On ignoring scientific evidence: The bumpy road to enlightenment
I’m starting to like this Hogarth guy….I highly recommend reading the excerpts below.
Click Here To Read: On ignoring scientific evidence: The bumpy road to enlightenment
Abstract (Via Hogarth)
It is well accepted that people resist evidence that contradicts their beliefs. Moreover, despite their training, many scientists reject results that are inconsistent with their theories. This phenomenon is discussed in relation to the field of judgment and decision making by describing four case studies. These concern findings that “clinical” judgment is less predictive than actuarial models; simple methods have proven superior to more “theoretically correct” methods in times series forecasting; equal weighting of variables is often more accurate than using differential weights; and decisions can sometimes be improved by discarding relevant information. All findings relate to the apparently difficult-to-accept idea that simple models can predict complex phenomena better than complex ones. It is true that there is a scientific market place for ideas. However, like its economic counterpart, it is subject to inefficiencies (e.g., thinness, asymmetric information, and speculative bubbles). Unfortunately, the market is only “correct” in the long-run. The road to enlightenment is bumpy.
Must Read Excerpt (Via Hogarth )
What happens, however, when events in the world do not conform to the predictions (implicit or explicit) of your model? Imagine, for example, that when you let something slip out of your hand, it floats instead of falling. Do you question your eyesight or your model? Or do you ask whether you are in strange conditions where the model “does not apply”? Note that this, essentially, is what scientists should do when they first meet surprising phenomena (where surprising means relative to model-based expectations).
Surprising results can have three causes: (1) the method used to obtain the result was flawed (in the example just given, perhaps there is something wrong with your eyesight?); (2) the model really is incorrect (left by themselves, objects do float instead of fall); and (3) there are specific circumstances – perhaps not previously encountered – where the model does not apply (perhaps you observed the object while traveling in a space vehicle where gravity has no effect?).
Possibly one way to think about the situation is to use the analogy of the market place for ideas where, in the presence of efficiency, ideas that are currently “best” are adopted quickly. However, like real markets in economics and finance, the market for scientific ideas is not necessarily efficient. There are many situations where the market is “thin” and not all traders (i.e., scientists) have access to information. There are speculative “bubbles” or fashions as some theories become extremely popular for a time and then fade away (consider what happened to many learning models in psychology or applications of chaos theory in the social sciences). Great rewards are also to be had for identifying certain ideas that could become popular (e.g., cold fusion) and this too could distort information that is made public. Finally, despite attempts made to regulate the exchange of ideas and the rules for doing science, people still find ways to circumvent regulations. In the final analysis, the market for scientific ideas can only become efficient in a long run sense. Unfortunately, as implied in a famous statement by Lord Keynes, our lives do not extend that far.
Click Here To Read: On ignoring scientific evidence: The bumpy road to enlightenment
