Modeling the Future: Tools from Complex Systems
2012 and Beyond: Tools for Predicting the Next Sixty Years
Is the world coming to an end on Dec. 21st, 2012, or not?
Very likely, not.
We’ll still wake up in the morning, in the same beds in which we went to sleep in the night before. We’ll still walk out to our cars, or get to our Metro stations, on time. And we’ll likely stop for the same “cup of joe” on the way to work.
But will our future, in any way, be significantly different from what we’re experiencing now?
My best-guess, and carefully-advised, answer to this is “yes.” But “yes” with a qualifier.
And that qualifier is: the difference(s) may be a bit difficult to discern.
A case in point. A certain type of solid undergoes a phase transition. Specifically, some “solid electrolytes” (e.g., silver iodides) undergo a phase transition at a certain temperature. Below this temperature (420 K for AgI), the solid is not a conductor of electricity. Above this temperature, and it conducts electricity; the Ag+ ions have become mobile.
Before the phase transition, and after it, the AgI is still a physical “solid.” It hasn’t melted into a puddle on the floor. It hasn’t gotten all waxy or goopy. But after the phase transition, its functionality changes a great deal.
The reason? We can model this substance as two intermeshed structures. The anion structure (the negative ions, or I-) is b.c.c. (body-centered cubic). The cations (the positive ions, or Ag+) are distributed among six possible “sites” for each anion. Clearly, there’s some room to move. And when this substance gets hot enough, the silver ions do indeed move about.
Up until the 420K phase transition, not much seems to be happening. Just as when we heat water; just before boiling, we put in more and more heat energy, and nothing happens. (The “watched pot” isn’t boiling.) Then, when we’ve finally put in enough heat energy, it boils – the phase transition occurs. And we go from something that has some degree of cohesion (water droplets stick together), to something with very little cohesion (steam).
In the silver iodide case, we still have apparent cohesion. There is still a structural lattice, formed of the relatively immobile large iodine ions. The iodine ions, almost twice as large as the silver ions, create a 3-D “mesh” through which the now mobile silver ions can slide. And given sufficient heat, that’s what they do. A current can now pass through this structurally-stable substance. (For the AgI heat capacity graph see “Heat capacity, thermodynamic properties, and transitions of silver iodide,” by R. Shaviv et al., M-2363, J. Chem. Thermodynamics, 1989, 21, 631-651.)
So why is this relevant to human history, both past and forthcoming?
Because – by way of analogy – our society can be compared to a solid electrolyte phase transition.
We’ll still have houses and beds, and cars, and our favorite morning “cup of joe.” That’s our stable anionic structure. But moving through it, rapidly, we have such things as: stock price fluctuations, news reports, companies forming, dying, and merging, and countless other info-items. The infosphere penetrates and moves through our physical sphere.
Practical application? Much of our tangible physical environment will stay the same. However, we’re approaching a series of “phase transitions” in our infosphere. We’ve been putting in enough “energy,” over the past decades. We’ve put in research dollars and manufacturing dollars, and we’ve put in lots and lots of human hours creating the data/info that moves through our infosphere. That is, over these past few decades, a lot of energy. And we’re building up to a series of “phase transitions” in our infosphere.
For details on these phase transitions, consult my previous blogpost Going Beyond Moore’s Law referencing a good, scholarly article on upcoming phase changes in the IT space.
Modeling these phase changes in our infosphere is important, if we’re to have a handle on our future. The phase transitions in very simple physical systems, such as AgI, are a starting point for giving us analogies. This means that they are not really precise models of what’s going on, but rather, they function as stories – means by which we can describe what is happening to ourselves.
From the very simple “stories” of phase changes in physical systems, we move on to understand more complex – but still “modelable” – systems. Cellular automata, neural networks, and genetic algorithms all give us useful tools by modeling different aspects of complex biological systems. We can also study these systems themselves, following works such as Self-Organization in Biological Systems, by Camazine et al.
As we gain a solid modeling and “story-telling” toolset, we can apply these tools to the world around us. Getting a sense of our hisory – not just names and dates, but rather forces, patterns, and emergent systems – is the next step. Recently, some authors have been giving us such insightful studies. For example, read Fukuyama’s works, e.g., Origins of Political Order. (And for a commentary and overview, see a John Reilly’s critique of Fukuyama’s Origins of Political Order.)