Many (if not most) things that are good for society happen because society grants social status to those who do them. Once the bare necessities are accounted for, this respect granted by society is the biggest carrot around– being high-status is one of the best feelings in the world, but moreover it’s convertible to so many different things, like money, preferential treatment, sex, etc.

Society benefits enormously from this. But there are at least three systemic biases in how society doles out status for achieving things good things:

1. There’s a natural bias toward the short-term. People literally get addicted to the social status cycle… just like a drug. It’s chemical. They go for short-term projects for a more steady ‘fix’.

2. Social status is scale insensitive. Minor things (like founding an animal shelter) can give almost as much social status as curing cancer, or Elon Musk’s attempt to get our species off this planet. It’s on a log-type scale, like the Richter Scale– if you do something 10x cooler, you only get twice as much status. This discourages people from aiming high and risky.

3. There’s a strong bias toward the easy to understand. Since social status depends on the perception of other people, achievements need to be able to be widely understood to ‘cash in’ on status. E.g., the Gates Foundation tries to do good things, but only within the context of stuff that everybody can understand. And so it ends up not doing REALLY GREAT things.

Of course, Tallinn is implicitly arguing that he (and his immediate audience, the Singularity community) should be granted more social status. He’s not a completely uninterested party here.

There’s also lots of interesting ground outside of Tallinn’s scope of ’the flaws in society’s algorithm for granting status based on achievements’. E.g.,

- Different reasons society grants status (for achieving great things; for looking pretty; for successfully signaling you’re a member of the ‘in’ group, etc);

- The distinction of prototypically-masculine “respect is earned” vs prototypically-feminine “everybody deserves respect” cultures and their tradeoffs;

- Evopsych-derived theories on the psychosocial dynamics of respect and how to “game” them. And perhaps most pressingly:

- If and how we can fix some of these ‘bugs’ in how society grants respect.

Still, I think he’s got some good points.

There’s an age old adage in sport that if you aren’t cheating you aren’t trying hard enough. What modern competition will become is a battle to have your particular advantage, stimulant, or beneficial genetic abnormality declared competition legal, while your competitor’s advantages are restricted.

Perhaps comprehensive gene expression tests combined with the promise of post-facto tests on samples could stop most doping. We shall see. But I can’t shake the feeling all this anti-doping testing might be sports’ Maginot Line — we’re so focused on doping that we may get caught flat-footed by types of cheating we don’t expect. Performance degradation of competitors comes to mind.[3]

Let’s put on our mad scientist caps and talk heat rays. Consider how easy it would be to hide a low-power, directional microwave array in standard AV/broadcast equipment— basically a set of dishes that can focus energy at some distant point and heat it up a bit. Something that could be aimed at, say, a runner and heat up their internal tissue just enough to hurt their performance.

Heat build-up in muscle and nerve tissues, it turns out, is one of the biggest factors that degrade athletic performance. Something like this — essentially a directional version of a microwave oven — wouldn’t hurt anyone at low power levels, but by heating up their muscle tissues and core temperature it could sap a few percent off their peak performance/endurance. Which is easily the difference between a gold and a bronze medal, or a having a killer comeback 4th quarter vs getting rotated out for exhaustion.

The tech is actually really simple… essentially a sophomore-level physics problem. You’d need to find the right wavelength and power intensity to penetrate skin and heat tissue (but not too much), you’d need to disguise the equipment (it’d look like a handful of DirectTV dishes*), you’d need a clear line-of-sight to the athletes, you’d need to figure out a workable area-of-effect focus (say, a sphere with a 3ft radius), and you’d need some way to control it. Maybe you’d have one of your “camera guys” point-and-shoot it manually, or you could write some software to track targets automatically. Governments could use this to cheat at the Olympics; pro sports teams could use this to tire-out key opponents. It’d sure be a slimy way to win, but effective.

So, what are the chances something like this will get used in London 2012? Or that it was used in Beijing 2008? Non-zero, I’d say. And unlike doping, which leaves traces in blood and urine samples which can be analyzed years later with more sophisticated tests, this would leave no trace. Just some momentary, inexplicable fatigue.

Scary.

*Since microwaves effortlessly pass through many materials, you could presumably hide these dishes *inside* boxes or other props.

—————————–

[1] Excerpts from a Spiegel interview with Angel Heredia, once a doping dealer and now a chief witness for the U.S. Justice Department:

… He had been in hiding under an assumed name in a hotel in Laredo, Texas, for two years when the FBI finally caught up with him. The agents wanted to know from Angel Heredia if he knew a coach by the name of Trevor Graham, whether he carried the nickname “Memo”, and what he knew about doping. “No”, “no”, “nothing” – those were his replies. But then the agents laid the transcripts of 160 wiretapped telephone conversations on the table, as well as the e-mails and the bank statements. That’s when Angel “Memo” Heredia knew that he had lost. He decided to cooperate, and he also knew that he would only have a chance if he didn’t lie – not a single time. “He’s telling the truth,” the investigators say about Heredia today.

SPIEGEL: Mr. Heredia, will you watch the 100 meter final in Beijing?
Heredia: Of course. But the winner will not be clean. Not even any of the contestants will be clean.
SPIEGEL: Of eight runners …
Heredia: … eight will be doped.

…
SPIEGEL: And how did you become the best in your world?
Heredia: With precision. You want an example? Everyone talks about epo. Epo is fashionable. But without adding iron, epo only works half as well. That’s the kind of thing you have to know. There are oxygen carriers that make epo work incredibly fast – they are actually better than epo alone. I call my drug “Epo Boost.” I inject it and it releases many tiny oxygen molecules throughout the body. In that way you increase the effect of epo by a factor of ten.
SPIEGEL: Do you have any other secrets?
Heredia: Oh yes, of course. There are tablets for the kidneys that block the metabolites of steroids, so when athletes give a urine sample, they don’t excrete the metabolites and thus test negative. Or there is an enzyme that slowly consumes proteins – epo has protein structures, and the enzyme thus ensures that the B sample of the doping test has a completely different value than the A sample. Then there are chemicals that you take a couple of hours before the race that prevent acidification in the muscles. Together with epo they are an absolute miracle. I’ve created 20 different drugs that are still undetectable for the doping testers.

…
SPIEGEL: Is there doping at every level of athletics?
Heredia: Yes, the only difference is the quality of the doping. Athletes with little money use simple steroids and hope they don’t get tested. The stars earn 50,000 dollars a month, not including starting bonuses and shoe sponsorship contracts. The very best invest 100,000 dollars – I’ll then build you a designer drug that can’t be detected.
SPIEGEL: Explain how this works.
Heredia: Designer drugs are composed of several different chemicals that trigger the desired reaction. At the end of the chain I change one or two molecules in such a way that the entire structure is undetectable for the doping testers.
SPIEGEL: The drug testers’ hunt of athletes …
Heredia: … is also a sport. A competition. Pure adrenaline. We have to be one or two years ahead of them. We have to know which drug is entering research where, which animals it is being used in, and where we can get it. And we have to be familiar with the testers’ methods.
SPIEGEL: Can the testers win this race?
Heredia: Theoretically yes. If all federations and sponsors and managers and athletes and trainers were all in agreement, if they were to invest all the money that the sport generates and if every athlete were to be tested twice a week – but only then. What’s happening now is laughable. It’s a token. They should save their money – or give it to me. I’ll give it to the orphans of Mexico! There will be doping for as long as there is commercial sports, performance-related shoe contracts and television contracts.

…
SPIEGEL: Are there still any clean disciplines?
Heredia: Track and field, swimming, cross-country skiing and cycling can no longer be saved. Golf? Not clean either. Soccer? Soccer players come to me and say they have to be able to run up and down the touchline without becoming tired, and they have to play every three days. Basketball players take fat burners – amphetamines, ephedrin. Baseball? Haha. Steroids in pre-season, amphetamines during the games. Even archers take downers so that their arm remains steady. Everyone dopes.

[2] Anthropologist John Hawks on doping:

John Leonard, executive director of the American Swimming Coaches Association, told of conversations he has had with coaches and scientists in China.
“We are really naive if we are to believe that the Chinese at this point are clean or that they are the only country in the world that is experimenting with genetic enhancement as we speak,” said Leonard, who was not a panelist but attended the conference and spoke during question-and-answer periods.
“There are lots of countries in the world who couldn’t care less about doing it safely, and there are lots of athletes who will take the chance that they will die in order to win medals. … Will the United States have the same viewpoint when we start losing gold medals?”

…
But really, there are plenty of people who would stand in line to trade 20 years of their lives to win an Olympic medal. And many who think that the current winners are simple beneficiaries of a genetic lottery. As soon as genetic modifications become routine to correct developmental problems, the kids who had them will start coming up through the sports ranks. The way it stands now, the Olympics and other sports venues are staging themselves as some of the last arbiters of “pure” humanity.

[3] A friend suggests,

You’re thinking too Star Trek. Easier to slip trace amounts of prohibited substances into an opposing athlete than rig heat waves.

Probably true. But might raise more investigative flags… and would definitely be less fun.

Cross-posted on opentheory.net and tvfury.wordpress.com.

Everybody who’s paying attention knows things need to change– that we’re at the wrong end of multiple unsustainable trends. Are we looking at a recession slowly leading into a recovery? A long-term recession characterized by stagflation as the new normal? A worldwide economic disaster? It’s hard to say. Nobody knows. All are real possibilities, though I think the Krugmans of the world are ignoring our structural problems and the magnitude of the pain required to solve them. What’s clear is we’re in a tight place, economically speaking, with a lot of risk and few good options.

Why do bad things happen to good economies? (Of Austrians, Keynesians, and the path of least resistance)

How’d we get into this mess? A lot of people blame greedy bankers, crony capitalism, partisan politics. There’s some truth in each of these, but one of the biggest factors is how we approach economic cycles. Keynesian economics suggests the healthiest way to handle cycles is to put money aside during the ‘up’ parts of the cycle, and spend these savings during the ‘down’ parts to smooth things out. It seems intuitive. Austrian economics, on the other hand, suggests that any attempt to subvert natural economic cycles is ultimately unhealthy, and we need to just tough out the recessions— moreover, the ‘down’ part of the cycle is actually the most healthy, since economic pain is the only way to cleanse an economy of bad investment and structural problems.

