Is Money an Emergent Phenomenon?

The two economists that have most informed my view of the current macroeconomy are Arnold Kling and Scott Sumner. In both cases, their models and explanations make sense to me.  They use solid reasoning and evidence; I don’t feel I’m getting a lot of hand waving. Unfortunately, at first glance, their views seem mutually exclusive.  Kling believes business cycles are the result of many planning errors by individual agents (for example, this recent post and this follow up).  Sumner believes business cycles are the result of contractionary monetary policy by the central bank (for example, this recent post and this one).

How can they both be right? I think they are operating at different levels. Yes, individual agents make their particular planning decisions.  In aggregate, these decisions drive monetary variables like interest rates, exchange rates, liquidity demand, etc.  However, these variables then feed back into the next round of planning decisions.  Moreover, at least some of these plans take into account the effect of the agent’s actions on the monetary variables.  So you get classic chaotic/complex behavior with temporarily stable attractors, perturbations, and establishing new regimes. There may even be aspects of synchronized chaos. I think the monetary variables are the key emergent phenomena here.  They are like “meta prices” that provide a shared signal across just about every modern economic endeavor.

Food for thought.  I’m going to keep this in mind when processing future articles on the economy and see if it helps my thinking.

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Answer to “Guess What Species?”

Yesterday’s puzzler was to guess the species being talked about here:

One became super efficient at gobbling up its food, doing so at a rate that was about a hundred times faster than the other. The other was slower at acquiring food, but produced about three times more progeny per generation.

The answer is…

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Is the Party Over?

I don’t like the Republican or Libertarian parties. But I’m also no fan of the Democratic party. In fact, I dislike all political parties and think they should be done away with.  And while I’m not naive enough to think that this will happen, it makes me glad to see that the “post partisan” utopia is closer today than it was a year ago.

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The Vanguard of Science: Bonnie Bassler

The import of this talk goes way beyond the specific and stunning work that Bassler and her team have done on quorum sensing.  In my mind, this is the prototype for good biological science:

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What is the Best Idea Ever?

Daniel Dennett and others have called Darwin’s theory of evolution the best idea anyone has ever had.  That means that all the ideas that Socrates, Da Vinci, Newton and Einstein ever had, plus all the ideas that everyone else has ever had are also rans.  It would be impossible to really justify such a claim objectively, but I will give my guess as to why it might be considered so, at least by luminaries in Western society.

My suggestion is that evolution is the first theory — in the scientific tradition — based on the principle of emergence.  That is, it looks at a system from the bottom up, starting with behavior at the micro level and yielding behavior at the macro level.

Regardless of the above, what gets your vote for the best idea ever?

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Micro –> Macro –> Micro, etc.

Kevin has a few threads regarding the effect that micro behaviors have when aggregated to macro behaviors:

• Society According to Kevin
• I May Have Been Wrong About Macroeconomics
• But I Was Probably Right About Climate Models

It occurred to me as I was reading this Huffington Post article that there is a reverse-emergent dynamic that occurs when countries (often through their leaders) send signals to other countries through word and action.

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Emergence 101

[I just noticed the video links were broken in my original post, so I’m reposting this]

Apparently this PBS NOVA program aired last year, but somehow I missed it.  Definitely worth watching (and looking at the examples), especially if you are mystified by all of this “emergence mumbo jumbo”:

Part 1

Part 2

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Going Meta on “Autonomy”

Continuation of: Focusing on “Autonomy”

I’ve been trying to reconcile Rafe’s an my views on this topic.  I actually think we agree on the broad themes related to our argument over “autonomy”.  From my perspective, it seems like the only real disagreement is on the implications for humans.

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Focusing on “Autonomy”

Continuation of: Superfoo

Rafe and I had a great chat on the phone today about Superfoos.  I think we agreed that there will be multiple instances of agents emerging in the level immediately above humans but there is always a single top-level network in local space.  I think we also agreed that the “awareness” at this level will be different from human -awareness.  It probably won’t subsume our awareness (at least without a technological singularity) but will exhibit properties such as self-preservation.

