football game around the same time. I know I went minigolfing for a couple birthdays in between there, and the minigolf place had an arcade. They probably had Pong, if not a few other video games in the arcade. Probably, then, I first laid eyes on a video game around 1976 or so.

So this Random Wikipedia article, 1973 in video gaming, comes a few years too early for me to have any personal memories. As a historical landmark, it’s one year too late. The big year in video gaming is 1972. In 1972, Atari was founded and they produced Pong. Additionally in 1972, Magnavox introduced the Odyssey, the first home video game console.

So 1973 was a period of infancy for video games–after they were invented, but before they became a major force in popular culture. Did the people working on video games back really believe it would later become a huge deal? Or did they assume they were just part of a temporary fad, just trying to figure something out, maybe eking out a living or something if they’re lucky, but not really suspecting they were incubating a baby entertainment industry that would eventually be as big as movies or TV?

And what’s the 2013 version of video gaming — the rough beast that’s just a baby now, barely even noticed, but one day will grow to be king of the world?

Today, the Random Wikipedia Wheel of Fortune sends us to visit the SS Mormacmail. SS Mormacmail actually the name of four different cargo ships built during World War II. The first three of these ships were converted to escort carriers and renamed.

Escort carriers in WWII were typically just normal cargo ships with a flight deck built on top of them. They were slower and had less armor than regular fleet carriers, but they were much less expensive to make. They were used, therefore, mostly as their name suggests, to provide air cover while escorting convoys.

All of which is quite fascinating to me because my father worked on aircraft carriers as an electronic technician when I was growing up. However, he didn’t work on small carriers such as these; he worked on “supercarriers” like the USS Enterprise (CVN-65), the kind of ships that were crown jewels of the fleet. But for every glorious USS Enterprise there are a dozen cheap clunky USS Stargazers, doing the more ordinary work that needs to be done.

* * *

As an aside, I was struck by this sentence I read this morning, linked to by Rod Dreher, written by Anthony Bradley:

For too many Millennials their greatest fear in this life is being an ordinary person with a non-glamorous job, living in the suburbs, and having nothing spectacular to boast about.

Which rather fits the theme that the Random Wikipedia Wheel of Fortune seems to be revealing. We live in a culture which tells us the greatest attribute a human being can possess is fame, and with it, glory. I feel like I have absorbed this message too much myself. It’s an unhealthy mindset to have, because the vast majority of humanity will fail to achieve it, and it will leave you unhappy in the end.

In a healthy culture, we ought to dismiss Fame. Honor, on the other hand, is both virtuous and achievable. We ought to be honoring Honor itself.

* * *

The first SS Mormacmail was purchased by the US Navy in 1941, converted to an escort carrier, and renamed the USS Long Island. Here is a picture of it at Pearl Harbor in August 1942, with the sunken USS Utah to the left, and the larger carrier USS Hornet (CV-8) to the right.

Because so much of the US Pacific fleet was destroyed at the Battle of Pearl Harbor, the USS Long Island was pulled into service in 1942 during the Guadalcanal Campaign. However, once more capable ships had been built, the USS Long Island mostly spent the rest of World War II transporting troops and cargo and operating training missions.

By the way, the Hornet in this picture is not the USS Hornet (CV-12) that currently sits as a museum a few blocks from my home in Alameda, CA where the USS Enterprise and other old nuclear wessels used to dock. The Hornet pictured above was sunk in three months after this photograph was taken in the Battle of the Santa Cruz Islands. The CV-12 was named to honor the CV-8, commissioned a year later in 1943.

* * *

The next two SS Mormacmails were both sold to the British Royal Navy. The first was rechristened the HMS Battler, and the second became the HMS Tracker. The HMS Tracker provided antisubmarine support during the before, during and after the D-Day invasion.

* * *

Finally, a version of the SS Mormacmail was built where the name stuck. It launched in 1946, and served as a cargo vessel until being decommissioned in 1971. It appears to have spent its career shipping cargo between the US, Sweden and South America.

