The Most Surprising Innovation Lesson on Earth? A Tropical Beach in Kazakhstan at Twenty Degrees Below Zero

Last month, I had the pleasure of enjoying a tropical beach.  But this was no ordinary tropical beach.  True, I got to sink my feet into fine, warm sand, lounging beneath palm trees that fringed crystal clear waters.

But the thermometer registered nearly twenty degrees below zero!

So where in the world was I?

Only the second coldest capital in the world!

Welcome to the indoor tropical beach in Astana, the capital of Kazakhstan!  This beach is located on the top floor of the Khan Shatyr shopping center, which also happens to be the world’s tallest tent structure.  The beach provides a warm and welcome refuge from the subzero temperatures outside, after a long day of work.

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Can Entrepreneurship be Taught?

Ryerson University prides itself on its approach to entrepreneurial education. It is home to one of the largest entrepreneurship programs in Canada, and promotes student entrepreneurship through organizations. It also focuses on experiential learning that requires a hands-on approach to facilitate creative thinking in even the most traditional professions. While entrepreneurial education is gaining popularity with post-secondary institutions, entrepreneurship as a teachable discipline is still having to contend with critics.

The common misconception is that entrepreneurship can’t be taught, because it requires too much real-world experience to master. Victor Hwang is the managing director of T2 Venture Capital and he has seen many qualified M.B.A-educated professionals try and fail as an entrepreneur.

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Who Will Be The Next Iron Chef Of Innovation?

“Cooking requires confident guesswork and improvisation– experimentation and substitution, dealing with failure and uncertainty in a creative way.”

― Paul TherouxSir Vidia’s Shadow: A Friendship Across Five Continents

Read any blog, business article, news story or management piece and you’re likely to read something about innovation. Each will offer a magic component, a secret sauce, a particular flavor  . . . always a specific ingredient that will give you the definitive “innovation recipe.”

Headlines declare:  “Ten Critical Changes To Make Your Company More Innovative” or “How To Organize for Innovation” or “How Your Chief Innovation Officer Can Make A Difference” or . . . well, you get the drift.

Read the full article here.

The World is (Or Should Be) in Chaos—In a Good Way. On government’s attempt to steer the economy

The Fear of Chaos…

To many people the idea of chaos is a frightening one.  They picture riots in the streets, wanton disregard for the law, murder, theft, assault gone unchecked—in short…anarchy—a system run amuck.  But let us not mistake chaos for anarchy.  A system based on chaos is no less lawless than a system based on deterministic rules; in fact, chaos indeed adheres to a very well defined set of rules, whereas anarchy is characterized much more by the absence of rules.   However, while the rules underlying chaotic function may be very well understood, the results, nevertheless, are unpredictable for a very simple reason—we simply do not know where to start.

This is the definition of chaos—that knowledge of a prior state is never sufficiently accurate to give any predictive power to determine a future state at any arbitrary time.

The fact that a butterfly flapping its wings in China causes a hurricane in Florida does not negate the rules of the physical world, it simply points out to us how poorly we can measure small effects that produce large results given large numbers of interacting elements.  As applied to the real world, this basically boils down to this:

When there’s a bunch of stuff interacting, it is impossible to predict the outcome at any arbitrary time in the future.  Predictions or attempts to control the weather, economy, or even three bouncing balls are essentially futile.  The world succumbs to chaos—but I will argue that this is a good thing when it comes to things like the economy.

The Complexity of Life

The root of chaos theory lies in a simple example called the Three Body Example.  To understand this idea, imagine three billiard balls that never lose speed due to friction, gravity or any other forces, that were bouncing around a billiard table.  The most modern physics and mathematics tell us something startling: It is impossible to predict the evolution of a system like this based on some arbitrarily accurate initial conditions.  To re-iterate: IT IS IMPOSSIBLE!  How strange is this?  I mean, three balls bouncing around and we cannot predict what is going to happen?  Absolutely not!  It is shocking for people to learn this at first, but the images below demonstrate this fact precisely.  These images show the evolution of a precisely defined physical state.  The line traces the path of a “planet” as attracted by two suns (the black dots).  The planets start on the exact same point with the sole difference being that one is give an initial velocity that is 1% greater than the other.  The systems are relatively predictable over a short term but quickly begin to diverge until they are utterly unrecognizable.  This is a 1% difference in initial conditions with only 3 interacting bodies and the results are completely unpredictable.  This example, of course, is actually calculated using discrete time steps with defined initial conditions so its evolution can be plotted, but in the real world, we have to measure initial conditions and we can never measure well enough…consequently, we can never predict the future outcomes!

