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IBM Plays SimCity With Portland, Oregon
Hugh Pickens writes "Portland, Oregon will be the first city to use IBM's new software called Systems Dynamics for Smarter Cities, containing 3,000 equations which collectively seek to model cities' emergent behavior and help them figure out how policy can affect the lives of their citizens. The program seeks to quantify the cause-and-effect relationships between seemingly uncorrelated urban phenomena. 'What's the connection, for example, between ... obesity rates and carbon emissions?' writes Greg Lindsay. 'To find out, simply round up experts to hash out the linkages, translate them into algorithms, and upload enough historical data to populate the model. Then turn the knobs to see what happens when you nudge the city in one direction.' One of the drivers of the 'Portland Plan' is the city's commitment to a 40 percent decrease in carbon emissions by 2030, which necessitates less driving and more walking and biking. After running the model, planners discovered a positive feedback loop: More walking and biking would lead to lower obesity rates for Portlanders. In turn, a fitter population would find walking and biking a more attractive option. But as the field of urban systems gathers steam, it's important to remember that IBM and its fellow technology companies aren't the first to offer a quantitative toolkit to cities. In the 1970s, RAND built models they thought could predict fire patterns in New York, and then used them to justify closing fire stations in NYC's poorest sections in the name of efficiency, a decision that would ultimately displace 600,000 people as their neighborhoods burned."
Tear up all the roads. Replace with rail.
Just make sure they disable disasters before they play. An alien monster destroying the power plant wouldn't be nice.
People put so much stake in computer models anymore that when they don't match up with reality, reality is blamed for the error.
"Ask not what your country can do for you." --John F. Kennedy
In the 1970s, RAND built models they thought could predict fire patterns in New York, and then used them to justify closing fire stations in NYC's poorest sections in the name of efficiency, a decision that would ultimately displace 600,000 people as their neighborhoods burned.
So the source is a wikipedia page, which cites this book, which is a dead end for now.
Are the authors talking about this study?
If anyone's got a source that actually backs up the notion that RAND explicitly recommended closing down fire stations in poor areas, or the actual claims that "they're just committing arson anyway", I'm very curious, as that's a pretty wild claim. I've emailed them for comment.
While I think that your dismissal of models is a bit excessive(in a sense, all of mathematics doesn't tell you anything you didn't assume in your axioms: it just so happens that there is a lot of interesting stuff that you didn't know you were assuming...); but one should certainly be cautious about them.
Both an accurate model and a shitty model are, in the hands of a suitably skilled consultant's graphic design team, essentially identical in their ability to provide a dense veneer of scientific rationality, 3D-rendered near-future utopias attractively large-format-printed on posters suitable for display at planning meetings, and other charming props to hang on your existing plans and prejudices...
Things can get particularly ugly if there are large fudge factors in your initial dataset: modeling material stresses, or aerodynamics or such is hard because it is easy to be wrong about difficult stuff, and easy for slight mistakes to cascade(at least, though, there are correct answers that you can hopefully find, even if you don't know them just yet); doing societal cost/benefit analysis is hard because there are lots of factors that don't have quantified costs or benefits, so you can shove the model around just by slapping different price tags on unquantified things.
Apparenty they found a computer model that infuses people with a desire to walk and bike:
After running the model, planners discovered a positive feedback loop: More walking and biking would lead to lower obesity rates for Portlanders. In turn, a fitter population would find walking and biking a more attractive option.
I find it very hard to believe that this feedback loop exists in real life to any significant degree. If it really was true, the professional sports athletes would prefer walking and biking over driving their cars, and the sport stars seem to be preferring their luxury sports cars today.
IBM's model must be missing one or more important variables to why people choose cars over walking.
You're misinterpreting that. It said that a fitter population would find walking and biking a more attractive option. Meaning more attractive than an unfit population would.
It's not that most fit people would choose walking over cars, especially not in all situations. It's that a higher percentage of fit people would choose walking or biking than unfit people would. Which makes perfect sense. If I'm going 3 blocks and I'm in good shape, that's not much of a walk. Especially if it's in decent weather. So I may walk it so that I don't have to deal with getting into my car, parking, etc. But if I'm 350 lbs., then that's a difficult walk, so I'm going to take my car.
If I'm going 10 miles or the weather is bad, then I'm driving no matter how fit I am.