Total Systems Quantification - Toward the "Everything Graph"

January 26 2009 / by Alvis Brigis
Category: Technology   Year: General   Rating: 5 Hot

Quantify: To determine, express, or measure the quantity of. - Merriam-Webster

abacus.jpgWhy do we compulsively quantify?

An army with a map of the battle terrain is more formidable than an otherwise equal opponent without access to that knowledge.  It can more quickly make decisions that will best optimize its chances for success.  So it's no surprise that good mapping, or quantification, has been essential to human warfare, and that armies nowadays work to create the most comprehensive real-time maps that technology will allow.  

But quantification isn't just essential to effective warring (unless you view life as a perpetual war or game).  It's also critical to human decision-making on all levels.  Whether we're taking short-cuts on the walk home, contemplating a new diet, planning to send our kids to college or writing software code, we're making these decisions in the context of systems maps (aka quantifications) that we run in our brains.  Thus we can reduce the amount of Space, Time, Energy and Matter that we waste (a process related to what Evo Devo philosopher John Smart calls STEM Compression), avoid situations that threaten our well-being and generate max value by taking advantage of opportunities to control resources and our environment.  

In short, quantification is an essential component of knowledge and leads to efficiency as we strive to survive, multiply and thrive. 

finger_count.jpg

Furthermore, quantification appears to be "rigged" into the game of life.  As organims evolve and life's complexity increases, new species with brains capable of greater quantification and abstraction 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 organism 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.  

To my mind, it seems likely that wherever life is found in the universe, it is required to steadily improve its ability to manage knowledge, lest it be overtaken by chaos or other organized life.  This, of course, requires the systematic quantification of its complex environment.  

Such understanding has always been essential, but now in the context of convergent acceleration (comm, info, tech, intel), we are scaling our knowledge and quantifications more quickly than ever before.  To cope with and/or catalyze this acceleration, we need to rapidly better our ability to generate knowledge.  Fortunately, we can make big leaps just by understanding the processes critical to knowledge, such as quantification.

By growing cognizant of our built-in quantification tendencies (quantifying quantification), it becomes possible to make more sense of much of our complex behavior.  We can develop  finer representations for phenomena like group behavior, social media and the success of Google, then use the new quantifications and abstractions to further bootstrap our view of the system in which we exist.

That argued, here's my docket of supporting abstractions, a list of more-or-less novel quantification-related paradigms and suppositions that help to inform view of the system and the social aspects of convergent acceleration:

  • BRAINS ARE SUPER-COMPUTERS: There are 6.756 billion human brains on Earth, each more capable at generating knowledge than the fastest super-computers. (Fred Wilson is right when he says "all social media is about the people that use it".  That's because social media organizes and catalyzes the most valuable processors to create big value.)  

  • BRAINS NETWORK WITH OTHER BRAINS & ENVIRONMENT: These brains function as a network, pan-hierarchically, in concert with other human brains, other species, and their environment.  (Howard Bloom nicely demonstrates this interconnectedness and plasticity, as well as the steady increase in informational processing ability, in The Global Brain and The Lucifer Principle.)

  • BRAINS GATHER & SORT RAW DATA INTO MAPS: To generate knowledge, these brains capture raw data from their environment (including themselves), compare that information to their existing information models/abstractions, and refine and expand these models, resulting in maps of various scale and resolution.  More accurate and updated system maps then allow operations or further generation of knowledge at a faster pace. (James Flynn convincingly argues that IQ is directly related to better abstractions of our system. Why do we assemble history and scientific models?)

  • BRAINS MAP SYSTEMS of INTEREST: To generate useful knowledge, brains focus on improving/updating maps, or quantifications, of systems slices critical to their survival and well-being.  Animals have been shown to do that to varying degrees.  Humans are the most capable species when it comes to quantification.  (Kevin Kelly demonstrates that we are working hard to quantify ourselves.  Esther Dyson extends that thinking to human social behavior on the web.  Pervasive sensing and computing trends extend the web into other physical systems.  Janine Benyus argues that we generate knowledge through biomimicry.  John Smart theorizes the universe is rigged to develop and discover knowledge, which I believe involves quantification and abstraction.)

  • HUMANS COMPULSIVELY QUANTIFY: We humans are compulsive quantifiers that share our mental models through communication and technology.  The digital web is the latest powerful example.  (Aaron Hirsch argues  that the web is driving larger and more complex efforts to generate more useful useful data in different ways, thus accelerating science.)

  • CASCADING KNOWLEDGE FUELS SOCIAL MEDIA: Web-based social media allows human brains to network effectively, catalyzing Knowledge Cascades, much like a scalable chemical reaction.  (Facebook founder Mark Zuckerberg observes that of late, social media is allowing people to share roughly 2x more digital data about themselves every year.  With better, cheaper video, audio, graphics, machinima, and search capabilities arriving regularly, this new content is steadily growing richer.)

  • QUANTIFICATIONS BEGET SUBSEQUENT QUANTIFICATIONS: These knowledge cascades result in larger and finer information graphs, or quantifications, that then allow other humans to generate value and knowledge at a faster pace.  (Open Street Map and Wikipedia participation increases in speed as more people jump on board.)

  • KNOWLEDGE MAPS = FLYNN'S ABSTRACTIONS: These new quantifications are synonymous with the abstraction upgrades that Flynn correlates with rising intelligence, meaning that we're all getting smarter faster.  (How much efficiency is generated through Google Search, Wkipedia, Google Earth?  A lot.)

  • TREMENDOUS VALUE is GENERATED: It is no accident that many of the world's largest companies generate value through scalable quantification.  (GoogleIBM, Facebook, Banks)  As the quantifications generated by these companies are commoditized, becoming redundant, they must continue to cascade knowledge, transform their business or quickly lose active brainshare.