Economists have spent a lot of air and ink debating the relative merits of each (note: link is to an econ rap battle). But, ironically, since 1987 we’ve done neither: we’ve injected liquidity — banker talk for “thrown money at the problem” — whenever things slow down, as the Keynesians suggest, but we haven’t been setting aside money in the good times. So for 25 years we’ve taken the path of least resistance and financed our way out of short-term recessions by taking on more long-term debt, enjoying the fruits of economic growth while kicking the can down the road. This can go on… until it can’t. The music may be stopping, the party winding down, and the hangover is starting to pound.[1]

The domino effect (and, “at least we’re not Greece”)

The larger issue here is that most nations are in roughly the same fiscal position as the US, or worse. Greece went pseudo-bankrupt and is essentially sliding into ‘failed nation’ status; Spain is likely close behind. Ireland, Italy, Portugal, and really most of the Eurozone is in pretty sad shape, burdened with inflexible, unworkable policy and mountains of debt. Japan is stable but almost completely underwater, India is staggering, and though China seems to have different economic problems than those in the West, it may be in no better shape. Most countries export to the US, so a slowdown here means slowdowns elsewhere. The specific watchword here is “contagion”, which means since everyones’ economies are linked to everyone else’s, a default (bankruptcy) of one country or major bank could interrupt cashflow to its trading partners enough to cause a chain reaction of defaults. The more defaults there are, the more likely this is to cause even more defaults. Here’s a simple video on the topic.

Contagion is a serious concern, the cause of the government’s oft-maligned emergency TARP loans and of the EU’s special dealings with Greece. This situation is further complicated by the existence of hundreds of trillions of dollars of CDOs and CDSes (JPMorgan alone has a $70 trillion derivative exposure, a figure higher than world GDP, though nobody–JPMorgan included–knows quite what this means). These are essentially hugely leveraged bets that countries won’t default on their sovereign debt, bets that will explode in the world’s face in a fiery ball of leveraged pain and contagious uncertainty if a country like Greece does technically default on its debt.

Caveats (and their caveats…)

Not everything is certain gloom and doom, and there are some particular bright spots– American technology and startups, singularity trends, and the small-but-growing China export market could all help gloss over a lot of structural dysfunction. Reasonable people can be hopeful. But these bright spots have caveats— Thiel makes a solid case for pessimism about technological progress, there are strong bear arguments on Chinese growth and stability, and the Chinese consumer market is turning out a lot smaller than expected anyway. We’re probably going to need to fix our problems the old-fashioned way– which translated, means we should expect to experience pain sufficient to compel us to fix the structural problems that got us into this mess, before things turn good again. And given how entrenched the problems are and how long we’ve deferred said reckoning, it’s going to be significant.

All this adds up to a rather scary prediction. I hope I’m wrong, and I wish there was more I could do to help.

What rich people are worrying about (the smart ones, at least…)

This brings us back to the point about worrying: let’s assume there’s a non-trivial chance that multiple unsustainable trends are going to come due in the next few years, that a lot of wealth is going to be destroyed, that the ‘economic pie’ is going to shrink drastically. The problem people with money face, then, is to find the pieces of the pie that will shrink the least. To make sure the wealth that’s destroyed is other peoples’. It’s not pretty, but economic contractions never are.

Pessimism doesn’t make hay; what to do?

There are so many rich economic pessimists so desperate for insulation against systemic risk that reasonably-priced hedges are few and far between. Gold, the standard hedge against fiscal uncertainty, has quadrupled in price since 2000. Farmland in the Midwest jumped ~25% in the past year after strong gains the past decade. The ol’ “hide your cash in your mattress” strategy isn’t very good when governments can simply inflate away its value. In other words, if you’re worried about finding a relatively disaster-proof way to store your wealth, you’re going to have to either pay a huge premium for being late to the party, or get a little creative and off-the-beaten-path.

A key problem here is the economic worth of most everything is linked to the level of economic activity. A hotel’s value, for instance, depends on how many people can afford to stay there. Copper’s value depends on lots of people wanting to make stuff with it. A vacation beach house’s value depends on there being people with enough disposable income for luxuries. So the ideal hedge would be something with inelastic or countercyclical demand, yet something that wouldn’t lose value if the financial apocalypse failed to materialize, or if singularity trends kept apace. Even better if it was a company or property that generated income under all such scenarios. And of course, you wouldn’t want to put all your eggs in one basket. It’s possible that something like the Vice Fund could be viable, but I have to say I think there are much better investments out there. We just have to find them. Or make them.

Notes:

[1] Furthermore, the US’s dirty little secret is that we’ve slowly, imperceptibly drifted away from a market-driven economy and toward a government-driven economy, which further distorts natural economic cycles. Government spending accounts for ~40% of GDP, and government influence in the economy, in forms ranging from egalitarian employment mandates, security administration at airports, to interest rate manipulation, is everywhere. (On the Fed’s role, my dad has noted the irony “that we are probably in the mess we’re in because a follower of Ayn Rand [Greenspan] decided that central planning was better than the markets – as long has HE was doing the planning”.) Capitalism is never pure, and in modern societies there’s always some element of central planning. But our government bureaucracy’s influence on what happens inside our borders is more pervasive and less accountable than strictly necessary, and its sheer size is burdensome… especially during downturns, when the private sector sheds its least efficient jobs but the government doesn’t. (Or would be, if we weren’t just borrowing the money to pay for it.)

Discussion:

- One pernicious issue is how many elements of society have outsourced the funding of their financial obligations onto continued growth. See, e.g., CalSTRS, or the pension fund for the California State Teachers’ Retirement System. At 10% growth, it fully funds all its pensions. At 7.5% growth, it’s underfunded by $64.5 billion. At 1-2% growth… things look pretty grim for retired teachers.

We can’t just not shrink, we can’t just grow a little; we need to grow a LOT just to keep our financial obligations from blowing up. It didn’t have to be this way, but it is.

- David Brooks has a reasonable op-ed on structural problems, and how the same playbook that got us into this mess won’t get us out.

- The elephant in the room in these economic debates is whether the growth of the middle class in the last 60 years is a ‘new normal’ or just a temporary aberration. As Taibbi worries,

I think people are going to realize what a blip on the radar American-style democracy in the 20th century was. A big middle class that had a huge powerbase, financial interests, bosses giving benefits… all those things. It’s just a little blip in history. For the most part, concentrated wealth will make all the decisions and everybody else is dictated to.

We measure inflation with the Consumer Price Index, which is basically an aggregate, pared down cost-of-living metric. How much it costs, month by month, to buy life’s essentials for the average consumer. If this ‘basket of representative goods and services’ goes up, we call that inflation. As a cost-of-living metric it’s pretty good, and as Krugman notes, alternate approaches turn up about the same numbers.

But ‘how far does a dollar go for the average consumer?’ and ‘how much is a dollar is worth compared to everything else?’ are very different questions.[1] Here’s my take:

When we get down to it, everyone has their own inflation rate, based on what they want and need to buy. Averages here miss a lot of trends. One trend that comes to mind is the current economic polarization and concentration of wealth. Let’s keep in mind, dollars are a commodity like any other, and inflation is just supply-and-demand. It happens when too many dollars are chasing too few goods and services. In 2012, there’s a huge oversupply of dollars held by rich people and investors; stuff that these people want to buy (investments, high-end and luxury goods and services) is getting bid way up.[2] On the other hand, in the lower tiers of society, there isn’t an oversupply of dollars. Official inflation rates are calculated based on cost of living for the majority of people— NOT, e.g., the cost of what people who hold most of the dollars want to buy. It’s an important distinction: in short, we look at inflation from the average person’s perspective, whereas we should look at it from the average dollar’s perspective.

I’m sure this alternately weighted, dollar-centric rate of inflation would be much higher than the official CPI. How could we calculate it reliably? I’m not sure. But you could make a lot of money if you figure out how.

Musings:

- Is this driven by an oversupply of currency or of credit? Probably both, e.g., “Some insights from my visit to the ECB“. And due to many people being desperate to hold anything but dollars (ABD).

- In terms of currency creation, this is definitely not limited to the US dollar. In fact, if the US is playing games with the Fed w.r.t. currency creation, every other government in the world has an incentive to play the same sorts of games (two incentives, really, since if you create more money to prevent your currency from rising too much against the dollar, you also get free money). Trends like this persist until they can’t.

- People think of inflation and deflation as opposites; I would say they’re cousins, in that they’re both products of and drivers of volatility. Both erode the leverage of the tools we use to manage our fiscal affairs, and I suspect both could happen in short succession, particularly with a whipsawing money supply– or even at the same time, in different sectors of our economy (just like different inflation rates).

- Why does this matter? Aside from skewing all economic statistics, this adds a great deal of volatility to anything connected with currency. Back in 2005 people scoffed at the possibility of a housing bust, pointing at a variety of statistics (all of which looked very solid and reasonable at the time). Now, people are scoffing at the possibility of a currency crisis, pointing mainly at the stability of the CPI. I don’t know what the future holds, but I know that’s not a good argument.

Notes:

[1] Walmart-style globalization, Procter & Gamble-style manufacturing efficiency gains, and Moore’s Law-type exponential improvement should all be strongly deflationary factors– that is, making peoples’ dollars go further. That we don’t see many deflationary pressures suggests to me they’re effectively subsidizing currency creation games.

[2] Some of this inflation in investment commodities is driven by the current extreme levels of uncertainty, but some isn’t. One could presumably quantify some of this by looking at option premiums. Market analysis of dollar-denominated commodities gets really complex when there may be hidden inflation, however, and government-numbers-derived tools like TIPS are pretty worthless qua tools.

I also have friends and family who work in the greater investment community. Their opinions of OWS are all over the map: some welcome the protests if they can bring about more market transparency and accountability, others are quite frustrated by the protesters’ general lack understanding, sophistication or solutions. To put (my) words to their feelings: things aren’t perfect, but many of the protesters’ demands betray a striking lack of comprehension about how the market works.

I’m not here to pick a winner. I am here to say that this dispute hides a much bigger problem, one independent from any issue of corruption and one that will unravel the fabric of society if we sleepwalk into it. Settle in, get a cup of coffee, and I’ll explain why.

Why people are mad: it’s not winning, it’s cheating
Matt Taibbi at Rolling Stone succinctly explains why the Occupy Wall Street protestors are mad:

Success is the national religion, and almost everyone is a believer. Americans love winners.  But that’s just the problem. These guys on Wall Street are not winning – they’re cheating. And as much as we love the self-made success story, we hate the cheater that much more.

In this country, we cheer for people who hit their own home runs – not shortcut-chasing juicers like Bonds and McGwire, Blankfein and Dimon.

That’s why it’s so obnoxious when people say the protesters are just sore losers who are jealous of these smart guys in suits who beat them at the game of life. This isn’t disappointment at having lost. It’s anger because those other guys didn’t really win. And people now want the score overturned.

All weekend I was thinking about this “jealousy” question, and I just kept coming back to all the different ways the game is rigged. People aren’t jealous and they don’t want privileges. They just want a level playing field[.]

