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.

Back on the old Baseball Toaster, I wrote 8,320 entries of various sorts.

I recently surpassed that number of posts on Twitter, and I have now reached my 10,000th tweet.

I wanted to do something special to commemorate the milestone, so I dug something up out of my old bag of tricks, and made a slideshow of my Top 30 2012 Vacation Photos and Baseball Player names.

Check it out.

* * *

If you enjoyed those, here are some older, similar slideshows built on outdated technology:

• 2003
• 2006
• 2007

Yesterday, I mentioned in passing how I enjoy baseball on two levels: one level in rooting for my team, and another in the aesthetic quality of the game. The day before, I defended the idea of cross-pollinating new scientific ideas with older fields of human endeavor, to see what comes out of the mix. So today, let’s make a new hybrid.

How can we explain the psychological attraction in rooting for a team? Why, when we’re watching two teams that we have no previous attachment to, do we often find ourselves rooting for one team or another anyway? And how is this different or separate from the aesthetic joy of watching a game?

* * *

As I write this, I am watching Ian Kinsler bat against my favorite baseball team, the Oakland A’s. On the rooting level, I want him to fail and flail badly. But on an aesthetic level, I admire Kinsler. His at-bats, the way he takes bad pitches and fouls off good pitches until he can get a good pitch to hit, are probably the most consistently good at-bats I’ve seen from any player since Rickey Henderson. If our enjoyment of sports were only about rooting interest, I should be incapable of appreciating Kinsler at all. If our enjoyment of sports were only aesthetic, I wouldn’t have a reason to want to see him fail.

Can baseball fandom be fully expressed in a mere two-dimensional chart, with rooting on the x-axis, and aesthetics on the y-axis? No, of course not. For instance, suppose the A’s pitcher were Bartolo Colon. Colon was suspended in August for performance enhancing drugs, but let’s say he’s served his suspension and now he’s pitching. Do I still root for him to succeed? Yes, he’s on my favorite team. But now there’s a moral dimension on the z-axis added to the mix, too. We can go on. Fandom is complex.

* * *

But still, we want to talk about it, so we need to model it. Do we need modern science to do so? Not really. For example, Aristotle, addressed such issues over two millenia ago. Here’s a paragraph on Aristotle’s aesthetics, from a 1902 version of Encyclopedia Britannica:

Elsewhere he (Aristotle) distinctly teaches that the Good and the Beautiful are different (heteron), although the Good, under certain conditions, can be called beautiful. He thus looked on the two spheres as co-ordinate species, having a certain area in common. It should be noticed that the habit of the Greek mind, in estimating the value of moral nobleness and elevation of character by their power of gratifying and impressing a spectator, gave rise to a certain ambiguity in the meaning of to kalon, which accounts for the prominence the Greek thinkers gave to the connection between the Beautiful and the Good or morally Worthy.

Not sure if Aristotle meant Good and Morally Worthy were separate things or the same, but I’ll assume they’re separate. So applying Aristotle to my example above, the A’s are Good, Ian Kinsler is Beautiful, but Bartolo Colon is Morally Unworthy.

* * *

Aristotle’s three dimensions are a kind of model of this aspect of human nature. And since this model is still being discussed 2,000 years later, we can certainly say that this model has a certain level of usefulness. But does this model accurately map to the actual structure and organization of the human brain? Can we explain this structure in terms of evolution, that there were some sort of selective pressures which led to this behavior?

Aesthetics and morality are huge subjects, so I’ll pass on those in this blog entry, and just focus on the rooting aspect.

Group behavior has always been a bit of a tricky subject for evolutionist to explain. It’s easy to explain selfish individual behavior: it’s behavior that’s directed towards passing your genes on to the next generation over the genes of your rivals. The prevailing explanation for most of the last 40 years or so has been kin selection: unselfish behavior towards your kin helps pass more of your genes along to the next generation. Any sort of unselfish behavior toward people who are not your kin is just sort of a side effect of unselfish behavior towards your kin.

But that’s an unsatisfying explanation, particularly if you apply it to team sports. Why do I go to the Coliseum, dress up in green and gold with thousands of other A’s fans, 99.999% of who are not my kin, and cheer the team together with them? It’s really hard to make a convincing argument that I’m doing it to pass my genes on.

The alternative explanation is group selection. Group selection is a theory that fell out of favor in the 1960s, but in recent years has been making a comeback. In his recent book, The Social Conquest of Earth, E.O. Wilson argues strongly in favor of group selection as an explanation for human social behavior.

Under group selection theory, human evolution happens in two dimensions. There’s a selfish dimension that pushes individuals to promote their genes over others within their group. But there’s also a dimension that pushes us to behave in ways to promote the genes of the group over the genes of rival groups. In times of war or drought or famine, those groups who behave in ways that encourage cooperation instead of selfishness survive to pass their genes on more than the groups whose individuals behave more selfishly.

Under group selection theory, the behavior we see in team sports makes much more sense. We naturally form emotional attachments to our groups, because we were evolved to do just that. As E.O. Wilson points out, every single animal that exhibits social behavior (including the one Wilson is expert in, ants) evolved its social behavior to protect and defend a nest. So we root, root, root for the home team, and find it extremely irritating when invading Yankee fans come into our home nest and chant for their team, instead. The joy we feel when our group wins, the pain we feel when our group loses — those are emotions that evolved in our brains to promote the genetic survival of our groups.

* * *

Note I said “our groups.” Jason Wojciechowski has an article today (Baseball Prospectus, $ required) on the use of the word ‘we’ in reference to team sports. Is it appropriate for fans to use the word “we”, or should that be limited only to the players on the team? Jason tries to define that line somewhere in along the lower level employees of the team. I don’t think that works (which Jason ultimately acknowledges).

Former Baseball Prospectus writer Kevin Goldstein used to rail against fans using ‘we’ on Twitter all the time. At one point (which I can’t find now — Twitter search sucks) — he argued that you don’t say ‘we’ to refer to your favorite band, so why should you do so for your favorite team?

I strongly disagree with Kevin here. A band is different from a team. You like the band primarily because of the aesthetic experience it provides you. But as we’ve seen here, the aesthetic experience is only a small part of the experience of watching baseball. Sports are the most popular activity on earth right now not because they provides an aesthetic experience alone — but because they have gone beyond that and tapped into the a primal root of human evolution: the network of emotions that group selection has hardwired into us.

The reason professional sports is a profession at all is because it creates the feeling of ‘we’. That feeling is the main point of team sports. We-ness is the product.

To have a business that sells a product, we, and then to deny those customers the use of the very word that best describes the product–that’s madness.

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.

Early in my life, I really didn’t have any sort of vision for a career. I just kind of drifted towards whatever opportunities came to me. I had an aptitude for computers, partly because my dad, who was an electronics technician, understood that they were the Next Big Thing. In 1980, he bought a TI-99/4, hoping that I would fiddle with it and learn from it. I did. And so as I grew up, the opportunities that fell into my lap happened to be with computers, because whenever there was some computer stuff that needed to be done, I seemed to be the guy who could figure it out.

Then in 1994, I was asked to set up a web server. Immediately, I knew. It was like walking up a big hill and just staring at your feet the whole time, and then suddenly you reach the top, see the view, and you suddenly realize the world is a whole lot bigger than the size of your feet. The Internet was going to be huge. It was going to be exciting. I decided I would bet my career on it.

I was far from the only one who understood that the Internet was a Big Deal. Looking back on it now, it’s clear that I was right THAT the Internet would be huge. It’s also clear that neither I nor anyone else had any idea whatsoever HOW it would be huge.

And so the dot-com bubble came and burst, and there were plenty of Pets.com and Webvan.com examples, where my generation made all sorts of big bets on the THAT, and completely missed on the HOW. The Internet would indeed change our lives, but it wasn’t going to be by giving us new ways to sell dog food.

* * *

About 10 years ago, I came to a similar epiphany with neuroscience. I had taken a class at UC Berkeley in the late 80’s that was primarily about aesthetics. The class asked, what made this work of art a classic, but that one forgotten? The question stuck with me for years, but I never could find an answer that made any sense to me. But one day in the early 2000’s it struck me that the answer wasn’t in the artwork, it was in the brain’s interpretation of the artwork. So I googled the word “neuroaesthetics”, wondering if there was such a thing. It turned out there was an International Conference on Neuroesthetics was being held in Berkeley just a few months later. I decided to attend.

I discovered that neuroaesthetics is a baby science, where everyone, including me, was excited THAT we can try to understand art from a scientific point of view, but at the same time, a science where no one really has any clue as to HOW understanding the brain will help us understand art. It seemed to me like looking at a jigsaw puzzle without knowing what it’s really a picture of yet. You start out by looking at this detail and that one, and seeing if any of the pieces fit together at all.

It’s taken about 10 years, but now people are trying to take this information and attach it to their existing models of human activity, to see how this changes the picture we thought we were looking at. Some of these attempts will probably turn out to be the equivalent of attaching the Internet to dog food. But we don’t learn that these things don’t work until we try and fail. Watching this process unfold is as interesting to me as watching the dot-com craze play itself out.

