Network Evolution and Invention in Technology Bubbles

How autocatalysis and scaling laws may shed light on how technological revolutions happen, and why diversity matters

There are a couple of relevant metaphors in this image. Please don’t sue me, Disney.

Introduction

The following article synthesizes concepts and frameworks from multiple books, papers, and articles I’ve recently read in order to better understand technology diffusion, organizational invention, and network evolution on both a micro and macro level. The resulting concepts are then applied to the current Blockchain bubble. I conclude with recommendations.

The “Basics”

In this section I will very briefly summarize the relevant concepts I am synthesizing. Included in each section is a video or videos featuring the authors which I believe to be illuminating, as well as links for further reading. For the sake of brevity I only scratch the surface of these authors’ works.

Carlota Perez — Technological Revolutions and Financial Capital

Researcher, lecturer and international consultant, Carlota Perez, discusses her work with Venture Capitalist Fred Wilson

Some say we are in the second technological revolution. Others the third. Carlota Perez posits that over the past 250 years five technological revolutions can be identified:

Source (accessed August 20, 2017): http://www.carlotaperez.org/pubs?s=tf&l=en&a=technologicalrevolutionsandfinancialcapital

Each has demonstrated development and diffusion of broad technological paradigms (e.g. mass production, electricity, IT) along a recognizable pattern, outlined below.

Source (accessed August 20, 2017): http://www.carlotaperez.org/downloads/pubs/PEREZ_TRFC_Ch%207.pdf

Major technological paradigms start gradually after their initial introduction. During this first stage, they are overshadowed by the prevailing technological paradigm while early advocates seek to incubate and solidify the foundations of the technology with the support of visionary financial capital.

As with any S curve, at some point adoption takes off. During this second stage a few things happen, all enabled and catalyzed as a result of the intense financial incentives, including:

• Infrastructure is built out en masse
• An incredible diversity of ideas are considered and experimented on

At some point, the bubble inevitably bursts. Historically, these corrections were dramatic, and devastating to broad swathes of the economy.

The first effect of the correction has been to wipe out the detritus generated by the frenzied investment and experimentation. Bad ideas are tossed out and good ones identified. Standards are raised. Measures (read: regulation) are put in place to prevent future abuse.

The second effect has been broader, due to the typically devastating impact of the crash on the broader economy. Weak firms are brought to their knees. Institutions are questioned. Generally, the stage is set for renewal, enabled by the experimentation and infrastructure produced during the bubble.

In the third stage, which she calls the Golden Age, the economy takes off on the back of the technological paradigm. New industry giants take hold and the economy is reshaped.

In the fourth stage, the paradigm inevitably begins to lose steam, and financial capital starts looking for the next big thing. It’s important to note that Perez readily admits this framework is not intended to explain everything, particularly as it relates to how technology diffuses across sectors, markets, and countries, so don’t get too caught up in the details. She writes:

In a more modest way, the model can simply serve as a frame of reference for social actors within the system as it now operates. Under those circumstances, those who grasp the sense of the times, correctly interpret the potential and the direction of change and deeply understand the characteristics of the relevant paradigm, are more likely to be able to pursue their goals with viable and realistic proposals.

Further reading:

Is Artificial Intelligence Really the Next Technological Revolution?_A comparison of AI with previous technological breakthroughs_shift.newco.co

The Carlota Perez Framework_I was reading William's post on the potential crash in the Bitcoin sector this morning and I thought of Carlota Perez…_avc.com

Second Machine Age or Fifth Technological Revolution? - Beyond the Technological Revolution_Second Machine Age of Fifth Technological Revolution? Different interpretations lead to different recommendations …_beyondthetechrevolution.com

John F. Padgett and Walter W. Powell — The Emergence of Organizations and Markets

Walter “Woody” Powell, Professor of Organizational Behavior at Stanford University, discusses the emergence of novelty in organizations and markets.

John F. Padgett, Professor of Political Science at the University of Chicago, discusses the evolution of novelty at the Center for the Study of Economy and Society at Cornell.

Padgett and Powell’s edited volume is massive (rarely has my Kindle told me there were over 30 hours remaining in a book), and as Joshua Cooper Ramo wrote in The Seventh Sense, it’s a “masterful study of complex connected systems”. I’ve included the above videos as good summaries of the ideas, but the depth of the research behind them is jawdropping.

