Monday, July 31, 2006

Norms and the Inevitable Consequences of Complex Adaptive Properties in the Legal System

Norms on the range

The Simply Complex Law
By J.B. Ruhl
Post 9: Norms and the Inevitable Consequences of Complex Adaptive Properties in the Legal System
July 31, 2006

Almost anyone accepts that the legal system evolves, the question being according to what principles and producing what effects. Evolution of a complex adaptive system (CAS) brings with it several inevitable consequences that we would expect to observe in the legal system, if it is a CAS, and which we will need to learn how to manage. In considering these effects, it is important to distinguish between legal events, which encompass any occurrence within or affecting the legal system, and legal decisions, which are legal events people cause to happen with intended effects in mind, such as adoption of a law, issuance of a ruling, or selection of a judge.

Feedback: Although a particular legal decision might initially be quite successful at achieving its intended purpose, it is likely to spin off other events in the system which may eventually reinforce or mitigate its own performance. Surgical laws or rulings are unlikely to leave as neat an incision as is hoped.

Multi-Scale Emergence: The legal system has a range of scales in many different dimensions (scope of authority between local, state, federal governments; one court, a district, a circuit, the courts in general; one rule, a set of rules, a field of law), the feedback flow relationships between which are panarchical. It will be difficult to predict events at any one scale based on the events of related scales. For example, although we often place great emphasis on the identity of individuals in the legal system, it is difficult to predict legal phenomena at “larger” scales based on who is in what position.

Sensitivity: There is the potential for what appear to be relatively “small” events to have “large” effects throughout the system, or for seemingly “large” events to have little lasting effect.

Path Dependence: Eventually, we might decide that a particular decision taken in the past is simply ineffective or counterproductive. But turning back the clock is impossible in a CAS. Repeal or overruling might mitigate in the future what we disliked most about the decision, but it does not unravel the damage or (because of the effects discussed above) avoid causing its own undesired events.

Co-evolution: The social CASs that are targets of or indirectly influenced by the legal system are likely to try to evolve around undesired effects and to evolve toward desired effects, meaning that over time any particular legal decision is likely to have effects with respect to those other social CASs of unintended scope and magnitude.

What makes these properties all the more frustrating for people is that decisions people make about the legal system generally are motivated by some normative agenda, whereas the CAS properties of the legal system are completely non-normative. Not all events in the legal system, therefore, can be attributed to a normative source. Yet, when a law or doctrine “goes wrong,” its proponents, who base their support for it on normative concerns, are likely to lay blame on a perceived competing normative agenda and to respond by boosting the intensity of support for their own normative agenda or opposition to the perceived counter-agenda. In other words, they may be inclined to adopt the astute strategy my old rowing coach used to bark at us: row harder, row faster.

But “failure” in the legal system often has nothing to do with a normative agenda of any particular actor or social CAS. Law A might be intended to have an effect on social CAS B, and may indeed have that effect, but having that effect may send signals to social CAS C, which motivates moves that send signals to social CAS D, and so on. The effect of this cascade of co-evolutionary events may be to give rise to a new challenge for the legal system with respect to social CAS N, or it may be to undermine the effects of Law A in social CAS B, but neither such effect necessarily must be based on any particular normative position with respect to Law A. Indeed, the actors and social CASs with which the legal system is now concerned as a result of the effects Law A set into motion may be completely unaware of Law A.

This, I believe, is an important lesson from complexity theory for law—i.e., that much of what happens in the legal system, and particularly what actors in and observers of the legal system might cast as “failure,” cannot be explained under any normative model of law and legal evolution. This is not to say that norms don’t matter or that we should not pursue them through the legal system. Rather, it is to say that we must expect that any normatively motivated decision in the legal system (adopting a law, the selection of a judge, the exercise of discretionary authority) is likely to have effects that are in some degree inconsistent with the normative goal, but that there is not necessarily an identifiable contra-normative actor or entity to blame.

So what are we to do? Do we have to “take the bitter with the sweet”? In some degree, yes, but one reason for studying complexity theory and law is to improve our understanding of how to design legal instruments that have a chance of exhibiting greater fitness and resilience. So the question really is, how can we design the legal system so as to get a better handle “the bitter” and to deal with it more effectively when it arises?

Next: Designing the complex adaptive legal system.

The Ouroboros's Long Tail

Chris Anderson’s phenomenally successful book The Long Tail has inspired lots of enthusiastic business commentary, and some critical academic commentary. The basic thesis is that new technologies of search and distribution make it much easier to find obscure content–so rather than relying on a few blockbusters as primary revenue producers, content owners (and, of course, creators) may be able to sell a smaller number of copies of a wider range of things.

At risk of sounding Manichean, let me speculate on two paths this realization could lead to. Many entities have succeeded with business models premised on making the “long tail” of content as accessible as possible. But it strikes me that Anderson’s book is really making a stir because business people want to squeeze revenue, not from the “long tail’ as a whole, but from individual works (by restricting access to them). That trend strikes me as potentially self-defeating--like the classical mythical figure ouroboros eating its own tail.

For example, might publishers resist Google’s book digitization project all the more strongly, hoping to ride a “backlist to the future?” If so, they may defeat the very enhanced searchability that made the long tail so important.

What role can law play? Well, Richard Lanham has a nice commentary in his Economics of Attention on the range of motives animating cultural production. On one side lies the desire for "fame, for wealth and honor;" on the other, "love of knowledge for its own sake," "pure play," etc. Lanham suggests that copyright law "simply ignores" the latter side of the equation. Perhaps an awareness of the necessity of "open access" to the "long tail's" success can lead to a more balanced copyright law.

PS: This is a mini-cross-post from

Sunday, July 30, 2006

An Interesting Posting on Katrina

Ed Wenk, a long-time student of how technology can experience catastrophic failures, has an interesting op ed. on what went wrong with Katrina:

Summarizing the Berkeley report on the New Orleans levee failure, to which he contributed, he says

The Berkeley team found that all modes of failure were preventable at modest additional cost, that the safety margin of 1.3 was too low, that the storm intensity assumed in design was too low and driven by political, not engineering, processes. That piecemeal funding led to piecemeal construction. Looking back, the system was a failure waiting to happen.

His conclusion:

The Katrina disaster hatches an imperative we dare not ignore. We can learn from its lessons of human failure how to cope more successfully with extremes of weather. Otherwise, nature will find the flaw.

Or, to put it more succinctly: be afraid. Be very afraid.

Fractal Octopus?

Wise blogging practice counsels saving this item for Jurisdynamics' Taxon of the Week feature, but given the prominence of complexity theory on this page of late, I simply couldn't resist.

This fantastic image of Octopus bocki, Bock's pygmy octopus, came to Jurisdynamics' attention by way of PZ Myers's fantastically entertaining blog on biology, Pharyngula. Appropriately enough, PZ asks of this image, "Why am I thinking of the Mandelbrot Set?" Why indeed.

This image appeared originally in Mark Norman, Cephalopods: A World Guide (2000).


Ann Bartow body-slams InstaPundit. With verve.

Saturday, July 29, 2006

Felis silvestris catus

The taxon of the week is Felis silvestris catus, more commonly known as the domesticated cat.

Why does the cat, the subject of too much lore and legend to recount through weblogging, deserve airtime on the Jurisdynamics channel? Because the story of feline domestication is the story of civilization. Foraging societies have no real use for the cat. But once humans began living in sedentary settlements, they quickly recognized the value of a superb rodent-killing animal with no proclivity of its own (unlike dogs) to eat grains, fruits, or vegetables. As urban landscapes dominate more of the human environment, the cat has become the consummate city pet. Although the number of American households owning dogs exceeds the number owning cats, cats outnumber dogs in absolute terms in the United States. Originally domesticated in support of agrarian society, cats now rule in the twilight of the farm.

