Author: Tom

Is London a big whale?

Why do cities survive atom bombs, while companies routinely go belly up?

Geoffrey West on The Surprising Math of Cities and Corporations:

There’s another interesting video with West in the conversations at Edge.

West looks at the metabolism of cities, and observes scale-free behavior of good stuff (income, innovation, input efficiency) as well as bad stuff (crime, disease – products of entropy). The destiny of cities, like companies, is collapse, except to the extent that they can innovate at an accelerating rate. Better hope the Singularity is on schedule.

Thanks to whoever it was at the SD conference who pointed this out!

Distilling Free-Form Natural Laws from Experimental Data

An interesting paper of that name came out in Science two years ago. There’s a neat video:

For centuries, scientists have attempted to identify and document analytical laws that underlie physical phenomena in nature. Despite the prevalence of computing power, the process of finding natural laws and their corresponding equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. We propose a principle for the identification of nontriviality. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging from simple harmonic oscillators to chaotic double-pendula. Without any prior knowledge about physics, kinematics, or geometry, the algorithm discovered Hamiltonians, Lagrangians, and other laws of geometric and momentum conservation. The discovery rate accelerated as laws found for simpler systems were used to bootstrap explanations for more complex systems, gradually uncovering the “alphabet” used to describe those systems.

The Eureqa application used to mine data for relationships has been released at the authors’ Cornell site.

I think an interesting question is, will this approach work on noisy or ill-defined systems like climate or organizations? My guess is that it will have the same limitations as human-produced science. There’s a reason that a lot of physical laws were nailed down centuries ago, but our models of biological, economic and social phenomena are still pretty limited.

Modeling is not optional

EVERY GOOD REGULATOR OF A SYSTEM MUST BE A MODEL OF THAT SYSTEM

The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto been regarded as optional, as merely one of many possible ways.

In this paper a theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated.  (The exact assumptions are given.) Making a model is thus necessary.

The theorem has the interesting corollary that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment.

That’s from a classic cybernetics paper by Conant & Ashby (Int. J. Systems Sci., 1970, vol. 1, No. 2, 89-97). It even has an interesting web project dedicated to it.

It’s one of several on a nice reading list on the foundations of complexity that I ran across at the Sante Fe Institute. Some of the pdfs are here.

Drunker than intended and overinvested

Erling Moxnes on the dangers of forecasting without structural insight and the generic structure behind getting too drunk and underestimating delays when investing in a market, with the common outcome of  instability.

More on drinking dynamics here, implemented as a game on Forio (haven’t tried it yet – curious about your experience if you do).

The seven-track melee

In boiled frogs I explored the implications of using local weather to reason about global climate. The statistical fallacies (local = global and weather = climate) are one example of the kinds of failures on my list of reasons for science denial.

As I pondered the challenge of upgrading mental models to cope with big problems like climate, I ran across a great paper by Barry Richmond (creator of STELLA, and my first SD teacher long ago). He inventories seven systems thinking skills, which nicely dovetail with my thinking about coping with complex problems.

Some excerpts:

Skill 1: dynamic thinking

Dynamic thinking is the ability to see and deduce behavior patterns rather than focusing on, and seeking to predict, events. It’s thinking about phenomena as resulting from ongoing circular processes unfolding through time rather than as belonging to a set of factors. …

Skill 2: closed-loop thinking

The second type of thinking process, closed-loop thinking, is closely linked to the first, dynamic thinking. As already noted, when people think in terms of closed loops, they see the world as a set of ongoing, interdependent processes rather than as a laundry list of one-way relations between a group of factors and a phenomenon that these factors are causing. But there is more. When exercising closed-loop thinking, people will look to the loops themselves (i.e., the circular cause-effect relations) as being responsible for generating the behavior patterns exhibited by a system. …

Skill 3: generic thinking

Just as most people are captivated by events, they are generally locked into thinking in terms of specifics. … was it Hitler, Napoleon, Joan of Arc, Martin Luther King who determined changes in history, or tides in history that swept these figures along on their crests? … Apprehending the similarities in the underlying feedback-loop relations that generate a predator-prey cycle, a manic-depressive swing, the oscillation in an L-C circuit, and a business cycle can demonstrate how generic thinking can be applied to virtually any arena.