Where we got stuck was on the concept of autonomy.  Stuck isn’t really the right word.  We both greatly expanded our conceptual space around autonomy.  But we didn’t come to agreement on a definition.  However, it was a very productive conversation, so I thought I’d put my impressions down here.

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Superfoo

Response to Superorganism as Terminology.

I was actually about to post something about terminology, so I’m glad this came up. It’s just so difficult to choose words to describe concepts that have little precedent, without going to the extreme of overloading on the one end (e.g. “organism”) or the other extreme of being totally meaningless (e.g. “foo”). I have tried to use terms that are the closest in meaning to what I’m after but there’s no avoiding the misinterpretation. I can only hope by defining and redefining to an audience that is not quick to make snap judgments but rather considers the word usage in context, we can converge to at least a common understanding of what I am claiming. From there at least we have a shot at real communication of ideas and hopefully even agreement.

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Response to “Superorganism Considered Harmful”

This is a response to Kevin’s post responding to my post.

Rafe makes an analogy to cells within a multicellular organism. How does this support the assertion that there will only be one superorganism and that we will need to subjugate our needs to its own?  Obviously, there are many multicellular organisms. Certainly, there are many single-celled organisms that exist outside of multicelluar control today.  So where is the evidence that there will be only one and that people won’t be able to opt out in a meaningful sense?

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The Emergent Universe

In a previous post I asked what you thought this was:

Here is the same system at different resolutions (lowest to highest):

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The Conflict Between Complex Systems and Reductionism

The following is a recent paper by Henry Heng published in JAMA.  I’ve linked concepts mentioned in the paper to corresponding explications from this blog.

JAMA. 2008;300(13):1580-1581.
The Conflict Between Complex Systems and Reductionism
Henry H. Q. Heng, PhD
Author Affiliations: Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan.

Descartes’ reductionist principle has had a profound influence on medicine. Similar to repairing a clock in which each broken part is fixed in order, investigators have attempted to discover causal relationships among key components of an individual and to treat those components accordingly.

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Singularity Summit: How Will We Get There?

Now that I’ve had a week to digest what I saw at the summit, I have some thoughts on the most likely path we’ll take to the singularity. From an absolute perspective, this path isn’t very likely because there are a lot of different ways to get there (or not get there). But given what I’ve seen so far, I assign this path the highest concentration of the admittedly diffuse conditional probability mass.

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Singularity Summit: Thoughts on AGI

As most of you know, one of the commonly proposed paths to The Singularity is the development of artificial general intelligence (AGI). As you can read in my rundown of the Singularity Summit, speakers showcased a lot of progress in hardware substrate and software infrastructure, but no significant conceptual advances in implementing executive function in software.

Absence of evidence isn’t necessarily evidence of absence, but I believe that if anyone were making headway on this problem, the chances that someone at the summit would have alluded to it are high. Therefore, I predict that the first being with substantially higher g than current humans is much more likely to be an augmented human than an AGI [Edit: more thoughts on electronically enhancing humans here].

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Go Forth and Reify, part II

In this video talk by Richard Darkins he gives some good food for thought on reification when he talks about Steve Grand’s views on things like whirlpools, electromagnetic fluctuations and walking sand dunes.  The most powerful example is this one (quoting Grand):

Think of an experience from your childhood. Something you remember clearly, something you can see, feel, maybe even smell, as if you were really there. After all, you really were there at the time, weren’t you? How else would you remember it? But here is the bombshell: you weren’t there. Not a single atom that is in your body today was there when that took place…Matter flows from place to place and momentarily comes together to be you. Whatever you are, therefore, you are not the stuff of which you are made. If that doesn’t make your hair stand up on the back of your neck, read it again until it does, because it is important.

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Go Forth and Reify

reify |ˈrēəˌfī|
verb ( –fies, –fied) [ trans. ] formal
make (something abstract) more concrete or real

Imagine if an alien landed on Earth to study modern society and you were assigned the task of being its local guide.  You get to the subject of money and the alien is perplexed.  What is money?  Is it paper currency?  Clearly not, since you can exchange that paper for other forms of currency, such as coins, foreign bank notes, electronic funds, treasury bills, and all sorts of derivatives, assets (both tangible and intangible, liquid and illiquid), services, promises, and so on.  After hearing all of the various aspects of money, the alien tells you that money doesn’t really exist.