Any person living with a cat understands that no cat is ever truly "owned" by a human. Among putatively domesticated animals, the cat is unusually capable of getting by without human asisstance. The saga of human-feline mutualism, which is often non-obligatory on both sides of the relationship, thus offers lessons for game theory. Given how late the mutualistic relationship arose in the shared history of humans and cats, those lessons may shed especially clarifying light on how spontaneous, opportunistic partnerships arise within human society.

The cat depicted here is Sasha. Her tortoiseshell coloring is an expression of the complicated genetics of color in cats. Among other things, being a "tortie" all but guarantees that Sasha is female -- male torties, mosaics in the genetic as well as casual sense, have the feline equivalent of Klinefelter's syndrome -- and that her tortoiseshell coat can't be duplicated through cloning.

Suffice it to say that Sasha is irreplaceable.

Friday, July 28, 2006

Law AND Complex Adaptive Systems vs. Law AS a Complex Adaptive System

The Simply Complex Law
By J.B. Ruhl
Post 8: Law and Complex Adaptive Systems versus Law as a Complex Adaptive System
July 28, 2006

Dan’s 7/27 post, which included comments from Paul Edelman, and his post of today prompted me to use today’s post as a sidebar (I’ll get back on track next week) to differentiate between law and complex adaptive systems and law as a complex adaptive system.

I am aware there are skeptics who believe complexity theory is not useful for any purpose and for whom the and/as difference is irrelevant. But I can also appreciate that some people might find the CAS model compelling in the context of physical and biological systems such as weather and ecosystems, but less so for social organizations (or that more empirical or technical proof is needed before they are swayed). For such people, the question is whether complexity theory provides any utility for designing legal responses to physical and biological CAS phenomena. This strikes me as the focus of Dan’s excellent series on disasters, and it poses an important question for law even though it falls short of the "law as" CAS position. If this is as far as CAS models ever travel in law, I'd be pleased, and I think the contribution would be enormous.

For example, if we are convinced that ecosystems are CASs, as many ecologists today tell us they are (see Simon Levin, Fragile Dominion: Complexity and the Commons (1999)), then the legal system, whether it is a CAS or not, ought to take the CAS model into account when engaging in the making of ecosystem management law. Would rigorous mathematical models of ecosystems or of law be necessary to derive value from the CAS model for this purpose? I think not. If we know that ecosystems do not evolve toward a steady state equilibrium, but rather depend on disturbance regimes and emergent properties that cannot be explained through reductionist methods of study, we ought not base legal decisions on the product of reductionist studies or on assumptions of steady equilibrium. As Dan mentions, Brad Karkkainen, myself, and others have suggested that legal instruments geared toward “adaptive management” are probably going to be more successful in the long run than will rigid, front-end decision making processes (see our recent articles in Volume 7, Issue 1 of the Minnesota Journal of Law, Science & Technology).

Of course, the usefulness of CAS models in the “law as” context is harder to establish than in the “law and” applications. Ecologists and economists can measure real-world phenomena to test against the CAS model, such as Dan’s discussion of power laws and hurricanes. That is going to be much harder in the social sciences. As I mentioned in response to a comment on Post 5 in this series, “measuring the legal system is a very interesting concept, and I'd love to have the time and money to do so. If I did, I would test whether the legal system exhibits power laws that seem pervasive in physical system CASs (see the late Per Bak's 1996 book How Nature Works). One might measure, for example, the ratio of preamble to rule text in the Fed Reg over time; the number of new rules over time; the frequency of SCOTUS overruling decisions relative to total decisions, and the time lags thereof; the length of opinions in the FSupp over time, etc. My point is that the legal system produces all sorts of quantifiable output that could be used to measure what it is doing, whether it is changing in meaningful system ways, etc.” I’d be delighted if some reader would like to fund such a study!

Until I find the time and money to do that, however, this series will remain theoretical and depend on non-statistical observations of legal institutions and events. I can appreciate that readers whose work is grounded in mathematical and technical disciplines may want more than that before accepting the “law as” proposition. Rather than have them disengage from this series, however, I am hopeful they will continue to probe the theoretical discussion and suggest studies that could be used to test the value of the CAS model in both the “law and” and “law as” contexts.

Next week I will return to the theme of describing law as a CAS.

Designing Institutions for a Complex World

Complexity theory -- or, if you prefer, an understanding of the world's propensity for creating surprises -- has some important implications for institutional design. Institutions may become extraordinarily good at performing specific well-defined tasks. For example, Detroit in the old days excelled in cutting the last hundredth of a cent of cost from components or manufacturing steps. As you may have noticed, this didn't turn out to be a good long-term strategy. When the world changes, the "Big Three" found themselves short of adaptive capacity.

Many institutional processes are designed to eliminate variance by fine-tuning techniques. We hope to perfect repetitive tasks like manufacturing to “six sigmas,” eliminating all variability of outcome through a perfectly honed production process. Even where risks are necessarily present, we seek to routinize the process of risk assessment and risk management through techniques such as cost-benefit analysis. All of these techniques are valuable, but they have their limits and can sometimes have counter-productive side-effects.

In a world characterized by complexity, we have to begin by admitting the impossibility of perfecting what we are doing. Perfection requires stability –- the notes in a Beethoven score never change, so it is possible to aspire to a perfect performance. But many of the problems that we encounter are more like a jazz improvisation with unpredictable changes in the players, instruments, and styles. Rather than perfecting the playing of each individual note, we need to be alert for new information that may change old answers; we need to realize that planning must be flexible; and we must avoid locking ourselves into decisions that may later prove misguided. And we also need to be able to enter into shifting partnerships with other organizations, as the scope and dimension of the problem and the need for expertise and resources shift.

There are actually some successful examples of such institutions, such as the nuclear Navy built by Admiral Hyman Rickover. Organizations that cannot afford failure cannot limit themselves to routine risks or even to those that have materialized somewhere in the past. They have to be alert to uncertainties, to surprising events that may shed light on future risks, and to smaller mistakes that indicate the need for reengineering human and technological systems.

There's an interesting body of social science research about these "high reliability organizations." (Here's a presentation by one of my colleagues at the Haas Business School on the subject.) Basically, however, if you want to know what an HRO looks like, think about FEMA or the Army Corps of Engineers or the pre-9/11 national security establishment -- and then imagine their diametric opposites!

See the accompanying reading list on complexity theory and high reliability organizations.

Complexity theory and high reliability organizations (HROs)

This reading list was compiled by Dan Farber in connection with Designing Institutions for a Complex World:

Read the complete post.
Argote, L., Beckman, S. L., & Epple, D. (1990) The Persistence and Transfer of Learning in Industrial Settings. Management Science, 36(2): 140-154.

Baum, J. A. C., & Ingram, P. (1998) Survival-Enhancing Learning in the Manhattan Hotel Industry, 1898-1980. Management Science, 44(7): 996-1016.

Beckman, C. M., & Haunschild, P. R. (2002) Network Learning: The Effects of Partners' Heterogeneity of Experience on Corporate Acquisitions. Administrative Science Quarterly, 47(1): 92-124.

Bosselman, Fred, and A. Dan Tarlock. (1994) The Influence of Ecological Science on American Law: An Introduction, Chi.-Kent L. Rev. 69: 847.

Cyert, R. M., & March, J. G. (1963) A Behavioral Theory Of The Firm. Englewood Cliffs, N.J.: Prentice-Hall.

De Holan, P. & Phillips, N. (2004) Remembrance of Things Past? The Dynamics of Organizational Forgetting. Management Science, 50: 1603-1613.

Duncan, Francis. Rickover: The Struggle for Excellence. (2001). Annapolis: Naval Institute Press.

Freeman, J. and Farber, D. (2005). Modular Environmental Regulation. Duke Law Journal 54: 795-912.