And like any craze, the bubble will eventually pop. Perhaps the first sign of that pop was when the leading journalist covering this neurofever, Jonah Lehrer, was found guilty of various forms of plagiarism. Since then, there has come a natural backlash against trying to apply brain research to all these forms of human activity. The most scathing attack came a couple weeks ago by Steven Poole in the New Statesman:

An intellectual pestilence is upon us. Shop shelves groan with books purporting to explain, through snazzy brain-imaging studies, not only how thoughts and emotions function, but how politics and religion work, and what the correct answers are to age-old philosophical controversies. The dazzling real achievements of brain research are routinely pressed into service for questions they were never designed to answer. This is the plague of neuroscientism – aka neurobabble, neurobollocks, or neurotrash – and it’s everywhere.

Indeed, there are flaws with many of these models that use brain studies for supporting evidence. I’m especially skeptical of those that use brain scans that show the brain “lighting up” in response to this or that stimulus. That’s like trying to understand how a computer works by making note of when the hard drive makes a noise when it spins. It can tell you a little bit about how a computer works, but not nearly enough to build an accurate model from.

I also am suspicious of any model that claims that there are “4 kinds of X” or “7 different Y”, such as Jonathan Haidt’s five six moral foundations. In computer programming, there’s an axiom that you design for cases of 0, 1 or N. You make sure your program can handle it when there’s no data. If there’s one specific thing you’re trying to solve, it’s OK to write something that handles that one specific case. But if you’re going to be handling a number of cases that’s above one, then you abstract your program to a level that can handle ANY number of cases, not just the number of cases you know about. Because otherwise, any time some new situation comes up, you have to write a whole new program. So I find it hard to believe that our brain has wired these specific six moral foundations into our brains, and only these six.

So Poole has a good point. We really don’t know enough about the brain yet to be drawing any grand conclusions from the information with a lot of confidence.

* * *

“Essentially, all models are wrong, but some are useful.”
—George Box

But at the same time, if we don’t use what little knowledge of the brain we have, we’d still be asking and trying to answer the same questions about ourselves. Only we’d be doing it without this added scientific information. What we had before this explosion in brain research in fields like aesthetics was not really a science at all. It was mostly just academic jargony humbug.

It’s like condemning the entirety of the Internet because Webvan.com was a disaster. Yes, there were a lot of crap businesses at the beginning of the Internet, and there are a lot of crap theories at the beginnings of neuroscience. But that’s part of the process. Until we can exactly replicate a human brain from scratch, everything is just an imperfect model.

Some of these models will be more useful than others. Today’s models may be deeply flawed, but they’ll be less flawed than yesterday’s. And upon a few of these models, the Googles and Facebooks and Twitters of neuroscience will be born, the models of the human mind that we find truly useful. I see no reason to give up on that vision.

In between shows, I went backstage to grab some food. One of the volunteers came up to me and said, “Hey, Ken, the lighting director is looking for you.”

I wondered why. Had I screwed up? I was a rookie at operating a spotlight, it’s entirely possible that I didn’t understand something correctly during the first performance, and they wanted me to get it right for the next show. Lighting was an element of the performing arts that I had never given any thought to, until one day earlier. Now I was trying to learn on the fly: what is the meaning of quality in the field of stage lighting?

I went and found the lighting director. Fortunately, I hadn’t screwed up. “We’re adding a new transition in the second show, after the broom act, ” he explained.

* * *

“Transitions are the subtle in-between details that we as human beings actually connect with and the reasons we fall in love with something rather than simply like something.”

—Brendan Dawes

Brendan Dawes has an interesting post about transitions in design on his blog. His thought is that the transitions between states of usage is the thing that makes the difference between a product that is functional and a product that is beautiful. A commenter named Robert Turrall added an excellent example of this idea in action:

“I remember having discussions with an industrial designer a few years ago about why interior lights in cars that dim gently after you’ve closed the doors go towards the perception of the car itself. BMWs had them, as did other more expensive cars, and this was one of the features that really made the car “feel” exclusive and expensive. Other cars had lights that just switched off abruptly – and they immediately felt “cheap”, almost on the basis of this alone.”

—Robert Turrall

There is likely almost no difference in manufacturing cost between a light that turns off abruptly and a light that turns off slowly. But little details like that can be the difference between cheapness and luxury, between amateur and professional.

* * *

I have operated plenty of car lights in my time, but until a month ago, I had never laid hands on a spotlight. I was called on to operate one of the two spotlights at Circus for Arts in the Schools, an annual fundraising circus show put on by professional circus artists to raise money for arts education.

The show is the brainchild of my friend Jeff Raz, a veteran circus performer who, among other things, played the lead role in Cirque du Soleil’s Corteo, and founded the Clown Conservatory, the only full-time clown training program in the US. Jeff is very well connected in the circus industry, so he manages to get some really amazing acts to come donate their time and skills for this cause.

Jeff recruits the acts and directs the show, while his wife and my wife co-produce it. And I…well, I do whatever I’m asked to do.

* * *

“Being a father, you’re not really the star of the show, the starting pitcher, the cleanup hitter, what have you, but you may be called upon at certain times to step off the bench and into the spotlight. You don’t have the uterus or the boobs or the 500 career home runs or the 300 wins but you still might be called upon to perform a small but necessary duty successfully. You can carry a car seat out to the car. You can change a diaper half-decently. Maybe once in a while you can get the kid to sleep. You are the pinch-hitter.”

—Josh Wilker

For this year’s circus, I was asked not to step into the spotlight, but to hold onto it. The lighting director gave me a crash course in how to operate the device. (I learned that in theaters, unlike in cars, turning a spotlight on and off quickly is a signal of high quality, and doing so slowly is considered “cheating”). And then we rehearsed.

In preparations for two 75-minute shows on Sunday, we practiced for five hours on Saturday night, and then another two hours on Sunday morning. Interestingly, we did not rehearse the actual circus acts in the show. Those were simply assumed to be ready to go. For the most part, the only thing we worked on were the transitions between the acts, and between various lighting and sound cues.

* * *

A show with acrobats and clowns consists of, as Jeff Raz says, “the superhuman and the supremely human.” If you had a show with just acrobat after acrobat after acrobat, your mind would quickly become numbed by the superhuman feats of these performers. That’s where you need to bring in the clowns.

Clowns get a bum rap in today’s culture, thanks to some bad horror films and a few other choice clichés. But after being involved with this annual circus for seven years, and having seen some truly top-notch artists at work up close, I’ve really grown to appreciate the art form.

The clown’s role in a circus is not merely to make you laugh. The clown is there to serve as the transition between acts in the show. They bring equipment onto the stage, and they take it off. But perhaps most importantly, they allow your mind to continue to enjoy the superhuman nature of the acrobats by reminding you of what it is like to be a normal human, by acting “supremely human”.

* * *

The new transition was inserted following an act by Matt White, who dances with a broom reminiscent of Fred Astaire’s hat rack. As soon as the broom act was over, I needed to find the clown in the wings. The clown would then turn on a fully functioning vacuum cleaner, and I had to follow him with the spotlight as he tried to dance with the vacuum cleaner across the stage.

It’s probably the oldest clown gag in the book. The clown earnestly tries to succeed like the act before him, but focuses on the wrong element of the act to emulate. It’s not the cleaning tool that is the source of the quality in the performance.

If you or I were thrust out on a stage and told to emulate Fred Astaire, we would probably fail miserably. Not because of one huge mistake like choosing the wrong prop to dance with, but by a thousand little things that we, as amateurs, simply do not understand.

By distilling these thousand little errors into one big error, the clown points out our own human flaws: we recognize quality when we see it, but recognizing is not the same as understanding.

* * *

What a piece of work is a man! how noble in reason!
how infinite in faculty! in form and moving how
express and admirable! in action how like an angel!
in apprehension how like a god! the beauty of the
world!

— Shakespeare, Hamlet, Act II, Scene II

Wanting to succeed is human. Failing to succeed because we don’t understand the elements of quality is supremely human. Persisting through those failures until we do understand — that is what redeems us.

A good circus is not just a series of good acrobats and good clowns. It’s the two working in concert to create something greater than the sum of its parts. It’s an expression of the entire human experience, moving from the innocent curiosity of childhood to the godlike comprehension of adult mastery. The result is an uplifting feeling of possibility — that we humans can get past our lack of understanding to accomplish amazing things — that makes so many people leave the circus show with smiles on their faces.

* * *

Later that night, when we got home, my four-year-old daughter was inspired. “I’m going to put on a show!” she declared. She went into our pantry, and pulled out a mop. “Watch me! Watch me!” Then she and the mop danced in circles all around the living room.

Alva Noë has an op-ed piece in the New York Times in which he rips into the young science of neuroaesthetics:

What is striking about neuroaesthetics is not so much the fact that it has failed to produce interesting or surprising results about art, but rather the fact that no one — not the scientists, and not the artists and art historians — seem to have minded, or even noticed.