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Complex Systems Concept Summary

I figured it was time for a reset and so the following is a summary of much of the foundational posting that I’ve done on this blog so far.  As always, a work in progress, subject to refinement and learning…

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Response to “Thoughts on Ants, Altruism and the Future of Humanity”

[ This is an edited version of a blog comment on Brandon Kein’s Wired Science post here ]

The question of whether we will “break through” to a superorganism or collapse through any number of spiraling cascades or catastrophic events is the subject of Ervin Laszlo’s book, The Chaos Point, which I highly recommend.  In it, he gives a sweeping view of the complex evolutionary dynamic (focusing on human society), and makes a solid argument that we are at an inflection point in history right now, similar to the “saltation” that begat multicellularity.

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Notes from TED

Here are some notes that I took at TED 2008.  I have a bunch more on each of the speakers individually which I may post as time permits.  Let me know if you want me to expand any of the notes below into a full post.

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Complex Links: TED

I attended the TED Conference this year for the first time.  It was a transformative experience, one that I hope everyone can have in some form or another before too long.  One way to simulate being there is watch as many of these incredible talks from past TED conferences as you can in a short period of time.  If you are inspired, check out the TED Prize and how you can be a part of a growing global meta-movement for positive change in the world.

I will be blogging about things that piqued my interest at TED, but below are some cool links that I came away with:

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Mechanical Turk

A few months ago, on a different blog I posted a method for reading books for free on Amazon. Hopefully they didn’t take offense to this but rather saw it for what I did which was a way to get people interested in a book enough to want to purchase it. But just in case Amazon has any hard feelings, I will make amends here by plugging one of their little-known but extremely powerful services called Mechanical Turk.

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Coherence

I posted earlier on emergent causality. One aspect that needs to be elaborated on is the concurrent, self-interdependent nature of emergence, or in other words the chicken and egg problem.

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Alex Ryan’s Diagram

Click here to enlarge.

I have spent a lot of time on this blog discussing evolution and emergence, the distinction between the two and the interplay thereof.  All the while I have wished that I had a diagram like like  Alex Ryan‘s above (posted with permission), as it does much better then the proverbial thousand words.

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Book Report: Complex Adaptive Systems

I just finished reading Complex Adaptive Systems and thought I’d share some of the stuff I underlined and point out how it relates to certain themes and claims in this blog. The organization of these quotes is my own, not related to the chapter or section headings of the book necessarily.

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Three Kinds of Cooperation

Ecologists speak about two types of cooperation — mutualism and commensalism — which distinguish whether both or just one of a pair is benefiting. I’d like to look at a different dimension of cooperation that has to do with communication. There are at least three different types of cooperation along this dimension, though perhaps you can distinguish more (if so, please post a comment!)

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The Logical Necessity of Group Selection

There has been a long-standing debate about the notion of group selection, the idea that populations of organisms can be selected for en masse over competing populations.  The Darwinian “purists” claim that natural selection (NS) only acts at the level of individuals.  But if that’s true, then how can multicellular organisms be subject to NS?  After all what are multicellular organisms if not a group of single cell organisms?

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Types of Emergence

Stability can be thought of as a measure of agency. That is, the more stable a system is, the better we are able to recognize it as a distinct agent, a system that actively, structurally or by happenstance persists through time, space and/or other dimensions. Burton Voorhees defines a concept of virtual stability as a “state in which a system employs self-monitoring and adaptive control to maintain itself in a configuration that would otherwise be unstable.” He clarifies that virtual stability is not the same as stability or metastability and gives formal definitions of all three.* By making a distinction between stability, metastability and virtual stability, we can gain further clarity on agency itself and the emergence of new agents and new levels of organization.