Houck, O. (2006) Can We Save New Orleans? Tulane Environmental Law Journal 19: 1-68.

Levitt, B., and March, J.G. (1988) Organizational Learning. Annual Review of Sociology, 14: 319-340.

March, J. G., Sproull, L., and Tamuz, M. (1991) Learning from Samples of One or Fewer. Organization Science, 2: 1-13.

McCurdy, H.E. (1994) Inside NASA: High Technology and Organizational Change in the U.S. Space Program. Baltimore: Johns Hopkins Press.

Miller, J.G. (1972) Living Systems. New York: McGraw Hill.

National Research Council (2002) Review Procedures for Water Resources Project Planning. National Academies Press., Wash., D.C.

National Research Council (2004) U.S. Army Corps of Engineers Water Resources Planning: A New Opportunity for Service. National Academies Press, Wash., D.C.

Nelson, R. R., & Winter, S. G. (1982) An Evolutionary Theory of Economic Change. Cambridge, MA: Harvard University Press.

Schroeder, Manfred. (1991) Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise. W.W. Freeman & Co.

Seed, R.B., et al. Independent Levee Investigation Team, DRAFT REPORT available at (last visited July 23, 2006).

Staw, B. M., Sandelands, L. E., & Dutton, J. E. (1981) Threat-Rigidity Effects in Organizational-Behavior -- a Multilevel Analysis. Administrative Science Quarterly, 26(4): 501-524.

Turner, B. A. (1976) Organizational and Interorganizational Development of Disasters.
Administrative Science Quarterly, 21(3): 378-397.

Wolf, F. A. (1980) Taking the Quantum Leap. New York: Harper & Row.

As a service to its audience, the Jurisdynamics Network offers interested readers the opportunity to obtain books through the Network's Amazon Store.  

Thursday, July 27, 2006

Is There a There There?

That, of course, being a reference to a remark that Gertrude Stein made about her hometown of Oakland, which she said was lacking in this regard. As an Oakland resident, I feel that we have a lot of there here, but who am I to argue with Ms. Stein?

The question of whether there is a real "there" for law and complexity theory was raised by my mathematician friend Paul Edelman. In a way, it's also touched upon by J.B.'s most recent posting.

Here's the question that Paul raised:

I get more and more frustrated reading about the supposed implications of CAS to law when no one will be precise about any of the definitions. I suppose it is just the mathematician in me, but until I see some specification of something that can be analyzed in technical way I remain skeptical that there is any there there.

Maybe you can help me in this regard by elaborating on your second post. You note that, as an empirical matter, that the probability of a quake given as a function of its intensity is best modeled by a power law. OK. You then go on to say that this makes a difference in the analysis of what to do in preparation. Why? The distribution is what it is. We can compute the expected damages under assorted hypotheses and do the cost-benefit analysis. What is it about power laws that make any difference to how we think about the question? It may affect the computation, but is there some independent significance to the realization that the power law applies?

You seem to indicate that people underestimate the expected damage because power laws have longer tails. But people are notoriously bad at estimating probabilities even when they are governed by binomial distributions. Are they that much worse in this circumstance. How about massive floods? Are they governed by power law or poisson? I don't know, but I don't know that we are any better there. How about nuclear power disasters? Power law or Poisson? And what about the distribution of hurricanes (whatever that means?) Is it power law or Poisson? If it is Poisson does that mean that everything is now OK with respect to hurricane preparedness?

So what work is all this CAS/power law distribution doing? We are bad at making the correct estimates. We should do better. If we know exactly what the distribution is then maybe we can do a better job, whatever that distribution looks like. What am I missing here?
This is obviously a very cogent and significant question -- as you would expect from the world's only joint appointment in mathematics and law.

Rather than tackling the larger question, let me explain why I think power laws specifically are relevant. To begin with, a lot of economic analysis of the kind used in environmental regulation assumes that variances are a second-order consideration -- the main issue is expected loss. For power distributions, variances can be very large compared with means, so risk aversion issues loom large. I was shocked by the very idea that probability distribution could have an infinite variance; I don't have any reason to think that this is an empirically important case, but it does make you realize that variance issues can be critical in risk assessment.

Second, rather than consider the full distribution, analysts often use what they consider to be the median estimate of loss (for example, by picking what they think is the central estimate of risk based on various studies). You see this all the time in risk analysis, where it is also often paired with criticism of EPA for being conservative in its risk estimates. Power laws typically have a mean that's a lot higher than the median, however. So , assuming that we want to use a point estimate in the analysis because using the full distribution would be too unmanageable, we may want to use much more conservative risk estimates even if we know that the risk is probably (more than 50% of the time) going to turn out lower.

In addition, the high degree of variance and the "fat" right tail of the power distribution have some implications for institutional design. In designing institutions, we can't just plan on the typical incident and then add a small allowance for the unexpected. Instead, we have to assume that outcomes may be much worse than "typical."

Finally, to get away from power laws for a minute, the "butterfly effect" aspect of complex systems has led to some interesting rethinking of ecosystem management. J.B. and others, such as Brad Karkkainen, have discussed the need for managers to monitor and adapt to system changes rather than trying to identify an equilibrium strategy.

At the end of the day, will these turn out to be important insights? I am tempted to paraphrase Keynes and say that at the end of the day we are all dead. In the near term, however, I think it's worth making a small investment in the project of applying complexity theory to law.

Is Complexity Theory More than a Metaphor for Law?

The Simply Complex Law
By J.B. Ruhl
Post 7: Is Complexity Theory More than a Metaphor for Law?
July 27, 2006

The idea that the legal system involves a lot of actors and evolves along with other social organizations is nothing new. Roscoe Pound famously observed that “the law must be stable, but it cannot stand still.” So what does complexity theory and its fancy lexicon bring to the table? Is it just a metaphor for law, or is a useful model for explaining the legal system’s behavior?

I confess I can’t prove the legal system is a complex adaptive system. I believe it is, but the most any theory of evolutionary behavior for phenomena of this magnitude can hope for us to supply a powerful model for predicting and explaining what is happening. I believe complexity theory supplies that for the legal system, that is more than just a metaphor.

A symphony is a metaphor for the legal system: a group of diverse musicians of law with a variety of skills and instruments which, when practiced under good leadership, makes beautiful music in the form of rules and doctrines, but which nonetheless often hits the wrong note. This is a nice way of thinking about how important it is for all the “sections” of the legal system to be on the same page of “music” and work together. But it has absolutely no explanatory power for law.

By contrast, law and economics is an example of a model for the legal system. It has explanatory power. It can be used in the design of legal instruments and institutions. We know it is not always right in its explanations. Law and economics, like any model, necessarily simplifies in order to be useful. We know people don’t really have marginal utility functions they pull out of their pockets to consult, and we know the “rational actor” is just a representation of behavior we expect to see based on the law and economics model. So law and economics misses the mark, sometimes grossly. We can try to refine the law and economics model by building in what we know (or think we know) about cognition and evolutionary biology, but these have their own problems of simplification and lack of completeness.

Are complexity theory and its principles of CAS dynamics more like a metaphor or a model for law? Indeed, I believe they have the potential to provide a more powerful model for law than is supplied through law and economics or its variants. I consider the emergence of the discipline of evolutionary economics a reflection of the need for a more dynamic understanding of economic behavior, and I believe the same is needed in law. Complexity theory and the CAS model are, I believe, the best bet for doing so.

Of course, my undertaking in this series is to convince you I am right, which I will try to do in future posts. Happily, I am not alone in thinking that complexity theory has useful applications in law. A separate post supplies a reading list of legal scholarship using complexity theory or some aspect of it to analyze the design and performance of the legal system.

Next: Some inevitable consequences of CAS properties in the legal system.

Complexity Theory in Legal Scholarship

Compiled by J.B. Ruhl in connection with "Is Complexity More Than a Metaphor for Law?"