Well, I minded and I noticed, but I’m also no one. I’m not a scientist or an artist or an art historian. I did, however, attend the a few of the initial international conferences on neuroaesthetics. But even though I am deeply fascinated by the idea of understanding art through understanding the brain, I stopped going to these conferences. I felt like the neuroaesthetics community was going down the path that wasn’t going to lead anywhere that would lead to any answers I had about art (What is art? How does it work?) anytime soon.

Mr. Noë seems to have the same frustration I did with the path this science is taking. But he reaches a different conclusion from me: he basically throws up his hands and suggests it’s probably hopeless:

For these reasons, neuroscience, which looks at events in the brains of individual people and can do no more than describe and analyze them, may just be the wrong kind of empirical science for understanding art.

I think that’s mistaken. I’ll try to explain why.

An example: one conference I decided to skip looked to be about examining brain scans of people in love. I’m not sure how and if love and art are related, and I’m skeptical of the usefulness of brain scans. I failed to see how that is going to tell us anything about the mechanisms of art, so I decided not to waste my time.

I’m a computer engineer. The computer analogy to using brain scans for understanding art would be trying to reverse engineer a piece of software by looking at which disk sectors are being accessed on a hard drive when that software is running. That information is almost useless. If you want to reverse engineer anything–a brain, a computer, a piece of software, a transistor, whatever–you need to know exactly two things: the inputs, and the outputs.

If you know what the inputs are (in this case, works of art) and the outputs are (human reactions to works of art), then you can try to reverse engineer the rest. If your inputs and outputs match the original, even if your new machine works in a completely different way from the original, congratulations, you’ve reverse engineered the product.

A reverse engineering of art must begin not with a cataloging of the mechanisms of art, but of the inputs and outputs. That’s where I think the neuroaesthetics community has gone astray.

That’s not to say that an cataloging of the mechanisms of the brain isn’t useful–it is. Usually–but not always–knowing some of the mechanisms of the original product can help you figure out how to complete your reverse engineering. It can help you better categorize your inputs and outputs. But if you’re focused exclusively on understanding the mechanisms and and not on understanding the inputs and outputs, you’re not going to get anywhere.

As I said, in this field, I’m a nobody. I’m not an academic or an artist or a neuroscientist. I’m just a guy. I’m no one. But I’ve done a lot of thinking about it over these past seven years, and I’m convinced that the key to reverse engineering how art works in the brain lies in the difference between the two types of memory in the brain: declarative memories and non-declarative (or associative or procedural) memories. Understand that mechanism, and reverse engineering the rest will fall right into place.

It all seems clear and obvious to me. A neuroaesthetics community that uses an effective approach to the problem of how art works can probably give us lots of useful and interesting information. I’ve blogged about this for seven years now, I still feel as if I’m the only one who gets it. I’m not getting the idea across. I’m a lonely community of one. I was hoping that reading Daniel Kahneman’s recent book “Thinking, Fast and Slow” would shed a little light on the issue for others, but I don’t think it does. Art doesn’t really come up in his book. But the declarative/non-declarative dichotomy I’ve been talking about is pretty much the same System 1/System 2 dichotomy that Kahneman talks about–I think.

Perhaps if the professionals aren’t going to figure it out, that maybe I’ll just have to write a book myself, where I lay out the whole thing, my understanding of how it all works.

That idea scares me, though. What if I spend all that time to write that book and still nobody gets it? Or worse, I’m dead wrong about it? Hmm…

Continue…

My baby daughter turns two months old today. For the first six weeks of her life, she didn’t do much of anything; she was like a cute little simple robot that was programmed to just eat and sleep and fill her diapers. Lately, however, there have been signs of sentience. If I sit her on my lap, she will stare intensely down at her own bare feet, studying them as if they were the two most interesting things in the universe.

* * *

I woke up yesterday morning and found my seven-year-old daughter in a state of hunger. Of course, she didn’t tell me this, I had to deduce it from her attempts to pick a fight with her older sister. When she’s hungry, she gets cranky and loses all ability to reason. She feels like nothing can ever possibly make things right (save food, but she’ll never admit that): she’s unhappy, that’s the way it is, and that’s how it always will be, and everyone else around her might as well be unhappy along with her.

Come to think of it, that behavior is not too much different from the two-month-old, minus the foot fetish. Plus ça change, plus c’est la même chose:

Me: What do you want for breakfast?
7-year-old: I don’t want breakfast.
Me: You need to eat. What do you want?
7-year-old: I don’t want breakfast.
Me: OK, let’s skip breakfast and go straight to lunch. What do you want for lunch?
7: I don’t want lunch.
Me: Dinner?
7: I don’t want dinner.
Me: How about dessert?
7: I don’t want dessert.
Me: You must be sick, if you don’t want dessert. Shall I call the doctor?
10-year-old daughter (sensing an opportunity): I want dessert for breakfast! Let’s have chocolate-chip cookies!
Me: I was kidding. You can’t have dessert for breakfast.
10: What about donuts? Can we have donuts?
Me: We don’t have any donuts, and I’m not going out to buy any.
10: How about chocolate-chip pancakes?
Me (sighing defeatedly, heading towards the kitchen): Oh, all right. I’ll make chocolate-chip pancakes for breakfast today…

* * *

Reason is an elevator to Enlightenment. But Enlightenment is a just a small, lonely bus stop on a long journey to a chocolate-chip beach. Enlightenment is nobody’s final destination. Dessert, on the other hand…

* * *

(You got your loaves, your cheeses, your walking on water, and then the topper–Wow! Look at the front of that bus! What a header! Who was that–Jesus or David Beckham?)

Continue…

Fact: 42 is an adjective.

* * *

This blog entry is a long, complex answer to a simple question. It uses big words. It is not a linear story. We start by observing some thoughts about baseball journalism. We collect trading cards. We visit the University of Minnesota. We ride bikes over the Golden Gate Bridge. We travel back in time, 15,000 years, to the time when the first humans reached Australia. We listen to R&B while penguins explode. We hang out in a New York City saloon. We discover that God is on a sailboat headed for Buenos Aires, and the truth is hiding under my kitchen sink together with Kareem Abdul-Jabbar.

And after all that, we will have the answer to the ultimate question of life, baseball, and everything.

* * *

At the top of my blogging to-do list has been to respond to Will Leitch’s Baseball Analysts essay regarding the changing nature of baseball journalism. Leitch writes:

We are no longer in the days of radio; if you have MLB.TV, or even freaking cable, you can watch every game. We do not need reporters to tell us the facts; we need people to tell us what it means. Or, more specific, to ask us what we think it means.

Leitch was talking about it on a game-to-game level, but if you look at the big picture, it’s a big question. What is the meaning of baseball?

I shall hereby demonstrate why journalists do not try to answer that question.

* * *

Calvin: Susie, do you want to trade Captain Napalm bubble gum cards? After chewing almost $20 worth of gum, I’ve collected all the cards except numbers 8 and 34. I’ll trade you any duplicate for either of those.

Susie: I don’t collect Captain Napalm bubble gum cards.

Calvin: It must be depressing to go through life with no purpose.

A recent University of Minnesota survey revealed that the most distrusted minority group in America are atheists.

This surprised me. A lot. For all the racism and sexism and homophobia and xenophobia we’re constantly hearing about, the group that Americans really dislike the most are atheists?

Folks, don’t let your kids marry an atheist! Or be raised by one!

Atheists have been a pretty quiet bunch, relatively speaking. They haven’t deliberately antagonized anyone by holding Atheist Pride Day Parades down Main Street or anything. I suspect, however, that they’re starting to get louder. The Charlie Rose show recently spent an hour discussing atheism (although it wasn’t Charlie Rose, who just had heart surgery, it was Bill Moyers–when is a rose not a rose not a rose?). But I doubt this stuff has reached mainstream America yet. So what is so threatening about atheists that generates such animosity?

Here’s my guess: anti-atheists can’t stand the idea that life could be meaningless. People want human life to have meaning, just like Will Leitch wants his baseball to have meaning. People for whom life has no meaning are dangerous, not only for meaningless itself, but because they are free to behave in any selfish way they choose. If nothing matters, and no punishment or reward awaits people after they’re dead, morality breaks down, and all hell breaks loose. Faith holds society together.

Atheists would probably counter that atheists shouldn’t be confused with nihilists–their lives can have both meaning and morality, even without God. But nonetheless, the confusion happens, and here we are.

I think a lot of the hostility towards statistical analysis, in baseball or elsewhere, is similar to this. The resistance isn’t towards math or logic, it’s towards meaninglessness. The idea that human behavior is governed by mathematical formulas is repulsive, because it seems to rob people of free will. We want to believe that good choices, good character and teaminess will guide us to victory. Without free will, how can baseball, or anything in life, have meaning?

* * *

I own a couple of David Byrne CDs. I guess that qualifies me as a David Byrne fan, even if I don’t really listen to them all that often. My fandom has grown in recent months, however, as I started becoming becoming a regular consumer of his blog. (Now with permalinks! Yay!) From day to day, paragraph to paragraph, he takes you on a series of short journeys of discovery, which are always interesting, even if you don’t always agree with what he says.