Each chapter covers a different historical period, from the emergence of the partnership system in renaissance Florence to the Boston bio-tech ecosystem, with ample data and analysis presented through the context of their model. Padgett’s work on Renaissance Florence is based on his own archival research and a resulting relational database:

For the past twenty years, I have been constructing from primary archival sources a very large relational database about social-network evolution over the two hundred years, 1300–1500, in Renaissance Florence. This unprecedented data set contains information on about 60,000 persons: 10,000+ marriages, 14,000+ loans, 3,000+ business partnerships/firms, 40,000+ tax records, 12,000+ political-office elections, and other matters.

Needless to say, the ideas are not conjecture, and are in my opinion cutting edge. That they have received limited direct attention in my spheres is probably due to the immensity of their book, but I am certain that will change.

The book is all about the concept of emergence, or how networks and systems emerge and evolve. A key aspect of their model is the importance of cross-network transposition, or processes being taken from one network to be used in another. The authors do this themselves in laying out the foundation of their model, taken from biochemistry: autocatalysis.

There are a few competing theories for how life emerged on earth (creationism notwithstanding):

the RNA-first position, which places all its explanatory emphasis on the self-organization of nucleic acids, and the metabolism-first position, which focuses on the self-organization of simpler energy-processing chemistries that RNA and DNA later regulated and reproduced. A minority position insists that lipid cell vesicles came first, which both types of chemistry came to inhabit… the concept of autocatalysis lies at the foundation of all of these positions (Source p. 1)

Autocatalysis, simply defined, describes a system that is self-reproducing, given the necessary inputs. Our bodies are autocatalytic in that (most of) our cells are regularly replacing themselves over time.

Padgett and Powell write how they apply this concept:

to the analysis of co-evolution of products and firms through the following analogy: Skills, like chemical reactions, are rules that transform products into other products. Products, like chemicals, are transformed by skills. Firms, like organisms, are containers of skills that transform products. Trade, like food, passes transformed products around through exchange networks, renewing skills and thereby firms in the process. In the macroeconomic aggregate, product inputs flow into, and outputs flow out of, this trading network of firms and skills. Economic ‘life’ exists if an autocatalytic network of interlinked skills and products can emerge and renew itself, in the face of continual turnover and ‘death’ in its component skills and products.

Padgett and Powell propose there is a common set of mechanisms, based on their autocatalysis model, that explain the emergence of important inventions throughout human history, including:

• The partnership system
• The stock market
• The modern state
• The commercial field of life sciences
• Open source

Padgett and Powell also like to use the following definition of autocatalysis:

A set of nodes and transformations in which all nodes are recreated by the transformations among nodes in the set.

This describes a system which re-creates itself, given the appropriate inputs. The value in this definition, however, is in how they adapt it to thinking about organizations and actors.

A network of people/processes/organisations and relations in which all people/processes/organisations are recreated by the relations among people/processes/organisations in the network.

To take a specific example, I recently read a reflection piece written by Chenyu Zheng, a past employee of Uber China. She writes about how Uber was so effective at taking lessons and processes from one market and rolling them out in another:

…religiously document best practices and share with global team via playbooks. To me, one of Uber’s most impressive practice is documentation: every successful campaign has been playbook-ed with step-by-step procedure, FAQs and doc ownership. For example, when China wanted to activate Ice Cream Day, marketing managers could search for Ice cream playbook and implement. Documenting religiously may be a painful practice to adhere to, but it will not only remove communications friction, inefficiency and error, it will allow any growth stage company to expand faster in a global context.

Uber had become autocatalytic with respect to how they rolled out markets and products. Many entrepreneurs and VCs would justifiably view this with envy. There is, however, a downside to such strong autocatalytic processes. In this case, I wonder whether or not Uber was approving market entries too often because a) they became so easy and effective, b) employees were motivated to achieve similar success, and c) because of the need to grow rapidly.

However, growth must be carefully managed, particularly when it involves developing a novel network. Now, they are left with an expansive global footprint but an underlying network structure that may be less robust than it could have been had they focused on marginal improvements to the network effects and unit economics of their model in fewer core markets.

Stratechery points out that Uber failed to develop financial-performance data tools (surprising for a company so intent on internally developing almost all scaling-dependent software they used), which likely handicapped both their ability to decide when to enter/exit markets, and how to evolve their unit economics:

Aside: I wrote about my vision for their network model last year:

The Network Effects of Uber’s Master Plan_I am going to describe and illustrate what I believe to be Uber’s network effects model. This does not represent their…_hackernoon.com

On the other hand, she writes that one of the great benefits of Uber entering China with the level of skill they brought with them is that these skills were transposed into the Chinese entrepreneurial system, with profound benefits which we are seeing now.

In China, Uber is nicknamed as “the Huangpu Military Academy” or West Point for tech talent. Any graduate of “Uber China” has the traits of hustle, extreme ownership and high productivity. In fact, bilingual talent as such is hard to find elsewhere in China.