* * *

So it was for all four versions of the SS Mormacmail: not a famous existence, but an honorable one.

Jason Wojciechowski is finding it difficult to watch A’s games in this pennant race, because any failures by his favorite team are too painful. He wonders:

Given my strong suspicion that we only get one shot at life, is it better that I spend my remaining years experiencing as broad a range of emotions as I can reasonably give myself? Do the lows make the highs sweeter such that they’re worth it as a simple matter of arithmetic?

I have been similarly tempted to look away. I’ve found over the years that I’m actually a happier person when the A’s are not competitive. Winning breeds expectations, and the more your team wins, the more you expect them to win. But happiness research seems to suggest that the key to happiness is low expectations. I suspect, therefore, that unless the A’s actually win the World Series, our happiness as A’s fans actually peaked around early August, when we started to realize the A’s were a good team capable of winning, but before that winning had become so commonplace that we began to expect it.

However, I enjoy baseball on more dimensions than just winning. The game the A’s lost on Friday against the Yankees was a beautiful ballgame aesthetically: it was a dramatic game where both teams played crisp, solid baseball with good pitching. I enjoyed it immensely. Saturday’s game, however, was awful: the A’s lost, but both teams played terribly, the pitching was horrible, the defense was shaky and even the umpires got into the act with several mistakes. And that was just in the first inning before I turned it off, and went out to do something else with my Saturday. The game kept on like that, and ended up lasting almost six hours, without me. I’m glad I (mostly) missed that one.

The next three games have been equally dramatic, but somewhat in-between aesthetically. Last night’s game, for example, featured a horrible error by Brandon Moss that cost the A’s two runs, followed later in the game by a fantastic catch by Moss that saved the A’s three. For me, the drama would be much easier to watch if the A’s were not playing so sloppily.

I don’t always watch pennant race baseball, but when I do, I prefer errorlessness. Play crisply, my friends.

* * *

If you want to innoculate yourself from the pain of your favorite team losing, you can consume your sports like Will Leitch recently did, by entering the RedZone. Leitch describes his first experience watching NFL RedZone on the NFL Network:

RedZone is a commercial-free, seven-hour block of every exciting play in every NFL game all day. You see every scoring opportunity, you see every two-minute drill, you see every moment of fantasy relevance. The general consensus: You’ll never watch football the same way again.
…
On RedZone, events happen and are then forgotten in the chaos. Something that happened three minutes ago is distant history.

That, I suppose, is both the blessing and the curse of living in this information age. You can’t tell a teardrop from a raindrop in a hurricane.

* * *

Felix Salmon has an article about journalism in the midst of such massive amounts of instant information. Being able to find that teardrop in the hurricane in basically the job of the modern journalist.

But if I were hiring, the first thing I’d look at would be the prospective employee’s Twitter feed. What are they linking to? What are they reading? If they’re linking to great stuff from a disparate range of sources, if they’re following smart people on Twitter, if they’re engaged in the conversation — that’s hugely valuable. More valuable, in fact, than being able to put together an artfully-constructed lede.

The tricky balance there is to be able to both swim in the flood of information to gather the data, but to step out of it long enough to gather your thoughts.

* * *

To celebrate the 50th anniversary of the Jetsons, the Paleofuture has started a series to look at all 24 episodes of The Jetsons one-season run.

Thanks in large part to the Jetsons, there’s a sense of betrayal that is pervasive in American culture today about the future that never arrived. We’re all familiar with the rallying cries of the angry retrofuturist: Where’s my jetpack!?! Where’s my flying car!?! Where’s my robot maid?!? “The Jetsons” and everything they represented were seen by so many not as a possible future, but a promise of one.

The deluge of information we now experience in the real future thanks to the Internet and television is vastly different from the one we imagined when we grew up watching the Jetsons. The Jetsons’ future seems so much simpler than ours. So when we feel overwhelmed, our fight-or-flight response kicks in and we want to reject it all and run away.