One day, he’s in Stockholm, turning a building into a musical instrument. Then he’s in the Bay Area, having lunch with Jonathan Ive, riding bikes with Dave Eggers, and having nightmares about a broken cellphone.

His life seems to be one interesting anecdote after another, which at times makes me feel somewhat jealous, yet at other times is inspiring, for it seems Byrne makes his life interesting by taking the time to appreciate the art form in everything he encounters, from lawns to grocery stores to muffins. Attitude is everything.

One of Byrne’s recent entries has him in Adelaide, Australia, taking pictures of nature dioramas and local election posters, and taking notes about the various forms of Australian cuisine he has encountered. He tells us about some strange Aussie animals that went extinct soon after humans first appeared on the continent.

In the middle of this stream of Australian trivia, Byrne inexplicably links to a marvelous essay about R. Kelly’s Trapped in the Closet.

It’s a total non-sequitur. Which means I loved it, because I’m a huge fan of non-sequiturs. Let’s step to the side for no reason whatsoever, and see what happens. I was watching Graham Chapman’s Personal Best recently, and they were discussing how Chapman would always find the perfect non-sequitur to insert into a scene to make the scene complete.

And now for something completely different…the penguin on my computer will explode.

Boom!

Dang, there goes my Linux box. Is that why humbug.com has been so quiet lately?

* * *

Back to R. Kelly. If you’ve never seen or heard it, Trapped in the Closet is a sort of R&B soap opera. Wikipedia has a good synopsis, plus links to the videos. In this essay (you gotta read it), Morgan Meis marvels at how throughout the whole series of songs, R. Kelly never once strays from his straightforward narration into any sort of analysis. Then Meis teaches us a couple of big words:

…you could also say that human thought can be divided into two basic categories, paratactic and hypotactic. They are the two most elemental ways of putting thought together. In paratactic arrangement, you just keep adding something more. The greatest ally to parataxis is the conjunction. Such and such happened and then such and such happened after that, and next was a little episode of this and that, and then it all came to a head with this particular series of events, and then after that a whole new thing started.

…[snip]…

Hypotactic arrangement, by contrast, nestles thoughts within thoughts, steps to the side, qualifies, alters, and modifies. It has the structure of reflection and argument rather than that of lived experience.

This is what Leitch was talking about: journalism provides parataxis (facts and events), blogging provides hypotaxis (meaning).

* * *

When I see the words “facts and events” appear somewhere, a neuroscience alarm bell rings in my head. “Facts and events” is a codeword for “declarative memories”.

The human brain stores two separate types of memories, called declarative and nondeclarative memories. These memory systems function quite differently. Declarative memories store facts and events, and are conscious. Jackie Robinson wore uniform number 42. That’s a declarative memory.

Nondeclarative memories are subconscious, and store motor skills and patterns. A motor skill like riding a bike, or a pattern such as a pitching motion, are nondeclarative memories. One of the characteristics of nondeclarative memories is that they are difficult to describe. I can’t easily describe Dontrelle Willis’s pitching motion, or teach you how to duplicate it, but I recognize it the instant I see it.

Now here’s the fascinating thing to me about Leitch’s conjecture, and why I wanted to write about it: journalism is dividing itself along the same boundaries as the human brain.

Journalism: facts, events, parataxis, declarative memories.
Blogging: patterns, meaning, hypotaxis, nondeclarative memories.

* * *

Perhaps that’s a natural divide. Which gets me wondering: are all successful human advancements simply steps towards a better mirror of human psychology? Did communism lose, and capitalism win, because the winner more closely mapped the human brain than the loser? Do Oracle (structured data) and Google (nonstructured data) have dominant companies because their technology represents the best computerized analogies to declarative and nondeclarative memory systems? Are the best artists simply the best accidental neuroscientists?

* * *

Let’s examine one of the best artists to find out. PBS recently showed a great documentary about Eugene O’Neill by Ric Burns. The documentary covers O’Neill’s life and career, but focuses on his two most revered plays, The Iceman Cometh, and Long Day’s Journey Into Night.

O’Neill was, at least in some sense, an atheist. From documentary transcript:

Eugene lost faith. He left the Church at fifteen years old. He never came back. It would do nobody any service whatsoever to try to reclaim him for the Church. He was an apostate.

O’Neill came to feel that religion was a kind of illusion that prevented us for acknowledging reality and truth. Many of the plays O’Neill wrote early in his career dealt with characters whose tragic flaw was a failure to face the truth about themselves. They cling to their illusions, and suffer the consequences.

In O’Neill, there’s this absolute sort of God-ordained mission, which is to keep searching, even if in the process he discovered that there is no God. It’s a terrifying sort of mandate, but it also, I think, should be the mandate of all artists, and in a way, of all people.

O’Neill won the Nobel Prize for Literature in 1937. At the time, he was too ill to travel to Stockholm to receive his prize, so his prize was awarded to him in a hospital bed in Oakland, California. (Which also awards us a very flimsy connection to this Oakland A’s blog.) What was unusual about this, besides having Oakland join Stockholm and Oslo as cities where Nobel Prizes have been awarded, was that O’Neill had won the award, and still had not yet written his masterpieces.

O’Neill’s greatest breakthrough comes when he finally acknowledges the truth about himself: that his relentless search for “reality and truth” was, in fact, the biggest tragic flaw of all.

The Iceman Cometh is an allegory about truth and faith, set in a New York City saloon which O’Neill frequented as a young man. The characters each embody one form of “pipe dream” or another: religious, political, social, romantic. They each cling to their own personal illusion. In comes Theodore “The Iceman” Hickey, a Messianic character who proceeds to persuade each of them to abandon their pipe dreams, and live a life of truth, without guilt or illusion.

The result is disaster. Without their pipe dreams, the characters find that their lives fall apart. Life without illusion is like death–existence without meaning. To believe otherwise is insanity. In the end, the other characters dismiss Hickey as insane, and return to their illusions.

Tony Kushner: The thing that makes the tragedy so powerful and true is that you’re not allowed to escape what’s horrible, you’re not allowed any kind of denial. It’s annihilating, and on one level, I don’t think you leave the theater feeling in any way uplifted, and then on the other hand, you are brought to the absolute worst place that a human being can go, and you have survived, you’ve come out of this nightmare alive, and as I said, the stage is now sort of purged of this horror. It’s catharsis. It’s what Aristotle was talking about. And it leaves open the possibility that now something new will come at the end after the bombs fall and the landscape is clean. It’s the nothing that gives birth to something.

* * *

It’s as if Eugene O’Neill had spent his whole life looking for the perfect journalist, who would lay all the facts out on the table, one after another, and expose the truth. Notice that R. Kelly tries to accomplish the same thing. We all have something hiding in our closets and under our kitchen sinks. We try to pretend we don’t, but R. Kelly insists, like the early O’Neill did, that every one of those things must be exposed. And the only way to do that is pure reporting. Just the facts, ma’am.

The thing that puts O’Neill into the pantheon of great artists, that allowed him to create his masterpieces, is that he goes the extra step, and contemplates what it means to have pure journalism. He builds a truer map of the human brain, and concludes that our minds are simply not equipped to handle the truth. We need our pipe dreams.

* * *

In Long Day’s Journey Into Night, O’Neill takes this insight and reflects on his own family, his own life. He comes full circle. His life begins with faith and illusion. He finds that faith stripped away, and goes on a lifelong journey to face the dark truth. When the journey ends, he is finally able to return to the faith that makes life worth living. From a monologue by Edmund, the character who represents Eugene O’Neill in the play:

Edmund: You’ve just told me some high spots in your memories. Want to hear mine? They’re all connected with the sea. Here’s one. When I was on the Squarehead square rigger, bound for Buenos Aires. Full moon in the trades. The old hooker driving fourteen knots. I lay on the bowsprit, facing astern, with the water foaming into spume under me, the masts with every sail white in the moonlight, towering high above me. I became drunk with the beauty and the singing rhythm of it, and for a moment I lost myself–actually lost my life. I was set free! I dissolved in the sea, became white sails and flying spray, became beauty and rhythm, became moonlight and the ship and the high dim-starred sky! I belonged without, past or future, within peace and unity and a wild joy, within something greater than my own life, or the life of Man, to Life itself! To God, if you want to put it that way.

…

And several other times in my life, when I was swimming far out, or lying alone on the beach, I have had the same experience. Became the sun, the hot sand, green seaweed anchored to a rock, swaying in the tide. Like a saint’s vision of beatitude. Like the veil of things as they seem drawn back by an unseen hand. For a second you see–and seeing the secret, are the secret. For a second there is meaning! Then the hand lets the veil fall and you are alone, lost in the fog again, and you stumble on toward nowhere, for no good reason!

Meaning itself is fleeting. But the dream of meaning keeps us going.

* * *

O’Neill had the sea. I have baseball. Baseball fans like me dream of the moment when our team wins the World Series. The fact is, my team only has a 1-in-30 chance to win it all any given year. The fact is, I’m chasing a pipe dream. The fact is, that even if and when my team does win the World Series, the joy of victory that I have been pursuing will be far too brief. But the joy itself is not the point. It’s the dream of that joy keeps me going day after day, year after year. I need my illusion. I insist on it.

