A Tough Trick: Giving People a Sense of Autonomy When Their Work is So Defined by Systems

Political turmoil always comes with economic progress because identity and the work we do is so intertwined.

I think that one of the tricks of the next economy that will be hardest to pull off is this: give people a sense of agency even though their productivity is defined by systems.

Right now almost no one I knows thinks that their salary has anything to do with dozens, hundreds of systems they have nothing to do with and yet what we make is 95% defined by systems rather than our own effort.

Machines automate more and more manual work every year. Algorithms are going to automate more and knowledge work every year.

Factory workers thought that their productivity was about them and not the factories they worked in. Knowledge workers think their productivity has something to do with them and not the educational and information systems they work in. It has been - and will be - tough to realize that's not the case.
We haven't evolved biologically in the last few thousands years but our productivity has gone up enormously. And continues to rise.

What are the systems that let the exact same animals be so much more productive?

Roads and highways and railroads and airports that let us send and get products and services from a broader region.

Educational institutions, unions, companies that have processes that make people more productive.

Information systems that let knowledge workers work more efficiently.

Laws and law enforcement that protect property and extend those principles to things like patents so that investors and innovators will invest in new products and technologies with the hope of returns.

The electrical grid and the appliances that work off it.

The fossil fuels and engines that require(d) thousands of innovators and inventors and that let a guy with a chain saw cut down more trees in one day than his great grandpa could in a month.

The social norms of employer and employee (Between 1800 and 2000, the percentage of workers employed by someone else rose from 20 to 90. By 2000, over half of employees worked for organizations with 500 or more employees; in 1800, none had.)

Language. Writing. Email. Software.

And so on, and so on, and so on.

The systems that most fascinate me appear at the level of economies. An agricultural economy has its own set of principles, practices, beliefs, and technologies. An industrial economy another. Those evolve and change and farmers and factory workers and knowledge workers in an information economy think that is who they are rather than just who people become in order to be productive. That identity, that definition of what it means to be productive, evolves and changes over time as the systems we live and work in evolve and change.

This is a big reason why social invention fascinates me. It means stepping outside of systems to shape them rather than let them shape us. (Okay. That's absurd. Our systems will always shape us.) 

Everything is made up and everything matters. Polygamy or monogamy? Made up. But it matters. The 10 most violent nations in the world practice polygamy which means lots of young men without partners wandering around angry. Dictatorship or democracy? Totally made up. But it matters. The 10 richest nations in the world are democracies.

One big obstacle to progress is that people defend the systems that define them even when those systems - like an agricultural economy for instance - are gradually made obsolete.

Progress comes from challenging and improving and inventing systems. That's tough work. Particularly when people define themselves by those systems. But here's the trick. Here is how you give people agency when their productivity is defined by the systems they live in and work with. You make them systems  thinkers and social inventors. You make their work the work of defining and shaping those systems.

Popularizing Systems Thinking

Models of complex behavior increasingly sit at the background of vital political discussions like global warming and pandemics. It is time to make them a more integral part of our political discussion. Until voters can understand and participate developing models to predict the behavior of systems, we will have unstable politics, particularly in a country like ours that puts so much stock in the opinion of everyone. This country was defined by a way of thinking. It’s time to expand that.

Our founding fathers did not pioneer Enlightenment thinking but they were the first to create a community organized around it. The Enlightenment shifted people from a reliance on authority and tradition (church and king) to reason and debate (science and democracy). Our founding fathers popularized education – most notably, Thomas Jefferson founded the University of Virginia – with an emphasis on rhetoric and analysis as essential to creating smart voters. They generally believed that education was necessary to freedom and democracy. But as it turns out, rhetoric is a poor way to understand or communicate complexity. We need to update what constitutes a good education.

Today we have expert systems thinkers but we haven’t popularized systems thinking, made it a part of the way we organize and act or even a part of what we include in education. Analysis focuses on parts at one point in time; systems thinking focuses on interactions over time, like how viruses spread at different rates depending on how we behave or how CO₂ builds in the atmosphere depending on our technology. Systems thinking is as important to an effective democracy in this 21^st century as Enlightenment philosophy was to an effective democracy in the 19^th and 20^th centuries. We can’t coherently debate systems as varied and crucial as our financial, environmental, education, and healthcare systems with fluency in systems thinking.

Hearing Bill Gates talk about a pandemic in 2015 and how serious it will be, he mentions what "our models told us." Listening to California governor Gavin Newsom in press conferences, he, too, references "our models." Models have the potential to explain futures we haven't yet experienced. Models will never be perfect; they can, however, be sufficient to inform good policy.  Once you understand compound interest, you may not be able to predict how much wealth you’ll have in 30 years but you know what to do: invest early and often to maximize that wealth. Once you understand how rapidly the coronavirus can spread, it informs policies like shelter-in-place. Even though models are sensitive to changes in assumptions and inputs, they can still point us in the right direction. The better people understand them, both their limits and the insights they provide, the more credible and helpful these models.

I work with really bright scientists and engineers to plan – or model – their projects to develop new products like drugs, medical devices and computer chips. Two benefits inevitably follow. One, each person gets insights into what others are doing and how that impacts them. Good models are key to coordination. Two, they learn more of what is possible as they play with the model, play a game of “what if” to see how they might accelerate launch. “What if we hired one more circuit engineer?” “What if we doubled the number of clinical trial sites so that we could enroll patients more quickly?” The models let them answer what-if questions and become tools for making really smart people even smarter, in the same way that a spreadsheet can help a financial planner to get and communicate insights. Models that a group jointly creates and maintains could be used to inform an entire populace about their policy options on issues like economic stimulus, global warming, or the spread of a pandemic. Even very simple models can help to illustrate important dynamics more clearly than rhetoric.

Democracy depends on education. Change is accelerating. We’re increasingly dependent on systems. Education needs to include system thinking. In a crisis like a pandemic, we have to react to what the models predict about consequences because if we wait to react to actual consequences or rely on our intuition (intuition informed by completely different circumstances) our actions will be tragically late. Models let us learn from the past and from possible futures. The AI that recently beat the world champion Go player Ke Jie was able to make a move no one had ever before seen, a move learned from millions of game simulations it had simulated play even before playing its “first” game with Ke Jie. When a community encounters something like the coronavirus, it would be nice to be at least as prepared as one might be for a game of Go.

There are a variety of ways to popularize systems thinking. One way might look like video games. Imagine kids learning about global warming or economic development by getting exposed to simple models that play out over time. They first learn to turn the knob on this variable and then that variable. They see which variables are akin to the butterfly's wings in Brazil that causes a snowstorm in Minneapolis and which are akin to a hundred moths beating their wings uselessly against a light bulb. Over time they begin to introduce their own data, their own variables, or even change the structure of the model. The class as a whole could build a model that represents their collective insights and predicts outcomes few – if any – minds are sophisticated enough to foresee.

Good education changes life outside the classroom. Eventually democracy might mean that we have collective, online models that represent our best knowledge and are as widely understood as an op-ed or debate. Policy could come out of millions of simulations that are largely transparent and contributed to and understood by millions of citizens. Perhaps working on models will become as much a part of citizenship as working on campaigns or reading and arguing about op-eds. In the same way that a car lets us travel further than we could on foot, good models can let us create better policy than we can with debates.