These works apply complexity theory or some component of it (e.g., path dependence, chaos, emergence) to law and the legal system. Please alert me to additional publications at

Read the complete post.

Edward S. Adams et al., At the End of Palsgraf, There Is Chaos: An Assessment of Proximate Cause in Law and Chaos Theory, 59 U. Pitt. L. Rev. 507 (1997) (applying chaos theory to the common law proximate cause doctrine).

Hope M. Babcock, Democracy’s Discontent in a Complex World: Can Avalanches, Sandpiles, and Finches Optimize Michael Sandel’s Civic Republican Community?, 85 Geo. L. J. 2085 (1997) (critiquing civic republican political theory using complex systems principles).

Erica Beecher-Monas & Edgar Garcia-Rill, Danger at the Edge of Chaos: Predicting Violent Behavior in a Post-Daubert World, 24 Cardozo L. Rev. 1845 (2003).

Susan W. Brenner, Toward a Criminal Law for Cyberspace: Distributed Security, 10 B.U. J. Sci. & Tech. L. 1 (2004).

Jim Chen, Webs of Life: Biodiversity Conservation as a Species of Information Policy, 89 Iowa L. Rev. 495 (2004).

Susan P. Crawford, The Biology of the Broadcast Flag, 25 Hastings Communications & Entertainment L.J. 603 (2003).

Robert A. Creo, Mediation 2004: The Art and the Artist, 108 Penn St. L. Rev. 1017 (2004).

Lawrence A. Cunningham, From Random Walks to Chaotic Crashes: The Linear Genealogy of the Efficient Capital Market Hypothesis, 62 Geo. Wash. L. Rev. 546, 581-92 (1994) (discussing the application of chaos theory to capital market regulation).

Lawrence A. Cunningham, Capital Market Theory, Mandatory Disclosure, and Price Discovery, 51 Wash. & Lee L. Rev. 843, 854-59 (1994) (applying chaos theory to capital market regulation).

Vincent Di Lorenzo, Legislative Chaos: An Exploratory Study, 12 Yale L. & Pol’y Rev. 425, 432-35 (1994) (developing a model for legislative decision making based on chaos theory).

Vincent Di Lorenzo, Complexity and Legislative Signatures: Lending Discrimination Laws as a Test Case, 12 J.L. & Pol’y 637 (1996) (using chaos theory to evaluate the legislative response to alleged lending discrimination).

Vincent M. Di Lorenzo, Equal Economic Opportunity: Corporate Social Responsibility in the New Millennium, 71 U. Colo. L. Rev. 51 (2000) (using chaos theory to examine legislative imposition of corporate social responsibilities).

Gerald Andrews Emison, The Potential for Unconventional Progress: Complex Adaptive Systems and Environmental Quality Policy, 7 Duke Envtl. Law & Pol’y F. 167 (1996) (applying complex adaptive systems theory to ecological protection policy).

Daniel A. Farber, Probabilities Behaving Badly: Complexity Theory and Environmental Uncertainty, 37 U.C. Davis L. Rev. 145 (2003) (using power law and other complex systems to evaluate different environmental law models for dealing with uncertainty).

Michael J. Gerhardt, The Role of Precedent in Constitutional Decision Making and Theory, 60 Geo. Wash. L. Rev. 68, 114-15 (1991) (explaining Supreme Court constitutional jurisprudence using, among other mediums, a discussion of chaos theory).

Thomas Earl Geu, Chaos, Complexity, and Coevolution: The Web of Law, Management Theory, and Law Related Services at the Millennium, 65 Tenn. L. Rev. 925 (1998) (applying complexity theory to business law and management settings).

Thomas Earl Geu, The Tao of Jurisprudence: Chaos, Brain Science, Synchronicity, and the Law, 61 Tenn. L. Rev. 933, 934-35 (1994) (discussing the potential significance of chaos and emergence to legal theory).

Daniel S. Goldberg, And the Walls Came Tumbling Down: How Classical Scientific Fallacies Undermine the Validity of Textualism and Originalism, 39 Houston L. Rev. 463 (2002).

Alistair M. Hanna, The Land Use System, 13 Pace Envtl. L. Rev. 531, 538 (1996) (discussing application of chaos theory and self-organization theory to land use regulation system).

Oona Hathaway, Path Dependence in the Law: The Course and Pattern of Legal Change in a Common Law System, 86 Iowa L. Rev. 601 (discussing the effect of path dependence on the evolution of common law doctrines).

Andrew W. Hayes, An Introduction to Chaos and Law, 60 UMKC L. Rev. 751, 764-73 (1992) (containing a general discussion of chaos theory and its application to judicial decision making).

Donald T. Hornstein, Complexity Theory, Adaptation, and Administrative Law, 54 Duke L.J. 913 (2005).

Scott H. Hughes, Understanding Conflict in a Postmodern World, 87 Marquette Q. L. Rev. 681 (2004).

Eric Kades, The Laws of Complexity and the Complexity of Laws: The Implications of Computational Complexity Theory for the Law, 49 Rutgers L. Rev. 403, 452-54, 476 (1997) (focusing on mathematically complex issues as they arise in law, such as cyclical priority issues in liens and property titles).

Jeff L. Lewin, The Genesis and Evolution of Legal Uncertainty About "Reasonable Medical Certainty," 57 U. Md. L. Rev. 389-93 (1998) (describing the evolution of the tort doctrine of "reasonable medical certainty" using complex systems principles).

Lynn M. LoPucki, The Systems Approach to Law, 82 Cornell L. Rev. 479, 480-82 (1997) (advocating an empiricist "systems approach" to legal analysis).

Patricia A. Martin, Bioethics and the Whole: Pluralism, Consensus, and the Transmutation of Bioethical Methods into Gold, 27 J.L. Med. & Ethics 316 (1999).

Andrea M. Matwyshyn, Organizational Code: A Complexity Theory Perspective on Technology and Intellectual Property Regulation, 11 J. Tech. L. & Pol’y xiii (2006).

Thomas R. McLean, Application of Administrative Law to Health Care Reform: The Realpolitik of Crossing the Quality Chasm, 16 J.L. & Health 65 (2001-2002).

Jeffrey G. Miller, Evolutionary Statutory Interpretation: Mr. Justice Scalia Meets Darwin, 20 Pace L. Rev. 409 (2000).

Randall C. Picker, Simple Games in a Complex World: A Generative Approach to the Adoption of Norms, 64 U. Chi. L. Rev. 1225 (1997) (using computational theories to examine norm competition).

David Post, "Chaos Prevailing on Every Continent": A New Theory of Decentralized Decision- Making in Complex Systems, 73 Chi-Kent L. Rev. 1055 (1999) (presenting a comprehensive exposition of complexity theory as applied to decision-making and governance generally, with a particular focus on "cyberspace").

David G. Post & Michael B. Eisen, How Long is the Coastline of the Law? Thoughts on the Fractal Nature of Legal Systems, 29 J. Leg. Stud. 545 (2000) (applying fractal structure theory to citation to precedent in judicial opinions).

Glenn Harlan Reynolds, Chaos and the Court, 91 Colum. L. Rev. 110, 112-15 (1991) (explaining Supreme Court constitutional jurisprudence using chaos theory).

Glenn Harlan Reynolds, Is Democracy Like Sex?, 48 Vand. L. Rev. 1635, 1639-40 (1995) (discussing the anti-parasitic effect of evolutionary processes as an analogy to democratic processes).

Mark J. Roe, Chaos and Evolution in Law and Economics, 109 Harv. L. Rev. 641, 643-65 (1996) (describing legal evolution according to path dependence theory and chaotic systems theory).

