I feel like the bourgeois gentleman in the Moliere play – for more than 40 years, I’ve been using “heuristics,” and I didn’t even know it.  More than that, I didn’t know how risky they could be.

Heuristics are experiential rules of thumb used for “problem-solving, learning, and discovery.”  We can’t operate without them.  Research shows, however, that some of our most hard-wired “rules” often lead us astray.

Two of the best books I’ve found discussing the nature and risks of heuristics are Massimo Piattelli-Palmarini’s Inevitable Illusions and Richards Huere’s The Psychology of Intelligence Analysis.  I was thinking about one of these heuristics – the desire for effects to have discernible causes – just this past Saturday.

I was trying to figure out why a lavender plant I’d pruned last week was not coming back.  I considered how I’d pruned, what I’d done to the plant after pruning, ran through all the green-thumb checklists I could recall.  I felt sure it was the weather – after a series of beautiful days, things had turned quite cold in the Washington DC area, and I persuaded myself that I’d cut back plants that were now going to die because of the cold snap.

As I brushed the dirt from my hands while walking away from the “dead” lavender, however, I realized that I was committing at least one heuristic error, and maybe many.

I was assuming that I knew “why” the lavender was now “dead.”  Of course, I was assuming that the lavender was “dead – itself an untested assumption.  But even if it was dead, how could I know that it was the weather that did it?

After all, a multitude of factors impact the lavender.  It’s on a corner of near the street, so perhaps a dog did it in by contributing an unappreciated watering.  It’s in a high-traffic area, so maybe someone stepped on it.  Maybe it was destined to go to lavender heaven regardless of what the weather (or I) did to it.  The possibilities boggle the mind, so long as I did not jump to a single “causal” conclusion.

We are, however, hard-wired to make such leaps.  In his terrific analysis of human decisionmaking, Heure notes that humans perpetually struggle to find meaning and causal explanation for phenomena:

One bias attributable to the search for coherence is a tendency to favor causal explanations. Coherence implies order, so people naturally arrange observations into regular patterns and relationships. If no pattern is apparent, our first thought is that we lack understanding, not that we are dealing with random phenomena that have no purpose or reason. As a last resort, many people attribute happenings that they cannot understand to God’s will or to fate, which is somehow preordained; they resist the thought that outcomes may be determined by forces that interact in random, unpredictable ways. People generally do not accept the notion of chance or randomness. Even dice players behave as though they exert some control over the outcome of a throw of dice. The prevalence of the word “because” in everyday language reflects the human tendency to seek to identify causes.

Heure, The Psychology of Intelligence Analysis (1999) at 129.

Experience teaches, though, that even where plausible, causal explanations are often complex, nuanced, and necessarily contingent.  In fact, over the past thirty years chaos theory has become a popular semi-heuristic device in itself, with the “butterfly effect” becoming a cliché to describe the wide ranging impact of seemingly minor and unrelated occurrences.

What does this mean from the standpoint of best practices?  Because we have a heuristic bias in favor of finding causes to all effects, it is wise to keep that in mind during analysis.  Rarely – in fact, I’d say never – is there a single cause.

Still, I felt sure it was the weather.  (And maybe it was, but that’s beside the point.)