Wall Street’s recent antics would probably irk people a lot less if the public didn’t have the perception the bankers are playing a “heads I win, tails you lose” game backed by taxpayer money. Institutions that are “too big to fail” take great investment risks and are either rewarded handsomely, or get bailed out by the government (read: taxpayers).

Nassim Taleb (of Black Swan fame) offers a possible solution for this kind of moral hazard:

[I]t’s time for a fundamental reform: Any person who works for a company that, regardless of its current financial health, would require a taxpayer-financed bailout if it failed should not get a bonus, ever. In fact, all pay at systemically important financial institutions — big banks, but also some insurance companies and even huge hedge funds — should be strictly regulated.

Critics like the Occupy Wall Street demonstrators decry the bonus system for its lack of fairness and its contribution to widening inequality. But the greater problem is that it provides an incentive to take risks. The asymmetric nature of the bonus (an incentive for success without a corresponding disincentive for failure) causes hidden risks to accumulate in the financial system and become a catalyst for disaster. This violates the fundamental rules of capitalism; Adam Smith himself was wary of the effect of limiting liability, a bedrock principle of the modern corporation.

I don’t agree with many of the OWS complaints, but it’s clear that some parts of Wall Street are broken. Regulatory capture is common, banks seem to operate above the law, and the game is often subtly rigged in a thousand little ways. HFT is arguably a parasite twice-over, siphoning both money and bright young people away from other areas into a negative-sum pit of cheat-or-be-cheated. Goldman Sachs does resemble, in the words of Taibbi, “a great vampire squid wrapped around the face of humanity, relentlessly jamming its blood funnel into anything that smells like money.”[1]

The richest 1% (and arguably the financial sector) have seemingly diverted almost all the economic growth of the past 30 years into their pockets, and to a large extent that’s been opportunistic, not meritocratic. What’s more, this ‘short-term greedy’ way of doing business threatens to spread, like a sickening disease, across more parts of our economy and government. We need to fix this or it’ll drag us, kicking and screaming, into a true kleptocracy.[2]

Many in OWS have completely lost faith in the political process, believing that these Powers That Be have successfully co-opted the acceptable mechanisms for change so completely that political disobedience is the only way to send a message.[3] I want to think they’re wrong, but at some level I have to agree.

Not just hippies: Image is retired Philadelphia Police Capt. Ray Lewis being arrested for ‘unlawfully blocking traffic’ during OWS. He had been loudly accusing the NYPD of serving as mercenaries for Wall Street. Given that there have been no high-profile arrests of the people who were responsible for defrauding billions from pensions and taxpayers and (proximately) causing the financial crisis, he may have a point.

Having said all that– and the more I think about this the more certain I am– OWS protesters are on the right side of this battle, but the wrong side of history. The story of why starts with monkeys and ends with robots.

Perception and complexity
Jonah Lehrer recounts a primate study centered around instinctual reactions to perceived injustice:

A similar lesson emerges from a classic experiment conducted by Franz de Waals and Sarah Brosnan. The primatologists trained brown capuchin monkeys to give them pebbles in exchange for cucumbers. Almost overnight, a capuchin economy developed, with hungry monkeys harvesting small stones. But the marketplace was disrupted when the scientists got mischievous: instead of giving every monkey a cucumber in exchange for pebbles, they started giving some monkeys a tasty grape instead. (Monkeys prefer grapes to cucumbers.) After witnessing this injustice, the monkeys earning cucumbers went on strike. Some started throwing their cucumbers at the scientists; the vast majority just stopped collecting pebbles. The capuchin economy ground to a halt. The monkeys were willing to forfeit cheap food simply to register their anger at the arbitrary pay scale.

This labor unrest among monkeys illuminates our innate sense of fairness. It’s not that the primates demanded equality — some capuchins collected many more pebbles than others, and that never created a problem — it’s that they couldn’t stand when the inequality was a result of injustice. Humans act the same way. When the rich do something to deserve their riches, nobody complains; that’s just the meritocracy at work. But when those at the bottom don’t understand the unequal distribution of wealth — when it seems as if the winners are getting rewarded for no reason — they get furious. They doubt the integrity of the system and become more sensitive to perceived inequities. They start camping out in parks. They reject the very premise of the game.

This is a fantastic experiment; I only wish the researchers had delved into the gray areas between ‘totally fair’ and ‘totally unfair’ — where monkeys were rewarded with grapes based on consistent but increasingly complex conditions. Where would their breaking point be?

Just like monkeys, our capacity for understanding economic complexity is not infinite.[4] A friend who works in finance suggested that past a certain threshold, it might be impossible to figure out if any specific part of our economy is fair. And some people are bound to interpret inability to determine fairness as unfairness.

I think this is true. On the other hand, perhaps past a certain complexity threshold, economies play host to greatly more parasitic activities. In fact, I think the complexity-driven decoupling between wealth creation and compensation almost guarantees it. Is the greater total wealth created in more complex societies worth the greater parasite load? And does a default assumption of fairness or unfairness serve us better when we see something we don’t understand? I can see it going both ways. The consequences of going too far in either direction are severe:
- with a too-permissive view of corruption, economically parasitic behavior and distrust can spread from one sector into others, undermining the contracts society is based upon;
- with a too-sensitive corruption radar,  the perception of unfairness (as with any negative emotion) can drive a vicious psychological feedback loop, and people (like monkeys) stop working. It might take a Hard Reset like the 1930s to cure this.

It’s a difficult balance, and the devil’s in the details. But the takeaway is that we’re not always in a position to judge what is fair, and, very importantly…

An increasing economic gap can be healthy!
Silicon Valley entrepreneur Paul Graham has a thoughtful article about attitudes toward wealth, arguing that a widening gap between rich and poor can be a sign of health if it reflects people getting paid for creating stuff people want. It’s the same form of argument that conservatives have been using for 30 years to justify the widening gap, but Graham’s perspective from the world of software startups, where success is tightly tied to the wealth one creates for others, is pretty powerful.

Where does wealth come from? People make it. This was easier to grasp when most people lived on farms, and made many of the things they wanted with their own hands. Then you could see in the house, the herds, and the granary the wealth that each family created. It was obvious then too that the wealth of the world was not a fixed quantity that had to be shared out, like slices of a pie. If you wanted more wealth, you could make it.

…

And since the ability and desire to create it vary from person to person, it’s not made equally.

You get paid by doing or making something people want, and those who make more money are often simply better at doing what people want. Top actors make a lot more money than B-list actors. The B-list actors might be almost as charismatic, but when people go to the theater and look at the list of movies playing, they want that extra oomph that the big stars have.

Doing what people want is not the only way to get money, of course. You could also rob banks, or solicit bribes, or establish a monopoly. Such tricks account for some variation in wealth, and indeed for some of the biggest individual fortunes, but they are not the root cause of variation in income. The root cause of variation in income, as Occam’s Razor implies, is the same as the root cause of variation in every other human skill.

In the United States, the CEO of a large public company makes about 100 times as much as the average person. [3] Basketball players make about 128 times as much, and baseball players 72 times as much. Editorials quote this kind of statistic with horror. But I have no trouble imagining that one person could be 100 times as productive as another. In ancient Rome the price of slaves varied by a factor of 50 depending on their skills. [4] And that’s without considering motivation, or the extra leverage in productivity that you can get from modern technology.

None of this excuses Wall Street corruption– far from it, a society where it’s easier to steal wealth than make it will demotivate talented people, and divert their efforts from creation towards theft– but the point is some people are naturally better at creating wealth than others. Moreover, technology leads to more winner-take-all scenarios, and Graham predicts this gap widening:

Will technology increase the gap between rich and poor? It will certainly increase the gap between the productive and the unproductive. That’s the whole point of technology. With a tractor an energetic farmer could plow six times as much land in a day as he could with a team of horses. But only if he mastered a new kind of farming.

I’ve seen the lever of technology grow visibly in my own time. In high school I made money by mowing lawns and scooping ice cream at Baskin-Robbins. This was the only kind of work available at the time. Now high school kids could write software or design web sites. But only some of them will; the rest will still be scooping ice cream.

The larger trend here is that:

Jobs are harder to find, easier to invent.
Thomas “the world is flat” Friedman has a great column about this theme that ‘jobs are getting harder to find, but easier to invent’:

I’VE done a lot of television book interviews lately, and I continue to be struck at what a difference there is in the technology in just a few years’ time.

Here is a typical evening at a major cable TV network: arrive at Washington studio and be asked to sign in by a contract security guard. Be met by either a young employee who appears to still be in college or an older person who seems to have hung on with tenure. Have your nose powdered by that person. Have your microphone attached by that person. Be positioned in the studio chair by that person, and then look directly into a robotic camera being manipulated by someone in a control room in New York and speak to whoever the host is wherever he or she is. That’s it: one employee, a robot and you.

Think of how many jobs — makeup artist, receptionist, camera person, producer-director — have been collapsed into one. I raise this point because there is no doubt that the main reason for our 9.1 percent unemployment rate is the steep drop in aggregate demand in the Great Recession. But it is not the only reason. “The Great Recession” is also coinciding with — and driving — “The Great Inflection.”

In the last decade, we have gone from a connected world (thanks to the end of the cold war, globalization and the Internet) to a hyperconnected world (thanks to those same forces expanding even faster). And it matters. The connected world was a challenge to blue-collar workers in the industrialized West. They had to compete with a bigger pool of cheap labor. The hyperconnected world is now a challenge to white-collar workers. They have to compete with a bigger pool of cheap geniuses — some of whom are people and some are now robots, microchips and software-guided machines.

I wrote about the connected world in 2004, arguing that the world had gotten “flat.” When I made that argument, though, Facebook barely existed — and Twitter, cloud computing, iPhones, LinkedIn, iPads, the “applications” industry and Skype had either not been invented or were in their infancy. Now they are exploding, taking us from connected to hyperconnected. It is a huge inflection point masked by the Great Recession.

It is also both a huge challenge and opportunity. It has never been harder to find a job and never been easier — for those prepared for this world — to invent a job or find a customer. Anyone with the spark of an idea can start a company overnight, using a credit card, while accessing brains, brawn and customers anywhere. [emphasis added]

This isn’t the only employment trend afoot, but it’s one of the most significant.[5] It’s hard to disagree with Friedman’s advice, but for one thing:

Half of all people are below average(!)
Friedman’s advice is not likely to be feasible for, or read by. the average person. And, save for exceptional (and fictional) havens like Lake Wobegone, half of all people are below average.

Fred Reed, a curmudgeon if there ever was one, grumbles about this lack of realism among the op-ed class:

Letting Them Eat Cake

When I read columnists or listen to talking heads on the lobotomy box, they strike me as delusional. What are these decapitated crania prattling about? From what morgue did they escape? What country are they from? Certainly not the America I grew up in.