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On the Brink of True Distributed Computing

[ The following is a repost from my MySpace blog, which is not accessible unless you have an account there. Also, the audience there isn’t really interested in this stuff :-) ]

The notion that the “network is the computer” – or at least that it could be – has been around for a while. But all actual implementations to date are either too specialized (e.g. SETI@home) or simplistic (e.g. p2p file-sharing, viruses, DDoS attacks) to be used for generalized computation, or are bound at some critical bottleneck of centralization. To this latter point, search engines hold promise, but the ones we are familiar with like Google are reliant on both central computational control (for web crawling and result retrieval) and central storage (for indexing and result caching). Lately social bookmarking/tagging has been used by those opting in to distribute the role of crawling, retrieval and indexing. It remains to be seen whether keyword tags and clusters thereof are semantically strong enough in practical terms to support general computation. Regardless, whatever heavy lifting is not supported by the representation level will end up falling on the protocol and computational levels. On the other end of the spectrum, the specialized and computationally intensive projects have the issue of how to divide the labor and coordinate results, and no efforts to date have yielded a way to generalize distributed computation without a high degree of specialized programming.

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Cooperation and Competition

It is well-understood that the primary relationship between agents in an evolutionary system is that of competition for resources: food, mates, territory, control, etc. It is also recognized that agents not only compete but also cooperate with one another, sometimes simultaneously, for instance hunting in packs (cooperation) while also fighting for alpha status within the pack (competition). If we look at inter-agent behaviors as existing on a continuum of pure competition on one end and pure cooperation* on the other, it is clear that there is broad range both within species and between agents of different species. Originally, cooperative behavior was explained away as an exception to the general competitive landscape and happened only when two agents shared enough genetic code (such as between parent and child) that cooperation could be seen as a form of genetic selfishness. While this true in a narrow sense, it misses the larger point which is that cooperation between any two or more agents can confer advantages to all regardless of genetic distance. Consider symbiotic species such as crocodiles and the birds that clean their teeth and get a tasty meal in return, without being eaten themselves.

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Generalized Evolutionary Theory

Over the years evolutionary theory has itself evolved to encompass new and more disciplines: social Darwinism, genetic algorithms, co-evolution of biology and culture, evolutionary psychology, economics, psychoanalysis, and more. Attempts to formalize evolution typically have focused on several elements or preconditions for natural selection:

1. a POPULATION of individual agents
2. a REPRODUCTION mechanism
3. a MUTATION mechanism that yields differential fitness of agents
4. a SELECTION mechanism which favors highly fit agents over others for reproduction

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Mechanisms of Agency

The following is a non-exhaustive catalog. Note that these mechanisms are in fact emergent properties of the system under study, a fact which has some fairly profound consequences when considering the lowest known levels in physical systems. Read Ervin Laszlo’s chapter, Aspects of Information, in Evolution of Information Processing Systems (EIPS) for more theoretical background.

Stasis

The most trivial form of stability we can think of is an agent existing in the same place over time without change. This may only make sense as you read on, so don’t get caught up here.

Movement

Keeping time in the equation but allowing physical location to vary, we see that agents can move and continue to exist and be recognized as the “same”. This is obvious in the physical world we live in, but consider what is going on with gliders in the Game of Life. The analogy is more than loose since cellular automata are network topologies which mirror physical space in one or two dimensions. Contrast this to other network topologies, such as the brain, which has many more than two dimensions in its state space.

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Cultural Agency

Talking about culture from a complex systems standpoint requires a bit of inductive leap of faith as follows. If you buy the argument that agents emerge from agents (and interactions thereof) at lower levels, then it is clear that there is some level of agency above individual humans.* What we call this level varies according to who is telling the story and what the thrust of their thesis is: population, culture, society, memetics, economy, zeitgeist, etc. The reality is that all of these levels (and more) co-exist, and we are talking about interlocking systems at varying “partial levels” with dynamic, and only loosely constrained, information flow. Nonetheless, there are common elements and properties that we can discuss that are at the very least distinct from the realm of an isolated individual human being.

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Agency

To understand the concept of agency and emergence thereof, it helps to think about very pure systems that exhibit agency emergence. One such system is Conway’s Game of Life, a kind of cellular automata system which exhibits some uncanny life-like behaviors. You should read the synopsis of Life as well as watch various simulations of it unfold so you get an understanding and an intuition about what’s happening. A remarkable aspect of Life that the rules that govern everything that happens in the system are extremely simple and only apply to a local neighborhood on a grid. What emerges as a run of Life unfolds could hardly be called simple though.