Skill 4: structural thinking

Structural thinking is one of the most disciplined of the systems thinking tracks. It’s here that people must think in terms of units of measure, or dimensions. Physical conservation laws are rigorously adhered to in this domain. The distinction between a stock and a flow is emphasized. …

Skill 5: operational thinking

Operational thinking goes hand in hand with structural thinking. Thinking operationally means thinking in terms of how things really work—not how they theoretically work, or how one might fashion a bit of algebra capable of generating realistic-looking output. …

Skill 6: continuum thinking

Continuum thinking is nourished primarily by working with simulation models that have been built using a continuous, as opposed to discrete, modeling approach. … Although, from a mechanical standpoint, the differences between the continuous and discrete formulations may seem unimportant, the associated implications for thinking are quite profound. An “if, then, else” view of the world tends to lead to “us versus them” and “is versus is not” distinctions. Such distinctions, in turn, tend to result in polarized thinking.

Skill 7: scientific thinking

… Let me begin by saying what scientific thinking is not. My definition of scientific thinking has virtually nothing to do with absolute numerical measurement. … To me, scientific thinking has more to do with quantification than measurement. … Thinking scientifically also means being rigorous about testing hypotheses. … People thinking scientifically modify only one thing at a time and hold all else constant. They also test their models from steady state, using idealized inputs to call forth “natural frequency responses.”

When one becomes aware that good systems thinking involves working on at least these seven tracks simultaneously, it becomes a lot easier to understand why people trying to learn this framework often go on overload. When these tracks are explicitly organized, and separate attention is paid to develop each skill, the resulting bite-sized pieces make the fare much more digestible. …

The connections among the various physical, social, and ecological subsystems that make up our reality are tightening. There is indeed less and less “away,” both spatially and temporally, to throw things into. Unfortunately, the evolution of our thinking capabilities has not kept pace with this growing level of interdependence. The consequence is that the problems we now face are stubbornly resistant to our interventions. To “get back into the foot race,” we will need to coherently evolve our educational system

… By viewing systems thinking within the broader context of critical thinking skills, and by recognizing the multidimensional nature of the thinking skills involved in systems thinking, we can greatly reduce the time it takes for people to apprehend this framework. As this framework increasingly becomes the context within which we think, we will gain much greater leverage in addressing the pressing issues that await us …

Source: Barry Richmond, “Systems thinking: critical thinking skills for the 1990s and beyond” System Dynamics Review Volume 9 Number 2 Summer 1993

That was 18 years ago, and I’d argue that we’re still not back in the race. Maybe recognizing the inherent complexity of the challenge and breaking it down into digestible chunks will help though.

Boiled frogs, pattern recognition and climate policy

A friend (who shall remain nameless to avoid persecution) relates:

I just have to share a somewhat funny, mostly frustrating story.  XXX and I went to Montreal to see U2 last night …

So at the end of the show, it started raining.  Not a light rain but a sharp, arctic windy rain to the point we were all saturated within minutes.  No exaggeration.  It took us 2 hours to get out of the stadium, to the Metro, and back to the hotel because there were 80,000 people trying to get out.  It was purgatory.  It was after 3 am before we finally got to sleep.

OK, that’s not the story either.  My point, besides sharing the night with you, is to explain my state of mind leading up to the customs experience. At the border, things were going smoothly … until the security guard asked us what we do for work.  When I told him what I do, he retorted, “Global warming is not happening. Have you seen the cold weather we’ve had for the past five years?” Of course, I couldn’t let that just sit there.  I explained climate change is not just warmer weather but more extreme events and  weather is different from climate.  So then we actually started arguing about this and I got all fired up …

Now the frustrating part.  As we drove away, though, I just felt so despondent that this is the battle with much of the public that we face.  How can we convince people to act and to demand their government to act when they really don’t think there is a problem?  I’ve been thinking we should utilize some of our time to reach out to the masses who are not looking to improve their mental models of climate change because they don’t even think such a thing exists.   …

The fundamental problem, I think, is that evidence for climate change relies on a variety of measurements dispersed over the globe, and physics and models at a variety of levels of complexity. Yet neither of these is accessible to ordinary people. Therefore, when presented with a mix of inconvenience of reducing emissions, false balance, and pseudoscience, people default to a “trust no one” approach, only believing what they can perceive with their own senses: local weather.

