Solving Problems Rationally in an Irrational World
Engineering is in many ways structured, usually quantitative, problem solving. Whether it is writing a software module that must integrate smoothly with existing legacy systems, balancing the many different design objectives and constraints that go into modern automobile design, or trying to update, operate, and maintain an urban transportation network, engineers are given massive, often contradictory, inputs and expected to produce solutions that work in the real world. And because engineering is a quantitative domain, as many as possible of the fuzzy and qualitative inputs are quantified so they can be included in the relevant models.
Problems thus arise when some inputs are so complex they can’t be quantified, because engineers want numbers and predictable behaviors. This is especially true with what’s known as “wicked complexity” — complexity that arises in the psychological, social, or cultural domains simply because of the nature of the human. You can’t optimize with wicked complexity; rather, you have to “satisfice” — come up with solutions that make most parties happy enough. In struggling with how to do this, engineers are remarkably similar to neoclassical economists, who routinely posit a “rational economic actor” with…
I accept that Teslaistic vehicles are
the future. But they have
no stick shift,
no double clutch,
no groaning as orgasmic metal constructions with straight pipes achieve Nirvana,
no screaming tires as one slides into Dead Man’s Curve,
no pretense of mythic.
They are little ideological creatures,
huddled around the pale fire of deep greens
and nerdish engineers
poking gingerly at Truth,
doomed to utilitarian drudgery in service to
those for whom 8 cylinders and a straight road are
evil creatures of some carbon Satan.
Granted, there were those
touched by grace,
called by predestination to greatness –
’65 Riviera…
Engineering is in many ways structured, usually quantitative, problem solving. Whether it is writing a software module that must integrate smoothly with existing legacy systems, balancing the many different design objectives and constraints that go into modern automobile design, or trying to update, operate, and maintain an urban transportation network, engineers are given massive, often contradictory, inputs and expected to produce solutions that work in the real world. And because engineering is a quantitative domain, as many as possible of the fuzzy and qualitative inputs are quantified so they can be included in the relevant models.
Problems thus arise when…
Brad Allenby
Brad Allenby, J.D., Ph.D., is President’s Professor of Engineering, and Lincoln Professor of Engineering and Ethics, at Arizona State University.