  • OPEN-SOURCE KNOWLEDGE MAPPING: As the web, new software and new hard technologies conspire to decrease the costs of coordinating people, it becomes possible to create more & bigger open-source public knowledge structures.  (Wikipedia, Open Street Map, Open MetaverseAI) This is why some are forecasting that by 2020 40% of IT jobs will be open source.

  • LARGER & FINER MAPS are GENERATED: Better knowledge maps, new technologies, new software and new social behavior allows humans to build larger and finer maps of everything.  As the process accelerates and becomes more obvious (thanks to the quantification of this same behavior), more humans get involved in knowledge processing at steadily lower costs.

  • KNOWLEDGE MARKET FLUIDITY INCREASES:  The more comprehensive our knowledge maps become, the more quickly we can determine the value of novel information, content and structures.  Quantification allows us to ask more questions and quickly arrive at more answers.  It allows us to more quickly place relative value on a structure and then transfer that value, fundamentally speeding up economics.  Thus we can more quickly ascertain the behavioral value of a rare species of bees in a rare section of the Amazon and pay someone to harvest them or protect their indigenous environment (which is also a critical part of the bee's behavior).

  • QUANTIFICATION MORE DIRECTLY REWARDED/VALUED: As we move deeper into the Information Age and people increasingly use emerging web structures to assume the roles of quantifiers, sorters, idea mixers, facilitators, etc, we all grow more cognizant of the underlying fundamentals driving value.  The drive to quantify systems becomes more obvious and is formalized and the way that we graph HR and other value evolves accordingly.

  • HIERARCHY of NEEDS: As the value of quantification becomes more obvious, we accelerate such efforts, which in turn helps us to make more efficient decisions, decreasing costs and increasing opportunities... unless it leads to a zero-sum world war or necessary period of creative destruction.

  • RISE of SOCIAL NODES: The rise of the prosumer, increasing knowledge market fluidity, more open-source and hybrid economic options, a larger $ pie, and advanced communication technology (hi-def video, real-time translation, 3d web, etc) catalyzes the formation of efficient international web-based economic tribes that can scale up and down very quickly and distribute value in innovative new ways.  It becomes possible to participate in many different nodes and switch affiliations rapidly.

  • TUNNELS of TIME: The quantifications that we create spread into all available dimensions, including time.  Thus we work to 1) retro-actively quantify everything we can (perhaps to the point of chasing our history on the light that has bounced off us), and 2) most accurately extend our simulations into the future.  The result is software that runs Tunnels of Time, then more multi-dimensional simulations of our system.  (We already do this individually and socially.  Compulsively.)

  • The QUANTIFICATION of EVERYTHING: Google is already leading the way into the mapping of space (Google Sky) and the the ocean (Google Ocean).  Other companies are quantifying the genome, viruses, proteins, underlying physical structures, etc.  We are already heading toward the quantification of everything, we just don't realize it.  It's a necessary behavior if we as an eco-system want to increase our chances of survival and growth.  It's a fundamental drive of any complex adaptive system, is a requirement for the evolution and development of intelligence and adaptibility.

  • EVER-ELUSIVE COMPUTATIONAL CLOSURE: Information and knowledge are relative.  Godel's incompleteness theorem is a reminder that no matter how much we've learned, there's always more to learn. If life is rigged to compute its system, then one logical possibility is that the cosmos is collectively working to close off its quantification of the total system.  Implications include the drive to network universal knowledge, the potential discovery of extra-systemic existence or expansion of systems boundaries, a possible universal singularity, and so forth.

Care, COUNT, then act.  It's what we all compulsively do.

Thoughts, reactions, criticisms and related links are very welcome!

(Big thanks to John Smart who helped in the evolution AND development of these abstractions over time, particularly by offering up his unique cosmic synthesis.)

Comment Thread (2 Responses)

  1. Not quite sure where you’re headed with all this Alvis, but it makes for diverting speculation. A note of caution if I might but first a question: would you stipulate that quantification is the mechanism by which humans delineate a feature, whether on its own or as a detail of some greater assemblage? If so, then the “Everything Graph” becomes the compiled delineation of all features measurable by human senses (whether directly or via mechanical aid) of any duration (see: Google Sea) in any time period from every possible perspective – all at the same time.

    Or, to coin a word, God.

    You don’t think small my friend, I’ll grant you that! :)

    And about that cautionary note; there is an adage that goes, “The map is not the terrain”. A common failure is to believe the image delineating a feature (in the literal context, that of a terrain feature quantified on a land navigation map) offers the sum of the necessary data concerning the feature. Stipulating that the data was accurate at the time of its compilation, that still doesn’t account for random events or the actions of other humans during the interim between the map’s creation and your perusal, nor does it allow the possibility for sufficient detail specific to your particular needs and intentions having been completely – not to mention prescently – accounted for by the compiler(s).

    You should seriously consider adding to your docket of abstractions a metric for confirming and, when needed, modifying the quantification record prior to taking any action based upon said quantification or map. In the integrated system you seem to be visualizing this would require near-constant updates and dissemmination throughout the system – to specifically include objection resolution mechanism(s) between alternative users.

    You think Wikipedia’s got problems?

    Personally, I think I’d rather have an eagle eat my liver every day, but being consigned to the “help desk” at this never-ending-work-in-progress might actually qualify for it’s own unique Circle in Hell.

    Admit it, you dreamed this up just to see how many of us you could get chasing our own tales* in the comment section, didn’t you? :)

    *No, that’s not a typo.

    Posted by: Will   January 30, 2009
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  2. An absolutely phenomenal read, including all of the links. Truly magnificent, worth the time to read every word.

    Posted by: Adam Cutsinger   January 31, 2009
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