As Jason says in his post above about turning off the A’s in this tense pennant race: “My gut the last few weeks appears to have made the latter choice for me, leaving me a little more time to spend with my cats, my wife, my books, and my thoughts.” Sometimes, you have to connect to the basic human needs that persist no matter what century you live in. And therein lies the dilemma of the real 21st century George Jetson: to know how to both live in the 21st century, and how to step away from it. It’s not easy.

The Space Shuttle Endeavor flew over Alameda this morning, so I went out to the rock wall on the shoreline near Encinal High School, a couple of blocks from my house. I took this video:

I couldn’t find an exact itinerary this morning, all I knew was that it was supposed to fly over the bay sometime around 9:30. It was actually more like 10:15 before it flew over. I remarked to my middle daughter, who had the day off from school and came with me, that it was like Charlie and the Chocolate Factory, where they keep opening candy bar wrappers, hoping it will be a golden ticket, only to find that it was just a bar of chocolate. Every time we saw an airplane on the horizon, we would wonder if it was the shuttle. But it was only an simple airplane, participating in the mere miracle of human flight.

Finally, an airplane with a very odd-looking silhouette appeared low in the sky near the Oakland Airport, and I immediately knew that this must be the shuttle. Here it is as it flew past Encinal High School:

Then it headed north a bit, then turned and flew over San Francisco. As it got to about Candlestick Park, it turned and headed straight towards us. Then it turned again, to make one more pass over San Francisco. Here it is as it passed close to us.

Then it flew over San Francisco one more time, then headed south towards Moffett Field, where it disappeared into the hazy morning sky.

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.

As Apple announces the iPhone 5 today, I want to make a confession. It’s a bit embarrassing for someone like me who has spent his career in high tech, but here goes: I don’t have a cell phone.

At first, my reason was this: I lived and worked and played on a very flat island with no tall buildings, so coverage was awful. I had reception in only one room of my house, not at all in my office three blocks away, and spotty reception where I play indoor soccer. I spent 95% of my time at those three places, and I wouldn’t be getting what I was paying for. When I went out somewhere that coverage was better, I’d borrow my wife’s cheap pay-as-you-go phone, and my needs were met.

The cell phone service providers made a mistake. They gave me an opportunity to learn that I could live without them.

* * *

This is the image of an industry suddenly collapsing.

Why did the newspaper industry suddenly collapse like that? Because it got hit from two sides at once by the Internet. Craigslist and eBay took away their classified ad business, while blogs and online news sources directed their readership elsewhere for the same information. Newspapers might have been able to handle a one-front battle, but a two-front battle was catastrophic.

But there’s something else that hurt the newspaper industry: the indirect nature of their feedback loop. It’s a business model that provides a service to one group of people, while taking money from a different group of people.

The best kind of feedback for a business is revenue. If your revenue increases or decreases, you’re going to notice. But when the users of your product aren’t providing the revenue for your product, your feedback loop has a natural delay to it. The people who give you revenue might lead you to innovate (or not) in a direction your users won’t like, and you won’t notice that you’re making a mistake because it takes a while for that problem to reach your bottom line. So you react too slowly, and that slowness can be fatal.

* * *

In fact, all businesses that rely on advertising have this problem. Their users want one thing, and the revenue generators want something different. So if a company like Facebook starts alienating their customers in an effort to maximize their revenues, they may find themselves not just the subject of an Onion parody, but ruining their business before the bottom line has time to let them know they’ve made a mistake.

* * *

Amazon CEO Jeff Bezos is a very smart man. He understands this problem. He knows that the key to keeping ahead of the rapid pace of high-tech change is to master the feedback loop between what his customers want next, and what his company makes next. That’s why in his Kindle press conference last week, he laid out this doctrine:

Think about the major players in high tech right now: Microsoft, Google, Facebook, Twitter, Amazon, Apple. Which of these has their revenues most directly aligned with what their customers want? It’s probably in roughly this order:
Amazon/Apple
(gap)
Microsoft
(gap)
Google
(gap)
Twitter/Facebook.

