Thursday, June 18, 2009

The Simulation Era

Simulation, aka the ability to generate knowledge maps in various formats and languages, resides at the heart of the convergence that is expanding human capability and driving the systemic creation of knowledge. It is absolutely critical to accelerating change in information, technology, problem solving, etc, and deserves a more central role in our models of economy, intelligence, society and living systems.

Accordingly, it is no accident that the market for humans who generate complex simulations is growing, as reported by the NYTimes earlier this week:

"Bill Waite, chairman of the AEgis Technologies Group, a Huntsville, Ala., company that creates simulations for various military and civilian applications ... estimates that 400,000 people make a living in the United States in one aspect or another of simulation. His company employs close to 200 people, with an average salary of $85,000."
Of course, thinkers such as Richard Florida, Rise of the Creative Class, and Alvin Toffler, The Third Wave, have long argued that society's demand for creative prosumers is expanding as we continue to free up brains for abstract endeavors not directly tied to classic survival behavior. Only now, having seen the formation and resulting efficiencies of simulations such as Google Earth (geospatial), Wikipedia (lingual, memetic), Blue Brain (human brain), Blue Gene (genomic), Facebook (social), fictional Virtual Worlds (imagination), etc, we can confidently confirm that these prescient forecasts were indeed right on the money.

But how far back does simulation go? And what role does it play in our broader life system, not just social, informational and technologicial systems?

Philosopher Jean Baudrillard, who has many great thoughts to offer on the matter, posits that simulation began with modern media technology. But I think that's a bit too clunky and binary, if you will, especially considering the work on conceptual metaphors as the basis of thought done by cognitive theorists such as Steven Pinker. Though Baudrillard's focus on externalized technology vs. internal processing of reality is very useful when analyzing a stretch of human history, it doesn't fit well with long-term and acceleration models. (Great work, but the abstractions need to be pruned to fit with modern theory. I do think that the hyper-reality argument has a lot of merit. More on that in the future.)

So where then do we turn for an updated version of this thinking?

In his recent excellent Atlantic Monthly article, Get Smarter, futurist Jamais Cascio convincingly argues the critical nature of simulation in human history, citing neurophysiologist William Calvin's research on our evolutionary development:
"According to Calvin, the reason we survived is that our brains changed to meet the challenge: we transformed the ability to target a moving animal with a thrown rock into a capability for foresight and long-term planning [aka simulation]. In the process, we may have developed syntax and formal structure from our simple language."
Technology scholar and Singularity proponent Ray Kurzweil goes even broader in his assertion, contained in The Singularity is Near, that the ability to model, or simulate, is essential to life forms of varying complexity:
"[T]he more complex any system becomes, the better it models the universe that engendered it, and the better it seems to understand its own history and environment, including the physical chain of singularities that created it." "..there is something about the construction of the universe itself, something about the nature and universal function of local computation that permits, and may even mandate, continuously accelerating computational development in local environments."
My personal take on the matter (original article), in alignment with both Cascio and Kurzweil's views, is that as organisms evolve and life's complexity increases, new species with brains capable of greater quantification and abstraction (simulation!) emerge at a regular clip. Over time, these organisms discover ways to expand their knowledge by communicating (actively or passively) information to one another and letting the network manage their quantifications and decisions. Then, eventually, the higher-level organisms figure out how to extend their knowledge into the environment through technology that allows them to communicate and retrieve it more easily than before. This is accomplished directly through technologies like language, writing, or classical maps, and indirectly through the hard-technologies like spears, paint, and paper that critically support knowledge externalization.

In other words, I believe that simulation plays a critical role in not only the evolution and development of the human species, but also of all forms of life on this planet and probably in our known universe (as suggested by recent findings that physical matter millions of light years distant closely resembles our own).