This leads to my first viewpoint: Uber did not fail in China, but incubated entrepreneurs, and most notably, the highest performers of Uber China took the battlefield from ride-sharing in 2016 to bike sharing in 2017.

In my opinion this too is a wonderful example of autocatalytic transposition between networks, in this case Silicon Valley and China via Uber, with lasting effects in China. As Padgett and Powell write:

The production and distribution of goods by firms are only half of what is accomplished in markets. Firms are also produced and transformed by the goods and people passing through them. Social structures should be viewed more as vortexes in the flow of social life than as architectural buildings.

Suffice it to say, I am intentionally scratching the surface of Padgett and Powell’s work, only to the extent necessary to continue with this piece. I encourage you to check on the above videos, and the excellent blog posts below.

Further Reading:

Padgett, Emergence of Organizations and Markets, Part I_I'm an idea junkie. I have fairly diverse interests and scan lots of things. But, for the most part, the things I come…_ecologicalsociology.blogspot.de

Padgett, Part II: Emergence of Partnership_A previous post described the basic outline of one of the most important ideas I've come across in the past decade…_ecologicalsociology.blogspot.de

Padgett, Part III: Autocatalysis in the Economy and in Persons_This is the third in a series dealing with one of the most interesting ideas I've come across in a decade: the theory…_ecologicalsociology.blogspot.de

Geoffrey West — Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies

The scope and depth of Geoffrey West’s Scale is so significant that I’m going to turn over the synopsis to The Institute of Physics, which sums the key points of the book up perfectly for my purposes:

The essence of any complex adaptive system — a person, a company or a city — is that there are many small interacting components within a network that iteratively follow very simple rules. Over time, complex behaviour emerges in the system, usually in an unpredictable way. Such networks can be observed all around us, and West maintains that they are the mechanism by which nature distributes energy and materials.

Within this framework, a company is much like a living mammal, consuming energy and resources to transform them into something useful — it has a metabolism, if you will. So what happens to that company as you scale it up in size? Common sense might dictate that doubling in size would require a doubling of resources, but that is not what West found when he analysed the data. An animal that is twice the size of another only needs 75% more food and energy per day, and the same goes for a company that is twice the size of another. It’s an example of sublinear scaling — and it’s the reason companies, like living organisms, have a finite life span. They grow rapidly when they are young, but growth gradually slows as they mature, until they “die” via bankruptcy, mergers or acquisitions.

Cities behave very differently, according to West. They show the same sublinear scaling when it comes to infrastructure: the bigger the city, the more efficient the distribution of its roads, cables, gas stations, power lines, railways and other infrastructure, so the fewer of those a city needs.

But the essence of any city is its people, interacting and collaborating with each other to innovate and create wealth. The socioeconomic aspects of cities — wages, number of patents, wealth, not to mention negative aspects such as crime, pollution and disease — exhibit what West terms superlinear scaling. Cities also become more diverse as they grow, while companies become more homogenized and risk-averse, making them less robust when the inevitable catastrophic fluctuation hits. Cities therefore rarely die, even after a catastrophic event. The Japanese city of Hiroshima thrives today despite the devastation wreaked on it by the atomic bomb in 1945.

Of course, there is a catch to West’s theory: such unbounded growth is ultimately unsustainable. It’s the Godzilla problem with a twist. Such a system will keep growing to infinity, requiring infinite resources, and that is just not possible in the real world. The key is innovation via disruptive technologies, for instance. A major paradigm shift will essentially reset the system, staving off collapse. But those shifts must occur at an ever-accelerating pace.

West is quick to point out the futility of seeking to break down and analyze the interacting component parts of systems and networks to the nth degree. This is not about designing and harnessing complexity. Case in point:

Rather, it’s about better understanding the dynamics on a micro level in order to guide the system on a higher level.

West wrote Scale for two reasons, in my opinion. First, he wanted to explain some very cutting edge concepts developed at the Santa Fe Institute (at which Perez, Padgett, and Powell have spent time), which more people should be exposed to. In doing so, he laid the foundation for his second goal, which is to outline what he believes is humanity’s next great challenge: to find a sustainable means of accelerating the frequency of disruptive innovation.

For the past several generations we have reaped the benefits of tremendous growth on the backs of successive technological revolutions. However, the increasingly dense and complex networked nature of humanity is leading to an acceleration of dangerous negative effects, which in turn require an accelerated frequency of technological revolutions to “reset” the clock. Specifically, he challenges us to think differently about what exactly technological innovations are, and what a prosperous and healthy system is measured by.