* * *

The dictionary says “42” is adjective, two more than forty. To Douglas Adams, 42 was a random number assigned to hold the ultimate answer to life, the universe, and everything. It was a symbol of absurdity, the meaningless of life itself. To a baseball fan, it’s more than a number, more than an absurdity. 42 goes beyond facts. Baseball goes beyond facts. It’s Dave Henderson, his gap-toothed smile, and the fun he insisted on having while patrolling center field for the Oakland A’s. It’s Mariano Rivera, a skinny man who somehow mastered one thing, a nasty cut fastball, and led his team to numerous championships. And, of course, it’s Jackie Robinson, overcoming incredible obstacles to inspire and lead generations of people. 42 is about the dreams we hold that, the real world be damned, sometimes come true.

* * *

Which brings us to today’s wørd: truthiness.

Truthiness is Steven Colbert’s term for what we feel to be right, not what the facts tell us. Now, Colbert points his satrical machine gun on the political uses of truthiness, but the power of truthiness extends beyond politics. Truthiness is about the triumph of meaning over fact, and it applies to all areas of human endeavors, because that’s just how the brain works.

So you know why I don’t like R. Kelly? He’s truth, not truthiness. He’s all fact, and no heart. And when I say heart, I really mean “nondeclarative memory system”, which is actually part of the brain, not the heart. But that doesn’t matter, because it feels like my nondeclarative memory system is in my heart, not my head.

Eugene O’Neill, on the other hand, rocks. He recognized, by living through the whole process himself, that pairs of words like “science and faith”, “truth and truthiness”, “journalism and blogging”, “statistics and scouting”–these things are not the opposite ends of a straight line. They are both points in motion on a circle. Science deconstructs faith, moves away from it, but eventually, the process brings it back.

Remember when science told us that chocolate was bad for you? Remember when baseball statisticians said defense was pretty much irrelevant, and there was no such thing as clutch hitting? Nobody believed them, because it didn’t feel true. Eventually, science did a 360.

Faith isn’t static, either. Faith, when confronted with science, will also adjust its position along the circle of knowledge. And when the whole process finally runs its course, when the facts have all been laid out on the table, and the meaning of those facts have all been analyzed, we will find that all these pairs of so-called opposites have ended up in the exact same place on the circle. Because that’s where we, as human beings, need them to go.

* * *

Universe man, Universe man
Size of the entire universe man
Usually kind to smaller man
Universe man

He’s got a watch with a minute hand,
Millenium hand and an eon hand
When they meet it’s a happy land
Powerful man, universe man

—Particle Man

* * *

So when R. Kelly tells me there’s someone hiding under my kitchen sink, and insists on exposing who he is, I will tell him it is Kareem Abdul-Jabbar. R. Kelly will tell me that I am lying. He will point out the fact that Kareem is way too large to fit under my sink. He will measure the sink, and demonstrate quite logically that the person under my sink must be someone much, much smaller than Kareem. He will insist on opening the door. He will open the door. He will show me who is really under my sink. He will say “Ha! See?” I will say, “Yes, I see. Thank you for showing that to me. I needed to see that.” And then I will continue to insist that the man under my sink is Kareem Abdul-Jabbar. For the things that I have hiding under my sink do not belittle me, they embiggen me.

Kareem represents the grand scale of my dreams. Those dreams may be unlikely or impossible, but they make me who I am as a human being. My dreams are my reality. I have faith in both faith and science, and I believe, that in the end, the truth and the truthiness will join together at last.

This is the sixth in a series of six articles.
Preview. 1. A New Science. 2. A Brain Lesson. 3. Hypothesis. 4. Some Explaining to Do. 5. A Lifetime of Art.

Beyond just explaining observed art phenomena, I imagine that this hypothesis could be used to make the creation and criticism of art more efficient.

The creation of art is a feedback loop between Android Brain and Animal Brain. Android Brain works through the steps of creating a work of art. The steps involve speaking in the language that Animal Brain understands: novelty, patterns, emotions, satisfactions and alarms. Animal Brain gives the artist feedback about the quality of the artwork, about whether new nondeclarative memories are being formed by it. Based on that feedback, the artist, in Android Brain mode, then alters the work.

Many artists just trust their own Animal Brain feedback and follow that. For those who are successful doing that, good for them. Don’t change a thing. But I think many artists would probably see the quality of their work improve if they had some good guidelines for Android Brain to follow.

Good rules can help artists be more aware of the choices they have and tradeoffs they make. Android Brain is built for step-by-step instructions. It’s methodical. There are already many good instruction books for artists to follow, but I think we can use the language of memory formation to make our explanations more precise.

Such explanations would not only be useful for pure artists, but also for advertisers and producers of goods whose measures of success are not counting new memories, but counting sales. As Virginia Postrel points out in her book The Substance of Style, aesthetic quality is becoming an important part of our economy.

A similar feedback loop pertains to art critics, too. Animal Brain is the source of our reactions. Android Brain has facts and rules about how art should work. It’s the source of our explanations. A good critic will move back and forth between Animal Brain and Android Brain, testing what their rules tell them against what their actual reactions are. If their reactions differ from their rules, they’ll adjust their rules. The goal of art criticism is to explain to Android Brain what’s going on in Animal Brain.

Some bad critics favor one system or the other. A bad Animal Brain critic will have a reaction and try to explain it without using any logic at all: I opine, therefore I’m right. That’s not helping Android Brain, which wants logic. A bad Android Brain critic will have rules about what art “should” be, and analyze according to those rules. But if you’re not testing the rules for accuracy against Animal Brain, you’re likely to have ineffective rules.

I can imagine people reacting negatively to thinking of art as a form of engineering. Even to me, it feels like the magic of it might be diminished. But because of that inaccessible data inside of our Animal Brain, I think art will always retain a certain mystery. The conversation between Animal Brain and Android Brain need never end.

To work with things is not hubris
when building the association beyond words;
denser and denser the pattern becomes–
being carried along is not enough.

Take your well-disciplined strengths
and stretch them between two
opposing poles. Because inside human beings
is where God learns.

  –Rainer Maria Rilke

   from Just as the Winged Energy of Delight
   translated by Robert Bly
   in The Rag and Bone Shop of the Heart

And finally: A summary in haiku form

This is the fifth in a series of six articles.
Preview. 1. A New Science. 2. A Brain Lesson. 3. Hypothesis. 4. Some Explaining to Do.

In my last article, I used my hypothesis to explain some commonly seen phenomena about art. In this article, I want to explore how our tastes change over the course of our lifetimes.

Babies

When my daughter was three months old, she laughed for the first time.

I bent over, so that my daughter could only see my hair. Then I suddenly lifted my head up, so my daughter could see my face again. My daughter burst out into a fit of giggling laughter.

The scientific term for this behavioral phenomenon is “peekaboo”.

Peekaboo is an art form. If you reveal your head too slowly–no laughs. If you lift your head up and down too quickly–no laughs. To achieve maximum laughs, must hide your face, and then reveal it, with a certain optimal delay.

My three-month-old daughter, who could not talk, who could not eat solid food, whose only major accomplishment of human behavior was to hold her own head up without it flopping over, was suddenly demonstrating a sense of aesthetic quality.

Child psychologists say that peekaboo tests the concept of “object permanence”. Object permanence is the concept that an object still exists even though you cannot see it. Before object permanence, when the face is gone, it’s gone. When it’s there, it’s there.

Object permanence turns peekaboo into a paradox: the face is not there (I can’t see it), but it is there (objects continue to exist even while not visible). It’s not there, but it is there! Two separate, and indeed contradictory, memories get associated with each other, and the result is a new memory.

Peekaboo’s effectiveness lasts for several months. At first, it seems you can play it endlessly and get a laugh every time. Slowly, though, the game gets more sophisticated. Your timing needs to be more precise to elicit laughter. You can’t emerge from the same place each time: you have to suddenly emerge from unexpected directions to get a laugh. Eventually, sometime after the child’s first birthday, peekaboo stops working altogether.

Peekaboo becomes a cliché. The child has become completely habituated to the idea of object permanence.

Preschool age

Why do kids like cartoons? Do you know of any young child who prefers a live action film to an animated one? I don’t.

As you saw with object permanence, one new memory can become half the building block for another. It’s a long process, though. Children take much longer to become habituated to new things than adults. Ask any parent who’s had to tell the same story over and over and over. And over. And over. And over.

Adults are habituated to so many more things than young children are. Children experience much more unrecognition with any given artwork than an adult does, and far less cliché.

Cartoons are simpler in every way than live action film. With live action, there is so much else going on: the colors, the lighting, the backgrounds, the body movements, the facial expressions–they are all more complex than a cartoon. There is so much more the brain needs to filter, and so the young brain becomes much less likely to recognize patterns in live action film.

In cartoons, however, there is much less information to sort through. The child can more easily recognize the patterns, the plots, the characters and their emotions–and trigger all those pairs of neurons, and create new memories.