Ron Davison lives in San Diego County, wrote The Fourth Economy: Inventing Western Civilization and works with teams in Fortune 500 firms and startups to accelerate product launch. @iamrondavison

How Exponential Growth Boggles the Mind

Somebody picks up on a problem in the pond. Lily pads are growing rapidly. By their calculations, they're doubling every day to cover more and more of the pond.

Assume that it takes 30 days for the pads to cover the whole pond. Someone who has been hollering about this problem for 25 days sounds shrill for a simple reason: on day 25 lily pads cover only 3% of the pond. From day 1 to 25, lily pads have only grown from a tiny fraction to 3.1%. Double that 5 more days, though, and you're looking at 100% coverage - enough to choke out the pond.
We don't have good intuition for exponential growth.

In related news, a week ago Italian hospitals were able to give each coronavirus patient high-quality care. Today they are practicing triage. Not everyone who comes into the ER is getting treatment - even some folks who are dying for reasons unrelated to the coronavirus. They simply haven't the capacity.

One Way to Beat Mitch McConnell in 2020

Here's one possible route to beating Mitch McConnell. I think it may work politically but in any case it presents the truth about Kentucky.

First, McConnell's opponent makes the case that she isn't a racist. This is said casually, sort of a nod to the normal tropes of modern politics. And then she says this.

"I'm not a racist which is why I know that Kentucky is the victim of terrible leadership. It's true that we have only half as many minorities as the average state in this country but that should not account for why we're poorer. Whether measured by median or average, our household income is 20% lower than the rest of the nation. And we have only half as many households that make over $200,000 a year.

"This isn't because the good people of Kentucky are any less as people. Birth doesn't explain this difference. It's not bad genetics but bad leadership that explains why Kentucky is poor. It's because the systems our leaders have developed are inferior. Our education systems. Our health systems. The systems we depend on for creating new businesses and with it new jobs and wealth. All of these are inferior here in Kentucky and that's because leaders like Mitch McConnell have done such a terrible job of nurturing and advancing these systems and the culture that embraces rather than rejects the disruption that comes from new ideas and businesses.

"What we need is a very different set of expectations. Mitch McConnell has kept Kentucky in the past because the ideas he has are anchored in the past. It's time to send someone to DC more intent on making the good people of Kentucky prosperous than he is on fighting to protect that past."

And from then you hammer the point that his terrible leadership is what has caused Kentucky to be 20% poorer than the rest of the nation rather than 25% richer, like Massachusetts (a place which has twice the percentage of minorities that Kentucky has).

The point is to clarify that Kentucky is not destined to be poorer than the rest of the country (while pointing out to the folks who are racists that a lack of diversity is probably one reason they're behind the rest of the nation) and that its culture and institutions - products of leadership and history - are making it poor and need to change. The way to make this change is to create the future rather than defend the past, to change leadership, starting with the most powerful man in the state.

Father's Day: How Dad and I Were Just Alike (and so very different) in Our Politics

In late January of 2009, I got a call from mom. Dad was in ER. About 90 minutes later, after midnight, I got up there.

I was chatting with mom after we'd been in to talk to him. I could not figure out what was going on. Finally, mom said, "I think your dad might just be having a stress attack of some kind. He can't believe that we have a black, Muslim socialist in the White House." At that I said, "Oh." And promptly drove back home, leaving him to his self-induced drama.

Growing up, I don't remember hearing about politics much. My parents had a lot of drama in their life and politics wasn't part of it. I read a lot and, as I got older, wrote a lot. It turns out that the combination of reading and writing resulted in a set of ideas that are little connected to my parents'. My dad and I probably cancelled each other's votes 90% of the time.

And yet I have become like my father in how I think about politics. Sort of.

Dad worked for Caltrans in highway design. In his last 5 or 10 years, he worked in traffic safety. They would simply identify dangerous sections of roads and highways based on statistics. On one section of road, accidents are 2X more likely. In another, someone is 20% more likely to die. And so on. They would analyze the data and then the section and redesign it so that accidents, injury and fatalities were less likely.

Police would identify individuals more likely to get in an accident. Lawyers would determine blame. That was not dad's job. His job was to make a section of road safer for everyone.

In that way, my sensibilities are very similar. I have a lot of conservative friends and even recessions they are likely to blame on individuals. I remember one conversation with conservative friends at the height of the Great Recession when the unemployment rate was nearly triple what it is now and they were discussing how someone's brother-in-law had taken a week's vacation (from looking for work) with his family in the midst of his unemployment. As if an outbreak of laziness somehow explained this outbreak of unemployment. They were the cops and lawyers, trying to figure out who was to blame and who to arrest.

I know that individual differences do make a difference. I just don't think those differences are very interesting or relevant. People worked 60 hours a week in 1900 and made about 1/8th of what we do. You might get excited explaining why one guy made 30% more than another in 1900 but that is incidental compared to the difference between that guy and his grandson who makes 800% more. That's fascinating. And relevant. And something you can aspire to "design" with a set of policies and technological and social inventions.

The questions that intrigue me are not the questions of the police about why someone got in an accident. My question is how we design the economy to lower the incidence of those accidents while still letting people drive faster. It turns out that even while I felt such a huge wave of relief to have Obama and Biden in to replace Bush and Cheney and my father thought it was a sign of the apocalypse, our perspectives are similar. (Well, his perspective on highways and mine on economies anyway.) 

This Sunday will be my sixth Father's Day without dad. It is a curious thing how every generation knows what they'll reject from the previous generation but takes longer to realize the ways in which they are just like them.

Systems Optimization and a Life

I'm going to argue two seemingly contradictory points. First, a point about systems optimization.

You don't optimize a system by optimizing any one part of it. To optimize a system, you have to sub-optimize its parts. Let me illustrate what I mean by talking about a life.

Your life is a product of so many things: your physical health and fitness, your mental health and learning, your social life and psychological well being, your sense of meaning, your connection to the community around you and your sense of individuality in the community around you, your sense of legacy, individuality, belonging, your income and financial security, your cool shoes or cool car or cool taste in music, your hedonistic pleasures of food and sex, the hunger for stories that comes in the consumption of books and movies, or your tribal urges that find expression by cheering for your team and so many other things.

Here is the deal, though. If you optimize any one of those, you will sub-optimize your whole life. Do everything you can to be in peak physical condition and you'll likely have little energy left for something like plowing through great literature or keeping current on important new books. And if you do both of those things while working a full-time job, working out and reading all the great books, your social life will suffer. Life is zero-sum and if you optimize to any one piece of the myriad pieces that make up a life, you will sub-optimize the whole of your life. Oddly, the way to optimize any system - including and perhaps especially your life - is to sub-optimize every piece of it.

The punchline is perhaps cliche: a balanced life means moderation in all things.

Now the contradictory point.

This week there was some furor over Elon Musk's claim that to accomplish anything a person needs to work 80 hours a week. People pointed out that an 80 hour week is counterproductive. I totally agree. Long term. Short term? I think he's right.