William H. Rodgers, Jr., Where Environmental Law and Biology Meet: Of Pandas’ Thumbs, Statutory Sleepers, and Effective Law, 65 U. Colo. L. Rev. 25, 46-48 (1993) (discussing chaos theory surfacing in evolutionary biology commentary as a metaphor for evolution of environmental law).

John M. Rogers & Robert E. Molzon, Some Lessons about the Law from Self-Referential Problems in Mathematics, 90 Mich. L. Rev. 992 (1992) (using Godel’s Theorem to analyze complex legal system problems).

Daria Roithmayr, Barriers to Entry: A Lock-In Model of Racial Inequality, 86 Va. L. Rev. 727 (2000).

J. B. Ruhl, Complexity Theory as a Paradigm for the Dynamical Law-and-Society System: A Wake-Up Call for Legal Reductionism and the Modern Administrative State, 45 Duke L. J. 849 (1996) (arguing that law and society coexist interdependently and dynamically similar to the behavior of nonlinear systems in the physical world).

J. B. Ruhl, The Fitness of Law: Using Complexity Theory to Describe the Evolution of Law and Society and Its Practical Meaning for Democracy, 49 Vand. L. Rev. 1407 (1996) (discussing the general evolutionary model).

J. B. Ruhl & Harold J. Ruhl, Jr., The Arrow of the Law in Modern Administrative States: Using Complexity Theory to Reveal the Diminishing Returns and Increasing Risks the Burgeoning of Law Poses to Society, 30 U.C. Davis L. Rev. 405 (1997) (discussing the direction in which the behavioral and evolutionary mechanics are leading the sociolegal system given its current transient state).

J. B. Ruhl, Thinking of Mediation as a Complex Adaptive System, 1997 B.Y.U. L.J. 777 (1997) (comparing litigation and mediation from the perspective of complex systems principles).

J. B. Ruhl, Thinking of Environmental Law as a Complex Adaptive System—How to Clean Up the Environment by Making a Mess of Environmental Law, 34 Houston L. Rev. 933 (1997) (evaluating environmental law and reform thereof using complex systems principles).

J. B. Ruhl, Sustainable Development: A Five-Dimensional Algorithm for Environmental Law, 18 Stan. Envtl. L.J. 31 (1999) (discussion of sustainable development policy as a multi-trait fitness optimization process, or "hard-combinatorial problem," requiring use of sophisticated policy algorithms).

J.B. Ruhl, Regulation by Adaptive Management—Is It Possible?, 7 Minn. J.L. Sci. & Tech. 21 (2005)

J.B. Ruhl & James Salzman, Mozart and the Red Queen: The Problem of Regulatory Accretion in the Administrative State, 91 Geo. L.J. 757 (2003) (using complex systems theory to describe feedback and other complexity effects the growth of regulation has on the ability to comply).

J.B. Ruhl & James Salzman, Regulatory Traffic Jams, 2 Wyo. L. Rev. 253 (2002) (exploring the negative feedback effects of regulation on compliance).

Robert E. Scott, Chaos Theory and the Justice Paradox, 35 Wm. & Mary L. Rev. 329, 329-31 (1993) (applying chaos theory to the legal dilemma between "present justice" and "future justice").

Daniel F. Spulber & Christopher S. Yoo, On the Regulation of Networks as Complex Systems: A Graph Theory Approach, 99 Nw. U. L. Rev. 1687 (2005).

Kevin Werbach, Supercommons: Toward a Unified Theory of Wireless Communication, 82 Tex. L. Rev. 863 (2004).

Mark White, Legal Practice and Economic Adaptation: Common Practice and Roman Practice Compared.

Kenton K. Yee, Coevolution of Law and Culture: A Coevolutionary Games Approach, Complexity, Jan.-Feb. 1997, at 4 (describing attempts to mathematically model evolution of common law according to complex adaptive systems dynamics).

As a service to its audience, the Jurisdynamics Network offers interested readers the opportunity to obtain books through the Network's Amazon Store.  

Fire and ice

Some say the world will end in fire,
Some say in ice.
From what I've tasted of desire
I hold with those who favor fire.
But if it had to perish twice,
I think I know enough of hate
To say that for destruction ice
Is also great
And would suffice.
Robert Frost, Fire and Ice (1920)

Jurisdynamics' series on complexity theory, which has pondered everything from disasters to global inequality to the very nature of law itself, has highlighted one of the fundamental divides among complex adaptive systems. As I discussed in Webs of Life, 89 Iowa L. Rev. 495, 550-51 (2004), not all systems exhibit the same resilience to exogenous shock. Neither natural, economic, nor legal systems can maximize productivity and stability at the same time. HOT systems exhibiting "highly optimized tolerance" maximize yield without incorporating safeguards against remote risks. The competing COLD strategy of "constrained optimization with limited deviations" sacrifices yield in order to hedge against a wider range of contingencies.

HOT strategies abound in ecology. Virulence in fungi, for instance, varies in direct proportion to the resistance of potential plant hosts. The resulting tradeoff between virulence and reproductive fitness reflects the ongoing arms race between a parasite's genes for virulence and a host's genes conferring resistance. The biosphere as a whole, perhaps the HOTtest system known, endures most crises (even if individual taxa fare poorly) but flirts with annihilation every time the planet collides with a large object such as the meteor that left the Chicxulub crater associated with the end of the Cretaceous.

By contrast, humans and their institutions tend to favor COLD systems. Law and economic policy, to name two of the most ambitious social systems, routine reflect a social judgment that "rank[s] other values higher than efficiency." INS v. Chadha, 462 U.S. 919, 959 (1983). This systematic tendency toward COLD risk-aversion, of course, is itself a product of HOT evolution over the course of humanity's natural history. For adaptation within complex human society, so it seems, ice seems as great as fire, and does suffice.

Technological announcements

The Jurisdynamics family of blogs is pleased to announce several technological improvements.

Please direct all technological questions about these blogs to Jurisdynamics' webmaster.

Wednesday, July 26, 2006

Fractal Inequality and Econo-Pandas

At Jim's invitation, I'm doing some guest posts here related to science and the law (from non-paying user to content provider--all right!) I've really enjoyed the insights of Jim, Dan, and J.B., and I'm glad to see a big-picture, synthetic blog in an era of analytic specialization. I'll start by cross-posting something I did over at Madisonian, to extend our discussion from the realm of biology to some "inorganic regularities" that may inform law.

I was just comparing a couple articles on income inequality, and thinking about how patterns in the natural world play out in the economic world. Here’s an account of a facet of the new “evolutionary economics:”

[Beinhocker argues that] economists should abandon blackboard deduction in favour of computer simulation. . . . An early example is the sugarscape simulation done in 1995 by Joshua Epstein and Robert Axtell, of the Brookings Institution. On a computer-generated landscape, studded with “sugar” mountains, they scattered a variety of simple, sugar-eating creatures, which compete for this precious commodity. Some creatures move faster than others, some see farther, and some burn sugar at a higher metabolic rate than their rivals.
Surprisingly, the results of their myopic lives can be gripping. Even simple rules of behaviour result in collective patterns that are impossible to foresee yet easy to recognise. The sugarscape, for example, is quickly beset by a division between haves and have-nots, which bears a strong statistical resemblance to the distribution of income in real economies. These macro-results cannot be deduced from the micro-rules simulators write. Rather, they emerge
from the interactions of the creatures in the model . . . .

In light of these results, it’s interesting to note how fractalized patterns of inequality are becoming. For example, here is Pogge on global inequality:

Though constituting 44 percent of the world’s population, the 2,735 million people the World Bank counts as living below its . . . $2 per day international poverty line consume only 1.3 percent of the global product. . . . The high-income countries, with 955 million citizens, by contrast, have about 81 percent of the global product.