School Age

When my daughter turned five, she was given a (fake) coonskin cap from a relative who had visited the Alamo. She loved it. When she started kindergarten, she wore it on her first day of school. She’s in first grade now, and she still sometimes wears it to school.

That won’t last. Nobody else in her school wears a coonskin cap.

Somewhere between second and fourth grades, ages 8-10, what other people think about art suddenly becomes hugely important to us. The clothes that looked fine before suddenly are rejected because that’s not what everyone else is wearing. Kids will suddenly develop passions for sports or pop music, because that’s what their peers are doing.

In other words, art becomes a social act. Before this, a child’s reaction to a work of art is almost purely its own. After this point, what other people do enters the database of patterns we build up in our brain, and becomes a factor in our judgments.

The child is building more and more sophisticated patterns every day. More and more adult-level patterns move from unrecognition into recognition, as the child-level patterns move into cliché.

Young adults

Mature adults often hate popular artworks aimed at a teenage audience. Adults see them as cliché, but the teenagers don’t. As the teenagers mature into young adults, and experience those patterns over and over again, that begins to shift.

Why don’t college radio stations play bubble-gum pop music? Because college-age students are finally at the age where they can easily recognize the clichés of popular culture. At an age where young adults are establishing their own independence, there’s a natural rebellion against the standards of popular culture from the previous generation.

The passing of generations is probably a vital creative force. In the effort to reject the old generation, a new generation puts a lot of effort into finding new kinds of patterns that they can identify as their own.

Mature Adult

So why don’t we just hate everything by the time we’re say, 50 years old? By then, we’ve probably seen so many patterns we become nearly impossible to please.

This is where I think my focus on habituation breaks down a bit. I focus on it because I think it plays such a huge role in how we perceive art. But all the other forms of conditioning can also affect how we form nondeclarative memories in our Animal Brain.

Nostalgia is the result of a kind of associative conditioning, similar to Pavlov’s dog. When you first enjoy a work of art, you get a positive emotion associated with it as a sort of byproduct. Those positive emotions will remain with that artwork, and any similar artworks that remind you of it. You become conditioned to enjoy that kind of art, the way the dog became conditioned to expect food after hearing a bell.

I still listen to a lot of the same music I listened to in college. Yes, I can recognize the clichés in the old stuff, but I still like it anyway. A lot of the new stuff is either too clichéd or unrecognizable to me.

I’m just an old fuddyduddy now, I guess.

Next: A better mousetrap.

This is the fourth in a series of six articles.
Preview. 1. A New Science. 2. A Brain Lesson. 3. Hypothesis.

We have a hypothesis, so let’s use it. We’ll begin by trying to explain some phenomena we frequently observe about art.

• What all art forms share

  Part of the problem with trying to decipher art as a whole is that art forms seem so different on the surface. What does painting have to do with music? What does dancing have in common with architecture?

  But if you look at the elements of each genre as a building block to a memory, you can begin to see the commonality. Since it takes two pieces of data to form a new memory, we can look at each art form for ways in which it creates associations between unrelated items.

  Some examples:
  In drama, you’re often given a conflict. One character wants something, and another character wants it, too, but for a different reason. The motivations are different, but there’s a common desire. Your brain creates an association between the different motivations, and a new memory is formed.

  Music composers often pair a major chord with its relative minor. Major chords are often described as sounding “happy”, and minor chords as sounding “sad”. But the difference between a C major chord (notes C-E-G) and an A minor chord (notes A-C-E) is only one note. By juxtaposing the C major chord with an A minor chord, the composer is creating an association: they’re dissimilar because of the major/minor difference, but they’re also similar because two of the three notes are the same.

  That’s what we’re looking for in each art form: juxtapositions of opposites, differences between similar elements, paradoxes, repeated sequences of different elements, associations between items: unrelated pairs which are combined to create a new Animal Brain memory. For want of a better word, let’s just call all these things patterns.

• The role of emotions in art

  Emotions do two things for us. They trigger automatic, physical reactions which keep us alive and breeding. They also serve to enhance memory formation. We’re more likely to remember things that are associated with emotions. Those emotionally enhanced memories keep us from repeating dangerous actions, and give us incentives to repeat beneficial behaviors.

  Although emotions are not essential to memory creation, they are a powerful enhancer. If the goal of art is to create new nondeclarative memories, the triggering of emotions is a very important tool in the process.

  I don’t think our physical reactions to art (clapping, cheering, booing, crying, toe tapping, etc.) are a factor in our judgment of the quality of art. I’d guess that quality judgments and physical reactions are two separate effects from the same cause.

• Why art is so hard to explain.

  You make a judgment about a work of art, and then you want to explain why you feel the way you do. The problem is this: the data you used to make the decision are not available to your conscious mind. The data that informed the decision are nondeclarative memories. They’re locked up in your Animal Brain, and you can’t query them.

  Instead, you go scouring for reasons in your Android Brain’s declarative memories, but that’s not where the answer is. Your Android Brain may contain facts about the patterns in the artwork, but it doesn’t have the actual patterns themselves.

  You cannot know for sure if the facts in your Android Brain match the patterns in your Animal Brain. It’s a bit like Schrödinger’s Cat. There’s no easy way to peek inside the box.

• Clichés and “I don’t get it”

  A cliché is simply a habituated memory. It’s something we’ve been exposed to so often, that we have learned to ignore it as insignificant, just as the zebra ignores the wind-blown grass.

  The “I don’t get it” experience happens when an artist intends for you to recognize a pattern, to make some association between two items and create a new memory, and you don’t recognize the pattern or association. I call this unrecognition.

  An artist has to walk a delicate balance between cliché and unrecognition.

  My baseball limericks suffer from both these problems. The limerick form is quite clichéd. Most people know the meter and rhyme pattern, so it’s hard to create a novel experience. And if you’re not a baseball fan, you’re unlikely to recognize the associations I’m creating by juxtaposing the attributes of various baseball players. The size of my audience is therefore quite limited. I’m doomed to mediocrity, at best. Oh, well. But speaking of mediocrity…

• Great vs. Mediocre vs. Bad

  The great works of art resist habituation. The patterns within them are so layered and interconnected that you can keep finding relationships between the details of the work, even if you experience the artwork many times.

  Mediocre works of art, on the other hand, may work to stimulate us once or twice. But sooner or later, habituation sets in.

  Bad works of art don’t even work the first time. They’re riddled with cliché and/or unrecognition from the start.

• Different opinions about the same work of art

  We’re measuring the creation of nondeclarative memories in our Animal Brain. To create a new memory, you need two bits of data. The bits can come from two sources: the artwork, or previous memories stored in the brain.

  The artist controls only one of those sources. Some brains won’t recognize patterns in the artwork, others will. Some brains will see clichés in the artwork, others will find the same pattern novel. Our own brain participates in the measuring of the artwork.

  For example, there are two songs about dying on Peter Gabriel’s album “Up” which I find particularly moving: “No Way Out”, and “I Grieve”. The reason I find them so moving is because they trigger emotional memories of my own father’s death. If my father were still alive, I doubt I would have had nearly as strong a reaction to the songs. Half the source of my emotional reaction is from the music, but half is from my own brain. The association between the two sources forms the new memory.

  For this reason, it really doesn’t make much sense to say a work of art is simply “great”. You really need to say the work of art is great to somebody. Any general measure of greatness needs to include some kind of demographics and probabilities. Hamlet is unlikely to seem great to preschoolers. It is more likely to seem great to adults.

• Rise and Fall of Genres

  Each genre of art has its natural building blocks, its common types of patterns, for creating new memories. As artists explore these genres, the building blocks get used over and over again. So as a genre ages, it becomes more and more difficult for the artist to avoid cliché.

  Eventually, the artists feel the need to break the boundaries of the genre. When this happens, though, the result is often unrecognition for the masses. The patterns become so complex that it begins to take a trained eye to recognize the associations the artist is making. At this point, the popularity of the genre begins to fade.

  You can probably recognize this phenomenon in the histories of painting and poetry. The patterns of abstract paintings and free verse are much more difficult for an untrained audience to recognize than those of representational paintings or rhymed verse, whose patterns are more obvious.

• Difficulty predicting future analysis of current works

  I remember the first time I heard the music of Prince. It sounded so strange to me! Unusual rhythms, weird chords: I just didn’t get it: unrecognition. Twenty years later, what seems strange that I thought Prince’s music was so hard to comprehend. Those rhythms and chords are everywhere now: cliché.

  The old artwork has not changed. Our brains have changed. And because our brains change, the things artists do to create associations will adjust to those changes. In turn, those adjustments change what kinds of patterns we recognize.

  It’s a cycle that is hard to predict very far in advance. Art history can turn unrecognition into attention, and attention into cliché, or vice versa.

• Critics who hate everything

  Some of us are more susceptible to habituation than others. I suspect that those members of the population at either extreme don’t make particularly good critics.

  If you are very difficult to habituate, everything will seem interesting to you. You’re going to like just about everything. That’s not very useful criticism. We need to know the difference between good and bad art.