three body

This idea of sensitivity to initial conditions is well accepted in all forms of physical science and is so fundamental to the governing principles of our world as to appear with as little as three interacting bodies.  The effect is widely understood in the realm of weather reporting as the “butterfly effect” and is commonly accepted by the general public.  In fact, in order to fully be able to predict the weather, we would need sensors essentially on every single atom in the world and even that may not be sufficient.  But we give weathermen a break when they are wrong—sometimes that is—because, hey, the weather is damn hard to predict!  And that’s even just the one week forecast within general limits of geographic location and season.  We intuitively understand that the weather is nearly impossible to predict with any accuracy even a week out in many cases because of the complexity of the system, yet we do not apply this same reasoning to other equally complex systems such as economics.  We cling to the idea that the “economic experts” know best, that for some reason their discipline is more rigorous and deterministic than the weather (to be fair it may be a bit less prone to chaos than the weather due to the fact that instead of having nearly limitless numbers of atoms interacting, we only have to deal with about 7 billion characters, but this hardly defrays the point).  This reasoning is an utter fallacy.

The truth is: Nobody can make accurate and predictive decisions regarding the future of such complex systems as the economy.  The basic reason is simple: nobody KNOWS enough.

Two Types of Knowledge

In his book The Constitution of Liberty, Friedrich Hayek lays out two very distinct types of knowledge that are useful for making decisions to understand our world: direct knowledge and indirect knowledge.  Direct knowledge is simple to understand, it is simply the things that you or I or any other individual person possesses in their head.  It encompasses all forms of formal and informal education, all experiential based knowledge that one has obtained over the course of life, and every other detail that a single person can acquire.  This knowledge is often quite useful for us in making decisions throughout our daily life.  It can provide us with a good job, decent living prospects and a security that we actually have an understanding of the world around us.  This type of knowledge can range substantially among individuals making it appear as if some are “superior” in intelligence than others.  Those that go to Harvard, for example, are held in high esteem as being “very knowledgeable” with an analysis based on a comparison to other individuals.  However, this is quite a flawed perspective as it is necessarily relative, and the range of that relative scale is quite narrow—quite frankly nobody really knows that much on an absolute scale of the knowledge of all of humanity.  In fact, even the brightest people on earth hold an insignificant percentage of all of human knowledge and when the range of differences in individual human knowledge are ranked on a scale encompassing all of human knowledge, we see that the entire range, from numbskull to genius, barely represents a hair’s width on the greater spectrum and is getting smaller every day as total knowledge exponentially increases.  As Hayek states:

“Compared with the totality of knowledge which is continually utilized in the evolution of a dynamic civilization, the difference between the knowledge that the wisest and that which the most ignorant individual can deliberately employ is comparatively insignificant.” (The Constitution of Liberty)

So this begs the question: how do we expect any one (or group) of individuals to have enough knowledge about the world to:

  1. Overcome the inherent randomness endemic to chaos in our world
  2. Actually provide an accurate analysis of the entire state of a system

And the answer is (once again) simple.  We cannot.  Nobody knows enough.

So what does this leave us?  How do we proceed to operate in a world where nobody knows anything sufficient to understand our state of existence?  The answer lies in indirect knowledge.