Amazon and Apple sell most of their products directly to their users. When their customers buy something they make, they know the product is good; when they don’t buy, they know immediately they made a mistake. Microsoft doesn’t sell directly to users– they sell to distributors and OEM manufacturers, so there’s noise injected into their feedback loop, and they land just a little lower on this spectrum. Google sells ads, but their ads are often directly related to what the customer wants; if someone is searching for jeans, they get an ad for jeans. Sometimes the ad happens to be exactly what the user wants.

Twitter and Facebook, on the other hand, need to inject their ads into an environment where the users wouldn’t really want to see ads at all if they didn’t have to. This leads to customer dissatisfaction, expressed not just in the Onion parody above, but also in a real-life alternative social networks like App.net who are trying to sell directly to users.

* * *

My favorite product of all is probably Major League Baseball. I consume a lot of Major League Baseball. But MLB is going in a very tempting, but dangerous direction. When MLB began, a vast majority of their revenues came from the product their users consume. They sold tickets to the games, and that’s how they made their money. But more and more of MLB’s revenues are coming from indirect sources.

At a local level, if you’re a team like the Oakland A’s, who play in an antiquated stadium that doesn’t generate a lot of revenues, a big proportion of your money comes from TV and league-wide revenue sharing. So you can do things over a number of years, like threaten to move away and trade away favorite players, that damage your brand but aren’t directly noticeable in your bottom line. Ownership may not even know how much their fans hate them, because their loyalty to their local team keeps them around despite their dissatisfaction. But eventually, there may be a straw that breaks the camel’s back. Los Angeles Dodger fans may have hated owner Frank McCourt for years, but it was only in the last year of his tenure that the dissatisfaction actually became truly noticeable in attendance figures. The feedback loop in baseball has quite a long delay.

In recent years, baseball’s misalignment problem has accelerated almost exponentially. Like the newspaper industry, the source of this change is new technology. Unlike the newspaper industry, however, the change has caused MLB’s revenues to increase, not decrease, dramatically.

The reason for this change is twofold:

1. The DVR allows people to skip through commercials on TV. This makes live events, which people can’t skip through, a much more valuable delivery mechanism for advertising.
2. Internet video allows people to watch television shows and movies without subscribing to any sort of cable or satellite TV service. Cable/satellite may or may not be shedding customers at the moment, but it’s certainly not growing much, and without sports would almost certainly be shrinking. This makes sports networks extremely important to cable and satellite providers: without them, most people will eventually learn to do without cable TV, and just get all their content from the Internet.

So this sets up a strange mismatch between what MLB customers want, and what their revenues tell them to do. MLB fans want to watch their favorite team on whatever device they prefer. But MLB’s revenue stream is depending more and more on their customers NOT being able to watch their team over the internet, forcing them to watch on TV.

MLB’s revenues come less and less directly from baseball fans, and more and more indirectly, from TV networks and cable/satellite providers.

This causes MLB to lose control over the customer experience of their fans. If a TV network and a cable provider can’t come to an agreement on price, for example, Padres fans can go a whole season without being able to watch their team on TV. And if not all TV networks are available on all cable/satellite services, fans have to scramble around to watch the games they want.

Or, fans just go without. And what does that do? It ends up teaching them that they can learn to live without your product. That too, may not be noticeable right away, until it snowballs too late for you to do anything about it.

* * *

But you can’t really blame MLB, can you? If you’re the Los Angeles Angels and someone wants to pay you $3 billion dollars over 20 years for your TV rights, do you turn that down? No, probably not.

In expectation of an even larger payday than the Angels got, the Los Angeles Dodgers recently sold for $2.1 billion. Given that the estimated value of the Dodgers just a year before that was about $800 million, over 60% of the value of the franchise lies in that regional TV deal.