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Evolution & Emergence

Evolution and emergence are not the same thing. Evolution is the process of change within a particular level. Emergence is the creation of a new level of organization through the coming into existence of one or more self-sustaining systems, or agents. These agents often co-exist in populations of other agents which are more or less similar to one another, for instance a species, a tribe, or an ecology of organisms from a variety of species.

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Emergent Causality

For whatever reason, perhaps a pervasive simplicity bias,* we as humans like to think of causality in very basic terms: each event has one and only one cause. Multi-causal explanations seem unsatisfying. We like to know who (or what) to blame or credit. Shared responsibility seems somehow not as real. In cognitive psychology experiments it is well-documented how a crowd of people will stand by watching someone else in distress without anyone offering to help. Yet any one of those same witnesses would invariably take action if nobody else were around. The literature explains this as a sort of “tragedy of the commons” in personal responsibility, i.e. each individual in a crowd of 20 is only 1/20th responsible. Furthermore, everyone assumes that somehow the other 19/20ths of the responsibility will take care of it, if they haven’t already.

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Parts of the Elephant

There is a story about several wise men fumbling around in the dark trying to understand the nature of an elephant by each feeling different parts of the body (leg, trunk, etc). This strikes me as analogous to an approach to understanding the mind that tries to isolate mental functions by mapping them to physical regions of the brain.

Sure, we’ve known for years that regions of the brain are correlated to mental functions like language, vision, controlling distinct parts of the body, et al. And we observe that gross damage to these areas correlates to loss of function. But the observations show many exceptions and edge cases, such as functional compensation during brain damage. An illuminating aspect of brain damage is the continuous (as opposed to discrete) loss of function, which contrasts sharply with damage to human-engineered systems like cars and computers. With technology, generally speaking if a physical region gets damaged, the function it was serving is totally gone. With biological systems, and especially the brain, function degrades “gracefully”, which is to say, you may be dsylxeic or a pour speeler, but y0u still by g3t qui find 99% of the time.

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Eliminating Political Parties

This is a repost from my MySpace blog, but it really belongs here.

Why Political Parties Exist, Why they are Bad, and How to Eliminate Them

Voting blocs are an emergent property of representative democracies wherein each new voting issue carries with it an automatic right for each representative to vote. In other words, when votes are treated like a continually renewable resource, there becomes incentive for each representative to give away votes on issues they care less about in exchange from something of greater value. When that thing of greater value is money we call it corruption. When the thing of greater value is a promise of future support from an outside agency, we call it lobbying. And when groups of representatives agree on an ongoing basis to trade away votes in exchange for membership, we call it a party.

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Levels of Organization

One of the paradigms in complex adaptive systems thinking that has great explanatory power is the idea that there are distinct systems organized hierarchically in various levels of complexity. So, for instance, you can look at atoms as being a system at one level of organization, on top of which sits the next level of atomically bonded compounds (aka molecules), on top of which sits the next level of molecular reactions (e.g. chains of enzyme reactions), and so on. It’s well-understood that within a given level, the individual elements (i.e. atoms at the atomic level, molecules at the molecular level, etc.) interact with one another and can be thought of as passing messages or sharing information. At the atomic level the interactions (mainly) come in the form of atomic bonds: two hydrogen atoms bind to an oxygen atom in a particular configuration in a standard and repeatable way. Incidentally — from the standpoint of the atom — we come to recognize this pattern and classify such a configuration as a water molecule. Incidentally — from the standpoint of the molecule — we recognize that water molecules can configure in several ways to form what we call ice, water, and steam/gas. It’s hard for us to think of atoms and molecules as message passing or information sharing, but at higher levels of complexity (e.g. the brain, humans with language, even enzyme chains) we instinctively recognize that information is created, destroyed, blocked, and used in many different ways. Importantly, information within a given level can be passed in chains from one element to another, and from there form feedback loops in which the end of the chain connects back to the beginning of the chain.

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