A moderate, balanced life is not something that one achieves in any given instant. You don't split up each hour into 7 minutes for workout, 3 minutes for reading great literature, 8 minutes for building relationships, 4 minutes for eating, etc. Even within the course of a day or week we focus on just one thing at a time. So in any given instant, we're certainly not balanced.

There are times in life when you need to move forward. In those instances you look for the limit or obstacle to moving forward and you challenge that. You do optimize to the part that is the limit .... at least until it no longer is.

So then the question is, if you are going to optimize a life but not any one part of it, what does it actually mean to sub-optimize in a way that is best for your life?  It means that you have stretches of life that really do optimize for one part of it and subordinate everything else. Let's say that you have children. You don't want the entire rest of your life dedicated to doing what is best for your children, optimizing everything for them. But in those first few months? First few years? Maybe even first decade or so? You will optimize for them. Nobody with a newborn is running marathons or throwing big parties or reading great literature. They're sub-optimizing pretty much everything to that one thing: the newborn.

If you create a dissertation or book or symphony or business, pursue a gold medal or partnership in a prestigious law firm, you will probably go through something similar to what one goes through with a newborn. You're going to sub-optimize to that one thing. At least for a few years. New parents are not going to say that they'll only put in 40 hours each to care for their newborn; it would die in the other 88 hours of the week. A similar, but less dramatic thing, can happen with any of these ventures. Balance suggests that you never dive into anything: success suggests that you do.

And maybe you just keeping diving into things for the whole of your life. Or more realistically, at various times in your life that could be separated by six months to six years of "la de dah," days in which not a great deal happens. (That perfect storm of incredible opportunity for which you are incredibly well suited at the right time of life only happens one, two, maybe three or four times a life.) You throw yourself into things that result in sub-optimization elsewhere. You're immoderately out of balance at every stage and the end result is a full life that is balanced in that it lets you experience life as whole over the course of a whole life, but never in any one instant. Because in the end, a life takes a lifetime and if you're interested in a legacy of any kind, you don't even optimize for a window that small. (But that's the stuff of another post.)

Progress and the Marketplace of Ideas (or, how our love of villains and heroes is an obstacle to understanding systems)

There is a marketplace for ideas. It doesn't necessarily reward more effective ideas. It does seem to reward ideas that are easy to explain. Often, simple explanations that are wrong will triumph over more complicated explanations that are right.

One thing that is easy to understand it villainy. Bad guys and good guys, heroes and chumps. We love the movies that show the lone guy against the system, Bruce Willis taking on bad guys, bad officials and an entire skyscraper.

As it turns out, systems do more to define people than people do to define systems. I speak English. I never chose that. I was born into it and even the question of whether I would learn another language came to me in English. So much of who we are is not even our choice.

Much of what happens is the consequence of systems, not the people within them. Stories lend themselves to blame or credit to the people in these systems, though, and so those are the explanations we offer.

***********

Progress doesn't really impress people. We make about 6 to 8 times what people made a century ago and can buy things that they couldn't even imagine. The thing is, nobody is really impressed with that. We don't compare ourselves with our great grandparents. We know that they didn't have smart phones. What matters is whether our smart phone is two years older than our friends. We compare ourselves with our peers. We have this tendency to care less about progress than status.

How we are doing relative to our grandparents is a variable sum game. It is possible for all of us to do better than all of them.

How we are doing relative to our peers is a zero sum game. It is impossible for all of us to do better than all of us.

The more we teach kids to focus on relative status the more unhappy and disengaged they will be. Not only is that a lousy way to walk through life in terms of happiness but even in terms of progress it is bad: unhappy, disengaged people will be less effective at making life better relative to their grandparents.

The politics of status will be fear-driven and angry. It promises villains, heroes and quick change.

The politics of progress is slow. It actually works across generations. It is less concerned with villains and heroes than the systems that throw people into such a role. It is a less engaging, less simple story. That doesn't mean that it'll always be rejected, though.


***********

Progress is boring. I suspect that people are ready for that now.

How Systems Thinking Will Define the Evolution of Democracy Within Your Lifetime

There is still a popular myth that our founding fathers fought a revolution in the late 18th century that - by the time they'd ratified a constitution in 1789 - culminated in democracy for all.

It was a much slower process than that. And understanding this process can give us a sense of how democracy will evolve.

Aristocracy were landowners. They inherited land and with it titles, privileges and power. Land was the basis of wealth during the emergence of nation-states and given that nation-states had borders it made sense that you'd look to the owners of the land within those borders (the king was often the chief landholder) and give political power to them.

In 1776 Adam Smith wrote Wealth of Nations and James Watt perfected the steam engine for use outside of mines. This birth of capitalism coincided with the birth of democracy across the Atlantic and what they represented was a shift in the basis of wealth from land to capital. The British had already seen a broadening of political power from landholders to capitalists even before the Americans designed a government that did away with royalty (the ultimate aristocrats) altogether.

At first, the vote in the United States was limited to landowning, Protestant, white men. It took nearly 200 years to guarantee the vote to minority, atheist, 18-year old women who rented. (A timeline for how democracy progressed from KQED is here.)

Commoners were allowed into the legislature throughout the West by about 1850. This dimension of democracy had to do not just with who could vote but who could craft legislation. About a century later, California gave voters even more power when the proposition allowed voters to completely bypass the legislature with a popular vote. By the time of Roosevelt's New Deal, voters weren't just able to vote for the folks who would craft their legislation but could actually craft their own legislation and put it before their fellow citizens for a vote.

Just like your car or computer, democracy has continued to evolve. And just like your car or computer, it has not yet reached its ultimate state. It will continue to evolve and I think that systems thinking will be a big part of what happens next.

Thomas Jefferson and our founding fathers understood how important education was to democracy. (Jefferson was apparently about as (more?) proud of founding the University of Virginia as he was in helping to found the United States.) Education still matters enormously to a functioning democracy but now it needs a new dimension.

Our lives are wildly dependent on systems. Ecosystems, financial systems, economies, healthcare systems, information systems, education systems, etc. If we get these wrong we get terrible outcomes; if we get these systems right we get wonderful outcomes. The most important political policy defines variables within systems and even the creation or change of systems. We can't make intelligent decisions about how to change or impact these systems without understanding their dynamics.

Systems often have lags and some causes explode to become a big deal and some causes dissipate into little or no consequence. Cause and effect in systems is complicated to understand and our systems thinking can be enhanced with the right kinds of simulations.

Cocaine makes you feel great but apparently isn't that good for your health longer term. Right now the American economy is phenomenal; 96 months in a row of uninterrupted job creation has doubled the old record (since records were kept in the late 1930s), unemployment at 3.7% is its lowest since 1969. Oh, and Republicans have doubled the deficit to one trillion dollars, its highest since the worst year of the Great Recession. We have a huge stimulus with unemployment under 4%. That makes for an interesting experiment but it also could be like cocaine binges that Trump's Economic Council Director Larry Kudlow was famous for in the 1980s. We may end up in rehab once the longer term consequences of this play out.