But think about that for a second. The new owners of the Dodgers spent $1.3 billion dollars on a business model that:
(a) depends almost entirely on another industry that isn’t growing, and would be in steep, steep decline without your industry. If either one of your industries catches a cold, the other one will necessarily start sneezing.
(b) puts your industry in a complete misalignment with your customers, requiring you to prevent your customers from consuming your product in the way they’d prefer, distancing yourself from the revenue feedback loop, making it more difficult to know if you’re doing any long-term damage to your product, and where you need to improve.

The new Dodger owners obviously didn’t care. Maybe they didn’t think about these risks. Or maybe they did, and thought the math worked anyway. Or maybe they considered it, but they thought they could sell the team to someone else before the whole house of cards fell in, like an investor in a Ponzi scheme who doesn’t think he’ll be the one who ends up being the victim.

Who knows. But me, I wouldn’t touch a business model like that with a 10-mile pole.

I’m sure my friends who work at Apple will have better Steve Jobs stories than this one, but this the one I’ve got, and this is the day to tell it.

Back in August of 1996, I helped found a company called Intraware. We started the company on the basic idea of being a reseller of web software to corporations. We also wanted to eat our own dog food — to use the web software we were selling to run our business efficiently.

The problem was, back in late 1996, all this software sucked. I was looking for some software, any software, that I could use as a platform to program our corporate web site with, and I literally could not find anything that I could actually get to do what I wanted it to do.

So during this process of searching for a functioning web programming environment, I went to a conference at the Moscone Center in San Francisco. I don’t even remember what the conference was, but I do remember there were a ton of web software companies there with booths and stuff.

And at some point during this conference, Steve Jobs was giving a presentation. This was during the Jobs’ wilderness years away from Apple. He was presenting the latest stuff that his company at the time, NeXT Computers, was working on.

I decided, what the hell, I’ll check out. I had already given NeXT’s WebObjects a look-see and rejected it. I thought it was way too complicated with too big a learning curve for our needs, plus their code generated the longest, ugliest damn URLs I had ever seen. (Which was odd, since Jobs’ companies otherwise never made anything ugly.) But maybe I’d learn something new.

Ten years later, whenever Steve Jobs gave a presentation, it was the hottest ticket in town. But back in 1996, I just showed up to his presentation, wandered in, and found a seat somewhere around the third row, and sat down to enjoy the show.

I honestly can’t remember a damn thing he presented. I do remember his stage presence, though. And then this: about 3/4 of the way through the presentation, he stopped to give an aside. “By the way,” he said (I’m paraphrasing it from memory here), “we’re looking for distributors for our products. So if you know anyone interested in distributing our stuff, please contact us.”

Looking back on that, it’s pretty funny. Can you imagine Apple begging for distributors? But that’s where NeXT was at the time, having trouble getting their foot in the door of corporate America.

And, as it so happens, the problem that NeXT was having was exactly the problem that Intraware was founded to solve. So when I got back to the office, I told our people, and they contacted Jobs’ people, and meetings started to happen. And then, not too long after that, there was an agreement.

Part of the agreement was that in exchange for selling NeXT products, we would get free use their software, and free training. So for a week in early December of 1996, I spent a week at NeXT headquarters, taking classes in how to program using WebObjects. I remember getting a tour of their very nice offices. We walked by Jobs’ office at one point. He wasn’t there.

So anyway, everything was ready and lined up for Intraware to start selling NeXT products after the new year except crossing the t’s and dotting the i’s on the final contract.

And then, on December 20, 1996, Apple bought NeXT. Steve Jobs returned to Apple.

And NeXT didn’t need no steenkin’ distributors anymore. Sorry, guys, deal’s off.

So we never sold any NeXT products, and we never used any either. Well, except the ones that later became part the MacOS. All I had left to show for that week I spent at NeXT was this little story.

But hell, if Intraware had to get shafted so that the rest of the world could enjoy the fruits of Steve Jobs’ labors at Apple over the following fifteen years, it was worth it. I’d happily offer up that sacrifice all over again. Rest in peace, Mr. Jobs. You were an inspiration.