  If you’re easy to habituate, you’ll quickly build up a considerable library of clichés in your brain. Over time, you will become harder and harder to please. These types of critics should probably switch genres often, so they can work with a balance of novelty and cliché.

Next: A Lifetime of Art

This is the third in a series of six articles.
Preview. 1. A New Science. 2. A Brain Lesson.

A brief recap:
The human brain has two separate decision-making systems.

One system is intuitive, fast, and subconscious. It’s designed to recognize patterns and react automatically to them. It holds your memory of motor skills and habits. We’re calling that system our Animal Brain.

The other is rational, slow, conscious. It’s designed to follow step-by-step instructions. It holds your memories of facts and events. We’re calling that system our Android Brain.

Animal Brain tends to dominate our behavior. It broadcasts all kinds of information to Android Brain. But Android Brain has no easy way to communicate back to Animal Brain.

The Hypothesis:

Now we’re ready for my guess as to how art works. Remember that this is just an attempt at reverse engineering: to make something that behaves the same way the original does. The internal workings of the brain may be quite different from this. If so, that’s OK. I’m really only concerned that the outputs are similar.

I propose that art is simply a way to communicate with our Animal Brain. We do that by taking advantage of Animal Brain’s own nature. Animal Brain is constantly on the lookout for unusual patterns in its environment, so that is what we give it with art.

So here’s my hypothesis, using my terminology:

The purpose of art is to provide a way for Android Brain to communicate with Animal Brain.

The definition of art is anything made with the intention of communicating with our Animal Brain.

The unit of measurement in art is a single new memory in our Animal Brain.

The quality of an artwork is the rate at which the artwork creates Animal Brain memories.

Now for the same thing, using scientific jargon:

The purpose of art is to enable the declarative memory system to communicate to the nondeclarative memory system. Or, to give System 2 a way to talk to System 1.

The definition of art is anything artificially constructed to stimulate the formation of nondeclarative memories.

The unit of measurement in art is the formation or enhancement of a single nondeclarative memory. Or, a chemical signal resulting from it.

The quality of an artwork is the rate at which nondeclarative memories are formed. Or, the cumulative strength of the resulting chemical signals.

If my hypothesis is correct, all we need to measure the quality of art is some kind of nondeclarometer, which can count the appropriate chemical signals from the Animal Brain’s nondeclarative memories as they are created.

New memories send out strong chemical signals. Habituated memories release weaker chemical signals. These chemical signals tell Animal Brain what to pay attention to and what to ignore. I’m hypothesizing that the strength of these chemical signals are what we are measuring when we judge the quality of a work of art.

Drat! I just Googled “nondeclarometer” and got zero hits.

Neural scanners are still pretty crude, but I imagine someday it might be possible to measure memory creation fairly accurately. But for now, measuring art is possible only in theory, not in practice.

The brain is a complex organic machine. I’m sure this simple hypothesis is just that, too simple. But if our goal is usefulness rather than accuracy, simple is probably better, anyway. A hypothesis is a beginning, not an ending. We can test our hypothesis against observable phenomena, and adjust it as we learn more. So let’s go use the hypothesis to explain some common phenomena we observe about art.

Next: Some Explaining To Do.

This (somewhat long) article is the second in a series of six articles.
Preview. 1. A New Science.

When we judge whether we like or dislike a work of art, we’re making a decision. To truly understand how to measure art, we need to understand how the brain makes decisions.

In his book The Metaphysical Club, Louis Menand describes an observation Oliver Wendell Holmes made about our legal system. Even though our legal system is set up to make decisions like this:

1. gather facts
2. analyze facts
3. make the decision

it seemed that most of the time, judges actually did this:

1. make the decision
2. gather facts that support the decision
3. present analysis to explain decision

People made their decisions first! How could they make their decisions before they had seen the facts? What, Holmes wondered, did they base their decisions on? Practical experience, Holmes decided.

(Holmes then went on to make some quite illogical decisions based on his own practical experience, including ruling that professional baseball should be exempt from anti-trust laws.)

Daniel Kahneman won the 2002 Nobel Prize for Economics. His studies have focused on how people make economic choices. Kahneman and others have found that people have two decision-making systems. One system is intuitive, the other is rational. From an interview in Strategy+Business (registration required, emphasis mine):

There are some thoughts that come to mind on their own; most thinking is really like that, most of the time. That’s System 1. It’s not like we’re on automatic pilot, but we respond to the world in ways that we’re not conscious of, that we don’t control. The operations of System 1 are fast, effortless, associative, and often emotionally charged; they’re also governed by habit, so they’re difficult either to modify or to control.

There is another system, System 2, which is the reasoning system. It’s conscious, it’s deliberate; it’s slower, serial, effortful, and deliberately controlled, but it can follow rules. The difference in effort provides the most useful indicator of whether a given mental process should be assigned to System 1 or System 2.

Kahneman tried to train people to make decisions using their rational system in instead of their intuitive system. But the effort was fairly futile:

Our research doesn’t say that decision makers can’t be rational or won’t be rational. It says that even people who are explicitly trained to bring System 2 thinking to problems don’t do so, even when they know they should.

In other words, he found the same thing Holmes did: that people have an extremely strong tendency to judge first, then reason later.

A just machine to make big decisions
Programmed by fellows with compassion and vision
We’ll be clean when their work is done
We’ll be eternally free yes and eternally young
—I.G.Y, Donald Fagen

Humans appear designed for inefficiency. Judges make decisions before they consider the evidence. Businessmen ignore logic and opt for less-than-optimal economic choices. Perhaps the song I quoted above is correct. We’d be better off having some kind of android making our decisions for us.

The perplexing thing is that each of us already has an android-like system for making decisions within us: Kahneman’s System 2. Let’s call this system Android Brain.

Android Brain does things methodically, in sequence, and follows rules to arrive at logical conclusions. You can give Android Brain step-by-step instructions, and it will follow those instructions. It’s programmable. It’s available to use. So why do we ignore it? Why do we so strongly prefer the intuitive system that is more error-prone? Are we designed wrong?

Not really. There’s a very good reason we do this.

Quick, tell me exactly what you do with your left big toe when you walk.

Don’t know? Well, actually, you do know. If you didn’t know, you couldn’t walk. So how come you can’t tell me?

Well, just as there are two reasoning systems in the brain, there are two memory systems, too. Scientists call the two types of memory declarative and nondeclarative.

Declarative memory is what we usually think of when we think of memory. It is our conscious memory. It contains facts and events. When it fails, such as in Alzheimer’s Disease, we lose our ability to remember what happened in our lives. Declarative memory is strongly associated with Android Brain, our reasoning system. Its processing center is an area of the brain called the hippocampus.

Sometimes called procedural memory, our nondeclarative memory is often overlooked because these memories are not conscious. They hold things like motor skills and habitual behavior. The reason you can’t tell me what your left toe does when you walk is because this is a nondeclarative memory. Your conscious mind does not have any access to this data. The processing center for nondeclarative memory is an area of the brain called the amygdala (a-MIG-da-la).

The amygdala has a second purpose besides handling your nondeclarative memories. It’s also the central processing center for your emotions. When you’re afraid, angry, excited, or happy, that’s your amygdala talking. The fact that the amygdala handles both your motor skills and your emotions is significant.

Imagine you’re a zebra, grazing on the savannahs of Africa. There’s a light breeze blowing the tall grass around. Suddenly, you notice a strange indentation in the grass. You feel fear, and in fear, you jump up and run away. A good thing you did, too, because that indentation was a lion sneaking up on you.

This is Kahneman’s System 1 in action. Let’s call this system Animal Brain.

Animal Brain has a tight coupling between emotions and motor skills. It’s an effective architecture, because quicker you react to danger, the more likely you’ll stay alive.

Animal Brain did three things to save your life:

1. It recognized an unusual pattern in your environment
2. The recognition caused an emotional reaction
3. The emotional reaction triggered a habitual, physical behavior

Because you were able to recognize this pattern and react to it in an instant, you are still alive.

This is why we have a strong preference for the decisions of Animal Brain over Android Brain. Any ancestor who favored using the slower, rational decision system of a Android Brain was more likely to be eaten by lions. The ones who preferred the quick decisions of Animal Brain stayed alive to pass their genes on to you.

So how did our imagined zebra know the difference between the motion of the grass caused by the wind, and that caused by the lion? Let’s take a slight detour and look at memory.

The process for creating Android Brain’s declarative memories is pretty complex. Animal Brain’s nondeclarative memories are more primitive and easy to explain.

In 1949, a scientist named Donald O. Hebb proposed a theory about how learning works in the brain. All learning, whatever the senses involved, uses the same basic mechanism: pairs of neurons firing together.

Fifty years later, a 1999 study out of Princeton University led by neurobiologist Joe Tsien revealed the genetic mechanism for Hebb’s rule. The gene, called NR2B, creates a protein which acts like a double lock on a door:

It needs two keys — or two signals — before it opens. As such, it is an excellent tool for creating memory, a process that fundamentally consists of associating two events. If two signals arrive at the same time — maybe one results from seeing a lit match and the other results from a sensation of pain — then the receptor is triggered and a memory is formed.