I conclude that they suffer from Commentator’s Disease, which consists in the confluence of several disabilities, the first being high intelligence. Washington, being a center of power, politics, graft, and corruption, attracts the very bright. An acquaintance once said, “Inside the Beltway, you assume that everyone is in the ninety-ninth percentile.” She meant that in the circles in which she moved, this was true. The city is rife with the very bright, most of them being invisible: campaign planners, pollsters, lawyers, scientists from NIH. The class includes many of the talking heads, the Pat Buchanans and Charles Krathammrs. They may be liberal or conservative, depending on their individual defects of character, but they are way smart.

The exceedingly intelligent form a social class seldom mentioned but inordinately influential. They are not recognized as what they are because they do not append IQs to their by-lines. As a quite ordinary example, consider the magazine The American Conservative, with many of whose writers I have some familiarity. The publisher, Ron Unz, studied theoretical physics at Stanford after graduating from Harvard. Bill Lind, Pat Buchanan, Taki, Steve Sailer, Kara Hopkins, John Derbyshire—I doubt that there is an IQ below 140 in the bunch. The same could be said of many other political slicks, left or right.

These people are not intellectual snobs. In the crowd they run with, they are average. The problem with them is that they hang out together. People tend to associate with those with whom they have things in common. At a hole-in-the-wall in DC like the Zoo Bar on upper Connecticut you may find a table of eight people in jeans and running shoes—Washington is about power, not style—consisting of a biochemist, an editor of a technical newsletter, a talking head you’ve seen, and so on, all highly educated. This clustering together by intelligence is sometimes called “cognitive stratification.” It exists, big time. The clusterers are by and large decent people, not full of themselves, and mean well.

But.

But they don’t know what they are talking about in important respects. They think the Beltway contains America.

The second symptom of Commentator’s Disease is relative prosperity. The nature of Washington is that the very bright usually do well financially. I don’t mean that they are rich, though some are, but that they manage to find secure jobs in government or with law firms or they invest wisely or, in the case of commentators, angle for well-paid gigs with syndicates or networks. Usually there is nothing crooked in this. They are simply smart enough to work the system, and they live where the system is.

The aggregate effect of their brains, security, and isolation is that they are out of touch with the country as it really is. They do not know the bleak strip-development of Route 1 South toward Fredericksburg, red dirt and franchised cholesterol chutes and roaring traffic. Here the diabetic veteran lives in a decayed residential motel and makes his way on crutches to the down-scale diner where he drinks beer and waits to die because he hasn’t got anything else to wait for. (The example is not hypothetical.) Here the aging waitress gets to the diner somehow, aching with arthritis. “Too tired to work, too poor to stop.” I knew this woman. She is much of America. You don’t see her at the Zoo Bar. She has never been to such a place.

I often see victims of Commentator’s Disease arguing against the minimum wage on abstract grounds of economic theory. It is what commentators do—bandy abstractions, railing for or against Keynes, assaulting their ideological opponents with pointed phrases. They have never had to do the arithmetic of forty times the minimum wage minus taxes minus bus fare minus rent and gotta pay the cable because it is the only thing they have after work. They have never had to choose between the electric bill and a new coat as winter comes on.

The commentators don’t realize that not everybody is like them. Those with IQs of 140 and up (130 gets you into Mensa, I think) unconsciously believe that anything is possible. Denizens of this class know that if they decided to learn, say, classical Greek, they could. You get the book and go at it. It would take work, yes, and time, but the outcome would be certain.

They don’t understand that the waitress has an IQ of 85 and can’t learn much of anything.

Conservatives think in terms of merciless abstractions and liberals insist that everyone is equal. Not even close. Further, people with barely a high-school education and low-voltage minds regard any intellectual task with utter discouragement.

Some commentators urge letting people invest their Social Security taxes in the stock market. To them it is a question of abstract freedom and probably the Federalist papers. The commentators are smart enough to invest money. I’ll guess that at least half the population isn’t. Go into the tit bar (does it still exist) in Waldorf, Maryland, and ask the dump-truck drivers and nail-pounders what NASDAQ is.

Liberal commentators want everyone to go to college, when about a fifth of people have the brains. Conservatives think that people can rise by hard work and sacrifice as certainly many people have. Thing is, most people can’t. Commentators only see those who made it.

The tendency of the Beltway 99th to live in an imaginary world, of conservatives to think that everybody can be a Horatio Alger, of liberals to believe that inequality arises from discrimination, guarantees wretched policy. Those who can do almost anything need to recognize the existence of those who can do almost nothing. Few of the latter are parasites. The waitress has worked all her life, as has the truck driver. They ended up with nothing.

Which is easy to do. A girl marries her high-school sweetheart in Busted Hump, Tennessee and he goes to work for the local pickle-bottling plant, which switches to hiring people as independent contractors to avoid paying benefits. Neither of the pair is real bright, just ordinary Americans trying to make a living. They live paycheck to paycheck because they don’t know how not to. Neither is lazy. They just don’t know how to start the next Microsoft. He dies of a heart attack at 45, she can’t make the mortgage, and…she is well and truly screwed.

At the Zoo Bar, they have great wings and some really good walk-in blues bands, and what you have to understand about Keynes is….

Commentator’s Disease.

Ultimately, I think Reed is right– life is tough for those on the left half of the bell-curve, poverty imposes its own cognitive costs, and a lot of people are simply incapable of following advice like Friedman’s.[5] In an increasingly ultra-darwinistic economy, the ungifted and unmotivated are pretty much screwed. And that’s scary, since…

In the long run, we’re all unemployable
This is deep crystal ball territory, but it seems clear to me the way the wind is blowing: sooner or later we’re all going to be on the left half of the bell curve, driven from our jobs by smarter robots and software. The automation trends that started in agriculture and manufacturing have spread to such rarified fields as translation, chess, and legal and medical research. Whatever rationale people have for why an algorithm can’t replace them is, regardless of field, relentlessly eroding.

Let me be clear: algorithms are sneaking up on your job.

IBM’s Watson and Apple’s new Siri digital assistant are essentially early prototypes of AI, and as time goes on they’ll only get better and more generally-capable, able to replace and improve more sorts of traditionally-human tasks. Over the next ten years many such jobs are going to disappear, never to return. Some of the people displaced will read Friedman and figure out how to thrive in this new “winner-take-all, darwinian, creative destruction economy”, but let’s be honest. Most won’t.

Thresholds, the unemployable, and a new social contract
Vernor Vinge has a quote that I’ve always found striking: “The work that is truly productive is the domain of a steadily smaller and more elite fraction of humanity.” To wit, as time goes on, there will be more and more total wealth, but a smaller and smaller fraction are actually creating the wealth. It’s not necessarily that the poor are lazy: often it’s that they really have nothing to offer, economically speaking. There are jobs, but not for them. (Or their jobs are subsidized– as when the average Walmart employee receives ~$1,000 of Medicaid, food stamps, and cash assistance from the government.)

So ultimately, how do we help our fellow citizens deal with this trend? When 25%– then 75%– of humanity have absolutely no conventionally-marketable skills, are absolutely not economic to hire (vs robots and software), what do we do? We can offer platitudes about education, retraining, and inventing your own job, but that’s not going to hold back the tide very long. There’s a trend here: we’re nearing the end of the “living wage era,” where we could talk about ‘everybody having the right to a living wage’ because this wasn’t too far from the fundamental economic realities. It was nice and egalitarian while it lasted, but what’s next?

Should society keep expanding social programs to permanently support this growing pool of unemployables? Should we keep subsidizing them (and Walmart) through aid to low-income workers? The Romans bought domestic peace with bread-and-circuses; will we need to take that route also? (Aren’t we already?) Or should we e.g., just keep expanding the DMV and TSA to give this class of workers a place to harmlessly soak up government dollars while feeling productive? (I say this only half in jest, since it appears to be the road we’re currently on.)

Moreover, given the social unrest possible once the unemployed/unemployable grows past certain thresholds, can we afford not to?[7]

I’m not being a snob; on a long enough timeline, I think we’re all in this boat.

Will OWS radicalize?
However one slices it, I think it’s clear that job economics will tighten. The “Occupy” groups are the vanguard in the populist pushback on this, and are spot on with some of their complaints.

It’s not always easy to see, but the political pendulum swings back and forth with tremendous force. We’re in a part of the cycle where we can see very keenly the power and abuses of large multinational corporations. It won’t always be like this: the OWS movement may be the start of powerful modern populism, cycling into focus just when the long-term feasibility of a “living wage for everyone” is naturally and irreversibly eroding.[8] It’s an interesting contradiction, and one which will bring its own excesses. With time we may remember parts of the current economic era fondly.

One danger I see is that this increasing technological displacement and growing pool of unemployables could strengthen, poison, and radicalize the OWS movement, giving it a louder voice and a weaker argument (re: living wages) at the same time. I think it’s a real possibility. We’ll need to figure out some sort of a fair solution to all of this before things turn ugly. I just don’t know how yet.

Interesting times.

Notes:

[1] Is there anything good about Goldman? In short, yes. Aside from the usual dealmaking, capital allocation, and underwriting tasks investment banks perform, Goldman’s known for being willing to make new markets — being willing to serve as a middleman or counterparty… and sometimes both(!) on unusual sorts of wagers (such as CDOs). This isn’t always economically healthy, as it can increase market complexity faster than regulators (or participants) can understand what’s happening, but being able to effectively buy or ‘short’ certain behaviors can also bring substantial market efficiency.

[2] Here’s Taibbi again, on Goldman and financial regulations:

The way I look at it is that this isn’t really a financial story, it’s a political story. It’s about how power works in America. They’ve figured out a way to hide power in these little regulations and the minutiae and it’s like a gigantic bulwark that separates ordinary people from those of influence. So in order to be a journalist you have to go through that whole maze. You need space and you need time, and nobody has it anymore….

   Do you still follow Russian politics? They’re gearing up for an election. I tend to envision Putin placing Medvedev on a platter and eating him on live television, or something of the sort.

They’re just your basic third-world kleptocracy—which is where everybody is headed. Well, everybody who still has a functioning government.

   Elaborate.

I think people are going to realize what a blip on the radar American-style democracy in the 20th century was. A big middle class that had a huge powerbase, financial interests, bosses giving benefits… all those things. It’s just a little blip in history. For the most part, concentrated wealth will make all the decisions and everybody else is dictated to.  

When it’s not uncommon for large, profitable corporations to pay their CEOs more than they pay in federal income tax, I think we have to take this notion of a sea change seriously.