Further reading:

The elegant law that governs us all_A dog owner weighs twice as much as her German shepherd. Does she eat twice as much? Does a big city need twice as many…_science.sciencemag.org

Growth, innovation, scaling, and the pace of life in cities_Theoretical Division, MS B284, Los Alamos National Laboratory, Los Alamos, NM 87545; ‡Global Institute of…_www.pnas.org

Geoffrey West's long-anticipated book Scale emerges | Santa Fe Institute_Soon, West and colleagues observed similarly predictable scaling regularities in nearly every quantity arising from…_www.santafe.edu

WHY CITIES KEEP GROWING, CORPORATIONS AND PEOPLE ALWAYS DIE, AND LIFE GETS FASTER_This is in complete contrast to companies. The Google boys in the back garage so to speak with ideas of the search…_www.edge.org

Summary

To briefly summarize the above concepts:

• The development and diffusion of technology over the past 250 years can be viewed through the four-stage framework developed by Perez, in which each of five major revolutions underwent a bubble stage, within which the intellectual, social, organizational, and physical infrastructures for the golden ages that followed were laid.
• The emergence and evolution of social, technological, and intellectual networks can be modelled using the biochemical concept of autocatalysis, which describes how skills can be transposed and replicated across interacting networks, and generally how complexity emerges from simplicity under the right conditions.
• The complex interacting systems underlying cities, companies, and organisms exhibit super- and sublinear scaling effects. This helps explain both why we live as long as we do, as well as why cities are hotbeds for innovation. It also points to problematic negative externalities should innovation not keep pace.

Synthesis

Drawing from the above sources, it appears bubbles are a common aspect of the historic diffusion of technological paradigms, serving as an environment in which:

• the metabolic rate of network activity is increased, due to availability of financial capital and intellectual hype cycles
• infrastructure is rapidly and massively built out
• development of and experimentation around a technology happens at an accelerated pace
• networks meet, combine, and transform, resulting in new organizational and biographical forms necessary to handle the challenges and opportunities presented by the new paradigm

Seen through the lens of West’s advocacy of cities as valuable accelerators of innovation and prosperity, the increasingly connected and networked world we live in may be enabling “pseudo-cities” to be formed in the context of technological revolutions, with both the benefits and negative side effects of actual cities.

This is not to suggest bubbles are a necessary or even positive aspect of technological revolutions. Rather, by understanding what is happening within what is essentially a vortex of financial, social, and intellectual capital, it may be possible to both limit the extent of the correction if not eliminate it completely, and maximize the benefits to innovation.

Furthermore, the hyperactivity of bubbles provide opportunities to study autocatalytic network evolution, lessons from which could be applied to non-bubble environments. In other words, they provide exception real-world experimental environments for scientists and economists.

Additionally, while Perez’s framework may have only been historically noticeable on a macro level, West’s work on scaling and metabolic rates may indicate an opportunity to (or risk of) seeing the phenomenon on a sub-paradigm level, as demonstrated by the current bubble.

Whether or not this dynamic is a risk or benefit to humanity depends on whether we are capable of learning how best to dampen our worst impulses and minimize collateral damage.

The Blockchain Bubble

The Blockchain bubble has many effects which we should now be familiar with.

• Infrastructure is being built out en masse. There are some obvious examples, including mined Bitcoins and Ethereum, GPU farms, and databases specializing in structured data. However, in the case of Blockchain it makes sense to think very broadly about what infrastructure means, and what an excessive of it would mean after a potential correction. (Edit: I went for a run after publishing and listened to this very relevant podcast from Andreessen Horowitz on infrastructure)
• An incredible diversity of ideas are being considered and experimented on. No stone is being left unturned and no crazy idea rejected (for the moment).
• An international and cross-sector cohort of people are meeting and building relationships, which means networks are overlapping, and transforming.
• New organizational forms and financing tools are emerging and being tested by the system. The best example of this is the ICO. This novel financing mechanism could be compared to multiple historical networking-tipping financial inventions covered by Padgett and Powell.

A key message is not to lose the forest for the trees. Yes, the emergence of the ICO and the accompanying loose capital funding them is leading to potentially dangerous chasms between productive potential of investments and financial expectations. However, it is also drawing more intellectual energy into a growing network, likely to result in more novel forms of development, investment, and governance.

What happens next is anyone’s guess. After all, emergence is as much about chance as about choice. I can only suggest that we’ve been here many times before, and while the results of history don’t repeat, the underlying processes do. The question is whether we are now capable of collectively seeing those dynamics with clarity, and acting accordingly.

Recommendations

In this section I will sketch recommendations. I have several in the works which I will not publish now, and I generally expect this section will grow and evolve over time.