Even folks who study economies cannot say with certainty whether we're now creating a bad bubble (one like the bubble leading up to 2008 that raised home prices but didn't really create more economic capacity) or a good bubble (like one leading up to 2000 that actually created lots of new internet knowledge and capacity that would change what was possible). But we expect the average voter to make a judgement on policies and the politicians who support them without any real chance to play with simulations that would help them to understand dynamics.

Simulations can help to create new understanding. I think smart communities will tap into this.

Democracy will evolve to include massive online participatory simulations of the systems we depend on. One of the reasons I love history is that it lets us quickly - in the course of a book, chapter or even turn of the page - see how dominoes fall, even if those dominoes took a generation or two to fall. Like history, simulations don't require us to actually spend years or lifetimes to learn outcomes.

Simulations are not perfect but they do let you learn about dynamics in ways that you would not from prose. You can set up a model to capture what data and / or common sense tell you about cause and effect (e.g., raising interest rates will lower borrowing but increase the value of your currency on foreign exchange markets) for lots of variables and then run simulations to see what range of effects are possible as you tweak the knob on those variables. You're obviously hoping for a good model for predicting the future but almost as important as prediction (which is always hard and is at best probable, not precise), is learning more about dynamics that none of us are smart enough to keep track of ourselves. Simulations can sensitize us to cause and effect that isn't instantaneous and can be mitigated or exacerbated by other variables.

As democracy evolves to include simulations we participate in, it will make us smarter. Very few of us can calculate mortgage rate changes to reflect 20 vs. 30 year mortgages or a 3.2% vs. 4.1% rate but with a computer we can all easily discern that ourselves without reliance on an expert. Very few people can get across town in 15 minutes by running but with a car most of us can. Tools enhance our capabilities. Systems simulations seem like the most important tool one can imagine for any democracy that needs to navigate and manage the systems that so define our lives.

Whether it be tax rates or emission levels or research funding, in the future such important decisions will be accompanied by systems models that simulate these phenomenon. Will these simulations be perfect or even great? Definitely not and probably not. Will they be immeasurably better than reliance on prose and statistics to make the same determinations? Undoubtedly. And will future generations wonder how we could pretend to vote on such issues in the past without the aid of simulations, in the same way that we wonder at how people got around without cars? Definitely.

Progress isn't done yet. Democracy will continue to evolve, just as it has for centuries. The popularization of systems thinking will be a big part of that.

Video Games, Systems, Consequences and the Afterlife

I'm a fan of video games. I think that the world will get better as we build more effective simulators to teach systems dynamics that include the behavior of nations at war, ecosystems, financial and labor markets, popularity, and the change in social norms. Different dynamics are tough to understand as prose or equations; sometimes the patterns become easier to see when they play out in video simulations that let us see causality that simulates centuries within an hour. I don't think that we've really understood how powerful this potential technology is for teaching systems dynamics that so define our world.

There is one lesson that these video games gloss over, though. And it may be the most important lesson of all.

What we enjoy or suffer today rarely has anything to do with today.

Mark Zuckerberg made $1.5 billion today. I'm not even sure he went into the office today. He may have stayed home with a cold or may have had a really important strategic meeting. I don't know what he did today but I guarantee you that it does not explain his gain in wealth today. That is the consequence of things he did years ago.

Probably 99.9% of what we enjoy or suffer from today is the consequence of something done in the past. Little of it even done by us. Today my portfolio is up. It is the result of investments and sacrifices I made in the past, but that's the least of it. It's also the result of the Dutch who came over to New Amsterdam and recreated the stock market they'd first established in Amsterdam. It's the result of countless employees and entrepreneurs who have created equity out of thin air. It's the result of laws that protect private property. And so on.

That lesson that evolutionary biologists and religious teachers would both teach you is that causality does not stop at death. There is an afterlife. The lives of people in the future will be diminished or enhanced based on what you do in your lifetime. I suppose it is a kind of evil to believe that your life has no consequence and a sort of good to believe that it does.

If you are looking for cause and effect that can be experienced within a day or even a year, it is easy to get discouraged. Little of consequence plays out that rapidly and if you are measuring the impact of yesterday or last month's efforts on today, you'll conclude that there's not much that can be done. But the stories that inspire are those of the immigrant mom who worked two jobs to get her kids through college. There is generational causality and it doesn't end with her grandkids. One of the reasons I love history is that it explains so much of what defines today. We are the product of decisions made centuries earlier.

The community you live in is the product of the despair or hope of past generations, their action or inaction, their creativity or conformity. One definition of foolishness might be to believe that nothing we do has any consequence; one definition of wisdom might be to believe that what we do has consequences for generations. (Even if that consequence is to have made no difference because even not making a difference makes a difference.)

Finally, I leave you these words of advice from one of my favorite people.

The Buddhists have a good piece of advice: “Act always as if the future of the universe depended on what you did, while laughing at yourself for thinking that whatever you do makes any difference.” It is this serious playfulness, a combination of concern and humility, that makes it possible to be both engaged and carefree at the same time. One does not need to win to feel content; helping to maintain order in the universe becomes its own reward, regardless of the consequences. - Mihaly Csikszentmihalyi

A Much Bigger Story Than Benghazi or Niger

Focusing on individual events can distract us from the systems that make those events more probable.

In the 1980s, the Japanese were taking market share from American and European car makers. One study at the time found that German car makers were reaching the same level of quality as the Japanese but needed three times as many employees to do it. Some German car makers were employing as many people at the end of the line to fix cars as some Japanese car makers were to work the line. When Japanese workers encountered an error they had authority to shut down the whole line and initiate an investigation into why the error had occurred. Rather than just fix the error at the place, they might change the upstream flow of work to lower the probability that someone would make that error again. Japanese workers were regularly fixing the system while Germans were regularly fixing cars.

Which brings me, curiously enough, to stories about our military. Right now, media and politicians are focused on the story of how four soldiers were killed in Niger. This is very similar to the focus on the four dead in Benghazi in 2012 and this focus on individuals misses a more important story about policy, the system that makes these tragic events more or less probable.

First of all, let’s assume for a moment that anyone killed in service to our country deserves honor and their families deserve acknowledgement and gratitude. Let’s further assume that whether or not they died in an incident that got an enormous amount of coverage, their families are equally shattered by this loss. Whether they were the only one killed that year in service to their country or one of 2,000, the trauma and grief their families suffer is real and they deserve our support.

Stalin was quoted as saying, “One death is a tragedy and a million is a statistic.” Perhaps it is because we can’t comprehend 2,000 deaths as easily as we do 2, we are made numb by the bigger number and saddened by the smaller. The media is currently gripped by the story of Myeshia Johnson, the pregnant widow of La David Johnson who received a phone call in which Trump’s offer of comfort included the phrase, “He knew what he was signing up for …” Yet a much bigger story is playing out here that is obscured by the odd way the media fixates on a Benghazi or Niger but ignores the bigger story about how many widows and widowers are experiencing what Myeshia Johnson is.