And here is Tritch on U.S. inequality:

[F]rom 2003 to 2004, the latest year for which there is data . . . real average income for the top 1 percent of households - those making more than $315,000 in 2004 - grew by nearly 17 percent. . . . In all, the top 1 percent of households enjoyed 36 percent of all income gains in 2004, on top of an already stunning 30 percent in 2003.

So the fractal patterns observed by scientists in the natural world (where patterns repeat, over and over, on smaller or larger scales, like the boundary of the "Mandelbrot Set" illustrated above) somehow manage to describe (or at least map to) patterns in the social world. Philip Ball’s book Critical Mass explores some of the implications; certainly policymakers should consider these studies as they continue to study patterns of wealth and income distribution. From Wolfram’s A New Kind of Science, we may be able to develop a new kind of social science.

What Is Fitness?

The Simply Complex Law
By J.B. Ruhl
Post 6: What Is Fitness?
July 26, 2006

Several comments to previous posts have rightly suggested that I should have included a definition of “fitness” in my description of complex adaptive system (CAS) properties. As the discussion has turned to law as a CAS, I’ll offer both a general and a law-oriented discussion of fitness in this post.

Most people are familiar with the description of fitness from evolutionary biology as the measure of survival and reproductive success of an organism, or a type of organism. But we need a more general definition for purposes of complex systems theory, because some systems don’t “reproduce” in the biological sense. So, what are we measuring in the case of CASs generally?

The underlying theme of the concept of a system’s fitness is that we are interested in what happens to the system over time in a changing environment. A CAS employs a schema for dealing with what the environment throws at it, for staying resilient over time. The schema consists of a model of the real world and a search algorithm for discovering rules for successfully surviving in the changing environment. In Hidden Order, John Holland suggests that fitness in the generalized sense thus must have to do with the “strength” of the schema.

Of course, the schema may (and strong ones likely will) involve testing different configurations and distributions of system characteristics, and devising new search rules, and thus the system at any one moment may not look like the system in previous or later states, and there is no steady end state in which indefinite survival is assured regardless of environmental change. So, there has to be some room for change bundled into the measure of fitness, but we also need to differentiate between change of that sort and change that is the direct result of perturbation and which may move the system through a critical threshold after which it really isn’t the same system as before. So it becomes pretty complicated when we ask about the fitness of, say, an ecosystem. It requires that we agree on what it is about Ecosystem X that makes us identify it as Ecosystem X, and from there that we can accurately measure those attributes.

Fitness in the legal system presents that kind of complicated, multi-attribute inquiry. Lawyers seem to be comfortable describing boundaries for different legal systems, such as the common law, administrative law, environmental law, and so on. So I think when we ask about the fitness of any such legal system, we want to explore its model of the real world, its schema for dealing with change in the real world, and how successful it is in that respect over time. By success I mean retaining its basic institutional design—e.g., what it is about the common law system that causes us to describe it as the common law system. In other words, I don’t propose using normative measures for defining fitness, such as some measure of just results, efficiency, or legitimacy. The normative perceptions other agents and social CASs have of a legal system have to do with the selection pressures they may put on the legal system in their co-evolutionary dance, but what we measure for inquiring about the fitness of a legal system is how well it’s schema has allowed it to maintain its institutional design over time.

Next: Is a Complex Adaptive System just a metaphor for the legal system?

Disasters, Chaos, and the Law (2)

This graph shows frequency of earthquakes versus intensity. Note that intensity is a log scale, so if you go from a 6 to 7 on the Richter scale you're moving up by about an order of magnitude in terms of the severity of the quake. This relationship is very typical of the behavior of complex systems. It means that more intense earthquakes are rarer than less intense ones -- that's the good news -- but the frequency falls off much more slowly than the danger of the quakes increase. That means that if you consider the total impact of all earthquakes, a disproportionate amount of the punch is concentrated at the right end of the curve.

Notwithstanding our best efforts at prediction, from time to time the world presents us with nasty surprises. Freak events of this kind present a dilemma to policymakers. It would be paranoid to assume that the worst will always happen. Yet, perhaps paradoxically, it is reasonably foreseeable that non-reasonably foreseeable events will occur from time to time. A planning process that ignores this reality will work satisfactorily nearly all of the time, but when failures do occur they may be catastrophic. The overwhelming majority of the Lincoln family=s theater outings went smoothly, but Mrs. Lincoln doubtless took little comfort from this observation.

Environmental regulation has grappled with this problem for several decades. This essay assesses those efforts in light of the developing theory of dynamic systems, sometimes called complexity theory or chaos theory. One lesson of complexity theory involves the peculiar statistical behavior of complex systems. Even people who have never heard of a bell curve (a/k/a normal distribution) have an intuitive sense of its properties, with most events bunched near the average and extreme outcomes fading away quickly. If the average cat weights ten pounds, we can expect that most cats will be within a few pounds of the average, and we can safely disregard the possibility of a two-hundred pound tabby. But complex systems are often characterized by a different kind of statistical distribution called a power law. If cats’ weights were subject to a power law, we would find that the vast majority of cats were tiny or even microscopic, but that thousand-pound house cats would cross our paths now and then. Under a power law, the possibility of freak outcomes (a one-ton Siamese) weighs heavily in the analysis, often more heavily than the far more numerous routine outcomes (the tiny micro-cats). The harmless kittens that litter your path would be much less of an issue than the enraged saber-tooth you you might encounter once in a lifetime. Indeed, a power-law probability distribution makes it somewhat misleading to even talk about the attypical, given the huge range of possibilities.

Ecological thought has moved away from the idea of equilibrium toward a more dynamic vision, as Fred Bosselman and Dan Tarlock have explained:

[E]cology is following physics as it owes much to chaos theory. Non-equilibrium ecology rejects the vision of a balance of nature. Change and instability are the new constants. . . . Ecosystems are patches or collections of conditions that exist for finite periods of time. The accelerating interaction between humans and the natural environment makes it impossible to return to an ideal state of nature. At best, ecosystems can be managed rather than restored or preserved, and management will consist of series of calculated risky experiments.
Rather than following the familiar normal distribution, the bell curve, outcomes in complex systems often follow what are called power laws -- that is, the frequency of an event is often given by its magnitude taken to a fixed negative exponent. A classic example is given by earthquakes. Other examples include the size of extinction events, the number of species present in a habitat, or the size of the Nth smallest species (meaning that almost all species are rare but a few have very large populations).

What all of this adds up to is that the world behaves less “normally” than we would expect. We are lulled into complacency by a host of small events, assuming that larger events will be on the same scale. We get used to hurricanes as an annual, almost routine event in parts of the country. Then Katrina comes along.

We need to adjust our planning to deal with a chaotic world. Systems that are designed for the routine or the slightly surprise will not hold us in good stead when the catastrophic happens. Katrina provides us an example of this, which we should not forget – but which we are likely to forget over time, unless we take steps to build long-term institutions based on this insight.

We're only beginning to figure out how to construct such institutions. In the next few postings, I'll be discussing some modest steps forward that we could take with FEMA, the Army Corps of Engineers, and other government agencies.

Tuesday, July 25, 2006

Pages of history

A "page of history is worth a volume of logic," thundered Oliver Wendell Holmes in New York Trust Co. v. Eisner, 256 U.S. 345 (1921). True enough. Till I contemplated some recent and anticipated adventures in reading, though, I hadn't realized how this Holmesian aphorism is true in more than one sense. Scholars who read the past for clues to the present and the future are pages of history in their own right, in the sense that they serve Clio by unearthing her secrets.

The trick often lies in finding an appropriate subject, an underappreciated event or individual worthy of study despite the lack of scholarly attention. In the fanfare surrounding the 50th anniversary of Brown v. Board of Education I, I thought myself clever for staging a conference on Brown II and writing an article on that decision's infamous "all deliberate speed" formula. This was a natural extension, I thought, of earlier scholarship using Bolling v. Sharpe as its springboard.

