Today’s Explorers Sail on Seas of Information. What Can We Learn from Hernando de Soto?

Mapping the human genome is akin to Columbus’ discovering America.” – Juan Enriquez, As The Future Catches You

About eight years ago it sunk in with me that today’s explorers are creating and exploring New Worlds of information. It’s not nearly as dangerous, but the long-term implications may be equally large.


Even eight years ago our final frontier was becoming the domain of information science. The Mars rovers, essentially robots, were on their way up. Now there’s a Robonaut on the shuttle. What we know of Mars and galaxies beyond is mostly beamed back in bits, and, in many ways, it’s an improvement. Still, back here on earth there’s still plenty of New Worlds of information being created or discovered, the genome is just one of many.


What happened eight years ago? What made this crystal clear for me was a map laid down by Hernando de Soto (but not the one you might think), who was recommended by Juan Enriquez. I met Juan Enriquez at a conference he co-developed with Time Magazine in 2003 to commemorate the 50th anniversary of the uncovering of the structure of DNA (He gave a great talk about various types of maps and how they led to new leaps in innovation, including the early maps of the New World).

The conference focused on what effect the biotech revolution was having on business, economics, medicine. It was a phenomenal who’s who of visionaries like James Watson, Richard Dawkins, E.O. Wilson, Craig Ventner, Jaron Lanier, Bill Joy, Ray Kurzweil, Chris Meyer among a multitude of others, all accessible. As a former neuroscience geek turned MBA, entrepreneur and technology geek, it was pure intellectual bliss. Like being backstage at festival with all your favorite rock stars. You can still see the program here.

Anyways, I was fortunate enough to chat with Juan several times and again over lunch over the days of the conference. If you’ve ever seen one of his TED talks, you know what a treat that was. He will change the way your think about what’s possible. During the discussions, which included a discussion of Brazil (I travel there a lot), he recommended a book by Hernando de Soto (also a great speaker I’ve had the great fortune of seeing since), a Peruvian economist, not the explorer (although they’ve both have become famous explorers of sorts in their own right) who writes about the differences between advanced and developing countries.

So, I went home and read de Soto’s The Mystery of Capital. It was mind-bending in explaining the differences between countries in the New World. But to take his ideas a step further, it shows how to build strong markets and economies of information and knowledge.

In the book, de Soto outlines six qualities that he says are the a hallmarks effective property systems, or what he calls “representational systems” of property. He believes these qualities are what separate advanced economies from third world and developing economies:

1. Fixing the economic potential of assets. In a broad sense, what de Soto describes here is building a layer of attributes around the assets, which describes the core info about their ability for exchange.
2. Integrating dispersed information into one system. In order to get maximum value, assets must be standardized so that they can be shared to the widest possible audience and compared to other properties.
3. Making people accountable. By establishing rules (like enforcing contracts) and attaching people to property.
4. Making assets fungible. Placing the assets in a form where they can be divided, merged, essentially a creation space to rearrange or recombine assets.
5. Networking People. Making it easy for people to connect for potential.
6. Protecting Transactions. Ensuring security and responsibility to enforce change of ownership.

While these qualities are interesting from a global economics perspective and how they relate to assets, the reason I’m writing about them is that I believe these same principles could be applied to any system that creates and distributes value, including biological systems and information systems, and may have some ability to predict which systems are most successful and will create the most value.

The de Soto qualities have 3 core effects as I see them:

  1. increasing access to resources by integrating asset/resource information into one system and networking people.
  2. increasing trust by protecting transactions and making elements of the system accountable, this minimizes the resources required to complete a transaction successfully.
  3. creation of an abstraction layer, what he calls “representational systems” by fixing the potential of assets and making assets fungible, the complexity of managing and mobilizing these assets is reduced.

Access is availability of resources that can help you get things done. Trust reduces the amount of energy spent in completing a transaction. Abstractions minimize the energy required to find and use and mobilize available resources.

Ultimately, as I alluded to in my last post, these effects change the thermodynamics of the system. Each has the potential to increase the reaction rate of networks. My hunch is that the affects are at least partially predictable.

We see the same things at work in biology.  Biology is a series of layered abstractions to help manage complexity from a new, higher level of control; from DNA to cells to organs to systems to us.  It’s a constant interplay between connection, increased complexity, abstraction, as well as feedback and learning (forever a type of ongoing natural selection) that builds and refines the effectiveness of those abstractions. It’s the essence of what life is. There’s constant refinement, and there’s increases in power and reach along with a decrease in energy, so the systems that do this well succeed and scale.

We can look at many of the related breakthrough information technologies of the last decade (web services architectures, social networking, Cloud computing, to name a few) and you can see the interplay betweeen connection/access, trust and abstractions/representations. They work because these systems increase opportunity, reduce cost and reduce complexity to get things done. It works, and so is persists, and exists, nearly everywhere. These are our New Worlds and they beget New Worlds.