If you appreciate the tragedy of Chris Stevens death (he was the ambassador killed in Benghazi) and the grief of Myeshia Johnson, you have to be humbled by the thought of losing more than a thousand soldiers a year. Between 1980 and 2010, an average of 1,575 American military were killed each year. Each year. During that time the lowest it ever dropped to was 796 (that was in 1999) and it rose as high as 2,465 (in 1983). In only six years during that 31-year stretch did the number killed drop below 1,000. (1996 to 2001.)

Each death involved a real person and deserved its own story but our policy made the number killed each year remarkably consistent. Policy was the bigger story than any one of those deaths because it was policy that made the number of those deaths so remarkably consistent for so long.

And then the most remarkable thing happened. The number killed steadily fell. In 2010 the number killed was 1,485. Then, in 2011 467 died. In 2012 it was 314, 2013 was 132, 2014 was 60, 2015 was 28 and then in 2016 it was 30.  30 is 2% of what it averaged from 1980 to 2010.

It’s not true that each of these numbers are mere statistics. We aren’t equipped to comprehend 1,575 grieving families and all their friends. We can scarcely comprehend one. But the limits of our empathy shouldn’t excuse the obvious: a year in which 2,465 of our military are killed is 82 times worse than a year in which 30 are killed.

Obama deserves criticism for reneging on his threat to intervene in Syria. His decision not to send in American troops may have resulted in more civilian deaths in the last few years. But Obama also deserves respect for his decision. For one thing, he couldn’t see the next move. Who takes power once Assad is out and how does that lower the number of casualties and refugees? (Not only did our invasion of Iraq result in somewhere between 100,000 and a million Iraqi deaths, it created millions of refugees. Attacking a country doesn’t guarantee a fall in casualties.) It is not clear whether his decision to keep troops out of Syria resulted in more Syrian deaths.

It is clear that during Obama’s last six years our American troops were safer. Only a fraction of the number who would have died with previous policies died during his last six years in office. This deserves more attention than it has received. Had our service people died at the same rate in Obama’s last six years as they had in the 31 years prior, 8,418 more of them would have been killed. 8,418 grieving families and their friends. 9 times more grief and tragedy than actually occurred. This is not just a statistic. It is not just a story. It is 8,418 life stories that get to be told in radically different ways. And it is not just their stories. It is the stories of their children who get to grow up with both parents. Or the story of the children who were born because a mother or father lived well past the date they would have if they had been deployed under the policies of a president more eager to put boots on the ground.

Progress doesn’t come from fixing each tragic event after it happens. Progress comes from making changes to the system, or in this case to the policies that determine how our troops are deployed.

Foreign policy that spares the lives of 8,418 soldiers may not seem as gripping as tragedies that take the lives of four but they matter more. If we’re going to be factual about it, they matter 2,000 times more. That, it seems to me, deserves at least as much attention as a tragedy in Benghazi or Niger.

--------------

Data sources on military casualties are harder to find now. Sites that formerly posted data now yield up an error. Here are the places I went for data months ago and just this week. It would seem the Trump administration or someone in DoD wants to make these numbers less transparent.

https://www.dmdc.osd.mil/dcas/pages/report_by_year_manner.xhtml

https://www.defense.gov/News/News-Releases/Customrelcat/12003/?Page=3

https://fas.org/sgp/crs/natsec/RL32492.pdf

https://www.defense.gov/casualty.pdf

What To Do About the Immaturity of Systems Modeling

Sam Harris recently had a conversation with Scott Adams (Dilbert creator and author of How to Fail at Everything and Still Win Big) about Trump. Adams predicted Trump's victory because he sees Trump as a master persuader. There's a lot to say about that but Adams made a really useful distinction about what he saw as the three stages of climate change policy. He distinguishes between:
1) The reality of climate change as an ongoing phenomenon that seems to be man made;
2) The ability to simulate future climate change with good models; and,
3) An appreciation of the economic policy implications of the above.

A decade or three ago, it was fashionable to dismiss climate change. This has become problematic for at least two reasons. One, the science is not that sophisticated. Certain industrial activity releases greenhouse gases. These gases - as the name suggests - work like a greenhouse and trap heat. That science is not exactly quantum entanglement and the data for greenhouse gas emissions and resultant warming seems to track pretty well to the theory. So Adams cedes this point and allows that climate change is probably real and ongoing.

Adams worked as a financial analyst at a bank, though, and challenges the second point: the ability to simulate future climate change. He said that it reminds him of the financial models he ran as an analyst that - should they reveal something his boss didn't like - could readily be changed with just a tweak of a few variables. Given we can't really forecast accurately what might happen, it is good to be skeptical, he says.

In this he has sort of put his finger on something really important and is sort of missing the point (probably intentionally).

What is really important is that systems define so much about what does or does not go well in our world - systems as varied as the economy and financial markets, energy systems, ecosystems and school systems - and yet we really don't understand system dynamics that well. Systems are tough to model and our models are not great. This is reason to be skeptical about any predictions but it also suggests that systems modeling deserves a massive infusion of research money. A crowd was gathered to watch a hot air balloon ascend and some woman said, "What is the use of all this new technology." Benjamin Franklin answered, "Madam, what is the use of a new born infant?" Systems simulation matters a great deal and is not that mature. Better to invest more heavily in it than to walk away from it. (And I think that computers' ability to simulate systems is maturing just when that capability is most needed for shaping policy dependent on such systems.)

And even with admitted limitations of models for any systems, it is worth asking whether even the models Adams was tweaking for his boss were all that bad. Once you understand a model for an economy or business, you articulate risks, a range of outcomes, and important variables. With good models you learn what factors they are most sensitive to (housing mortgages are sensitive to widespread economic downturns or refinancing from a drop in interest rates, for instance) and even spotty historical data can give you some sense of the probability of those events. (Yes. Nassim Taleb has rightfully pointed out that markets can be rocked by unpredictable events but risk mitigation can protect you from some of these rare events. A person who has saved three years of salary is better prepared for an event "they never could have predicted" than is someone with only three months of salary.)  Financial models are a little sketchy in prediction but there are ways to gauge their efficacy in spite of a large margin of error. (For instance, only about 20% of businesses succeed past 5 years. If your bank lending model assumes that is going to raise to 50%, it will probably be wrong; if it assumes that it will raise to 25% or drop to 15%, it could be right but done properly even that should require a coherent explanation that tracks to the numbers rather than arbitrary tweaks.) Further, to the extent that Adam's boss was unique in cheating the models so that they showed what he wanted, his bank would suffer. There is a drive to make models more accurate and - within the financial world at least - big rewards for such accuracy.

Models force questions and conversations about what variables matter and they bound reasonable outcomes. It is true that climate change models will be wrong but the simplest truth is pretty easy to predict: we will emit more greenhouse gases and temperatures will be higher than they would have been without these emissions. There are a host of unknowns that come with that (will particular regions benefit or lose, will changes in wind or sea currents result in unexpected cooling in certain regions, might unforeseen natural phenomenon or new technology absorb these gases, etc.) but the general story is known. If you invest in stocks over a 25 year period you can't be sure of when your portfolio will drop by half or raise 20% a year for successive years but you can reasonably guess that over your lifetime you'll be a better shape for having saved 10% of your income than not. Same with greenhouse gases; reducing emissions will drive less uncertainty, disruption and climate change.