As I contemplated the double meaning of Holmes's "pages of history," though, I realized that it takes a truly insightful scholar of civil rights, immigration, and education law like Michael A. Olivas to document the underappreciated case of Hernández v. Texas, 347 U.S. 475 (1954). Michael is the editor of Colored Men and Hombres Aquí: Hernández v. Texas and the Emergence of Mexican American Lawyering, a forthcoming collection that represents the first book-length treatment of this landmark civil rights decision. Though overshadowed by the contemporaneous decision in Brown I, Hernández remains one of the leading cases on racially biased jury selection. The book's title comes from Chief Justice Warren's observation that the courthouse at issue in Hernández had "two men's toilets, one unmarked, and the other marked 'Colored Men' and 'Hombres Aquí' ('Men Here')."

Meanwhile, prominent antitrust scholar Spencer Weber Waller has delivered the first full-length biography of Thurman Arnold. Perhaps best known today as one of the founders of Arnold & Porter, Arnold was in fact one of the twentieth century's greatest legal factotums, a lawyer who made his mark as a small-town lawyer, an elected politician, a law professor, a law school dean, head of the Antitrust Division, a D.C. Circuit Judge, and a civil rights warrior during the McCarthy era. So varied a life in law demands a versatile biographer, and Spencer has certainly proved worthy of the challenge.

Disasters, Chaos, and the Law

I want to begin by thanking Jim for inviting me to participate in this blog. For the past year, I've been spending a lot of time thinking about disaster issues. I'd like to make that the subject of my first few posts.

The devastation wrought by Hurricane Katrina revealed failures across an array of human institutions in crisis preparedness, response and recovery. These institutions included federal, state and local agencies, as well as private health care providers and firms involved in energy, the environment, and telecommunications. Analyses of the disaster generally emphasize the internal shortcomings of specific organizations. But not only were individual groups clearly overwhelmed, there were also critical breakdowns in collaboration and coordination.

Moreover, the organizational problems did not begin when Katrina made landfall. The flood control system itself was a patchwork of projects with little in the way of systematic, rigorous planning. The fault for this does not lie with individuals, but with the poorly organized system of planning for flood control.

If Katrina was a “one of a kind” event, then what went wrong would be relevant only for assigning responsibility. But in fact, Katrina may be far from unique. For example, Sacramento is also considered to be highly vulnerable to flooding on a similar scale, while the possible collapse of the levees system in the nearby Delta area could imperil much of California’s water supply. More generally, complexity theory teaches us that low-probability but high cost events are a predictable possible outcome of complex systems (such as oceans, weather, and ecosystems). We need to revamp our approach to these problems in light of what we know from complexity theory.

Raising these issues is easier than providing solutions, of course. I'll talk some more in my next post about how complexity theory relates to disasters, and I'll also float some ideas about how we can do better in the future. But first I want to see if this really works & my post actually ends up on the blog!

Is Law a Complex Adaptive System?

The Simply Complex Law
By J.B. Ruhl
Post 5: Is Law a Complex Adaptive System?
July 25, 2006

In the previous set of posts (1-4) I laid out the basic framework of complexity theory and its lexicon for describing complex adaptive system (CAS) behavior. In this and the next few posts I set out the basis for applying complexity theory to law’s domain and the consequences this has for legal design.

I am going to assume most readers have no problem accepting that complexity theory provides a powerful analytical model for understanding many physical and biological systems, such as weather and ecosystems. Social scientists, however, are increasingly using complexity theory to understand how social organizations (corporations, the military, crime networks, families) behave at macroscopic scales. Some good background is found at the New England Complex Systems Institute, Australia’s Evolutionary Theories in Social Science site, and France’s Complexity in Social Sciences project(which wound down in 2003, but still has a very useful site).

So, why not law? Any lawyer is used to referring to “the legal system.” I got 10.8 million pages when I punched “the legal system” into Google today. Presumably the modifier, system, in that term of art means something to a lot of people. I propose it means the following:

The legal system (law for short) is a social organization comprised of a multitude of heterogenaeous, interacting agents (judges, lawyers, legislators, etc.) that respond to information inputs according to many rules. Law is focused on managing other social organizations (the economy, healthcare, crime, businesses). Frequently the intended effect of law is to influence how the target social organization treats a physical phenomenon (e.g., environmental law) or another social organization (e.g., employment law). Given that actors in the target and indirectly-influenced social organizations are likely to react to what law is doing to them, and that some of those actors are either actors in the legal system as well or can devise ways to influence actors in the legal system, law experiences feedback from its own behavior and co-evolution with other social (and physical) systems.

Now law is starting to look like a CAS. For example:

  • Can the legal system be understood through reductionist study of its agents?
  • Does anyone believe the path of the law is linear?
  • Go back in time, change some events (say, 9/11) and ask whether that would have made a difference for law’s evolution.
  • Examples of crossing critical thresholds? See Joseph Tainter’s 1988 book, The Collapse of Complex Societies, and Jared Diamond’s more recent and popularized book, Collapse.
  • The problem of conflicting constraints? Did someone say Patriot Act? Hard to have our cake and eat it too.

And so on. In the next few posts I am going to tease out these points in more detail and respond to questions, objections, and concerns I expect readers might have, such as whether complexity theory is just a metaphor for law (see comments to Post 2 of the series), and the role of norms.

Next: What should we expect if law is a complex adaptive system?

Monday, July 24, 2006

Andrea Matwyshyn, Jurisdynamic Idol

Jurisdynamics is pleased to announce a new feature, the Jurisdynamic Idol competition. From time to time, this blog will identify junior faculty members and other aspiring scholars in law and allied fields. A few conditions aside, the primary criterion is scholarly excellence.

The inaugural Jurisdynamic Idol is Andrea Matwyshyn. Andrea is starting her second year as an assistant professor of law at the University of Florida and as executive director of Florida's Center for Information Research (CIR). Andrea's research focuses on information security law and information technology policy. In particular, Andrea's research examines how developed bodies of law such as contract law, copyright and trademark law, tort law, and corporate law can offer legal strategies for addressing new information policy problems such as widespread corporate data leakage, hacking and identity theft. She also examines complexity theory and how its lessons about emergent structures can inform the development of successful strategies for regulating technology. Her most recent publications are available from her SSRN page.

CIR's mission mirrors Andrea’s research. CIR seeks to contribute to the multidisciplinary discourse related to information policy and its intersection with information technology through conferences, a speaker series, and a technology policy wiki.

Andrea currently teaches contracts, e-commerce regulation and data security law. She serves as the faculty advisor to the Florida Journal of Technology Law and Policy and Florida's technology law moot court team.

In addition to her appointment at University of Florida, Andrea is an affiliate of the Centre for Economics & Policy in the Institute for Manufacturing at the University of Cambridge, where she is part of an international group of academics who explore issues at the intersection of information technology and manufacturing. Her recent presentations include talks at Cambridge, the University of Oxford, Stanford University, the University of Edinburgh, the University of Illinois, the Kellogg Graduate School of Management, RSA Security, and BlackHat. Before joining the University of Florida, she taught at Northwestern University School of Law as both an adjunct and a clinical assistant professor and practiced for four years as a corporate technology transactions attorney in Chicago. She holds several graduate degrees from Northwestern, including a J.D. with honors and a Ph.D. Her hobbies include reading books that have “cyber” in the title, travel, photography, coffee, and samba.

Announcing the Jurisdynamic Idol competition

With Andrea Matwyshyn’s designation as the inaugural Jurisdynamic Idol, Jurisdyamics will endeavor to make a regular feature of highlighting young scholars in law and allied fields. Would you like to be the next Jurisdynamic Idol? Please enter the competition. The rules are simple:
  • You must not be receiving a paycheck from my employer.

  • You may have a job, even a very good one you hope to have for keeps, but you can't have tenure.