It seems that the development of economies in the New World and the wide variety of economic successes and failures we’ve seen, (including our own recent financial crisis- a failure of accountability and abstraction), make a lot of sense in the context of de Soto’s ideas on property systems. I believe many of the success and failures we have seen and will see in the New Worlds of technology will as well.

I look forward to exploring the implications.

This is a lot of information to cover in one post, so I hope to clarify and refince these ideas futher in posts to come. I’ll continue on this subject in a series of posts about what it takes to create effective systems, effective markets and effective innovations from the “biologicification” of information systems, and why this pattern works so well. I’ll also review a multitude of phenomenal new books that touch on the subject, including: The Power of Pull, What Technology Wants, EffectiveUI, Reality is Broken, and The Decision Tree.



The Revolution Reaction Rate

Malcolm Gladwell was now famously gobsmacked over Egypt. It sure seems like he lacked imagination about the potential for social media to impact social change.

No, twitter and facebook were not the cause of what happened in Egypt, they were a metalayer on top of what was happening. Still, it’s undeniable that social tools speeded things up dramatically, and that could have been the key factor. Metalayers often are the very reason that things can happen when they couldn’t have happened before. They reduce the work and the energy needed to organize systems. Maps are one example. How did we ever find our way anywhere before GPS or Google Maps? It’s a repeating pattern.

Yes, I understand and agree there were many contributing factors to the recent events in the Middle East: youth, unemployment, access to the internet, discontent with the regime, etc.   We can’t rerun the experiment without social technologies or by changing any other variables, but we can observe the trend and chalk it up as another case study.

So let’s take a look at what these technologies do, and how they might have had an impact, then let’s look at how to quantify them.

It’s true, initial social media ties are weak ties. Nobody’s going to become your best friend on twitter in an hour in 140 character tweets.  Yet to say, as Gladwell did, that twitter and Facebook create only weak ties misses some major points about what these platforms can do:

  1. The platforms provide a platform to find other people with a common purpose.
  2. The platforms create ties (even if initially weak) where none existed before, and these weak ties formed around a common purpose are a first step to developing stronger ties, but even weak ties with enough passion can create stunning results.
  3. The platforms provide a means to coordinate mobile action, by massive amounts of people, at very high speeds, on the fly.

Most imporantly, once people are found, ties created, and actions coordinated, the participants go out in the real world, do something meaningful, and then come back and share what they’ve learned and realign.

These platforms create neural networks of us. They learn, we learn, then they learn again.

What would a quantification of the social media impact look like?

We hear the word “catalyze” used, and overused, on a daily basis, but I do think it makes sense to think of impact much like the catalysis of a chemical reaction:


Figure from Wikipedia, Activation Energy.

At a given temperature, basically, a reaction will only move forward with any meaningful speed if a catalyst is present.  Catalysts lower the activation energy of the reaction by placing the molecules in the right orientation to react.

By connecting, coordinating and mobilizing people, online networks do something similar.

Much like chemical catalysts working on molecules, online communities create a space for two ideas to come together and create something new. Like chemical reactions, they need a critical mass (concentration) to get things moving. Like chemical catalysts they create the ability to coordinate actions by aligning the participants. The ability to coordinate activities in real time with massive inputs and mobile access makes them a potent regime changer.

Yet networks are messy. They aren’t purified reactants mixing in the closed system of a chemist’s beaker. People are not uniform sets of molecules. We are all massively complex adaptive systems with further complex adaptive systems.

Without getting into social complexity theory and the like (we should be able to quanitfy the effect or the probabilities), I think the crux of the matter is this: social media technologies make it simpler and incredibly faster for groups of people to mobily organize, on the fly, to impact change. A group of people is just a mob, but a network of people with a common purpose is an organization.  And with these technologies, they have potent abilities to act. Before, strong leaders and large organizations coordinated massive groups of people by means of hierarchical structures. Now, the network is not only the leader but also the (initial) organizing capability of the group.

No wonder they shut down the internet. It’s more powerful than guns. Smart mobs with online capabilities are defeating status quo organization ruled by hierarchy and unfamiliar with coordinating technologies. These mobile smart mobs can be built on the fly in a matter of hours or days and they will continue to get smarter. Reaction rates are getting much, much faster.

Startups can be built by remote groups of people in a few days and can release a product in a week. Businesses and governments alike are just beginning to feel the effects. We are just beginning to see the potential. Stay tuned (to your network).

I’m looking forward to exploring deeper into how the effects of these organizational abilities might be quantified in future. Special thanks to Mike Vickers for helping to catalyze this post.