Denying climate change is in a long tradition of denying scientific results like the health hazards of tobacco or the notion that we orbit the sun. Climate change deniers are traditionalists who conflate market economies with oil and gas and see an admission of climate change as a threat to those forces. (It does seem like climate change will threaten oil and gas. The possibility of oil and gas being displaced by alternative energy is not a refutation of markets that periodically unleash gales of creative destruction, though, but is instead an affirmation. Markets are no more dependent on oil than horses and markets don't treat fossil fuel industries as sacred.)

As to Adams' third point about evaluating the economics of climate change policy, I'll just say this. If it is inevitable that we'll adapt new energy technologies, there is less likely to be a penalty for rushing into creating and then converting to alternative energies than there is to be a penalty for delaying that change.

How Gaming Is Shaping a New Worldview

Mary Meeker delivered her annual Internet report Sunday. One of the points she made was about gaming.

• Entrepreneurs are often fans of gaming, Meeker said, quoting Elon Musk, Reid Hoffman and Mark Zuckerberg. Global interactive gaming is becoming mainstream, with 2.6 billion gamers in 2017 versus 100 million in 1995. Global gaming revenue is estimated to be around $100 billion in 2016, and China is now the top market for interactive gaming.

One question she and the team at Kleiner Perkins asked was what does gaming prepare us for? I think it is teaching simulation to a generation who will need to become more adept at systems thinking.

The more one can play with the variables of a system, the better one understands it. To use a simple example, our company has software that lets a business unit forecast project completion dates based on shared resources and project priority. As you change the number of resources, project priorities, and how you model the use of resources within projects, the projected launch dates for these product development projects changes. One of the senior managers I once set up with this capability drove from Philadelphia down to Delaware each day for work. He told me that on his commute he would think about variables to change in order to explore what was possible to accelerate product launches. "I always sort of understood my business unit," he says, "but doing these simulations I came to understand it far better than I ever had. I learned what happened when I changed this variable or that one, what made a surprisingly big difference and what made hardly any difference and in what conditions. I understood the dynamics of the system in ways I never had before."

A great deal of what we see today shows graphs and numbers. "India is growing at 8% a year." "Smart phone sales are growing by 10% a year." What we have less experience with is simulations that allow us to change recent trends. "What might happen to its growth if India's move away from paper currency results in more theft from hackers?" "What happens to smart phone sales if they become a replacement for credit cards?" 

A simulation lets us do a few things. One, it lets us play with policy ideas. Two, it lets us explore the implications of entrepreneurial initiatives. Three, it helps us to better understand the way variables might interact to create emergent behavior that is the result of a the interaction of the variables in the system rather than the actions of any one variable in the system. Simulations will never be accurate. They can, however, be informative.

We are at the infancy of systems thinking in the same way that Europeans in 1700 were in the infancy of Enlightenment thinking. We will get better at simulating and thus understanding systems, systems as varied as ecosystems, financial systems, and educational systems - the variety of systems on which we're so dependent for our quality of life.

What is gaming prepare us for? It gives people practice with countless simulations, learning how changing one thing can change another, how this strategy results in an early death and this one lets you conquer the kingdom. Gaming teaches us that systems never depend on just one variable and that outcomes can never be determined even though probabilities can be changed. Gaming will make systems thinking and systems simulation intuitive to a new generation. That's pretty cool.

What a Manager Should Know: Deming's Four Elements of Profound Knowledge

Deming argued that there are four elements of profound knowledge that define a what managers should know.

1. Appreciation for a system

2. Understanding of variation

3. Psychology, and

4. A theory of knowledge

To effectively manage or understand an organization, you don't need a deep understanding of any one of these but you need some understanding of all of these. Also, each of these elements makes more sense within the context of the other three; the four form a system.

"A bad system will beat a good person every time."

- Deming 

1. Appreciation for a system and 2. understanding of variation

Deming used things like control charts that tracked data over time to determine what was common cause and what was special cause. To understand variation is to understand the difference between what comes from the system and what does not. People in 2000 in the US were 6X more productive than people in 1900 in the US. It wasn't because they worked harder (in fact, average work weeks dropped from about 60 hours a week to about 38 hours a week in that time). It's because they had better systems. You'll never get as far trying to make people work harder in an old system as you will by improving that system.

Here is a set of 100 data points representing rework (imagine an auto assembly line that created 1,000 cars a day, say) that mostly varies from about 10 to 40 cars that need to be reworked each day That much variation yields a control chart that suggests that normal variation falls within a range of 1 to 47 cars. (Normal variation is what we can expect from the system.)

Only one data point in the above chart - the one on day 16 that hits 57 - appears to come from special cause. All the rest of the variation is just a normal part of the day to day variation. 

Normal variation can still be explained as special by people who don’t understand it. It often is. "Orlando was not paying attention and we had 6 cars in a row assembled with the brake pads swapped. That's what happened." There is always a story to go with the data. And there is often a person we can name in that story. Normal variation can be explained but those explanations are themselves randomly associated with outcomes of a stable system. (This does not just happen on assembly lines. Each day, regardless of whether it goes up or down, moves a lot of moves a little, analysts say things like, "Investors were skittish today because of ..." What would actually be remarkable would be a day in which the major indices finished exactly where they started. Variation is normal. It is only over longer periods of time that you can spot a general direction.)

The only story for a data point that deserves explanation in the above graph is what happened on day 16. That is unusual and the explanation for that day will likely tell you something. It is special, meaning that what happened on that day isn’t explained by the normal rise and fall of our system, is variation that lies outside the normal bounds of daily variation.

Meanwhile, if you don't like it when you have to rework more than, say, 25 cars in a day, you need to look at the system. Is the process you're using dependent on guys like Orlando performing four different assembly steps every 5 minutes for 2 hours in a row before he gets a break? Is there any data suggesting that the average person can sustain focus and accuracy for that long without attention wandering? It's easy to say that Orlando should focus but do you have any data suggesting the average person hired for this role does? If that part of the process is consistently contributing to, say, 4 to 15 of the rework events each day, then we know that changing that process has the potential to reduce rework by about 10 units a day. (Note that this goal of ten is not the product of some arbitrary goal that came of the fact that we have ten fingers but instead comes from examination of the data that suggests we get an average of 10 errors a day from the process Orlando works.)

Once we know what is wrong with the system, rather than blame Orlando for the errors, we can brainstorm solutions. What if we gave Orlando breaks every 90 minutes instead of every 120? What if we rotated the person responsible for this really demanding process step so that no one had to do this task more than 2 hours a day? What if we changed the process so that Orlando has to do just 3 steps every 5 minutes instead of 4 steps? And so on. If we find a plausible theory for improvement, we can implement it for, say, another 30 to 100 days to see if this brought down errors. If it did, we have made progress and we can turn to some other issue within the system.

The behavior of the system is typically stable even as we change who we hire. (And the hiring process is part of the system. If we make a real change in what we screen for when we interview candidates, that too, might improve our system.) Systems define most outcomes. Changing teachers or politicians, employees or bankers is often like changing the cast in your play in the hopes that Romeo & Juliet will end happily.

