Kill your iPad?

Are iPads the successor to the dark side of TV?

I love the iPad, but it seems rather limited as a content creation device. It’s good at some things (GarageBand), but even with a good app, I can’t imagine serious model building on it. Even some social media activities, like twitter, seem a bit awkward, because it’s hard to multitask effectively to share web links and other nontrivial content.

It seems that there’s some danger of it becoming a channel for content consumption, insulating users in their filter bubbles and  leaving aspiring content creators disempowered. The monolithic gatekeeper model for apps seems potentially problematic in the long term as well, as a distortion to the evolutionary landscape for software.

It would be a bit ironic if cars someday bore bumper stickers protesting a new vehicle for mindless media delivery:

“You watch television to turn your brain off and you work on your computer when you want to turn your brain on.”

— Steve Jobs, co-founder of Apple Computer and Pixar, in Macworld Magazine, February 2004

“You watch television to turn your brain off and you work on your computer when you want to turn your brain on.”
— Steve Jobs, co-founder of Apple Computer and Pixar, in Macworld Magazine, February 2004

The Insidious Dynamics of Driving to School

When I passed by my old high school a few years ago, I was astonished to see that they’d paved over a nice grass field to make room for a vast parking lot, which must be for students. There’s really no excuse for driving to school in Palo Alto, CA – the weather is great, it’s flat, and no one lives more than a couple miles away.
Most of the responsibility falls to this nest of positive feedback loops:

I’ll start with a perception: parents worried about the safety of their kids start driving them to school (or, in Palo Alto, buy them a BMW so they can drive themselves). All that extra driving adds to traffic density, reinforcing the perceived danger on the roads. Over the long haul, all that traffic demands more lane space, so bike lanes and sidewalks get crowded out. And who wants to bike next to a bunch of hot, smelly tailpipes?

The more students drive, the less fit they get, which diminishes the fun of riding. They also become less tolerant of weather – in spite of Gore Tex, a lot of people react to a little water falling from the sky like the Wicked Witch of the West.

The result of all this is a kind of phase transition – at some point, conditions are right for all these positive loops to kick in, and everyone shifts from bike-dominated transport to driving.

This transition should not be irreversible, if one is patient. One can move the point at which the phase transition occurs, to encourage bicycling. I think there are two leverage points. First, a society that can afford cars for kids can afford to provide Dutch- or Danish-style traffic separation, breaking the safety loop and decreasing the attractiveness of driving by removing traffic lanes, which causes congestion until people go back to bikes. Second, make the cars pay for the infrastructure they use and the environmental and safety externalities they cause. Once people are back on bikes, they’ll get fitter and healthier, and the positive loops will help lock in a more sustainable mode.

Inspired by a comment in Bert de Vries’ talk this morning at the 30th Balaton Group meeting.

The GDP Song

In SD, we often talk about the pitfalls of managing systems with delays and feedback while paying attention to the wrong indicators. The classic example is navigating a car at high speed in the fog on an icy road by looking in the rearview mirror.

A related problem is managing your system to maximize the wrong goals, e.g. running the economy by a problematic metric like GDP. Here’s Alan AtKisson’s musical take on that:

Sharing Systems

I’m at the 30th Balaton Group meeting this week. A group of us just put our heads together to think about online approaches to teaching and sharing systems thinking and systems modeling. The basic question was, if you needed thousands of systems thinkers in a hurry, how could you scale up systems education quickly?

My list of interesting things people might want to do online:

  • Model building
    • Group model building (in the spirit of SUNY Albany work)
    • Collaborative modeling (e.g., a distributed team working on federated modules of a model, but not necessarily involving the client and group conceptualization processes)
    • Collaborative causal loop diagramming
    • Model code sharing and reuse
  • Model consumption
    • Online games (playing through a simulation in real time) – possibly multiplayer
    • Online simulations (interactive experimentation with a model) – possibly with a social aspect as at Climate Colab

Much can already be done through online model services like Forio and other means. However, I think there’s a lot more to be done. In particular, we’re weak on providing shared model transparency and quality control for any but the simplest models.

Some interesting systems & sustainability online learning links that came up in the conversation:

A natural driver of increasing CO2 concentration?

You wouldn’t normally look at a sink with the tap running and conclude that the water level must be rising because the drain is backing up. Nevertheless, a physically similar idea has been popular in climate skeptic circles lately.

You actually don’t need much more than a mass balance to conclude that anthropogenic emissions are the cause of rising atmospheric CO2, but with a model and some data you can really pound a lot of nails into the coffin of the idea that temperature is somehow responsible.

This notion has been adequately debunked already, but here goes:

This is another experimental video. As before, there’s a lot of fine detail, so you may want to head over to Vimeo to view in full screen HD. I find it somewhat astonishing that it takes 45 minutes to explore a first-order model.

Here’s the model: co2corr2.vpm (runs in Vensim PLE; requires DSS or Pro for calibration optimization)

Update: a new copy, replacing a GET DATA FIRST TIME call to permit running with simpler versions of Vensim. co2corr3.vpm

Gumowski-Mira Attractor

I became aware of this neat model via the Vensim forum. I have no idea what the physical basis is, but the diverse and beautiful output it generates is quite amazing.

Interestingly, if you only looked at time series of this sequence, you’d probably never notice it.

This runs in any version of Vensim. gumowski mira.mdl

Exploring stimulus policy

To celebrate the debt ceiling deal, I updated my copy of Nathan Forrester’s model, A Dynamic Synthesis of Basic Macroeconomic Theory.

Now, to celebrate the bad economic news and increasing speculation of a double-dip depression replay, here are some reflections on policy, using that model.

The model combines a number of macro standards: the multiplier-accelerator, inventory adjustment, capital accumulation, the IS-LM model, aggregate supply/aggregate demand dynamics, the permanent income hypothesis and the Phillips curve.

Forrester experimented with the model to identify the effects of five policies intended to stabilize fluctuations: countercyclical government transfers and spending, graduated income taxes, and money supply growth or targets. He used simulations experiments and linear system analysis (frequency response and eigenvalue elasticity) to identify the contribution of policies to stability.

Interestingly, the countercyclical policies tend to destabilize the business cycle. However, they prove to be stabilizing for a long-term cycle associated with the multiplier-accelerator and involving capital stock and long-term expectations.

I got curious about the effect of these policies through a simulated recession like the one we’re now in. So, I started from equilibrium and created a recession by imposing a negative shock to final sales, which passes immediately into aggregate demand. Here’s what happens:

There’s a lot of fine detail, so you may want to head over to Vimeo to view in full screen HD.

This is part of a couple of experiments I’ve tried with screencasting models, as practice for creating some online Vensim training materials. My preliminary observation is that even a perfunctory exploration of a simple model is time consuming to create and places high demands on audience attention. It’s no wonder you never see any real data or math on the Discovery Channel. I’d be interested to hear of examples of this sort of thing done well.

Energy unprincipled

I’ve been browsing the ALEC model legislation on ALECexposed, some of which infiltrated the Montana legislature. It’s discouragingly predictable stuff, but not without a bit of amusement. Take the ALEC Energy Principles:

Mission: To define a comprehensive strategy for energy security, production, and distribution in the states consistent with the Jeffersonian principles of free markets and federalism.

Except when authoritarian government is needed to stuff big infrastructure projects down the throats of unwilling private property owners:

Reliable electricity supply depends upon significant improvement of the transmission grid. Interstate and intrastate transmission siting authority and procedures must be addressed to facilitate the construction of needed new infrastructure.

Like free markets, federalism apparently has its limits:

Such plan shall only be approved by the commission if the expense of implementing such a plan is borne by the federal government.