Will OWS turn to economic vigilantism as a force for change if political disobedience fails? And if they do, can we blame them?

[3] Many liberal groups would love to use OWS to advance their goals; while I was at Occupy LA there were activists (mostly racial and environmental) who were trying hard to get their pet causes into the mission statement. I think it’ll take a lot of energy to fend off opportunists and keep focused. The Democratic Party in particular is drooling over the possibility of co-opting OWS (just as the Tea Party has been co-opted), much to the movement’s irritation:

The corporate media is anointing a false leader of the Occupy Movement in Van Jones of Rebuild the Dream.

The former Obama administration official, who received a golden parachute at Princeton and the Democratic think tank Center for American Progress when he left the administration, is doing what Democrats always do—see the energy of an independent movement, race to the front, then lead it down a dead end and essentially destroy it. …

At Occupy Washington, DC, we recognize that putting our time, energy and resources into elections will not produce the change we want to see. What we need to do right now is build a dynamic movement supported by independent media that stands in stark contrast to both corporate-bought-and-paid-for parties.  

Democratic operatives want to steal the energy of the Occupy Movement because they do not have any of their own.

[4] I personally think humans have a really good ‘unfairness detector’ module. Give us a complex math problem, and most of us will wilt; give us a card game (of similar abstract complexity) where someone’s cheating, and many of us will figure it out. But again, our capacity here is not infinite.

[5] A large factor in wages is simple supply-and-demand. People get paid more for doing what the market needs. And employment supply-and-demand is notoriously dynamic. A friend relates that the boom in domestic oil exploration has led to people with degrees in petroleum geology landing jobs paying over a million dollars right out of college. People who are willing to move to North Dakota and drive trucks for the oil economy are making over $120k. Meanwhile, people with degrees in English Literature and Social Work are competing with hundreds of other applicants for starting salaries in the low 30ks, salaries that look even bleaker once today’s ridiculous student loan payments are factored in. An average of 40% of college grads resort to jobs that don’t require degrees, a number which is steadily rising.

Is this fair? Do people who choose to study e.g., art history deserve to make living wage working in their field? I think “deserve” is a loaded term here. The top 1%-.1% of a field will always be able to write their own ticket, but supply-and-demand dynamics will drive compensation for the rest, with little regard for concepts such as a “living wage”.

Of course, supply-and-demand doesn’t happen in a vacuum – policy plays a huge role in creating the employment context it emerges from. We could learn a lot from China in how to nurture emerging domestic industries (or at least not smothering them on the altar of the status quo). Part of this is willingness to experiment– China is now limiting college majors which are correlated with high post-graduation unemployment, an interesting move. Immigration policy matters. Education matters and we could be doing better (though perhaps we tend to be too hard on ourselves, mistaking demographics for quality of instruction).

[6] The unspoken assumption of the Friedman school is that once we provide good, rugged, and cheap internet devices to the third world, they’ll be able to lift themselves out of poverty by educating themselves, learning foreign languages, science, programming, and design via something like OpenCourseWare, and joining the global economy. It’s a great idea, certainly worth doing, and will work for some. However, regardless of where one stands on IQ as a primary component of economic potential or a lagging correlation which rises with prosperity, I think it’s betrays an overenthusiastic estimate of the quick malleability of human capital, and I also doubt the Vast majority will be able to bootstrap before algorithms and robots eat their niches.

[7] There is precedent here: many people have argued that welfare got its start essentially as protection money paid to those in LA’s slums, to give them something to lose so they wouldn’t burn down the place.

[8] My father, on economic policy:

Natural selection is the way things work, but I should say that I’m not at all comfortable with the results – when it comes to people.  It is easy to see that the benefits of living in this country are unequally distributed, and, as you point out, that can be beneficial.  I think we need to ask some questions, however.  Who “owns” this country?  How much control should someone who wants to work hard and make lots of money have over someone who does not wish to devote his life to making money?  The two are not separate, as one will drive up prices of goods and that will affect the other – right?  Does one person have the right to produce products offshore and sell them freely here in the US, even though it makes the labor of the other person much less valuable?  And, does the laborer have the right to band together in a union to gain advantage over other workers – using the political process to mandate that advantage?  If you take all the laborers here in the US, do they have the right to demand that manufacturing jobs be returned to the US if the investors wish to sell the goods here?  (This would simply be a much larger labor union, wouldn’t it?)

Politics is the art of taking money from one group and giving it to another.

…

And, I think we need to have a discussion about not only the benefits of living here, but we need to talk about the responsibilities too – on both sides of the spectrum.

Edit, 4-4-12: Mindflash has a light but fun infographic: Can your job be done by a robot?

Edit, 4-11-12: A friend has an interesting point on my Inflation, briefly post:

4. Our understanding of the expanding wage and wealth gap my very well be flawed. There may NOT be a gap being created or expanding, like the statistics show. If, for a sustained period of time, there are differential inflation rates for the different income segments of the population, then there can be differing wage or wealth growth without there being a gap in REAL wages or Wealth being created.

Edit, 4-29-12: From The Atlantic, a piece on How Computers Are Creating a Second Economy Without Workers:

Let’s do some arithmetic.

The Gross Domestic Product for the United States in 2011 was around $15 trillion. There are a little over 130 million non-farm employees. So each worker adds a little over $100,000 to the domestic output. The numbers are quite different for a Google employee. Google has a little more than 32,000 employees and its $38 billion in revenues means it generates about $1.2 million per employee. The numbers are similar for Facebook.

Walmart has some two million employees, and annual sales of around $200 billion. Given that many work part-time, I figure that the company has sales of around $100,000 per employee. With 56,000 employees in 2011, Amazon generated a little over $800,000 per employee.

Here’s the challenge: In the past, every million-dollar increase in economic output generated on the order of ten jobs. In the future, in the productive Second Economy, it may generate only one or two.

When I listen to politicians and policy makers explain how they will create jobs in the future, I never hear mention of the Second Economy. If a large portion of future economic growth will occur in the rapidly expanding and highly productive Second Economy, where will the jobs come from?

The author suggests in a second installment that a ‘repurposing construction boom’ could provide significant employment, as a changing economy will lead to different requirements for city layouts, office, industrial, and residential needs, and so on.

Here’s the idea: construction will be the engine for a much larger fraction of job growth in the Internet Age than we are currently anticipating. I call it a repurposing construction boom. … The faster and cheaper we can move information , the less retail, factory, and office space will be required on a per capita basis.

This means that much of the existing space will eventually be repurposed. Office buildings and shopping centers will be torn down and become locations for apartment buildings, possibly even parks. …

Just as Henry Ford may not have predicted the rise of drive-in movie theaters when he invented the Model T, the Internet Age will produce changes to our physical landscape we can’t yet envision. And other changes that we do expect might never happen, or happen in a different way. The urban transformation may not take the form that I have suggested. But what I am certain will happen is that the Internet will drive the physical restructuring of society.

However, with progress in robotics and the technology of construction (e.g., ’3d printing a house’) it’s not clear this will mean more jobs for the unskilled.

(1) physics is ultimately the foundation for basically everything,

(2) when we get down to details it’s pretty darn weird, and

(3) while most fields have moved away from metaphysical questions and toward inaccessible problems of complex emergence, there are still cool, unsolved, fundamental mysteries in physics.

People seem really engaged by the weirdness and mysteries in theoretical physics, even to the point of feeling an ownership interest in them, and I think that’s awesome.

And so with this year’s Nobel Prize in Physics announced, I wanted to give readers a quick rundown on current Big Mysteries in Physics. It’s not a comprehensive list[1], but I argue that most other questions will ultimately trace back to these three.

1. How do we combine General Relativity and Quantum Dynamics?

Right now Physics rests uneasily on two fundamental theories. General Relativity deals with relationships between spacetime, velocity, and gravity (generally speaking, properties associated with large objects) and is amazingly predictive at what it does. Quantum Dynamics deals with sub-atomic particles, the quantized nature of the strong, weak, and electromagnetic forces, and the weird statistical rules these things obey (generally speaking, properties associated with very small things), and is amazingly predictive on quantum scales. We have one theory for big things like planets and spaceships, and another for small things like electrons and quarks.

The trouble is, the math– and metaphysical assumptions about reality– of these two theories are very different, and we don’t have a good way to fuse them together to talk about things like black holes or the big bang, things which straddle both the quantum and relativistic. Most physicists find the situation very troubling, not to mention deeply ugly, since it feels like the universe must have a single set of rules, not two. Presumably, if we found a more general model which explained each theory as a special case of a more general system, all sorts of little mysteries in physics might solve themselves (just like the theory of DNA solved lots of mysteries in biology). String theory, quantum gravity, and other, even more esoteric field theories are attempts at unification, but to date no attempt at unification has made any successful prediction that departs from what each separate theory suggests.

2. What is Dark Matter?

There are two huge fudge-factors in physics. One is Dark Matter– a hypothetical sort of matter that interacts with other matter only via gravity (“dark” means “we can’t see it”). It was introduced in 1934 to explain why galaxies rotate so fast: according to our equations, without this fudge factor, many galaxies rotate fast enough that they should simply fly apart. However, instead of disappearing quietly like fudge factors often do, we still need it today to explain galactic dynamics and certain other observations. Most cosmologists agree that it’s very probably not just an artifact of some mistake in our calculations, but some very real and very mysterious type of matter.

What we know: based on our calculations ~83% of all matter is “dark”. We think this dark matter is found in most or all galaxies, and there’s a good chance some passed through you as you read this. There are conflicting theories about where it’s most heavily concentrated– some models have it primarily concentrated in the dense center of galaxies, some have it more spread out, some in a halo. We’re pretty sure, whatever it is, that dark matter is “cold” — i.e., not moving at a significant fraction of the speed of light. There are a lot of experiments trying to conclusively detect dark matter, either (1) from its gravitational effects or (2) directly, if dark matter happens to occasionally interact (‘weakly interact’, in the lingo) with normal matter. (A shoutout here to the Sanford Underground Laboratory, which is in the running, and within spitting distance from my folks’ house.)

3. What is Dark Energy?

The 2011 Nobel Prize in Physics was awarded for discovering a mystery: that our universe’s expansion hasn’t slowed down since the Big Bang. In fact, it’s actually sped up. And we have no idea why.

The standard assumption prior to 1998 was that our universe was either going to contract due to gravity (the “big crunch”), or was somehow exactly balanced (Einstein’s static universe hypothesis), or that the initial energy from the Big Bang would keep the universe expanding, albeit ever more slowly as gravity tried to pull everything together.

