In This Issue
Spring Bridge on the US Metals Industry: Looking Forward
March 29, 2024 Volume 54 Issue 1
In this issue of The Bridge, guest editors Greg Olson and Aziz Asphahani have assembled feature articles that demonstrate how computational materials science and engineering is leading the way in the deployment of metallic materials that meet increasingly advanced design specifications.

Invisible Bridges: Engineering Our Wicked Problems

Friday, March 29, 2024

Author: Guru Madhavan

Life comes with pernicious problems, some with recognizable plots. We excel in solving the well-behaved ones, but intractable problems create more questions. In a 1965 lecture, the British philosopher Karl Popper classified problems using the metaphors of clocks and clouds. He compared systems that obey logic to clocks and those that defy logic to clouds. Unlike a timepiece’s predictability, the shifting subtleties of clouds reside in their myriad forms and shadows.

For William Shakespeare, clouds were simultaneously dragons, bears, lions, citadels, capes, and cliffs. And in John Constable’s assiduous sky paintings, the cloudscapes were “the chief organ of sentiment.” Their fluctuations and formlessness made it clear that “no two days are alike, not even two hours.” Clock systems construct our comforts. They direct electrons to send messages, summon shared rides, trade stocks, swipe for dates, and livestream K-pop. With cloud systems, we have only shadow­boxed the problems. And then there are the cloudiest of them, the “wicked” problems.

Clocks and Clouds

Each wicked problem is unique. These challenges have vexing staying power, working like franchises, with premieres and prequels, remakes, reissues, reboots, sequels, spin-offs, and streaming on demand. One can’t opt out, log off, autocorrect, unsubscribe, block, mute, cancel, or shut down wicked problems. Nor can we click and clear them like browser history. As their forms change, so do their formulations. With wicked problems, we tend to carve off pieces that invite rational solutions, leaving the rest for others to manage. Often, however valuable, technical fixes and related policy statutes may become the first and the final solutions for problems that are other­wise significantly behavioral and cultural. But tackling part of a problem may deceive us into thinking that the whole problem is tamed. “Look, I’ve not tamed the whole problem,” as scholar Charles West Churchman once observed, “just the growl; the beast is still as wicked as ever.” And scholar John Warfield used the term “spreadthink,” the opposite of groupthink, to describe how, in a wicked problem, individuals cannot focus and agree on its critical elements.

 A simple equation named “the monster” can help us think about wickedness: I=2n(n–1), where I is the number of states a system could have with n number of elements. Suppose all the components interact with one another straightforwardly. Then, a two-element system results in 4 states, and a three-element system has 64 states. In a ten-element system, the number of states will exceed the number of stars in our galaxy. While wicked problems are inherently knotty, we increase their complexity with our human bramble of beliefs and deficits, paradoxes and priors. And worse, wicked problems are invoked so often, they are tainted by simple familiarity; consider how often we evade—even disregard—the daily degradations from “climate change,” even if those words are now routine.

Engaging with wicked systems requires more than good intentions, creativity, and expertise. We need a ­communal code of conduct—or in an engineering sense, a concept of operations to train and treat our approaches (including, especially, education) to gain greater improvements. To do so, we need an engineering vision for civics and a civic vision for engineering. Engineers, after all, aren’t commonly invoked as enablers of democracy, yet they do more than “tech support.” Engineering is a carrier of history, simultaneously an instrument and the infrastructure of politics. It’s among the oldest cultural processes of know-how, far more ancient than the sciences of know-what. And through engineering, civics can gain a more structured, systemic, and survivable sense of purpose. By applying engineering concepts in a civic context—and by proactively educating engineers how to do so by incorporating insights from history, philosophy, and cultural evolution—engineering can usefully grow the policy lexicon and enhance its cultural relevance. The usefulness of civics and engineering is often realized only in their breakdowns, much like trust, most longed for in their absence.

A Systems Engineering Sensibility

Developing a civic consciousness to achieve democracy’s goals will fundamentally require a systems engineering approach, which is not some specialty tool embedded in an AIE (acronym-intensive environment). Indeed, before specialization altered many engineering practices beyond recognition, a kind of “systems sensibility” pervaded early engineering. Consider the thinking behind the development of the Indus Valley from the Bronze Age. Sophisticated food production, grid-town planning, drains, dams, and dockyards were a testament not merely to civil engineering but to a form of civic engineering. They improved both standards of living and thinking. Systems planning to those engineers meant braiding commerce and culture, from recreation to conservation. Many Native traditions have applied such overarching awareness. Prominent successes of industrial systems engineering, including telecommunications and missile defense systems, were evident during World War II. The applications reached a broader scale between the 1950s and the 1970s in the defense, aerospace, urban-planning, and manufacturing sectors.

Systems engineering, like civic duty, occurs under the constraints of costs, schedules, and performance requirements. While systems engineers often focus on the needs, desires, end points, and context of a problem set, they know that local fixes will not produce a globally viable solution. An engineering process based on cost, schedule, and performance requirements works well for aircraft assembly. Once that plane begins to fly, however, it enters a broader social system with different levels of complexity. Should we add capacity at a near-city airport or build new facilities farther away? Each option now involves considerations far afield from aircraft yet central to the aviation system. That’s why systems engineering often works best when it’s not expected to produce an “engineering” solution.

