What Is The Question?

Finding the question can be fun, as in thinking of a cartoon caption. But it can also be extremely difficult psychologically. Scientists are often expected by the public to know it all, and yet, “feeling stupid” is a common mode of operation for us. Science is the art of dealing with things we do not know enough about. As Wernher von Braun, the father of German and US rocket programs, phrased it: “Research is what I’m doing when I don’t know what I’m doing.” Science is humbling in this way. For young scientists, it is often very difficult to understand that it is perfectly normal to not know the answer—or even the question. Learning to embrace this uncertainty is part of our maturation as scientists.

Uri Alon has an intuitive image to describe the process of re-finding our questions. Given what we know about a given topic “A,” a researcher predicts that it should be possible to arrive at point “B,” a scientific destination that seems interesting—a hypothesis. However, the plot inevitably thickens over the course of the research project, and new hurdles force the scientist into a meandering path. Soon, the researcher is lost, having lost sight of the start point (which suddenly seems shaky) and end point (which appears unreachable). Uri calls this “being in the cloud”—you have lost your original question, but the reason why this has occurred is strange and thus potentially exciting and itself worthy of study. From inside the cloud, the situation may seem desperate, but Uri sees the cloud as the hallmark of science: if you are in the cloud, then you might have stumbled upon something non-obvious and interesting. “I’m very confused” a student would tell Uri, to which he would reply, “Oh good - So you’re in the cloud!” Eventually, a new question that arose inside the cloud may lead the way to an unexpected destination “C.”

Embracing uncertainty

The scientific method is often perceived as a simple sequence that leads from a problem to an answer, possibly through long iterations of modified hypotheses. But our reality is much less structured: it often starts with a topic and some observations, leading to the finding of patterns and questions about those patterns, possibly long before we have any explicit hypothesis or any direct tests. And even if a project starts out with a very specific hypothesis, in our experiences, it still generally arrives at a very different point than expected.

In some way, then, night science may be most productive when it has no agenda, when there are no particular questions it is trying to reshape or resolve. When the scientist does not have a hypothesis, she is free to explore, to make connections. In some sense, any kind of expectation on how things are to behave—a hypothesis—is a liability that could obstruct a new idea that awaits our discovery. Once night science elucidates and reframes this question, the researcher can use the full power of day science to solve it. In this sense, a major discovery is typically both the solution and the problem.

Much of basic, curiosity-driven science is exploration, and night science is a fundamental part of that; yet funding bodies often demand that research must be hypothesis-driven. But while some part of night science can be done with the help of an armchair and some good coffee, other parts require the exploration of large and complicated data sets. If no funding is provided for such endeavors, the generation of new questions may be stifled, hindering scientific progress: in science, the problem that is eventually solved is often not the one that was initially sought out.

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