An examination of a specific type of star explosion– Type Ia supernovae, which due to various dynamics all explode with roughly equal energy and brightness– provided a basis for an historical record of the universe’s expansion. Since we know how much energy is released in these explosions, we can calculate how far (which is another way of saying ‘how old’) it is based on how bright it is for us. Likewise, we can tell if it’s moving toward us since the light will be “blueshifted”, or if it’s moving away from us, it’ll be “redshifted” (think of how a siren’s frequency changes depending on whether it’s moving toward or away from you).

What we found when we put these things together was that basically everything is moving away from us, but– here’s the kicker– the closer, newer stars are moving away from us proportionally faster than older stars. The universe is not only expanding, but the expansion is accelerating.

Cosmologists don’t know what’s causing this. The convention has been to refer to it as “dark energy” since the cause of the expansion is generally fudged-in as an energy term in our equations, but we don’t really know if it’s a hidden form of energy, an emergent property of space, or something even more esoteric. There are theories, but they tend to be mathematically inelegant – and given our lack of a high-resolution expansion timeline, remain little more than untested guesses. If it is actually energy, there’s a lot of it:

Pretty large for a fudge-factor. Image credit: NASA.

A shameless plug for a pet theory:

I don’t know what Dark Energy is, but I do actually have a guess. If you’re in the mood for some cosmological speculation, and particularly if you’re in a position to give feedback on such, I encourage you to check it out. Like any new theory, it’s probably wrong– but based on my reading of the field, I don’t think it’s more likely to be wrong than other theories on the topic, and throwing one’s hat in the ring is how science progresses.

A Suggested Model for Dark Energy.

[1] Another major mystery is why there’s way more matter than antimatter in the universe. “Antimatter” sounds so weird and esoteric, but it’s actually rather common– there’s probably lots of antimatter popping in and out of existence in the room you’re in now. We commonly create antimatter in labs, and it actually forms the basis for tech like PET scans. It’s just that matter is WAY more common, and there’s no a priori reason we can see that this should be the case. I talked a bit about this in my 2008 obituary of John Wheeler.

In practice, even though we have billions of nucleotides, our DNA cannot follow billions of genealogical lines. Recombination over 30 — 40 generations does not divide chromosomes down to individual nucleotides. In the medium term, most human DNA is separated by recombination hotspots into lengths of around 50 kilobases. Across very short spans of 30 generations, DNA is for the most part inherited in chunks of hundreds of kilobases or longer. So dividing six billion nucleotides by 50 kilobases yields a number of around 120,000 ancestral lines at most from which any individual inherits his or her DNA. Recombination will increase this number somewhat further and further back in time, but not nearly so fast as the doubling of possible ancestral lines in every generation. This means that the vast majority of your ancestral lines more than around 17 generations ago have left no DNA to you whatsoever.

Granted, this is relative to the massive redundancy in our family trees– humankind is one huge, partially-inbred extended family. I.e.– if you go back 40 generations, you have over a trillion great-great-great-(etc) grandparents. There weren’t a trillion people alive in 1000AD, so a lot of those slots were filled by the same people.

Most importantly, I want to get people thinking about what emotion is, without cop-out references to ‘happiness neurochemicals’ or ‘regions of the brain which control emotion’. When it gets down to it, those are just ways of saying, “we don’t know what emotion is.” For instance, using these poor, correlative explanations of emotion, it would seem we could build a computer that could feel happiness by dumping some dopamine extract on its processor, or make it feel pain by fusing some human nociceptor nerves onto the motherboard. Clearly this is not the case. If we want to deal with emotion at anything except a trivial level, we need to dispense with correlative explanations and move toward an information-theoretic approach, to be able to explain affect in our brains as a special case of more general equations.

So what is emotion? I suggest we look to the mathematics of music theory for a possible answer.

(This is really technical and hypothetical; if you don’t enjoy mathematics and speculative neuroscience and would prefer alternative entertainment, why not check out these captioned pictures of cats instead?)

I. A structural homologue between music and thought: on consonance, keys and chord structures.

In short, I suspect that we’ll find the structure of frequency patterns in music to be rough reflections of the structure of frequency patterns within our heads. We’ll be able to look at brain frequency patterns via many of the same types of signal analyses we normally apply to music. More specifically, many brain frequency patterns will have identifiable chord structures and music-like rhythms, and these music-like structures are what inherently encode affect in the brain.

In other words, the direct, mechanistic cause of happy/sad affect is that the frequency of one’s neural firings is arranged in a strongly major/minor chord pattern. Being sad means having thoughts which are literally in a minor key– i.e., the same sorts of mathematical ratios between frequencies that are universally present[1] in minor chords will also be present in the neural firings of someone who is sad. (And arguably, to suffer from Depression is to have one’s brain literally tuned to a minor key.)[2] Not all thoughts have a clear emotional counterpart, but the presence of these ratios and music-like patterns within thoughts is necessary and sufficient to cause affect.

More generally, I think we’ll unearth that music theory is actually neuroscience in disguise, and we’ll need to borrow liberally from the mathematics of music to accurately model the mind. To put this slightly differently– music is mathematics, and our brains’ frequency dynamic is mathematics, and I suspect the mathematics of each are essentially the same. E.g., the defining, characteristic mathematics of a happy song are literally the same as the defining, characteristic mathematics of a happy mood.

So given that this ‘structural homologue’ hypothesis is true– what kinds of mathematics might neuroscience end up borrowing? I’d point to the following:

(1) the specific, mathematical ratios which define, organize, and constrain music (my hypothesis: these ratios inherently generate analogous emotion when in the context of neural activity);

(2) the mathematics of resonance, acoustics, and dissonance (my hypothesis: these richly describe brain region system dynamics and the neurophysical dynamics of mood);

(3) the modeling of musical structure as geometric constraints within a non-euclidean space (my hypothesis: these constraints will imply bounds on the sorts of neural activity which give rise to emotion).[3]

I may appear to be making a metaphorical, explorative connection between thought and music; I’m not. I’m saying thought and music are literally the same things, just in different contexts, and if we translated the patterns of frequencies in our neurons onto sheet music, some of them (the ones that have associated affect) would literally be in major and minor keys. Insofar as they resemble music, these patterns would carry affect. These “songs” would be terribly, horribly complex, and it will be exceedingly difficult to define or isolate singular thoughts, even given proper frequency normalization across regions and much better measurement technology– but I predict that as the years pass and we learn how to slog through the complexity, this is what we’ll eventually find.

Caveats: of course, a great deal of how we interpret a chord is context (both musical and cultural), and our emotional reaction is not determined by the chord. “Major=happy,” “Minor=sad,” and “consonance=pleasure,” “dissonance=pain” is of course a gross simplification of a very complex system— a more nuanced theory would include rhythm, chord progression, and novelty, since these are also critical in music and of course the brain has myriad anti-feedback loops. Just as context is key in how we interpret music, so too it will be in neural patterns. Additionally, Maher (1976), among many others, suggests that the physiology of musical interpretation involves some cultural plasticity. However, our emotional reaction is not independent of a chord either, and I’m building my hypothesis of a structural homologue around this core of physiologically-dependent interpretation.[4][5]

Another way to put this is that peoples’ general physiological responses to music are tightly coupled with their general emotional landscapes. A difference in one means a difference in the other. This does suggest that one could meaningfully ‘type’ different emotional landscapes via measuring peoples’ brains’ response to different types of music.[6] An endeavor fraught with complexities, surely, but interesting to consider.

II. A three-variable model of affect:

I would offer the following: all else being equal,

(1) positive (‘major chord’) emotion feels better than negative (‘minor chord’)[7][8];

(2) any coherent (non-dissonant) emotion feels better than no coherent emotion;

(3) musical-style consonance in neural patterns is inherently pleasurable; dissonance within or between neural patterns is inherently painful.[9]

There are more factors in play (just as there are more factors in music theory), but these are the ones that appear to me as the most dominant w.r.t. affect. These factors each pull in a slightly different direction, and to wax slightly existential, this leads to behavioral tradeoffs and illuminates a great deal about the human condition.

III. The bigger picture: toward a psychophysical law?

To go even further, putting on my Philosopher’s hat, this is a possible start on a psychophysical law. What is a psychophysical law? Essentially it would be a translation function between the brain and qualia. “When X (in the material world), then Y (in the world of sensation/emotion/thought)”. We don’t really know any yet, but we know they’re out there.*

*I tend to agree with David Chalmers (and perhaps he’d even agree with my paraphrase) that ‘qualia arise from computation within systems which are above a certain threshold of a certain sort of organizational complexity’. My hypothesis is an attempt to quantify how the frequency dynamics of a certain type of such a system constrain the associated qualia.

With something this abstract, examples are really important. Consider the following questions which we lack the answers to:

To answer these sorts of questions, we need psychophysical laws (like the one I’m proposing). Moreover, such laws are absolutely necessary for such tasks as

At any rate, I’d like to extrapolate my ‘chord theory of emotion’ to all computational systems, and subsume the human-specific stuff under this. I.e., given that this chord theory IS right, then… it’s not a quirky biological coincidence that certain relational frequency structures within computational systems lead to qualia with certain properties, or that coherence feels good and dissonance feels painful, but rather a specific realization of a more general, fundamental, invariant, and universal psychophysical law.

Yeah, I know it’s a weird topic. But it’s important!

*I think understanding the universe’s psychophysical laws is as important to designing a friendly AI (FAI) as understanding aerodynamics and gravity is to designing a safe aircraft. You can muddle through for a while without a good, formal theory, but it’ll probably result in a terrible accident at some point. I don’t think people in AI research (or even FAI research) see this point.[10]

[1] What about atonal societies? I suspect, following this theory, that they experience emotions differently than those from tonal societies. Having said that, (1) atonal music isn’t devoid of structure, and (2) perhaps there are cognitive-functional reasons why most societies (and/or the most successful societies?) are tonal.

[2] Arguably, there are three types of characteristic affect in Depression: one is sadness (thoughts in a minor key). Another is feeling nothing at all (dullness, incoherence, emotional blunting). A third is strong dissonance within ones brain (different neural patterns fighting for dominance, which is inherently painful).

[3] On (3), ‘music structure as geometric constraints within a non-euclidean space,’ I’m reminded of this post by John Hawks:

The lead report in Science this week was this paper by Dmitri Tymoczko, titled “The geometry of musical chords”:

A musical chord can be represented as a point in a geometrical space called an orbifold. Line segments represent mappings from the notes of one chord to those of another. Composers in a wide range of styles have exploited the non-Euclidean geometry of these spaces, typically by using short line segments between structurally similar chords. Such line segments exist only when chords are nearly symmetrical under translation, reflection, or permutation. Paradigmatically consonant and dissonant chords possess different near-symmetries and suggest different musical uses (Tymoczko 2006:72).