Knowledge-ManagementIndirect knowledge is an emergent property, it is something that no one person or group knows but it arises from collective behavior.  To understand this idea is straightforward.  Take any household object—say a bottle of wine—and ask yourself simply: what is the value of this bottle of wine to society (while assuming no external controls)?  You may say a particular value, while your neighbor says a higher value.  The point is that neither of you are right, nor have any claim to being even the most accurate.  The value of that bottle of wine to society will only be determined in a free system by the collectively agreed upon price that represents general consensus.  Two things are important to note here:

  1. No individual or group of individuals can accurately predetermine a value.
  2. The “consensus” estimate is necessarily defined by multiple independent entities acting in self-interest, not by the consensus of a central committee.

This is the core of indirect knowledge and it is something that is inherent only to free market economies.

Let us evaluate what would happen if this system were tampered with.  Imagined that the equilibrium price of said bottle of wine was $8. Under these circumstances, producers would compete to produce said wine for under $8 to make a profit.   Let is now assume that a central authority fixes the price to $10 to “be fair”.  This results in two potential outcomes:

  1. The excessive profits of the wine producers due to preferential treatment (rather unfair behavior)
  2. The inefficient use of resources and excessive waste as wine producers no longer have to operate good businesses to make a profit.

Neither of these outcomes is beneficial to the overall growth of the economy.  Both are the roots of waste and excess that is the cornerstone of the movements against the “crony capitalism” that is so prevalent in today’s government.  And once again, the reason is simple:

No person or group or persons knows enough about the economy to make intelligent decisions about value.  Value arises SOLELY from indirect knowledge.  The direct knowledge of individuals is egregiously insufficient to extend into the complexities of systems outside of ones own life (and even there it is insufficient to predict the future)…

The Extent (and Utility) of Knowledge—The Black Swan

The argument against direct knowledge (i.e. people) attempting to make intelligent decisions regarding such complex systems as the economy that are, in fact, predicated on indirect knowledge is clear.  However, even comparatively simple systems (such as our own lives) are insufficiently predicated on our direct knowledge.  In his book, The Black Swan, Nassim Taleb argues that, in fact, the defining characteristic of everything in existence is its unpredictability.  In colloquial terms this is simple to understand: it is the idea of “being in the right place at the right time”, the “unexpected pregnancy” that leads to a wonderful family, the job offer that comes out of the blue.  The defining characteristic of these events is that that they are entirely unpredictable.  In fact, I argue that the milestones by which many people demarcate their lives are (in a prospective viewpoint) entirely random.  And while people have the inherent urge to justify, explain and describe all of the conditions that led up to a particular event, any sort of rationalization serves little utility in predicting the occurrence of the next.  In other words, hindsight is 20/20 and we suffer from an extreme survivorship bias that makes us believe that we can define the events that precipitated a particular event, and that the observation of similar events in the future will produce similar outcomes.  We look at Warren Buffet and try to distill his characteristics that made him successful such that we can apply them in future for a similar outcome and find ourselves failing.  The reason? Simply that we do not take into account the element of randomness—that in a group of 1000 people, one may become a superstar simply by the Gaussian distribution of chance.  It is not a point of contention whether Warren Buffet is intelligent or business savvy, but there are many of those of equal or greater caliber that are not worth $50B.  To single him out is useless.  The gist is that the world is too complex to distill generic rules that we believe can predict the future.  It is important to note that this does not preclude the idea that we might try, but the danger lies in the trust of the infallibility of the “experts” into whose hands we place our livelihood and in the authoritarian power of a central government to force compliance.

The Paradox of Uncertainty—Academics vs. Politicians

The real paradox of the idea that “experts” can make rational and intelligent decisions regarding the future of something as complex as the economy is viewed in reflection to perspective in academia.  It is widely regarded in academia (and often in the general public) that it is impossible to predict the progress of knowledge in research—or rather that research should be left unfettered to discover what it will and that bounding it will only hinder its ability to uncover the wonders of our world.  In fact, this idea is so prevalent in academia that the entire system of tenure is based upon it—that we should give freedom to accomplished researchers to pursue avenues of inquiry free from the shackles of responsibility to allow for the free flow of ideas and the often “accidental” discovery.  Indeed, many of the major discoveries of academia have been a direct result of this intellectual freedom, from the serendipitous “discovery” of penicillin by Louis Pasteur, or a chemist who didn’t wash his hands after working with coal tar and ended up finding the popular sweetener saccharin, all the way to the confirmation of the Big Bang by the random discovery of cosmic background radiation while trying to clean bird crap off some satellite dishes.  The point is that we as a culture regard the unfettered search for knowledge in the sciences as an indispensible tool for future progress and indeed it has been enormously successful.  Scientists are the first to recognize how little we really know about the world around us and the first to open the door to experimentation.  But this same knowledge does not apply to the disciplines of economics or social engineering.  In these arenas, the “champions” advocate the accuracy and reliability of their models instead of their uncertainty, and their arrogance breeds devastating results.

