“Why do research on the Higgs boson?”
“Because it is there … probably.”
I recently presented my planned future work in psychology. One of the main questions was: “Why do you do what you do?”.
It’s a good question and one should have good answers. But answering this question and related ones (like “Why this setting?”, “Why this content?”, “Why this tool?”), I couldn’t help but wonder — why the fixation on the motivation? I haven’t heard anyone asking a physicist why he or she searches for the Higgs boson. Yeah, there are good reasons like checking grand theories, but personally? Why Higgs boson and not some other particle? Or why do particle research at all? But somehow psychologist seem to be scrutinized more about their motifs.
And I think that some kinds of motifs are regarded with more skepticism for psychologists than for other scientists.
For example, the importance of the topic in a social or technical sense would be universally accepted as a good reason, but what about the practicability of data gathering? What if one reason is that a scientist needs good data and that the chosen setting can provide these data? Why should anyone complain against that? But I think in psychology they often do, calling it cutting corners or doing convenience samples (or topics). Sure, it must not be the only reason and the results must be checked for their generalizability, but besides that? Scientists study what is there (or expected to be there) and what they can study. As a physicist I would not try to plan a study that requires an LHC when I could not access one. As a biologist, I would not try to plan a study about Platypus if I could not travel to Australia. But with psychology there are arguments like ‘but why do you not analyze topic xyz’ instead of topic ‘abc’. And the practicability of data gathering is seen as suspect, very suspect.
And then there is expertise and a personal relationship with the topic. If you want to study a subject, it helps if you know much about it. Usually, the first or even the second study in a new domain is full of mistakes (and often unpublishable). It takes time to develop expertise, to know where the pitfalls are, how certain dependent measures can be best measured, and how to influence behavior in this setting in the best way. But even this is sometimes regarded critically, especially if one chooses a certain topic (which is the basis for later generalization to other topics) based on personal preference. If I would design a learning tool, I’d probably take Psychology or Photography as topics. Why? Because I have expertise in both topics. I know enough to quickly develop a knowledge test, I know the domain (somewhat) and in some areas even the field. If generalizability is taken into account in the beginning, where is the problem?
Sure, expertise can lead to the use of heuristics that ignore the individual case, leading to less creativity in that area, and expertise can also bias decisions if it is overshadowed by personal opinions. There are topics which I would not choose as a topic for a learning system, simply because I know that I am biased with these topics: My opinions would influence me no matter what. But besides topics where this is the case (e.g., religion, operating systems), I think expertise and personal relationships with the topic are a boon, not a curse.
It’s the same with partnerships that occur (more or less) by accident. If you have access to experts in a certain domain, it would be stupid to forgo this access simply because it was not planned in advance (of your career). This is true for professional partnerships between researchers or institutions; there has been great work done in interdisciplinary teams. And this is also true for personal/private partnerships — for example, having a partner who works in another domain who can provide expert knowledge. It may be a coincidence like sharing the same building, belonging to the same non-scientific organization, or simply meeting a person after a concert and having a few drinks, but it’s a lucky coincidence, so why not use it?
In reality, these things often happen, and they are used — luckily. When someone asks why a scientist did do a project, many scientists often find reasons after the fact (better call them rationalizations). And if these accidents, convenience samples and personally interesting topics do not influence the research negatively, e.g., by limiting the generalizability of the sample or the topic, I see nothing wrong with it. After all, there are good reasons (rationalizations) for doing so.
Trying to treat scientific research like its actors — scientists — were angels in a white room, deciding unemotionally and without outside influence which topics to study and why, is naïve. And I think many psychologists have a socialized insecurity about their status as empirical scientists and overreact in a way that could best be called “lab coat envy”: Some want to be in that white room.
Don’t get me wrong: I am a strong proponent of scientific integrity and research ethics, and in an empirical science there are good rules and reasons how to do things. And I think that some topics are of more importance than others — but that is my opinion and preference. Likewise that I think that one should select topics that matter in the societal sense, after all, they pay you and you want to make an impact. But regarding the motivation what to study and why — I think that’s a personal decision. Public(ated) reasons often come after a personal decision, which is often based on personal preference and convenience, and are in reality rationalizations, not the initial causes and arguments. And this, again, is a boon, because it allows for great academic freedom of research that makes an academic career special and very satisfying (with limitations, nobody is completely free in his or her studies).
So, let’s take it as a blessing and not as a curse — I study what I study because it is interesting to me, because it is something I can deal with (e.g., conduct professional research in the domain, have organizational, emotional and cognitive access to the domain/methods/field) — and because it’s there where I try to make my impact.
And I have other good reasons for it.