Like a lot of things mathematical, the mathematical description of this is fairly distant from everyday experience. Cosmic Log provides a pretty good summary of the mathematical connections. This is pithy:

For years, string theorists have used music as a metaphor for fundamental particles, and now Tymoczko is using the mathematics of string theory to understand the fundamentals of music.

The next couple of paragraphs capture the essence of the work:

The math makes it easier to understand objectively what great musicians and composers do in their head. “When you sit down to interact with a piano, you’re actually interacting with a non-Euclidean space, because there are many different ways you can play a C-major chord on a piano,” Tymoczko said.

He said orbifolds capture the multidimensionality of music: how harmony interacts with counterpoint, how chords are connected with each other, even how notes are arranged “to minimize the amount of effort that musicians have to make when moving from chord to chord.”

I think it helps to read a few different descriptions, and so I’m also linking the perspective in Science by Julian Hook, which includes some history, showing why Tymoczko’s paper is part of a long tradition of mathematical application to music:

Mathematical music theory, although terra incognita to practicing musicians and even to many professional music theorists, has in recent years blossomed into a sizable and multifaceted industry. Pitch-class set theory (3), the study of a discrete 12-note quotient space, was developed as a means of confronting the analytical challenges posed by “post-tonal” music of the 20th century, whose harmonic materials are more varied and complex than those in most earlier music. Diatonic set theory (4, 5) investigates the subtle and beautiful relationship between the 12-note chromatic scale and diatonic scales such as the C major scale, with seven unequally spaced notes per octave (a scale type of great importance in many styles of music). Scale theory (6, 7) studies structural properties of scales and their subscales more broadly, allowing variation in both chromatic and diatonic cardinalities and occasionally engaging considerations of tuning and acoustics.

…

A particularly active area is neo-Riemannian theory, which synthesizes modern group-theoretic techniques with inspiration drawn from the work of the prolific German musicologist Hugo Riemann (1849-1919) and his contemporaries. In its basic form (9, 10), neo-Riemannian theory investigates certain transformational relationships among the 12 major and 12 minor triads in ways that are algebraically elegant, musically suggestive, and readily visualized in various forms of a graph known as a Tonnetz (tone network), in which the harmonic path traced by a musical composition may be plotted (Hook 2006:49-50).

In other words, musical progressions form paths or shapes in multidimensional spaces. Music that is part of the classical Western tradition actually falls within a fairly restricted set of possible paths; other musical traditions also form paths that to a greater or lesser extent overlap (although the dimensionality of the spaces may be different for different systems).

Eventually we may move away from the ‘thoughts are music’ homologue and discuss affect in terms of properties of thoughts’ shapes in multidimensional spaces, but that day is far away, and such a complex understanding will have music theory as its foundation.

[4] An alternate formulation of the general form of this hypothesis might deal with a structural homologue between consonance and dissonance in music and in the brain– e.g., the same patterns of consonance and resolved dissonance in music that we find pleasurable also obtain in our brain frequencies when we experience pleasure.

[5] What about people with autism who don’t experience any emotional expression from music? I would suggest that the music may get ‘summarized’ by their neural circuitry, but unlike ‘normal’ people, the musical pattern doesn’t actually enter the brain in any deep fashion where it can resonate.

[6] I think the cultural version of this — that differences in musical tuning and musical theory between cultures implies difference in emotional landscape — is of particular interest.

[7] I say this with the caveat that brain tuning also matters. Some peoples’ brains are tuned differently, and thus different types of patterns will create the least dissonance. Or perhaps someone’s brain may be tuned to a predominantly major key, but minor-key songs are pleasurable for the novelty.

[8] It could be that there’s nothing less inherently pleasurable about minor chords (except a slightly higher internal dissonance factor?), but instead our brains are designed to create dissonance when they detect minor chords in certain brain regions, in order to elicit action for external change. Our brain wiring only resolves this dissonance when the minor chords (and the things that caused them) are gone. I would be surprised, but it’s possible. If this is true, we could have a one-variable model of affect (musical consonance > incoherence > dissonance) and chalk ‘major > minor’ up to our specific brain architecture.

[9] I would quantify dissonance as a weighted ratio of LCM(frequencies) to number of frequencies, given a certain threshold of frequency strength.

[10] Perhaps we could partially direct an AI’s behavior by constraining it to a specific emotional range.

Further Musings:

- Few patterns stay pleasurable in the long-term without substantial permutation, due to the brain’s inherent anti-feedback / pro-novelty mechanisms. Dissonance makes signals more resistant to these mechanisms, muddying the waters. But what is the theoretically “most pleasurable” neural pattern? According to this theory, a very pure, coherent major-key pattern with many in-tune harmonics. (This leaves aside the question of rhythm.)

Can we use music theory to say anything about rhythm and affect in the brain? It’s hard to say. Is there anything that makes a rhythm major vs minor? Which rhythms are inherently pleasurable? How does one quantify how much dissonance is inherent in a rhythm, as one can a chord? How about quantifying dissonance in various chords played in various rhythms? These are hard questions. But there’s a hint of a partial answer in the NYT’s exploration of what makes music ‘expressive’ and the concept of natural, inherently pleasurable body tempos:

Anders Friberg, a music scientist at KTH Royal Institute of Technology in Sweden, found that the speed patterns of people’s natural movements — moving a hand from one place to another on a desk or jogging and slowing to stop — match tempo changes in music that listeners rate as most pleasing.

“We got the best-sounding music from the velocity curve of natural human gestures, compared to other curves of tempos not found in nature,” Dr. Friberg said. “These were quite subtle differences, and listeners were clearly distinguishing between them. And these were not expert listeners.”

I wouldn’t be surprised to find these same tempos in other physiological contexts. Moreover, I suspect these tempos will be elegantly derivable from what music we find enjoyable, thus supporting my hypothesis of a structural homologue between thought and music.

- I’m open to the idea (and perhaps metaphysically forced into) that the qualia we experience are only a fraction of the qualia associated with the mass that makes up our bodies. Does a cell have qualia? Likely so, though of a simple sort since it lacks a sense of self, but if it does we can’t feel it. Does this change anything? Perhaps the qualia associated with the cellular strain involved in a heavy-drinking night out on the town is ethically significant. Who knows.

- Is this a theory whose mode of explanation is generalizable to all thoughts, to explain all qualia, across all substrates? I don’t see why not… though I don’t see how yet. But I will be happy if we can just explain emotion via categorizations of frequency structures in the brain.

- Why isn’t music ‘infectious’ for dogs, as it is people? I would suggest they have much different audio translation circuitry– that computationally, a similar thing is going on inside a happy dog and a happy person, but they simply hear differently, and though a dog’s hearing is more sharper, a human’s hearing more accurately conveys structure. Perhaps in a dog’s brain, there just isn’t the neural wiring in place to connect audio-in to the rest of the brain with good signal fidelity. And at some level, there will be a difference in capacity for signal complexity. Alternately, it could be a matter of ‘brain tuning’. (Perhaps we could explore computational space for ‘dog music’ which they would enjoy?) There are many possibilities and it’s hard to say at this point.

- Though we can’t yet measure what’s happening in the brain directly, we can imply things about the structure of thoughts by such proxies as:
-> What sorts of simple inputs create the strongest response?
-> What sorts of patterns resonate the longest?
The answers to these will undoubtedly cluster around evolutionarily adaptive responses, e.g., things having to do with survival and reproduction. But if we control for this, and examine deviations from what evolutionary biology would predict, we may find hints about the structure of thoughts, types of patterns which our brains respond to strongly because they’re written in the internal language of the brain. I think music is a very interesting such deviation, lending moderate support to my hypothesis.

- What is pain? I would move away from the idea of nociceptors and neurochemicals, and focus on topology and frequency dynamics. Specifically, I suggest pain derives from nerve cells specifically set up to create sharp dissonance in the brain if triggered past certain thresholds. These nerves would be linked into the musical topology of the brain so as to be substantially disruptive of any coherent emotion, with different sources of pain distinguishable by the frequency topology of the injection point. I suspect our brains have substantially shaped themselves around this ‘law of psychodynamics’ in order to emotionally incentivize adaptive action.

- It’s not direct evidence for my hypothesis, but I encourage you to consider whether there are any similarly-specific alternative models that explain and predict affect. We know certain sorts of neural patterns give rise to certain emotions somehow, as intrinsically weird as this is, and I daresay my structural homologue hypothesis of precisely how this happens is about as elegant, predictive, and generative a theory as we’re going to get a priori without vastly improved data collection capabilities. My hypothesis may turn out to be wrong, or it may be more correct as metaphor than literal interpretation. But I think a strong case can be made for a very literal interpretation, and that’s the case I push.

- Several establishments are using classical music to drive away hoodlums and malingerers. It’s a clever approach, and arguably evidence for the ‘dissonance is painful’ hypothesis. Presumably classical music is substantially dissonant with whatever’s going on inside young hoodlums’ heads.

Twenty years ago, the British psychologist John Sloboda conducted a simple experiment. He asked music lovers to identify passages of songs that reliably set off a physical reaction, such as tears or goose bumps. Participants identified 20 tear-triggering passages, and when Dr. Sloboda analyzed their properties, a trend emerged: 18 contained a musical device called an “appoggiatura.”

- Why are certain thoughts and emotions apparently contained within certain brain regions and not others? Why are certain thoughts associated with certain neurochemicals and not others? Both are critical questions for understanding the brain. I believe both get down to frequency resonance. In short, the most important functional attribute of brain regions is what kinds of patterns naturally resonate within them; the way neurochemicals change thoughts and emotions is by changing the resonant timbre of certain brain regions.

- There are alternative ways of quantifying what the brain does which might also (eventually) give rise to a scientific metaphysics of emotion: e.g., information-centric theories of mind and computation-centric theories of mind. But I think a frequency-centric theory of mind (involving, e.g., frequencies, chords, chord progression, resonances, constructive/destructive interference, neuroacoustics, etc) can be construed as an interesting special case within either framework, one with many variables already fixed and predictions inherent in its structure. In other words– I suspect other theories to converge on something akin to a frequency/chord/music-centric understanding of emotion as they get more predictive.

What kinds of computation produce emotion? What kinds of computation are inherent in music? What kinds of ordered complexity produce emotion? Is time simply another dimension for such order, or a privileged one? These are difficult questions.

Notable quotes:

“If music confers no survival advantage, where does it come from and why does it work? I suspect that music is auditory cheesecake, an exquisite confection crafted to tickle the sensitive spots of at least six of our mental faculties.”   - Steven Pinker, “How the Mind Works”

Relevant resources:

- Marvin Minsky: Music, Mind, and Meaning.

- Pallesen, et al.: Emotion Processing of Major, Minor, and Dissonant Chords.