Animal Brain memories are altered by various forms of conditioning: repeated exposure to stimuli in the environment. The most famous example of conditioning is Pavlov’s dog. The dog drooled when he heard a bell, because he had been conditioned to expect food after a bell rang.

One form of conditioning is called habituation. In the book Memory: From Mind to Molecules, authors Larry Squire and Eric Kandel describe it like this:

…habituation is learning to recognize, and ignore as familiar, unimportant stimuli that are monotonously repetitive. Thus city dwellers may scarcely notice the noise of traffic at home but may be awakened by the chirping of crickets in the country.

When we’re first exposed to something new, a new memory is formed. If we are repeatedly exposed to it, though, and it proves harmless, we get conditioned to ignore it.

Thus, a zebra who is repeatedly exposed to the pattern of grass waving in the wind will become conditioned to ignore it. However, a change to that pattern could indeed have alarming consequences: it could be a lion. The zebra won’t ignore that stimulus.

Now, back to the two brain systems. Let’s compare them:

The reasoning skills of our Android Brain seems rather unique to humans, although other mammals do have declarative memories. It should be obvious that all mammals, if not all animals, have a brain system that works more or less like Animal Brain.

Although the human Animal Brain shares many things in common with a zebra’s, they are not identical. Humans have evolved some very important differences.

At the Neuroesthetics conference I went to, Dan Fessler, an anthropology professor from UCLA, gave a presentation about shame and pride, two uniquely human emotions. These emotions depend on the ability to imagine what someone else is thinking. For example, you don’t feel ashamed if you’re alone and you discover your fly is open. You only feel ashamed if you know that someone else knows that your fly is open.

But by far the most important difference between a human’s Animal Brain and a zebra’s is language. Language is a function of our Animal Brain: it is an automatic and subconscious skill. We speak and understand without deliberate effort. It has a sophisticated type of pattern recognition (listening), and an associated motor skill (speaking).

What happens when the two systems need to interoperate? It was pointed out in the Neuroesthetics conference that the conversation is extremely one-sided. Animal Brain broadcasts all kind of information to Android Brain: emotions, sensations, decisions, language. But Animal Brain seems to be completely unaware that Android Brain even exists. Hardly any information at all flows in the other direction.

Remember, Animal Brain is designed to keep you alive and reproducing. From an evolutionary standpoint, nothing is more important than that. And Animal Brain knows it.

Frog and Toad ate one very last cookie.

“We must stop eating!” cried Toad as he ate another.

“Yes,” said Frog, reaching for a cookie, “we need will power.”

“What is will power?” asked Toad.

“Will power is trying hard not to do something that you really want to do,” said Frog.

  –Arnold Lobel, Frog and Toad Together

In this delightful children’s book, Frog and Toad have a problem. Their Animal Brains are telling them to eat more cookies. Their Android Brains are telling them not to. They are finding it extremely difficult to ignore their Animal Brains.

Animal Brain is like that guy you meet at a party that you can’t get away from. He talks and talks and never listens to a word you say. If you try to ignore him, he STARTS TALKING LOUDER. If you try to turn away, he pulls you back: THIS IS IMPORTANT! DON’T MISS A WORD! You have no choice but to humor him.

Animal Brain: what a jerk.

Now, if his message is “there’s a lion sneaking up on you,” you’re grateful for his message. But if you’re on a diet, and he keeps telling you “EAT ANOTHER COOKIE”, it would be better to ignore his message. But it’s very hard to do so. He’s so insistent! Animal Brain assumes everything is urgent. Every situation is life or death.

How do you handle a jerk like that?

Well, one way is to use your own strengths. One of Android Brain’s strengths is the ability to follow rules. So we come up with rules that help us manage the behavior of Animal Brain and correct its errors: Ten Commandments, Twelve-Step Programs, Seven Effective Habits, that sort of thing.

Another way is to exploit his weaknesses. And Animal Brain does have weaknesses. That’s where art comes in.

Next: Hypothesis

This is the first in a series of six articles.
Preview.

Art is nebulous. In sports, you can measure success with wins or points scored. In economics, you can measure success with dollars or euros. But the arts are different. We know quality in the arts when we experience it, but we have a hard time describing exactly what it is.

Aesthetics is the branch of philosophy that deals with the nature and value of art. Theories of aesthetics have been around since Plato and Aristotle. None have delivered a useful way to measure art. But a new science is emerging, that gives us some hope of a solution. It’s called neuroesthetics, the study of the relationship between the brain and art.

I wanted to get a sense of the current state of neuroesthetics, so in January, I attended the Third International Conference on Neuroesthetics, which focused on “Emotions in Art and the Brain.” A wide variety of speakers gave their thoughts on how the brain works in relation to art: neurologists, psychologists, evolutionary biologists, art historians and some artists themselves. The Washington Post wrote a good summary of the conference (registration required).

I learned a lot, but I did not learn the one thing I most want to know: how do you measure the quality of a work of art? The speakers all either implicitly or explicitly avoided the issue. Neuroesthetics seems to be in a cataloging mode right now: gathering as many facts as possible.

This makes sense. If neuroscience is in its infancy, neuroesthetics is a newborn sibling. Neuroesthetics has a long way to go before it can give mature, scientifically valid answers to any of its questions.

That doesn’t help me much. I’m just an amateur artist, but I want tools right now to help me build better things. By the time the science can provide me with something useful, I may be in a nursing home. A scene pops into my head:

Bones:	You present the appearance of a man with a problem.
Spock:	Your perception is correct, Doctor. In order to return us to the exact moment we left the 23rd century, I have used our journey back through time as a reference, calculating the co-efficient of elapsed time in relation to the acceleration curve.
Bones:	Naturally. So what’s your problem?
Spock:	Accleration is no longer a constant.
Bones:	Well then, you’re just gonna have to take your best shot.
Spock:	Best shot?
Bones:	Yes, Spock, your best guess.
Spock:	Guessing is not in my nature, Doctor.
Bones:	Well….nobody’s perfect.

Guesses can be useful even if they aren’t always accurate. Long before I had found out about neuroesthetics, I felt compelled to make a calculated guesses about how art worked.

I did this by using my training as a computer engineer to approach measuring art as a reverse engineering problem. I knew what the inputs were (works of art), what the outputs were (judgments). The goal has been to design a new machine that takes the inputs and produces outputs similar to the original, and hope that it leads to useful information about art.

I gathered the data I had, and began tinkering around with numerous possibilities for arranging that data. But it wasn’t until I started learning more about the brain that I was able to find an algorithm that satisfied me.

The resulting hypothesis proposes that measuring art is possible, but it requires technology that isn’t currently available. Although we’ll fall short of one goal–being able to keep score in the arts–we will meet another: finding useful tools for creating and analyzing art. Whether I’m programming a computer, writing a limerick, or just watching a TV show, I now find I can approach my artistic endeavors with more purpose and precision than I ever could before.

Next: A Brain Lesson.

Suppose, for a moment, that there were no statistics in baseball. None, not even the score itself. No runs, hits, or errors were tracked. What would the sport be like?

To begin with, everyone would have a different opinion about who won each game. You’d pick a winner based on how the experience of the game felt to you. Which team’s play did you like better?

“The long home run in the sixth inning was impressive. The home team was the winner, in my opinion.”

“No, that diving catch in the fourth inning was awesome. I give it to the visitors.”

Nothing would have any set value. Perhaps you find the arc of a fly ball to be beautiful, and the team that seemed to hit the best fly balls is the one you’d pick as the winner. Who could argue against you? You like what you like, right?

Pity, then, the poor statisticians, who would have no numbers from the game to analyze. They’d have to resort to measuring the opinions of the audience.

How would you rate Sammy Sosa’s performance today on a scale of 1 (bad) to 5 (great)?
5 – 15%
4 – 28%
3 – 33%
2 – 14%
1 – 10%

Average: 3.24

MLB GOA (Game Opinion Average) Leaders:
Derek Jeter: 4.14
Ichiro Suzuki: 4.05
Neifi Perez: 3.95
Eric Byrnes: 3.92
Juan Pierre: 3.88

Intellectuals, of course, would come forward to take on the challenge of deciding who is best. We cannot trust mere public opinion with such a task. It takes experts to truly understand this stuff!

So then we’d be flooded with essays like “Baseball Analytics: A Postmodern Approach”, “The Influence of Global Capitalist Hegemony on Individual Player Evaluation”, “Oedipal Dynamics in Team Construction”, and “The Role of the Female Orgasm in Baseball Management Decisions“.

In other words, there would be an awful lot of humbug.

For baseball, this is a silly imaginary exercise. But for the arts, this is reality. Nothing can be measured, every opinion is valid, and surveys of those opinions produce absurd results.

I have felt for a long time that the arts would make a lot more sense if it had a statistic like “runs scored”. If we knew exactly what we were trying to accomplish with a work of art, we could speak about it with more accuracy and less humbug.

It seems like an impossible goal, but there’s no harm in trying to reach it. So this week, I will present a series of articles where I explore the nature of art, why it’s so hard to explain, and take a guess at how it could be measured.

Next: A New Science