Convexity Effects in Fragile Systems
Small modifications in an overoptimized system can produce compounded, nonlinear effects that drastically amplify negative outcomes, as illustrated by New York City officials underestimating the traffic impact of a bridge closure.
THE IDEA
Someone Call New York City Officials
An apt illustration of how convexity effects affect an overoptimized system, along with misforecasting large deviations, is this simple story of an underestimation made by New York City officials of the effect of a line closure on traffic congestion. This error is remarkably general: a small modification with compounded results in a system that is extremely stretched, hence fragile.
One Saturday evening in November 2011, I drove to New York City to meet the philosopher Paul Boghossian for dinner in the Village—typically a forty-minute trip. Ironically, I was meeting him to talk about my book, this book, and more particularly, my ideas on redundancy in systems. I have been advocating the injection of redundancy into people’s lives and had been boasting to him and others that, since my New Year’s resolution of 2007, I have never been late to anything, not even by a minute (well, almost). Recall in Chapter 2 my advocacy of redundancies as an aggressive stance. Such personal discipline forces me to build buffers, and, as I carry a notebook, it allowed me to write an entire book of aphorisms. Not counting long visits to bookstores. Or I can sit in a café and read hate mail. With, of course, no stress, as I have no fear of being late. But the greatest benefit of such discipline is that it prevents me from cramming my day with appointments (typically, appointments are neither useful nor pleasant). Actually, by another rule of personal discipline I do not make appointments (other than lectures) except the very same morning, as a date on the calendar makes me feel like a prisoner, but that’s another story.
As I hit Midtown, around six o’clock, traffic stopped. Completely. By eight I had moved hardly a few blocks. So even my “redundancy buffer” failed to let me keep the so-far-unbroken resolution. Then, after relearning to operate the noisy cacophonic thing called the radio, I started figuring out what had happened: New York City had authorized a film company to use the Fifty-ninth Street Bridge, blocking part of it, assuming that it would be no problem on a Saturday. And the small traffic problem turned into mayhem, owing to the multiplicative effects. What they felt would be at the worst a few minutes’ delays was multiplied by two orders of magnitude; minutes became hours. Simply, the authorities running New York City did not understand nonlinearities.
This is the central problem of efficiency: these types of errors compound, multiply, swell, with an effect that only goes in one direction—the wrong direction.
When to use it
Urban planning: assessing the true impact of road closures or infrastructure changes on traffic flow.
Risk management: evaluating the potential for small shocks to cascade into systemic failures.
Personal productivity: avoiding overoptimization of your schedule by leaving buffers for unexpected disruptions.
Business operations: understanding how minor bottlenecks can escalate in supply chains due to nonlinear effects.
FROM THEORY TO EVERYDAY LIFE
In practice
New York City Bridge Closure
In November 2011, New York City authorized a film company to close part of the Fifty-ninth Street Bridge on a Saturday. Officials assumed minimal disruption, but the closure caused multiplicative traffic effects, turning anticipated minutes of delay into hours of gridlock.
A MOMENT TO REFLECT
Put it to work.
Think of a system you interact with daily. What small changes could lead to disproportionate negative effects, and how might you build in buffers?
Why do authorities often underestimate nonlinear effects in traffic or other systems, and what can be done to improve forecasting?
How can you apply the concept of convexity to your own decision-making to avoid creating fragile outcomes?
CONTINUE THE CONVERSATION
Source texts
- Antifragile (Nassim Nicholas Taleb)