That’s a problem, for several reasons. First, local weather is extremely noisy, and only loosely correlated with global energy balance. So, even a person with unbiased weather perception and perfect recall over a long time period really shouldn’t be drawing any conclusions about global conditions from local measurements.

Second, no one has unbiased perception and perfect recall over long periods. Consider the “cold weather we’ve had for the past five years.” Here’s the temperature from the USHCN Enosburg Falls, VT station, near the border crossing, from 1891 through the end of 2009, in degrees Fahrenheit:

It’s hard to imagine something happening in 2010 and 2011 that could lead one to feel good about conclusively calling a 5-yr cold spell. In fact, almost the only thing you can see here is a slight upward trend.

Continue reading “Boiled frogs, pattern recognition and climate policy”

Androids rule the earth

Android activations are apparently growing 4.4% per week, on a basis of around 100 million sales per year.

By the rule of 72 for exponential growth, that means sales are doubling every 16 weeks, or about three times per year.

If sales are growing exponentially, the installed base is also growing exponentially (because the integral of e^x is e^x). Half of the accumulated sales occur in the most recent doubling (because the series sum 1+2+4+8+…+n = 2*n-1), so the integrated unit sales are roughly one doubling (16 weeks) ahead of the interval sales.

Extrapolating, there’s an Android for everyone on the planet in two years (6 doublings, or a factor of 64 increase).

Extrapolating a little further, sales equal the mass of the planet by about 2030 (ln(10^25/10^8)/ln(2)/3 = 19 years).

Limits? What limits?

Delayed negative feedback on the financial crisis

The wheels of justice grind slowly, but they grind exceedingly fine:

Too Big to Fail or Too Big to Change

…

While the SEC has reached several settlements in connection with misconduct related to the financial meltdown, those settlements have been characterized as “cheap,” “hollow,” “bloodless,” and merely “cosmetic,” as noted by Columbia University law professor John C. Coffee in a recent article. Moreover, one of the SEC’s own Commissioners, Luis Aguilar, has recently admitted that the SEC’s penalty guidelines are “seriously flawed” and have “adversely impact[ed]” civil enforcement actions.

…

For example, Judge Jed Rakoff castigated the SEC for its attempted settlement of charges that Bank of America failed to disclose key information to investors in connection with its acquisition of Merrill Lynch (“Merrill”), including that Merrill was on the brink of insolvency (necessitating a massive taxpayer bailout), and that Bank of America had entered into a secret agreement to allow Merrill to pay its executives billions of dollars in bonuses prior to the close of the merger regardless of Merrill’s financial condition. The SEC agreed to settle its action against Bank of America for $33 million in August 2009, even though its acquisition of Merrill resulted in what The New York Times characterized as “one of the greatest destructions of shareholder value in financial history.” In rejecting the deal, Judge Rakoff declared that the proposed settlement was “misguided,” “inadequate” and failed to “comport with the most elementary notions of justice and morality.” …

…

It has increasingly fallen to institutional investors to hold mortgage lenders, investment banks and other large financial institutions accountable for their role in the mortgage crisis by seeking redress for shareholders injured by corporate misconduct and sending a powerful message to executives that corporate malfeasance is unacceptable. For example, sophisticated public pension funds are currently prosecuting actions involving billions of dollars of losses against Bank of America, Goldman Sachs, JPMorgan Chase, Lehman Brothers, Bear Stearns, Wachovia, Merrill Lynch, Washington Mutual, Countrywide, Morgan Stanley and Citigroup, among many others. In some instances, litigations have already resulted in significant recoveries for defrauded investors.

Historically, institutional investors have achieved impressive results on behalf of shareholders when compared to government- led suits. Indeed, since 1995, SEC settlements comprise only 5 percent of the monetary recoveries arising from securities frauds, with the remaining 95 percent obtained through private litigation ….

I think the problem here is that litigation works slowly. It’s not clear that punitive legal outcomes occur on a relevant time scale. Once bonuses have been paid and leaders have moved on, there are no heads left to roll, so organizations may only learn that they’d better have good lawyers.