Taking a systems engineering approach—duly considering all facets of a problem—with a far broader scope might sound unnatural, especially for the issues of business, govern­ment, and civic life. The idea of dividing a year into days or a circle into degrees and using clocks was unnatural and required an initial mental leap. Even flying was—and is—unnatural for humans. Still, we acquired the skills to do it, with iteration eventually becoming intuition. In practice, systems engineers recognize ­sensitivities (as in all too commonly, when an economic incentive can deleteriously affect the environment), shape synergies (where multiple actions can achieve a benefit that a single activity cannot), and account for side effects (what influences what, beneficially and adversely).

The next time you drive across town, think about ­energy efficiency. You can technically express how efficient your car is in fuel use or how economical it is to get to your destination compared to other modes of transport. But the fact that you chose to drive could be behavioral, and having to go across town could result from poor urban planning, which may be political. Across these levels, engineers seek a baseline understanding of facts and assumptions, often shaping their products and services as an exercise in trade-offs. Certain factors and viewpoints are privileged over others, akin to a projector spotlighting the main actors, leaving the rest behind the scene. Further, engineers often characterize themselves as “problem solvers,” so much so that it’s part of their primary professional identity. But for wicked problems, one must go beyond mere problem-solving, and engineering education should contribute to this crucial cognizance.

Scholar Russell Ackoff observed that not all ways of viewing a problem are equally productive. Still, the most productive views are seldom evident. Problems should be approached from as many angles as possible before the measures are selected to address them. Effective problem formulation requires, first, awareness of the types of problems that lead to wickedness.

The Hard, the Soft, and the Messy

Call the first type “hard problems.” They are bounded and boundable, and scientific principles, market pressures, and sponsor requirements neatly specify them. The outcomes are directed— even dictated—by customers, consumers, and clients. Have you used your smartphone to check into a flight? Or, did you self-checkout at the grocery store or use a QR code to order tacos at a chic gastropub? These outcomes are products of hard problems. And as with standardizing production processes for Coca-Cola, cars, and cans of crinkle-cut carrots, they can be solved by recombining and repurposing existing tools and techniques. Such problems can be mathematically manipulated, chemically configured, and materially improved. Ultimately, they can be “optimized” by applying available knowledge and experience with the idea that the best possible outcome exists and is achievable.

The second class, call it “soft problems,” is in the ­arena of human behavior, which is complicated by political and psychological factors. Because their end points are unclear, and thorny constraints complicate their design, soft problems cannot be solved like hard problems; they can only be resolved. There are no easy fixes to a problem like traffic congestion. Adding more road capacity won’t necessarily clear out bottlenecks on a throughway, nor can congestion pricing if the charges are unaffordable for most people who use a tunnel. Such interventions depend on the contexts for which they are designed: what works for Charing Cross Road may not work in Chengdu or Chennai. Even in the same city, what works for one bridge may not work for another.

Notably, soft problems often involve how we assign value to time and how much we are willing to pay for it. They require political buy-in that may eventually pay for a service and behavior change that might inspire elements such as added public transportation or more flexible teleworking arrangements. Since soft problems involve technology, psychology, and sociology, resolving them yields an outcome that’s not the best but only good enough—and what’s best for one area might not be always best for the others. As Ackoff characterized it, the results are based not on optimizing but on “satisficing,” an approach that satisfies and suffices.

The third class, “messy problems,” emerges from differences and divisions created by our value sets, belief systems, ideologies, and convictions. A disease outbreak may involve hard problems with solutions such as barcode-tracked supplies or antibiotic deliveries. The outbreak’s soft problems might require resolutions like mapping infectious disease spread or retooling the indoor environment to prevent the propagation of infection. Neither resolution is exact, but both are good enough. By contrast, a messy problem can involve a pathogen gaining antibiotic resistance or intersecting with delicate religious rituals, as was evident with the Ebola outbreaks in recent years. How can we reframe centuries of tradition into safe, acceptable burial practices while respecting cultural sensitivities? Such messy situations may only be abstractly dissolved by transforming them into a different, possibly manageable state. Messy problems can be reframed out of existence not by optimizing or satisficing but by “idealizing.” In Ackoff’s words, this entails getting the matter, as in creating dignified burial rituals and promoting safe public health practices, “closer to an ultimately desired state, one in which the problem cannot or does not arise.”

Solutions, Resolutions, and Dissolutions

A wicked problem emerges when hard, soft, and messy problems collide. If they were works of art, hard problems would be photographs, offering clarity and directness. Soft problems are like blurry brushstrokes of impressionism, and  problems are spilled and splattered abstractions. A wicked problem emerges when hard, soft, and messy problems collide. Think of them as a cubist collage where the truth is simultaneously sharp, shaky, and squiggly. All three are required for wickedness. Seen this way, there’s hardness nestled in soft problems, and hardness and softness reside within messy problems. By extension, a solution can be within a resolution, and a dissolution might contain resolutions and solutions.

 Of course, one might absolve the world’s problems with a doomed shrug—but that’s not the point of good engineering education, let alone practice. Engineers should consider how hard problems become soft, how soft problems evolve into messy ones, and how hard, soft, and messy problems conspire to produce wickedness. This is a requisite competency—and consciousness—for us to develop a balanced blend of hard solutions, soft resolutions, and messy dissolutions to wicked problems. To do so, we’ll need to exercise and enrich a broader systems engineering sensibility—in education and practice.

Inspired by the name of this quarterly, this column reflects on the practices and uses of engineering and its influences as a cultural enterprise.

About the Author:Guru Madhavan is the Norman R. Augustine Senior Scholar and senior director of programs at the National Academy of Engineering. His new book is Wicked Problems: How to Engineer a Better World (W.W. Norton, March 2024), from which this article is adapted.