Diversity Matters for Disruption

This image is very big, because this section is very important, and I want to catch you if you are skimming. There are several metaphors related to technological development and diversity wrapped up in this meme. Painting (one of my favorites): The Fighting Temeraire tugged to her last berth to be broken up, 1838 by J.M.W. Turner — Quotation: Ron Burgundy by Will Ferrell in Anchorman

History indicates this is going to hinder, not help Blockchain’s ability to change the world.

The work by Padgett and Powell on autocatalytic emergence in my opinion makes a clear case for diversity in teams and organisations that aspire to have a truly transformational impact on the world.

One concept I did not explain earlier is the difference between innovation and invention. According to the Padgett and Powell:

Innovations improve on existing ways (i.e., activities, conceptions, and purposes) of doing things, whereas inventions change the ways things are done. Under this definition, the key to classifying something as an invention is the degree to which it reverberates out to alter the interacting system of which it is a part. To some extent we understand micrologics of combination and recombination. Yet the invention puzzle is that some innovative recombinations cascade out to reconfigure entire interlinked ecologies of “ways of doing things,” whereas most innovations do not.

So, innovation explains improvements, while inventions are the truly disruptive changes that cascade throughout a system or systems. Both are necessary and important aspects of technological revolutions, but I believe the most ambitious entrepreneurs and investors are seeking to foster inventions, not innovations. They want to tip networks into new, more productive states.

Although Padgett and Powell don’t explicitly write it, one of my biggest takeaways from the book is the value diversity played in some of the most important and disruptive inventions of the past 7 centuries. Homogeneous networks certainly produced innovations which made money, but they had limited lasting impact. But, when diverse networks and actors are either brought together by a powerful player (ex. Chapter 5: Steps taken by Popes and King of England during Crusades brought together networks inadvertently leading to the emergence of the corporate merchant-bank and multiple important business techniques, including “regularized business correspondence, bills of exchange, complex account books, and the making of deposits into investments”) or organically as a result of strong financial, social, and/or intellectual incentives, novel inventions can emerge and cascade to terrific effect.

What this means, in my opinion, is if you are building an organization or investment strategy that does not explicitly incentivize and encourage a diversity of players and related networks, you should not expect to profoundly change the world. Diversity is not a guarantee of success, but it should be seen as a prerequisite.

Sources

I am not an academic, and as such this was not heavily footnoted nor perfectly covered existing literature. For all I know, this combination is not novel, and if not, please point me to more things to read! I do, however, think it’s important to include the inspiration (roughly in order of accessing them).

• Diplomacy by Henry Kissinger
• ‘War by Other Means: Geoeconomics and Statecraft’ from the Council on Foreign Relations
• Geoeconomics and what it means for Europe from the European Council on Foreign Relations
• How Megacities are Changing the Map of the World with Parag Khanna
• Cass Sunstein and David Brooks — How a Nudge Can Change Everything and the related paper Availability Cascades and Risk Regulation by Cass Sunstein
• The Transformation of the World: A Global History of the Nineteenth Century by Jürgen Osterhammel
• The Crisis of the European Mind: 1680–1715 by Paul Hazard
• How Aristotle Created the Computer by Chris Dixon
• Patrick Collison has a Few Questions for Tyler — Conversations with Tyler Podcast with Patrick Collison and Tyler Cowen
• How Europe became so rich by Joel Mokyr
• The Chessboard and the Web: Strategies of Connection in a Networked World by Anne-Marie Slaughter
• Technological Innovation, Resource Allocation, and Growth by (my Booth professor) Amit Seru et al
• Team of Teams: New Rules of Engagement for a Complex World by Stan McChrystal
• The Seventh Sense: Power, Fortune, and Survival in the Age of Networks by Joshua Cooper Ramo
• Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms by Geoffrey West
• The Emergence of Organizations and Markets by John F. Padgett and Walter “Woody” Powell
• Transportation, divergence, and the industrial revolution by Nick Szabo
• Is Artificial Intelligence Really the Next Technological Revolution? by Tobias A. Huber
• Naval Ravikant’s “Blockchains will replace networks with markets” tweet storm by Naval Ravikant
• Did Uber fail in China? Perspectives from a former employee 1 year from the merger by Chenyu Zheng
• Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages by Carlota Perez
• The False Prophecy of Hyperconnection by Niall Ferguson
• Network structure of production by (another Booth professor) Chad Syverson et al

Whitney D. Zimmerman (@WhitneyZim) | Twitter_The latest Tweets from Whitney D. Zimmerman (@WhitneyZim). 🇺🇸 in Munich @BMW. Enjoy 🏔 & Lederhosen, but not together…_twitter.com