This is a companion article to my presentation "Designing the Design Problem."
When I first started working at frog, the people around me kept referring to the problems we were tackling as "problem spaces." When pressed, no one could give me an answer as to why, so I went out and tried to find one for myself. And I think the beginnings of an answer just might be—at least metaphorically—in the splendor of the night sky, full of glistening stars.
On one level, stars are just information in the form of light that has traveled a substantial distance to reach my eyes. In our imaginations, however, we can visualize a limitless number of galaxies teeming with life. To the mathematician, they represent reams of elegant formulas describing the very structure of the universe.
What words do we use to describe these stars? "(28978) 2001 KX76" doesn't quite roll off the tongue, so we have organizations such as the International Astronomical Union for stars and the Center for Small Body Nomenclature if you care to seek out and identify minor plants. Bright stars often have historic names, and are clustered and patterned due to their naming in Greek and Roman mythology over the ages, while in the domain of science, we use computers to catalog which now—according to Wikipedia—numbers over 998 million distinct astronomical objects.
Clearly, we can't keep in our mind a million names for objects, let alone a few thousand. The names of myth are what become stuck in our mind, as well as the stories associated with them. We lie on the roofs of our homes in the late summer, pointing out constellations as we sip iced tea from sweaty, tall glasses. Those moments of our lives always feel steeped in wonder.
It's probably those nights of my youth, straddling both science and myth, that helped encourage me to become a designer. My endless curiosity about what I saw reflected in the dark bowl of the sky—and what could live between those stars, binding the universe together—I often find reflected in the ebb and flow of human behavior. The information that we kick up in our daily efforts, like dust glinting in the sunlight, are the particles of a never-ceasing struggle to create better conditions for life to continue.
Hence, we have problems, and through design, we hope to provide solutions. But creating a solution is not an activity that provides any full measure of closure.
In the course of daily life, we make problems. And the problems are always remaking us. In the process, we often mistake smaller problems that are more apparent, missing the larger problems that limit improvement for the human condition.
To be blunt: The quaint dictionary entry that describes a problem being "any question or matter involving doubt, uncertainty, or difficulty" doesn't quite reflect how the utility of more precisely defining what a problem means today to any designer.
In life, we deal most satisfyingly with closed problems. It's easy to add five and two to make seven, or a bit more difficult to learn how to reconstruct a carburetor in a car. In either case, there's a limited set of ways to reach the desired solution.
Then, there are the open-ended problems that bedevil us.
Conceptual frames for how to think about open-ended problems, such as wicked problems, are gaining more and more currency—and rightly so—because most major societal issues and corporate business objectives can't be met through the efforts of dozens or even many thousands of people in concert. They are too systemic for an immediate or medium-term solution. Besides, after a year or two has elapsed, everyone's understanding of the problem will have changed due to emergent considerations and constraints.
But while we've discussed different frames for open-ended problems, there's a higher-order concern for me: How we consider any type of systemic, open-ended problem, whether wicked or not. Hence, the term "problem spaces," which I'd like to take a stab at defining for the domain of design: Problems are spaces for change from the real to the ideal.
In the domain of science, problem spaces describe the total amount of information and possible states that can occur in the pursuit of a desired outcome. For any human, there is a finite limit to the amount of information that we can handle, until we are overwhelmed. Even for a scientist aided by a computer, too many variables leads to too many possible states that describe too many sets of outcomes that, when considered as part of the world around us, is just too much complexity to bear.
This latent complexity is even buried in the origin of the word "problem," derived from pro-, "in front of," and ballo, "to throw, to cast, to hurl." If someone throws or places some object or information in front of you, what do you? Examine it. Probe it. Perhaps step over it and continue on your way. There are a limitless number of possible moves from that single action. As interaction designers, we consider these affordances for objects that we design, but the number of affordances we can give any possible bit of information is, by all measures, limitless.
So here, in the definition of a problem space, you can already see the first problem we humans have with analyzing information in pursuit of a desired outcome: We always have to create boundaries when considering problems that keep us from being overwhelmed. Much as the reason we limit the number of mythological names we can provide to the billions of stars we have catalogued, too much information in a problem space is a burden on providing a solution within a reasonable, set time period. Otherwise, we are overwhelmed and rudderless. Constraint allows creativity, but this can be double-edged, as Edward de Bono says: "The more specific the description, the more one is trapped by it."
In the domain of design, problem spaces contain many possible futures—but unlike controlled scientific inquiry, the value of design is that we discover novel solutions by moving laterally towards considering and visualizing outcomes we had never considered at the outset. Our understanding of where the boundaries of the problem space exist changes each time we move, iteratively, through the design process, considering and disposing of hypothetical solutions to arrive at the one which is most ideal.
At the same time, as we generate solutions and begin to narrow the type of information we're considering—moving from many types of research data as input to the data embodied in artifacts as designed output—produced designs begin to suggest new problems to solve. Problem spaces need to be constrained for effective design to happen, but upon completing a tangible, designed artifact, they billow and expand further.
So, how do we describe the boundary of a problem space? It's indeterminate, much like looking at archeological remains from thousands of years ago, attempting to extrapolate what could complete each beautiful fragment. We have enough knowledge and information now to know that design problems are tangled up hopelessly in world problems, no matter how much we say they are not related. But this is not a situation without opportunity. We have even more intelligence with which to make even more educated guesses and attempts at influencing a world problem for the better.
We have a responsibility not only for the solutions that we create, but also the problems that we make. Solving a stated design problem will always make space for more problems. This is neither good nor bad—it's entropy. With mindful curiosity and awareness of constraint, we can realize these ideal futures that help to stem that flow of energy out of the macro-system we call our home: Earth.