Abstract: Musicians and nonmusicians listened to major, minor, and dissonant musical chords while their BOLD brain responses were registered with functional magnetic resonance imaging. In both groups of listeners, minor and dissonant chords, compared with major chords, elicited enhanced responses in several brain areas, including the amygdala, retrosplenial cortex, brain stem, and cerebellum, during passive listening but not during memorization of the chords. The results indicate that (1) neural processing in emotion-related brain areas is activated even by single chords, (2) emotion processing is enhanced in the absence of cognitive requirements, and (3) musicians and nonmusicians do not differ in their neural responses to single musical chords during passive listening.

- World Science Festival 2009: Notes and Neurons: In Search of the Common Chorus. An interesting panel, with topics ranging from the elements of music, relevant regions of the brain, cultural expectations regarding musical scales, physiological reactions to music, and performances by Bobby McFerrin.

- Berridge and Kringelbach, Psychology of Well-Being: Theory, Research and Practice 2011, 1:3: a nice review of the state of neurochemical and brain-region models of happiness.

The brain appears frugal in mechanisms that that are causally sufficient to generate ‘liking’ or magnify pleasure to high levels. These few mechanisms are candidate brain well springs for hedonic happiness. / Compelling evidence for pleasure causation as increases in ‘liking’ reactions has so far been found for activation of only a few brain substrates, or hedonic hotspots.Those hedonic hotspots mostly reside -surprisingly, if one thought pleasure to resideprimarily in the brain cortex – deep below the neocortex in subcortical structures.

… The results of such studies reveal a network of several brain hedonic hotspots, distributed as a chain of ‘liking’-enhancing islands of brain tissue across several deep structures of the brain. The network of separate but interconnected hedonic hotspots acts together as a coordinated whole to amplify core pleasure reactions. Activating one recruits the others as a system (Smith et al. 2011). Each brain hotspot may be merely a cubic-millimeter or so in volume in the rodent brain (and would be expected to be a cubic-centimeter or so in you, if proportional to the larger human volume of whole brain). The small size of each anatomical hotspot indicates a surprisingly localized concentration of sufficient-cause mechanisms for generating an intense pleasure in the brain. The network properties reveal a fragile substrate for pleasure enhancement that requires unanimity across the several parts in order to elevate hedonic ‘liking’ (Pecina 2008; Pecina and Smith 2010; Smith et al. 2011; Smith et al. 2010).

… Analogous to scattered islands that form a single archipelago, the network of distributed hedonic hotspots forms a functional integrated circuit, which obeys control rules that are largely hierarchical and organized into brain levels (Aldridge et al. 1993; Berridge and Fentress 1986; Grill and Norgren 1978; Peciña et al. 2006). At the highest levels, the hotspot network may function as a more democratic heterarchy, in which unanimity of positive votes across hotspots is required in order to generate a greater pleasure.

… But all of these findings on brain pleasure generators are focused on making pleasures nicer than usual. … Yet well-being is a more continuous state of hedonic normalcy, in which pleasures are not tied to any particular sensation but rather are frequent or sustained. What in the brain is required for creating the daily continual level of a normal pleasure gloss?

It turns out that only some of the hotspots able to amplify pleasure are also necessary for maintaining normal hedonic levels of ‘liking’ to pleasant sensations.

… it still remains unknown if even the mid-anterior pleasure-coding site of orbitofrontal cortex actually causes a positive pleasure state.

… Conclusions

While some progress has been made in understanding brain hedonics, it is important not to over-interpret. We do not yet have a neuroscience of happiness. … We do not pretend to see deeper into the nature of happiness than those thinkers of earlier times, but simply point again to the empirical convergence of hedonic and eudaimonic features together in most people who are actually happy. And we note in conclusion, that so far as positive affect contributes to happiness, then at least some progress has been made in understanding the neurobiology of pleasure in ways that might be relevant.

Mapping the connectome is a great step toward understanding the brain. The problem is, what do we do with a connectome once it’s built? There’s a lot of important information about the brain’s connectivity packed into a connectome, but how do we extract it? Read on for an approach to broad-stroke, comparative brain region analysis based on frequency normalization. (Fairly technical and not recommended for a general audience.)

The challenge: turning connectomics data into knowledge.

There’s a worm called c. elegans that scientists study a lot because it’s so simple– its whole body has only 302 neurons. We’ve made a lot of progress on understanding it, but we’re still working on figuring out what each neuron does and mapping the logic of its neural circuits. With the human brain having a hundred billion neurons, it’s clear that we need some big-picture tools to make sense of all the wonderfully combinatorial complexity in our brains.

It’s not an easy task: what sort of analytical lens can we use to study the brain’s neural networks that elegantly illuminates system properties and differences between people, simplifying without being too simplistic? What sort of analysis ‘carves our brains at the proverbial joints’, to paraphrase Aristotle?

A thought: frequency is the internal language of the brain.

The brain is horrendously emergently complex— but all the really interesting signal encoding and processing in the brain is frequency based. Most likely, the texture of our cognition and emotion derive from the high-level frequency dynamics in our brains. Even more strongly and less vaguely, I’d argue that most other elements of our neuro ontology (neurotransmitters, action potentials, fMRI activity, etc) are functionally important only insofar as they influence, or are proxies for, the frequency dynamics of the brain.

It’s a strong statement! But I think it’s warranted. Following this, if we want to understand neuron activity on large scales we’ll eventually need to enable comparative frequency analysis. To normalize neural networks somehow to allow apples-to-apples frequency comparisons between neural circuits or brain regions or people.

An approach: can we construct a normalized framework for analyzing neural networks by flattening them into a one-dimensional bundle of interconnected pathways?

In the previous section I said we’ll need to enable comparative frequency analysis to really understand and predict neuron activity on a large scale. But this is a very hard problem. It’s hard because frequency analysis (e.g., performing a fourier transform) depends on a certain sort of structural consistency in the medium under measurement. There’s a difference in kind between sound waves bouncing around a room and electrical pulses bouncing through a neural network. They’re both based on frequency, but neural networks have complex topology and state*, whereas sound does not. If we want to analyze network frequencies on scales larger than individual neurons (which do not shed much light on overall frequency dynamics), and particularly if we want to apply non-trivial amounts of audio terminology (which seems like a no-brainer to me), we need to control for these differences.

Leaving aside the question of internal state of neurons for now, I have a suggestion on taming the topological issue such that we could attempt structure-normalized, apples-to-apples comparisons of high-level frequency dynamics between neural circuits or brain regions or people.

In short, we could try to computationally flatten out the pathways of a neural network (e.g., a brain region’s connectome) into a one-dimensional bundle of interconnected pathways. Essentially it’d involve trying to flatten the network into a semi-redundant, 1d, massively parallel, linear dataset, of which we could take cross-sections to measure frequency profiles, and which can be easily compared between neural networks.

There would be lots of technical hand-waving required… and lots of pruning too, given the combinatorial nature of the dataset. E.g., perhaps we’d need to filter pathways via minimum threshold of feedback loops. Fully appreciating the benefits, drawbacks, and process of this transform would take much more mathematics and expertise with complex topologies than I have. But I believe it could be an approach that drastically reduces the complexity of a neural network while still preserving many important network properties, and enables comparative frequency analysis on the network.

Ultimately I think the best way to understand large neural network will not be in terms of neuron connection statistics, but in terms of the frequencies and rhythms the network can generate and support. To go a bit further, I believe this structural transform also makes it easier to quantify resonance inside neural networks (and treat a brain region as an acoustic chamber, in which certain patterns resonate much more strongly than others), something I think is very important.

*A little more on the complex topology and state of neural networks: neural networks have ‘state’ in that each neuron is a unique device with its own internal variables. We can’t understand exactly how the network works, and what frequencies and rhythms it can support, unless we can decipher the internal settings of each neuron in the network (and this changes over time). Contrast this with sound, where the signal medium doesn’t have state.

Likewise, neural networks have ‘complex topology’. Sound waves travel in straight lines in three dimensions (“simple/euclidean topology”). However, signals in neural networks travel along the connections between neurons, which are definitely not arranged in neat, straight lines. It’s more like high-dimensional, non-euclidean space, an “Alice in Wonderland” style area where things don’t move in straight lines so much as between a tangled web of nodes. This is NOT to say that there is NO frequency to be analyzed, nor that other elements of audio theory (resonance, harmonics, constructive/destructive interference) aren’t present. There is and they are. It’s just that we need to find SOME way to simplify the topology before we can start to quantify the frequency data and apply concepts from audio theory. And if we ignore the problem and don’t bother with this sort of simplification/normalization, we’ll never get good frequency data, period.

At any rate, this is a possible approach, and it may or may not end up workable. But however we enable frequency analysis inside the brain, I hope more people start thinking seriously about the normalization problem soon. Frequency is of central importance in neural function, and having a method to normalize frequency within the brain will be central in understanding how it all works.

Image: Neurons from the limbic area of the Central Nervous System. Image copyright and courtesy of Bryan W. Jones.

[1] I’m reminded of this curmudgeonly letter regarding the ‘omics’ situation:

It is an old maxim that if you want to get on, invent a new word for your particular niche in an old area, and so become an instant expert. This process seems to have gone mad. A recent article in The Scientist that referred to “nutri genomics” [1] prompted me to see just how many -omics had now been coined. Well over 100 neologisms are listed at http://www.genomicglossaries.com/content/omes.asp. A few of the more ghastly examples are foldomics, functomics, GPCRomics, inomics, ionomics, interactomics, ligandomics, localizomics, pharmacomethylomics and separomics. None of these refers to areas of work that did not exist before the coining of the new word. Perhaps, as an electrophysiologist working on recombinant ion channels, I should dub myself an expert on ohmomics.

This habit of coining fancy words for old ideas might be thought harmless, merely a source of endless mirth for thinking scientists. I’m not so sure though. Apart from reinforcing the view of scientists as philistine illiterates (at least when it comes to etymology), actual harm is done to science as the public becomes aware that some among us seem to prefer long words to clarity of thought.

David Colquhoun

University College London

Indeed, playing against Watson turned out to be a lot like any other Jeopardy! game, though out of the corner of my eye I could see that the middle player had a plasma screen for a face. Watson has lots in common with a top-ranked human Jeopardy! player: It’s very smart, very fast, speaks in an uneven monotone, and has never known the touch of a woman. But unlike us, Watson cannot be intimidated. It never gets cocky or discouraged. It plays its game coldly, implacably, always offering a perfectly timed buzz when it’s confident about an answer.

Perhaps somewhat less funny from Ken’s perspective, a question asked during his reddit interview:

How’s it feel to be owned by something that asked “What is leg” ?