Abstract
This special symposium in Perspectives on Psychological Science answers the question, “Do you believe the field of psychological science is headed in the right direction?” Respondents are a sampling of Association for Psychological Science award winners over the past 5 years dating back from publication of this symposium.
You are about to read a special symposium of Perspectives on Psychological Science addressing the question, “Do you believe the field of psychological science is headed in the right direction?”
In order to select invitees, my colleagues and I compiled a list of major award winners of the Association for Psychological Science (APS) over the last 5 years, starting from the 2017 list. The list is larger than usual because in 2013 the Board of Directors selected 25 scientists to receive the William James and James McKeen Cattell Awards as a way to mark APS’s 25th anniversary. I asked my associate editors which award winners they particularly would be interested in hearing from regarding the future of the field. I then selected a sampling of the names they chose. (Obviously, other award winners would have great things to say as well, as would many nonaward winner, but we have only limited space.) Participants were asked to address the following questions:
Do you believe the field of psychological science is headed in the right direction?
Why? In particular, what aspects perhaps are headed in the right direction and what aspects perhaps are not?
What should the field do, if anything, to steer itself better in terms of future directions?
Please share your wisdom: What one piece of advice would you give your colleagues, especially younger ones, about preparing to engage with the field of psychological science as it will exist in the future?
Tell us a little about yourself. Please provide a very brief biographical narrative and state what you believe, or at least hope, will be your greatest accomplishment toward steering the field in the right direction.
The symposium was inspired, in the short run, by a polling question asked frequently by pollsters of all stripes: “Do you believe the country is headed in the right direction?” But it was inspired, in the long run, by a mountain-climbing incident that happened to me once, some years back. Let me explain the context of the incident.
In numerical analysis, there is a method for solving optimization problems called the “method of steepest ascent,” which optimizes the solution to a mathematical function. Metaphorically, imagine you are climbing a mountain range. You do not know much about the topography of the mountain. What you do know is that the range is tall and vast and that it is at least three dimensional. In theory, the mountain range could have any number of dimensions—you just don’t know for sure what’s out there.
What makes the climb especially difficult, aside from the vastness and height of the mountain range, is that you are climbing in the darkness: You can hardly see a thing. You use a walking stick to feel the terrain around you, trying to find the next point to which you should take a small step to continue your climb up the mountain. You realize that many steps you take will likely keep you at the current altitude or even bring you back down the mountain. So gradually you work your way up the mountain until you reach a point where every way in which you explore with your walking stick leads you down rather than up the mountain. The question is: Have you reached the top of the mountain?
Of course, you have no way of knowing whether you have reached the top of the mountain. The problem is that it is pitch black so you can’t see where you are: You may just have hit a local maximum, which might be close to the top or really quite far from the top.
Oddly, in climbing a small mountain, I once had a similar experience. It was getting dark, and I shouldn’t have stayed out there. I reached a point where I could not find my footing to go up the mountain, but when I tried to go down, I could not find footing to go down either. I was stuck! Eventually, I took a leap up and just made the next foothold. It might not have worked out so well.
The climb up the mountain, I believe, is a metaphor for scientific progress. We try in small steps to climb to the top—to learn “the truth” about a scientific phenomenon. But we are climbing in the dark: We really cannot see the entire terrain. And when, after small steps, we reach what seems to be the top—understanding of a scientific phenomenon—we should know that most likely our feeling of being there is not really the same as our being there. We may have settled upon a local maximum.
There are three principal reactions, I believe, to being stuck at what is likely to be a local maximum in scientific research. First, you can become complacent, because you really believe you have hit the absolute top. You’ve found the scientific “truth.” Second, you can decide to enjoy yourself in your triumph at reaching a peak, at the same time at least realizing that you may not have hit the absolute top (assuming or at least hoping that there even is an absolute top!). In this case, you decide that your scientific theory or results are good enough, even if they are not what you ultimately might hope for—a sort of satisficing reaction (Simon, 1997). Third, you may decide that you want to see whether you are indeed at the global maximum and not just a local one. You know that another small step will get you nowhere you want to go. So you muster your courage to take a big leap in the dark, realizing that there is a good chance you may land lower than where you are at present—or that you may fall to your doom! But even if you go lower, if the big jump puts you on a different part of the mountain, you ultimately may be able to climb higher than you were before. In this case, you decide to think about whether there is a different theory, empirical study, or even paradigm that better might be able to answer the scientific question you want to address (Kuhn, 2012; Simonton, 1994, 2002; Skyrms, 2000; Sternberg, Kaufman, & Pretz, 2002). Eminent scientists tend to follow this path to the future, always looking beyond where they are rather than dwelling on where they comfortably have been (Sternberg, Fiske, & Foss, 2016; see also Sternberg, 2003).
A highly nonoptimal solution, I believe, is the first one: to accept where you are and decide that you have found “the truth.” It is easy but foolish to become complacent, believing that somehow we are the privileged scientist who has somehow uncovered truths unavailable to other, merely ordinary scientists (see Sternberg, 2002). We become eager to disconfirm other’s work, but not our own (cf. Popper, 2002). This attitude could be with regard to a phenomenon, or a theory, or a method. In my own career studying human intelligence, I have seen many putative “truths”—factor-analytic models, developmental models, reaction-time models, computer-simulation models, and now perhaps neuropsychological models (Sternberg, 1990; Sternberg & Kaufman, 2011). Similarly, scientists studying intelligence have gone through a series of stages trying to understand group differences and especially socially constructed racial differences (Sternberg, Grigorenko, & Kidd, 2005). Each time, some scientists hoped that the existing paradigm finally would yield true understanding, as though there were a clearly defined problem with a clear solution (see Davidson & Sternberg, 2003; Sternberg, 1985, 1997). But we never know for sure if we are at the top of the mountain, and given the vastness, height, and multidimensionality of the mountain, it is a safe bet we have reached only a local maximum. So we need to think about what the next big leap might be that will take us beyond what is in all likelihood a local maximum. We can become so busy in our careers that we do not find time to look ahead to where we might go and to think about whether we really are at the top of whatever mountain we are trying to scale. Every once in a while, there is value in reflecting on what the future may hold.
This symposium represents diverse approaches to reflecting upon the future of psychological science, and we at Perspectives on Psychological Science hope you enjoy it.
Footnotes
Acknowledgements
I am grateful to Brad Bushman, Alison Ledgerwood, and Jennifer Tackett for comments on this article.
Declaration of Conflicting Interests
The author declared no conflicts of interest with respect to the authorship or the publication of this article.
