Are we getting worse at solving problems?

He didn’t believe it was possible, but that didn’t stop him from doing it. Wilbur Wright said, in 1901, that man would not fly for another fifty years. Two years later he and brother Orville made the first successful flight in the history of self-propelled, heavier-than-air aircraft. Since then, jet engines, breaking the sound barrier, commercial air traffic, and space flight. All in less than a hundred years.

Our technologies show us the history of our ability to solve problems. All built on the inventiveness and discoveries of those who went looking for new ways to solve interesting problems. But all to quickly, the creativity that led to those discoveries gets distilled down into a framework to be packaged for others to use, freeing them from the need for their own creative thought or discovery.

Perhaps there is a demand for such pre-packaged thought. Perhaps there is an over-reliance on it. But Orville and Wilbur didn’t follow The Six Steps For Inventing Flight. They discovered a way forward, they created a solution. As did those who invented the jet engine, and built planes that could fly faster than the speed of sound or carry lots of people long distances, and those that created rockets to take people to the moon.

Maybe, because so many problems have already been solved and because we aren’t solving such ground-breaking problems, we tend to believe that there are no new problems and that every problem can be solved by applying someone else’s solution. Maybe we aren’t very good at telling the difference between problems that can be solved in that way and those that can’t.

Henry Mintzberg, professor of management, draws a distinction between what he calls ‘pat puzzles’ and ‘puzzling puzzles’ when it comes to solving problems. In pat puzzles the pieces are supplied, each is clean-cut, they fit together perfectly and they come with a picture on the box so you know what you’re making. Whereas in puzzling puzzles, the pieces have to be discovered or created, each appears obscure, like a fragment, they need to connect, although never neatly, and there is no future state picture to guide the construction. Frameworks are like pat puzzles. They are whole and complete, with a picture of where you’re trying to get to and all the pieces ready to be used. They provide a shortcut in thinking, but they also fix our thinking, limiting our ideas, allowing only what the framework already includes.

And if we tell ourselves that the problems we’re trying to solve are simple and so don’t require creativity and discovery to solve, then perhaps frameworks are a shortcut to a solution. However, it may be that far more problems are puzzling puzzles than we appreciate. If this is the first time in history that a particular combination of people, skills, technologies, resources, limitations and opportunities have occurred then it is a new problem. Attempting to solve new problems with frameworks as if they are pat puzzles reaches ineffective and unsatisfactory solutions. And then we blame the framework for falling us when really the failure was that we tried to use a framework in the first place. Creativity and discovery are search problems. How do we find new solutions when we don’t know what we’re looking for, or even where to look?

Kenneth Stanley’s research into open-ended algorithms asks the same questions. Just as evolution has no goal in mind, Stanley’s attempts to develop AI that leads to human-level intelligence “travels the road with no destination in mind”. His work has shown that the strange stepping stones we stand on along the way don’t look like they lead to the outcome we want to achieve, that potential solutions may be deceiving and take us in the wrong direction, and that preventing divergent thinking slows down our ability to recognise novel and interesting things. He says that, “to achieve your goals you have to be willing to abandon them”.

If we want to truly solve puzzling puzzles, the problems where the pieces of the solution don’t neatly fit together and we don’t have a picture on the box to follow, then we need to approach problems like Stanley. We need to experiment. Try things that spark our curiosity. Don’t predict the outcome, and let the path be unknown. Take stepping stones that lead to new ideas. Explore ideas that don’t resemble the final end state. Don’t converge on single solutions, but let multiple solutions emerge.

To solve our problems we have to willing to abandon them.