The Great Stagnation: Why Hasn’t Recent Technology Created More Jobs? [PBS Newshour]


As part of his continuing coverage of Making Sen$e of financial news, Paul Solman reports on why more good jobs haven’t been created in recent years. Can new technological innovations create widespread job growth as past generations have seen? Tyler Cowen (George Mason / Marginal Revolution) argues “there is an innovation drought, relative to the industrial revolutions of the past and to other countries today.” Erik Brynjolfsson (MIT Solan) counters “I’m an optimist about technological progress, but I’m not nearly as optimistic about our ability to keep up with it.  We have got some real problems. I just want to make it clear that the problem is not stagnation. The problem is more serious in some ways, which is our basic human ability to keep up with technological progress. That problem is going to get worse and worse as technology speeds faster and faster.”

 

Controllability of Complex Networks [via Nature]

Abstract: “The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system’s entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network’s degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.”

How Long is the Coastline of the Law: Additional Thoughts on the Fractal Nature of Legal Systems [Repost]

Do legal systems have physical properties? Considered in the aggregate, do the distinctions upon distinctions developed by common law judges self-organize in a manner that can be said to have definable physical property (at least at a broad level of abstraction)? The answer might lie in fractal geometry.

Fractal geometry was developed in a set of classic papers by the late mathematician Benoît Mandelbrot. The original paper in the field How Long is the Coastline of Britain describes the coastline measurement problem.  In short form, the length of the coast line is a function of the size of measurement one employs.  As shown below, as the unit of measurement decreases the length of the coastline increases.  The ideas expressed in this and subsequent papers have been applied to a wide class of substantive questions. In particular, the application to economic systems has been particularly illuminating. Given recent economic events, we agree with views of the Everyday Economist arguing the applied economic theory built upon his work should have earned Mandelbrot a share of the Nobel Prize. [Check out Mandelbrot @ TED 2010]

A more abstract fractal is the simple version of the Sierpinski triangle displayed at the top of this post. Here, there exists self similarity at all levels. Specifically, at each iteration of the model, the triangles at the tip of each of the lines replicate into self similar versions of the original triangle. If you click on the visual above, you can run the applet (provided you have java installed on your computer). {Side note: those of you NKS Wolfram fans out there will know the Sierpinski triangle can be generated using cellular automata Rule 90.}

For those who are interested in another demonstration consider the Koch Snowflake — a fractal which also offers a view of the relevant properties.  The Koch Snowflake is a curve with infinite length (i.e. there is no convergence even though it is located in a bounded region around the original triangle).  Click here to view an online demo of the Koch Snowflake.

So, you might be wondering … what is the law analog to fractals? As a first-order description of one important dynamic of the common law, we believe significant progress can be made by considering the conditions under which legal systems behave in a manner similar to fractals. For those interested, a number of important papers have discussed the fractal nature of legal systems.  While discussing legal argumentation, the original idea is outlined in two important early papers The Crystalline Structure of Legal Thought and  The Promise of Legal Semiotics both by Jack Balkin.  The empirical case began more than ten years ago in the important paper How Long is the Coastline of the Law? Thoughts on the Fractal Nature of Legal Systems by David G. Post & Michael B. Eisen. It continues in more recent scholarship such as The Web of the Law by Thomas Smith.

In our view, the utility of this research is not to adjudicate the common law to be a fractal. Indeed, there exist mechanisms which likely prevent legal systems from actually behaving as unbounded fractal.  The purpose of the discussion is determine whether describing law as a fractal is a reasonable first-order description of at least one dynamic within this complex adaptive system. While full adjudication of these questions is still an area of active research, we highlight these ideas for their important potential contribution to positive legal theory.

One thing we want to flag is the important relationship between the power law distributions we discussed in these prior posts (here and here) and the original work of  Benoît Mandelbrot. The mapping of the power law like properties displayed by the common law and its constitutive institutions is part of the larger empirical case for the fractal nature of legal systems. Building upon the prior work, in two recent papers, which are available on SSRN here and here, we mapped this property of self organization among two sets of legal elites — judges and law professors.

Dynamic Reconfiguration of Human Brain Networks during Learning [From PNAS]


Abstract: “Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes—flexibility and selection—must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.”

Bommarito, Katz & Isaacs-See –> Virginia Tax Review [ Online Supplement and Datasets ]

Our paper An Empirical Survey of the Population of United States Tax Court Written Decisions was recently published in the Virginia Tax Review. We have just placed supplementary materials online (click here or above to access).

Simply put, our paper is a “dataset paper.” While common in the social and physical sciences, there are far fewer (actually borderline zero) “dataset papers” in legal studies.

In our estimation, the goals of a “dataset paper” are three fold:

  • (1) Introduce the data collection process with specific emphasis upon why the collection method was able to identify the targeted population
  • (2) Highlight some questions that might be considered using this and other datasets
  • (3) Make the data set available to various applied scholars who might like to use it

As subfields such as empirical legal studies mature (and in turn legal studies starts to look more like other scientific disciplines) it would be reasonable to expect to see additional papers of this variety. With the publication of the online supplement, we believe our paper has achieved each of these goals.  Whether our efforts prove useful for others — well — only time will tell!

Applying the Science of Similarity to Computer Forensics (with lots of other potential applications) [via Jesse Kornblum]

From the talk description: “Computers are fantastic at finding identical pieces of data, but terrible at finding similar data. Part of the problem is first defining the term similar in any given context. The relationships between similar pictures are different than the relationships between similar pieces of malware. This talk will explore the different kinds of similar, a scientific approach to finding similar things, and how these apply to computer forensics. Fuzzy hashing was just the beginning! Topics will include wavelet decomposition, control flow graphs, cosine similarity, and lots of other fun mathy stuffs which will make your life easier.”

I have been quite interested in the “science of similarity” and its application to a variety of questions in law and the social sciences.  Whether it concerns the sort of analogical reasoning described by legal scholars such as Edward Levi or Cass Sunstein or cognitive biases such as the availability heuristic (Tversky & Kahneman (1973)), developments in “science of similarity” are of great relevance to theorists in a wide variety of sub-fields.

While there has been lots of skepticism regarding the application of these principles (particularly by those in legal theory),  from our perspective it appears as though computer science ∩ psychology/cognitive science stands on the cusp of a new age in the “science of similarity.” I offer the slides above as I found them to be both interesting and useful. Stay tuned for more …