Consequently, I find it likely that we will soon discover a proof, power law or other theorem
for complex systems that correlates increased simulational ability with increased 1) control over environment and 2) survivability. It may look a little bit like the following diagram, with the added explanation that simulation drives the creation of more knowledge as our informational inputs are expanded by technology that steadily increases the data we mine from withion our environment (inner space) and across the universe (outer space):

This perspective or paradigm is useful in that it can 1) help us recontextualize and simplify much of what's going on in exploding domains such as search, the semantic web and structured data for enterprise, and 2) help to streamline the abstractions we use to describe our system upn which we can then build cleaner new theories.

It's particularly interesting to observe the web trending toward advanced simulation. As I noted above, many of the web's most valuable properties are rooted in super-simulations - massive bodies of structured data that can be viewed as a whole or sub-sections. It is clear that the major players are now racing to add both more data and more structure to these simulations in order to fend off sharp-witted competitors and amass more resources, a very life-like behavior indeed.

Math savant Stephen Wolfram, the big brain behind "computational knowledge engine" Wolfram Alpha, who has written convincingly about his belief that life evolves from basic micro-interactions that he describes using the example of cellular automata, lends credence to the argument, claiming that search engines will soon have the ability to "simulate in real time based on [text input] descriptions", which makes sense to me considering the growing amount of structured data (thanks in large part to an increase in data, semantic tagging and knowledge engines such as Alpha, Google and IBM's enterprise quantification software) that can easily be converted into visual formats and models.

Wolfram then extrapolates this capability, suggesting that search may subseqently move onto "creat[ing] things that have never been created before, in real time".

That's right. One of the brightest structural minds on the planet sees our knowledge processors first becoming amazing simulators, then using that simulation data to piece together new structures that have never existed. (Pretty cool that he's also running an influential business.)

It kinda sounds like the human process known as thought or imagination, the ongoing processes of input-sorting-output, just dramatically scaled and accelerated. Which brings us full circle to my initial assertion that simulation is a critical component of accelerating change and to the tandem argument that it deserves a more central role in our models of economy, intelligence, society and living systems.
CONCLUSION: Simulation is crucial not just to our contemporary economy, but to life's knowledge engine(s) at many different levels. Understanding this can help us to better simulate our environment, history and future.

  • By using quantifiable terms like simulation in concert with updated and rigorous definitions of information and knowledge, we can begin to move away from and/or bring clarity to subjective and scientifically problematic terms such as "intelligence" and "the human". This may well prove critically important for unified knowledge (insightful paper) and information theory efforts.
  • By more actively crediting the power and role of simulation in our system and behavior we can develop better understanding of the importance of simulations and thus allocate resources more efficiently. This may lead us to the realization that many or even all humans contribute to our simulation economy, more-or-less directly (everyone a part-time quantifier?). The ability to measure this could have profound impact on prosumer behavior. (This should make simulation and serious games advocates/experts like the grossly underappreciated Clark Aldrich happy.)
  • By viewing simulation as en essential component of knowledge creation we can develop better understanding of culture and social dynamics, and develop better metrics for social change, stress and transformation.
  • By better measuring simulation, we can prove or disprove the argument that the creation of better abstractions fuels the Flynn effect, steadily expanding general human intelligence.
  • By developing our understanding of the role of simulations, we can develop better testable theories re: universal computation and the possibility of simulation chains (add some meat to Bostrom's ultra-subjective simulation argument and its predecessors).
We are simulators. It's in our nature to get better at simulating the present, past and future - the entire system around us. And now that we've entered the knee of some powerful accelerating curves, it's becoming clear that we're about to take our simulating behavior to the next level. With the help of simulation enhancers like Google, Facebook, Alpha (that make economic sense) and new cultural norms, it is highly probable that we are going to 1) increase the complexity of our simulations (drive new knowledge), 2) increase the number of humans directly dedicated to to complex simulation and 3) increase the number of humans indirectly employed to contribute to the formation of simulations.

After all, it's in our interest, as living beings who want to survive and figure our or universe, to do so.

Enter the Simulation Era.

The whole of science is nothing more than a refinement of everyday thinking.