Also, systems can behave in unexpected ways. A system has emergent properties that none of its part have. For instance, an engine cannot get you across town, nor can a steering wheel nor tires nor an axle. But when these parts are brought together in a system like a car, they can. Organizations are made up of knowledge workers who have to coordinate in order to create value. The person who designs a new product is worthless unless there is a person who can make it. Even those two are worthless if someone can't sell what they make, and so on. Just like the parts of the car cannot get you across town, the parts of an organization can't create value; through coordination, though, these people can create enormous value that emerges from their interactions. As a manager, you need to understand their current output as something that has lots of normal variation and you need to appreciate that the efforts in one part of the process can create problems in another step. (For instance, optimizing each part of the car could result in 87 different size bolts. This complexity could make it more difficult to keep all your parts stocked and even errors in assembly as you raise the risk of someone using the wrong bolt that is just fractionally off in size. Doing what is best for the system - changing the design so that it relies on just 3 different size bolts for instance - might mean doing what is less than optimal for a specific part.) The point is to optimize the system and that depends on people within it cooperating rather than competing.

Which brings us to psychology. 

If you have people within a system compete for promotions and raises rather than cooperate to create a fabulous product, you lay land mines for issues. If you have people work towards local goals rather than cooperate to create a success for the whole organization, you can easily encourage sub-optimization. Worse, you can disengage people through the use of extrinsic motivation.

The worst kind of motivation focuses people so much on the rewards that they don’t pay much attention to the task itself. One study of four-year-old children who tend to love a drum at that age broke the kids into three groups. One group was told that the box in front of them had a special gift for them for playing the drum. They stared at it distractedly the whole time they were pounding. Another group was told, almost in passing, that they’d get a prize for playing the drum. The third group was told nothing but was turned loose in the same toy room that included a drum. The second group was most likely to later identify the drum as their favorite toy, which gave rise to a notion of minimal sufficiency principle, [Mark Lepper] “using rewards or threats that are minimally sufficient to get kids to do the desired behaviors, but not so strong that the kids view the threats or rewards as the reason they are acting that way.”

As with systems or variation, psychology is rich with much more than the simple considerations I’ve mentioned. Deming felt that so much of what we do in school and work undermines the intrinsic motivation of people to learn, engage, cooperate, and create. He often showed this chart (video to follow).

This psychological question of how the system you have designed engages or disengages people might be the most important question of all.

"90% of what matters cannot be measured."

- Deming 

Finally, the fourth element of profound knowledge is the theory of knowledge. How do you know what you know? Your data and people’s behavior might be stable but what if the environment changes? How do you know that customers like your product? What about it do they like? The advances in UX since the time of Deming (he died in the early 1990s) have taken this question seriously. It’s worth remembering that he made his name as a management consultant but first got to Japan as a person to help with the census (“How do we know how many people live in Nara?” “How do we count people staying in a hotel on the night of the census? Are they counted as residents of the city of the hotel or the city they claim as home?”). And he got into the position to help to define this after getting a PhD in Physics. He studied phenomenon and tried to understand how we knew what we knew, and carried that basic inquiry into the question of how to count the population of an entire nation and how to measure quality in a product or service.

Evidence for what you know comes from data but data comes after you’ve formulated a theory. If you change what you are trying to measure or what you believe about the phenomenon, the data may suddenly be made obsolete or you’ll need to collect it differently. Your theory of knowledge is bound up in how you measure variation and how you define and understand the system you expect people to engage in.

Theory of knowledge, psychology, variation and systems. You can start anywhere and go everywhere but the real goal is to understand what you are dealing with in terms of a system and how that enables or disables people from realizing their potential within that system. This means understanding the difference between common cause and special cause variation and even a deeper understanding of how you know anything at all. All of it is humbling but it also leads to continuous learning and improvement as you continue to inquire on all of those fronts. Systems evolve with the people within them and the environment around them … or they become obsolete.

Ultimately, a successful social inventor or entrepreneur creates a system that outlasts them. The US didn’t collapse when Thomas Jefferson and John Adams died hours apart on the country’s 50^th anniversary. Apple’s stock didn’t fall to zero when Steve Jobs died. The real value is less about your efforts within a system than your ability to improve or create the system. It’s true that some people run much faster than others but no one outruns a jet; what you want to do in improving or creating a system is to create something that performs much better than the people within it could hope to on their own.  A great manager does the same and I’m not sure how you’d do any of it without at least some intuitive or learned understanding of Deming’s profound knowledge.

Why Our Media Will Make it Difficult for Anything Good to Come of Ferguson

Protests flared up around the country and violence and looting resulted in at least one death last night in Ferguson following the Grand Jury's decision not to indict Darren Wilson. So what's the good news? All of this media attention and turmoil is in the wake of the killing of an 18 year old boy rather than a man of Martin Luther King's stature. That, for me, signals hope. But it's a signal that could get lost in our media's noise.

I've become increasingly disillusioned with our for-profit media. A for-profit media is motivated to increase revenue. If that means making a big deal about Kim Kardashian's butt than they'll do that. Real progress is slow and takes some sophistication to cover. It's like writing a novel: you have to be skilled to get it right and it takes a long time. The conversation the media needs to facilitate now is one about causes and cures for the huge cost of being a black American.

The simple fact is that a black man can expect to die in his 60s and a white man in his mid-70s. (White males life expectancy is 75 years and black male's is 6 year less.) Household income for blacks is only 59% of whites' and wealth of black households is 20% of white households.

There are only two explanations for this. The first is that blacks are inferior and this is a natural consequence. We can dismiss the fact that blacks - once excluded from sports and pop culture entertainment because of their supposed inferiority - have proven that they're more than able to compete in their athleticism, comedy, creativity and music ability.  It's possible that they really are as good as whites on a variety of performance measures but just happen to be bad at business. Or it could be that business relationships are one area where it's still common to be unscientific and instead rely on  our judgments that are colored by folklore, gut, instinct, and racism that we scarcely admit even to ourselves. Which brings us to the second explanation for the gap between whites and blacks: racism.

It's obvious that there is still plenty of racism alive today. It's less obvious that when we're talking about issues like wealth and income, racism suffered by your grandparents puts you at a disadvantage.  Privilege and opportunity - for good or for bad - dominoes across generations. Even if we eradicated all racism today, blacks would still take generations to catch up simply because privilege and opportunity provide advantages that take generations to dissipate. Even if the average American's income stopped growing for decades, it would still be higher than that of China's.

Good policy starts with facts and then makes plans to change them. It doesn't ignore facts. It doesn't defend the status quo. And it looks beyond the stories of heroes and villains to systems. It's true that privileged whites screw up their advantage sometime. It's true that disadvantaged blacks rise above obstacles. But it's not the folks who do well or poorly in spite of prevailing norms that should concern policy makers. The focus of good policy is on improving the distribution of the whole population, not putting a spotlight on outliers. And of course, outliers - the violent youth or wealthy businessman - are the focus of our media, which makes it so hard to hope for policy that will change normal rather than spotlight the extremes.

Is the Web Conscious?

