Earlier this year, Malcolm Gladwell wrote an article for The New Yorker called "Open Secrets" in which he discussed the distinction between two types of problems: what he called "puzzles", which are simpler, and "mysteries", which are more complex. Building on the work of national security expert Gregory Treverton, he wrote:
"Osama bin Laden's whereabouts are a puzzle. We can't find him because we don't have enough information. The key to the puzzle will probably come from someone close to bin Laden, and until we can find that source bin Laden will remain at large."
"The problem of what would happen in Iraq after the toppling of Saddam Hussein was, by contrast, a mystery. It wasn't a question that had a simple, factual answer. Mysteries require judgments and the assessment of uncertainty, and the hard part is not that we have too little information but that we have too much. The C.I.A. had a position on what a post-invasion Iraq would look like, and so did the Pentagon and the State Department and Colin Powell and Dick Cheney and any number of political scientists and journalists and think-tank fellows. For that matter, so did every cabdriver in Baghdad.
Gladwell further developed his point by describing how the trials carried out in the wake of the Enron collapse simplified a mystery into a puzzle, thus missing the point--and the lessons we could have learned from them. He describes other examples where mystery-thinking was necessary to solve a problem first looked at as a puzzle.
Although this is a little too gimmicky for my tastes, I think that Gladwell makes a meaningful distinction here. I was thinking about this distinction last night when I addressed the incoming class of the Texas A&M University Undergraduate Research Fellows Program, A&M's senior undergraduate thesis program. These students are embarking on a year-long undergraduate research experience, which will culminate in an undergraduate thesis, so I talked in part about how Gladwell's puzzle/mystery distinction applied to the work that they would be doing this year.
For Gladwell, one of the defining characteristics of a mystery is the presence of an overload of information. Just to put this into perspective, let's take a look at the situation facing life scientists today. For example, when I did a PubMed search for the word "cell", I got a totally overwhelming 3,372,198 hits.
But, that was Monday. On Tuesday morning, that number was 3,373,026, meaning that almost one thousand new research articles with the word "cell" in them were published in less than 24 hours. Today, it was up to 3,373,442. Along those same lines, search for "protein" and 3,859,439 articles come up. Search for "DNA", and you'll get 928,505 hits. Who knows how many will come up tomorrow?
Certainly, then, the key to progress in biomedical science is not just the generation of new data, but the careful analysis of data--both new and preexisting.
Although it is insightful and nuanced, even Gladwell's writing here is a little too simplistic. Rarely is a problem just a "puzzle" or a "mystery", but usually it is both, requiring not just the careful analysis of existing information, but also the creation of new data.
So it goes in research, and I told these beginning undergraduate researchers that this year they would be solving a problem with both puzzle and mystery characteristics. This will likely require the generation of new data, whether as a scientist working at the laboratory bench, as a historian digging through historical archives to find primary sources not previously examined, or as something completely different. In that sense, these students would be collecting the pieces to solve a puzzle.
Most importantly, though, they would be using their intellect and analytical capabilities to solve a mystery. It is in this respect that academic researchers truly create new knowledge, and this is what separates them from machines or technical workers.
These skills, this understanding of research as a process, and the ability to break down complex problems are relevant not just to research in one's chosen field, but to research in general, and they are in fact highly translatable to a variety of endeavors. Even if these students I talked to last night, who are just starting their undergraduate research, don't decide to go on to graduate school next year and stay in academic research, hopefully they will after this year at least now be able to look at the world in a more sophisticated and nuanced way, and be better citizens for it.
That is very interesting and a reasonable way to look at things. I have always divided problems into two classes as well. Technical problems are problems which can be solved with time and resources, and do not require a paradigm shift. Theoretical problems are those which are unsolvable under the present paradigm, and require a paradigm shift, a change in understanding of the universe.
I had not thought about the information overload aspect. However, I recall a chemistry professor commenting, maybe 30 years ago, that it was easier to put a graduate student on solving a problem than to do a literature search to see if it had previously been solved.