  • You don't need to work in law, but you do need to work with law.

  • Law school, graduate school, and clerkship credentials are nice but not terribly weighty. Actual scholarly performance is much nicer and very weighty.

Jurisdynamics will independently scour the universe of legal talent for new Idols. Would-be Idols may nominate themselves or be nominated by others.

Idol status, to be sure, brings very few tangible benefits. That said, Jurisdynamics can offer you two things. First, each Idol has an open invitation to post on Jurisdynamics as a guest. Second, you are entitled and invited to post the Jurisdynamic Idol emblem, depicting Jurisdynamicsmascot, somewhere on your homepage and/or blog.

I intend to name new Idols on a reasonably regular basis. I look forward to receiving nominations and applications.

Merci, Belle Lettre!

During Jurisdynamics' first ten days of existence, I've assiduously attempted to keep my posts focused on this forum's core mission. Having just read this extraordinarily gracious post at Belle Lettre's Law and Letters blog, however, I must make an exception. All I can say, mindful of how woefully inadequate I will sound, is thank you.

Belle Lettre, que les étoiles illuminent la voie devant tes pieds.

Attributes of Complex Adaptive Systems (Part II)

The Simply Complex Law
By J.B. Ruhl
Post 4: Attributes of Complex Adaptive Systems (Part II)
July 24, 2006

The previous post introduced terms describing internal attributes of complex adaptive systems (CAS). Now we turn to terms describing co-evolution between CASs.

Co-evolution: No CAS is a closed system, thus any CAS has a set of other CASs with which it co-evolves. CASs can co-evolve horizontally on the same macroscopic scale, or vertically in nested hierarchies. Except in computer-based CAS models, defining the boundaries of a CAS thus is an artificial conception, as it may be that a seemingly small link between two CASs provides the information flow that sets of large effects in one or both, though it may be difficult to trace that causal property by studying either CAS.

Radical Openness: At some point a CAS may become so open to effects from another CAS that they essentially merge into a new CAS.

Fitness Landscape: Taking all of the attributes discussed in this and the previous post into account, each CAS has a fitness landscape, each point of which represents the fitness level associated with a particular configuration of its agents, rules of interactions, and so on. The point of adapting is to maintain high fitness. If the fitness landscape is rugged, attributes such as feedback, emergence, and path dependence will be pronounced, and it could matter significantly what the agents do on each move. Also, the CAS might find when it reaches a particular fitness “peak” that there are higher peaks nearby, but getting to them through incremental evolution is a poor strategy as it involves walking downhill before walking uphill. The CAS may need to cross a critical threshold in order to “jump” to the fitness slopes of higher peaks. All of this is complicated by the “Red Queen” effect—because a CAS co-evolves with other CASs on their own fitness quests, the former’s fitness landscape is constantly shifting below its feet. A CAS may need to run just to stay in place.

Next: The basic framework for thinking of law’s domain—its subject matter and the legal system itself—through the lens of complexity theory.

Sunday, July 23, 2006

Attributes of Complex Adaptive Systems (Part I)

The Simply Complex Law
By J.B. Ruhl
Post 3: Attributes of Complex Adaptive Systems (Part I)
July 23, 2006

In the previous post I suggested that the evolutionary path of a CAS is difficult to predict notwithstanding that all the agents in the CAS follow rules of behavior. Complexity theory uses a number of formal terms and concepts to describe what is happening in and to a complex adaptive system (CAS). This is the lexicon I will use in the series, with additional terms introduced as needed in later posts. The terms described in this post focus on the internal dynamics of a CAS.

: Because each agent in the system applies a set of rules to incoming information to decide what to do in the next system move, it is possible, even likely, that what any agent does in a move will eventually affect the information being received by that agent in a later move. This kind of feedback can either reinforce or mitigate the agent’s behavior.

: The micro effects of each agent’s actions aggregate with those of other agents at successively macroscopic scales to produce emergent behavior of the system at different scales. Feedback flows begin to move not only horizontally between agents, but also between system scales. The result is that the system behavior at “higher” scales cannot be understood through reductionist study of the individual agents

: With feedback flows and emergent behavior set into motion, the evolutionary path of the system becomes nonlinear over time. Large perturbations from the exogenous environment thus may have small effects on the system, and small perturbations may have large effects on the system.

Sensitivity and Path Dependence
: A CAS is sensitive to conditions at any particular move and its point on its evolutionary path thus is a product of all prior moves. Hence, if one could observe two absolutely identical CASs at time n and alter conditions in one infinitesimally compared to the other, over time the paths of the two CASs could depart substantially.

: The fitness of a CAS is governed in large part by its resilience—the ability to adapt so as to maintain its basic structural dynamics while taking advantage of its environmental conditions and responding to perturbations.

Conflicting Constraints
: Adaptation usually presents trade-offs, such that evolving a particular set of attributes to improve resilience to one type of environmental condition or perturbation can impair resilience to another type of condition or perturbation.

: The evolutionary path of the system may cross thresholds, or tipping points, past which system dynamics are massively and irreversibly altered. It is generally believed, however, that the most resilient CAS behavior exists at the edge of these critical thresholds. CASs, in other words, evolve toward self-critical states.

Stable Disequilibrium
: A CAS might “sit” in a self-critical state for quite some time, which an observer might mistakenly interpret as some form of climax equilibrium stage of system evolution. In fact, however, what keeps the system self-critical is its constantly dynamical behavior.

Next: Co-evolutionary properties of complex adaptive systems.

Announcing Law Blog Central

Jurisdynamics is proud to announce the creation of a sister blog, Law Blog Central. Law Blog Central is intended to provide a no-frills way to preview new content on Jurisdynamics and other law professor blogs. To visit the blog of your choice, just click the name on the top of its box.

Law Blog Central hopes to feature blogs by junior law professors and other young scholars who aspire to teach law. The featured guest blog will appear in HTML format on the left side of the blog beneath Jurisdynamics' preview window. The first featured guest blog is Info/Law, the blog of my new colleague at Minnesota, Bill McGeveran.

I hope you make a habit of visiting both Jurisdynamics and Law Blog Central.

Saturday, July 22, 2006

Small copper (Lycaena phlaeas)

The taxon of the week is the small copper (Lycaena phlaeas) . Indeed, after a false start last week, the small copper will claim the coveted title of Jurisdynamics' mascot and henceforth grace the top of this blog. A very small small copper will serve as the favicon for Jurisdynamics in the Internet browsers and bookmark files of this blog's readers.

The small copper wins these coveted honors not because it is commercially valuable, threatened or endangered with extinction, or otherwise subjected to careful legal scrutiny. Indeed, I have chosen the small copper as Jurisdynamics' mascot precisely because subspecies of Lycaena phlaeas are widely distributed across North America and all three continents of World Island. As Holly Doremus reminded us in The Special Importance of Ordinary Places, 23 Environs 3, 4 (2000), "[t]hose of us who love nature ... need to think about saving ordinary places and ordinary things."

The embodiment of biological populism, the small copper lives in a wide variety of habitats in Europe, Asia, north Africa, and North America. Perhaps no other place on earth, though, is as readily associated with the small copper as Great Britain. For its part, Britain has played host to one of the most comprehensive and frightening studies of biodiversity loss. A 2004 article in Science magazine documented staggering losses across a wide variety of taxa. Because insects represent more than half of all fauna and respond more quickly to environmental change than most other animals, a decrease of 71 percent among butterfly species in Britain portends similar declines in other organisms. These losses confirm, sadly, "that the biological world is approaching the sixth major extinction event in its history."

Notice: This picture of a small copper was taken by Olaf Leillinger on May 16, 1998, has been deposited within the Wikipedia Commons, and now is displayed under the terms of the Creative Commons Attribution ShareAlike 2.5 License and the GNU Free Documentation License.
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