It is an irony that we accept so readily the validity of freedom of both thought and execution in the halls of academia (and benefit greatly from the fruits of their often random discoveries) and hold so fast to the conviction that in arenas of social and economic policy, these same rules of serendipity do not hold—but rather that these disciplines (uniquely) can be steered intelligently.  Simply imagine if we limited all scientific research to ideas that the government deemed useful—how many things we would be without.  As Hayek says, “To extol the value of intellectual liberty at the expense of the value of liberty of [actually] doing things would be like treating the crowning part of an edifice as the whole” (The Constitution of Liberty)

The Downfall of Prediction—The Great Depression Relived

As is often said, “the proof is in the pudding”.  If we are to evaluate the attempts of government to direct and control such behemoths as the economy in this time of dire circumstances, the worst economic downturn in nearly 100 years, we need look no farther than the past and the prescient words of Franklin Roosevelt’s Secretary of the Treasury and chief architect of the New Deal, Henry Morgenthau, who accurately stated the results of Keynesian economics:

“We have tried spending money. We are spending more than we have ever spent before and it does not work…. After eight years of this administration we have just as much unemployment as when we started…and an enormous debt to boot!” (Roosevelt and Morgenthau, John Morton Blum 1970)

It is no secret that current Federal Reserve Chairman Ben Bernanke is an authority on the Great Depression of the 1930s, publishing numerous academic papers on the topic. It is, however, curious that the conclusions reached by the Treasury Secretary of the 1930’s is not recognized by today’s denizens of economic policy.  Taken to the extreme, history’s greatest experiment ever in central planning was also one of its greatest failures.  The fall of the Soviet Union vindicated anyone who advocated free markets, yet we continue to make steps in that direction, with government advocating for more regulation, more control, and more restriction on private enterprise.  So much for learning from the past.

Bottom Line: Chaos is not only beneficial for economic growth, it is essential.  It allows for experimentation unfettered by arbitrary restrictions made by the limited “direct knowledge” of the few.

Chaos is not lawlessness.

Chaos is not randomness.

Chaos is the idea that we have no idea what the future will hold

Chaos is the idea that we can’t guide what the future will hold

Chaos is the idea that the best results come from experimentation

Chaos is freedom

And Chaos has done us well ‘till now

Let’s take Chaos into the future…it has to be better than any central plan

A future determined by the many is preferable to a future determined by the few  

Global Innovation Agenda Will Grow Stronger in 2013

As we begin a new year, we’d like to wish all our followers a happy and innovative new year in 2013.  The past year, 2012, involved some major activities in the evolution of The Next Silicon Valley, and our visibility seems to have aligned with an equally growing interest in the innovation agenda globally. Many countries have been involved in some way in innovation-related conferences, events or activities – whether they have been governmental, not-for-profit, or for-profit organizations.

We worked very closely with some of these, including the Global Innovation Summit in San Jose and innovaBRICS in London.  We also worked with the International Association of Science Parks annual conference IASP 2012 in Tallinn, Estonia.
The Global Innovation Summit, drew around 400 delegates and participants from 49 countries to Silicon Valley, not to gawk at reality TV crews or to rub elbows with the next Mark Zuckerberg, but in search of answers to what has become one of the world’s – if not the Valley’s – most urgent questions: “How do other countries, regions and cities cultivate ‘innovation ecosystems’ and what is the secret to building the next Silicon Valley?”
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