Everything Is Obvious (once you know the answer)

A fun, provocative, little book by Duncan Watts...

Watts is a sociologist, but this book ranges far into psychology-- with a number of interesting applications to marketing, social networks, and even, to people's beliefs about religion and history (including evolutionary mechanisms).

I learned about the book from a review in the WSJ by Christopher Chabris. (Well, at least, I have the review tucked into the book.) Quoting Chabris, Watts' conclusion is that "common sense is a shockingly unreliable guide to truth and yet we rely on it virtually to the exclusion of other methods of reasoning." In this, Watts runs counter to more popular works by Malcolm Gladwell.

One of the symptoms is ex post story-telling. We see something happen and then arrive at what we see as a compelling explanation. But we often fool ourselves into thinking that 1.) our stories are explanations; and 2.) what seems compelling is merely reasonable (and often, ultimately, wrong).

The root problem: profound information problems. We know so little-- in general and with respect to any given aspect of life. Drawing inferences with little info, we (implicitly) use a ton of "faith" (or whatever term you prefer, if you're allergic to that one) which is based on our inevitably-flawed worldviews and our inherently-limited theories.

Of course, humility and self-correction (often with the help of others) are potential remedies. But humility is difficult to embrace. And self-correction is easier said than done, especially when we a.) choose evidence selectively; b.) read narrowly; and c.) find it relatively difficult to shift from one paradigm to another. (Struggles in all of three of these are a mark of fundamentalism-- common in both religious and secular settings.)

Watts identifies "what is arguably the central intellectual problem of sociology...the micro-macro problem...the outcomes that sociologists seem to explain are intrinsically macro in nature...[but] all these outcomes are driven in some way by the micro actions of individual humans." Beyond sociology, he notes that something like this "comes up in every realm of science". Watts then illustrates the concept with claims about "emergence" and the supposed development of life through evolutionary mechanisms. "How do you get from one 'scale' of reality to the next?" The chosen approach: "Historically, science has done its best to dodge this question, opting instead for a division of labor across the scales." (61-63)

More broadly, much of what Watts offers is applicable to beliefs about evolution, especially as a comprehensive "explanation" for the development of life. Watts spends a lot of time on such "explanations".

Watts (27): "What appear to us to be causal explanations are in fact just stories-- descriptions of what happened that tell us little, if anything, about the mechanisms at work. Nevertheless, because these stories have the form of causal explanations, we treat them as if they have predictive power. In this way, we deceive ourselves..."

Other considerations: "the combination of the frame problem [the inherent circularity of drawing inferences from context about context; p. 45-46] and the macro-micro problem means that every situation is in some important respect different from the situations we have seen before" (110). Thus, "it is all too easy to persuade ourselves that we have learned more than we really have" (111).

"Historical explanations...are neither causal explanations nor even really descriptions-- at least not in the sense that we imagine them to be. Rather, they are stories." (131) Continuing: "Scientific explanations often start out as stories as well...[but] in science, we perform experiments that explicitly test our 'stories'...however, our inability to do experiments excludes precisely the kind of evidence that would be necessary to infer a genuine cause-and-effect relation. In the absence of experiments, therefore, our storytelling abilities are allowed to run unchecked... (133). 

Evolution, on a "micro" level (or again, whatever term you prefer), can be tested in many cases. But, on a "macro" level (or choose your own term), it's difficult to imagine how it could (really) be falsified. 

Moreover, it's odd (and unreasonable) to expect science to carry that type of load. The upshot: "Expecting history to obey the standards of scientific explanation is therefore not just unrealistic, but fundamentally confused." (133) Why the fundamental confusion? A failure to understand "science" or a need to have one's beliefs validated by something with authority.