“Several years ago, I spent a day and a night in a library reading through issues of the
Journal of Experimental Psychology from the 1920s and 1930s. This was professionally a most depressing experience. Not because these articles were methodologically mediocre. On the contrary, many of them make today’s research pale in comparison to their diversity of methods and statistics, their detailed reporting of single-case data rather than mere averages, and their careful selection of trained subjects. And many topics—such as the influence of the gender of the experimenter
on the performance of the participants—were of interest then as now. What depressed me was that almost all of this work is forgotten; it does not seem to have left a trace in the collective memory of our profession. It struck me that most of it involved collecting data without substantive theory. Data without theory are like a baby without a parent: their life expectancy is low.”
It can rarely be said of a psychologist that everything they write is worth reading. Gigerenzer is one such psychologist. He writes in plain English (presumably his second language) and understands his material so thoroughly that he can explain it simply, the sign of an intelligent and honest teacher. This straightforward approach means that you can follow this heuristic to make you smart: if you cannot understand him first time round, it is worth reading him several times until you do. With lesser writers, if you cannot understand them first time, turn elsewhere.
Gigerenzer's lament is about the paucity of solid theories in psychology. He laments that there are only surrogates: one word explanations (vague, unspecified references to something like “similarity” offered without any definition or metrics, even when such things are available); redescriptions (such as opium making you sleepy because of its dormative properties); muddy dichotomies (pointless battles between overlapping categories) and data fitting (exquisite mathematical models which re-describe the findings, but cannot explain them).
In defence of the beleaguered dabblers in mental philosophy, it could be argued one has to start somewhere. Data fitting may at least show you where the main currents are in the stream, even if one has no theory of fluid dynamics to explain why there should be currents in the first place.
So, where next? No good calling for more pointless theories and grand delusional castles in the sky. Perhaps we should concentrate on some basic problems.
For example, what makes problems difficult? To make that a little easier, what makes one simple problem slightly more difficult than another simple problem? Other than it having the quality of being slightly more difficult?
No time limit.