Systems have characteristics that their parts do not. This emergent phenomenon defines them. Your car got you to work today. None of its parts could do that. Not the engine. Not the wheels. Not the drive train. Systems are defined by the interactions of their parts rather than the action of their parts.

Which brings me to global consciousness.

James Surowiecki, author of The Wisdom of Crowds, wrote an interesting piece in the New Yorker titled "The Collective Intelligence of the Web." The first example he uses of collective intelligence is of a project NASA began in 2000 to map Mars.

"There were two very interesting things about the results. First, although there was no financial incentive to participate, more than a hundred thousand people took part in the study, generating more than 2.4 million clicks. Second, and even more striking, the collective product of all those amateur clickers was very good—as a report put it, their 'automatically computed consensus” was “virtually indistinguishable from the inputs of a geologist with years of experience in identifying Mars craters.'"

He goes on to write about how Google ranks pages based on the actions of millions of users, and cites other examples. This isn't just about judgment. This is about creating. At one level this is not new. For centuries humans have been walking down trails that have been defined by the steps of thousands of people who have come before. But this capability of the Internet to knit together individual consciousness into something collective is something newly emergent, it seems to me.

Collectively, civilization can do what individuals can't. On our own, we really are just intelligent apes. But with one other person we can create a new human. With one million other people we can create a new community or set of institutions. And with billions of people online, maybe we can create a new sort of understanding that would be impossible for the individual or even any community within it.

It might just be that the web is enabling a new kind of consciousness to emerge, awareness and problem solving and project execution that would never be possible at the level of individuals or even teams traditionally managed. If so, it raises a fascinating question. Has the web developed consciousness yet? And if it was self-aware, would we be aware of it?

Why Cities Keep Growing, Corporations And People Always Die, And Life Gets Faster | Conversation | Edge

Why Cities Keep Growing, Corporations And People Always Die, And Life Gets Faster | Conversation | Edge

Geoffrey West shares some fascinating things that he and his team have learned about systems dynamics. (Click through on the subtitle to see his talk or scroll down to read the transcript.)

One, growth in cities provides some economies of scale. Give him the number of people in a city and he can give you the number of gas stations, miles of roads, etc. The good news is that these kinds of things grow more slowly than the population.

Economic activity, however, grows faster than the number of people. Incomes and innovation within a city grow faster than the population. This, too, is a good thing.

His team has recently analyzed data on companies and he's found a few odd things. One, the profits to sales ratio shrinks as a company gets larger. Two, the rate of innovation also slows. Three, the volatility of sales each year actually becomes greater than the profit percentage. (For instance, at a particular stage, volatility in annual sales of 10% might accompany a profit rate of only 5%.) Companies die as they become less tolerant of crazy ideas and crazy people (their rate of innovation, consequently, slows).

Oddly, as cities become larger they foster more innovation yet as companies become larger they become less innovative. This - it seems to me - has to do with how citizens are "managed" less than employees.

One of the things that makes this so fascinating to me is that it suggests that these dynamics explain more about rates of growth and life expectancies (yes, even of companies) than more traditional explanations like culture, history, and conscious policies. For me, it is further confirmation that an understanding of systems is not just going to be nice in this new economy: it will be necessary.

And Sometimes the Butterflies' Wings Carry it Over to Pollinate the Tree of the Knowledge of Good and Evil

I got introduced to systems thinking by the management guru W. Edwards Deming. He made the point that when assessing a team made up of three people, it is easy to think that we’ll know how the group would perform simply by looking at the performance of each individual. The team performance of Tom, Carmen, and Jin could look like this:

Tom’s performance [T] + Carmen’s performance [C] + Jin’s performance [J] = team performance [x]

In fact, that might well be the least of the equation. The team’s performance is also a function of

Tom’s working relationship with Carmen [T~C] + Carmen’s working relationship with Jin [C~J] + Jin’s working relationship with Tom [J~T] + the dynamic that emerges between all three [T~C~J]

An equation that at first blush looks like:

T + C + J = x

Is actually

T + C + J + [T~C] + [C~J] + [J~T] + [T~C~J] = x

This is not a problem of simple addition. This is a problem of relationships and emergent phenomenon. Jin could be a great guy but cause the other two team members to perform poorly. Carmen may be a poor performer on her own but might make the team perform better. The symbol ~ sometimes adds and sometimes multiplies as team members bring out what is better in each other; it sometimes subtracts and sometimes divides as they, at other times, undermine each other or leave each other feeling like less. What emerges out of relationship is not simple and cannot be reduced to the parts. Systems are defined by emergent properties, not just their parts.

“In an avalanche, each snowflake pleads its innocence.”

-         - Proverb

And of course, the world in which we live is defined by system dynamics, by the interaction of systems and even the performance of systems within systems. Cultures and societies are not the product of just one person, they emerge out of a dynamic between people and their times and circumstances. Your work place, your town, your portfolio, your marriage… these are defined by not just by emergent properties but how they, as systems, fit within the larger system we call the environment. Like Russian dolls, our world is not only composed of systems but has layers of systems. Your respiratory system can perform in ways that allow you to run a marathon or be unable to rise out of bed; if you are king, this difference can ripple across a kingdom to shatter a fragile peace. 

Sometimes the butterfly stirs up a storm and sometimes it gets pinned inertly into the collection. It’s hard to predict which it will do by just looking at the butterfly. 

Stork Delivers Babies / Black Swan Delivers Perpetual Apocalypse

This last year has given us some momentous news: eco-disaster with the Gulf Oil spill, devastating earthquakes in Haiti Chile, and Japan, threat of nuclear meltdown, riots in the Middle East, and sluggish recovery from a financial crisis.  Economic, ecological, urban, energy, and political systems have all been pushed beyond their presumed limits.

It might be that global news and the Internet have simply brought events that decades ago would have been marginalized in the back pages of our newspapers to the forefront of our attention, resulting in a sense of perpetual apocalypse. Or it could be that the modern world has been overshadowed by a flock of Black Swans.

Nassim Taleb's bestselling book, The Black Swan, tells the story of how experience only predicts the future as long as systems are stable. Of course, the defining events shift the system boundaries rather than stay within them. (Taleb tells the story of the turkey convinced that he's loved and cared for and that his owners want the best for him until the day before Thanksgiving when ALL of his experience is suddenly made meaningless and his world view is shattered. The events of 9-11 and the Great Recession, of course, are events that change what is predictable.)

Our modern world may just be so dependent on interdependent, ultimately fragile systems that a parade of news like we've seen in the past year is inevitable. Even if the probability of any one system collapsing or causing destruction is only .1%, we live in a world so populated by these systems that the probability of ONE system reaching a tipping must be close to 100%. Somewhere, a political system will have reached a tipping point and a people will be thrown into violent clashes and social turmoil. An energy system will either become expensive, unstable, or blow up. And the list goes on.

This is a time of perpetual apocalypse for a simple reason: we depend upon systems that we still understand only dimly and can predict and manage with even less confidence.

Isn't it time to invest massive amounts of research money into the development of better models for understanding and managing these systems? The world will not become less complex, but only more so. If we have to live with Black Swans, perhaps we can at least get them to fly in formation.