of expectations are the backdrop against which anomalies arise. These
features of ordinary circumstances usually go without saying,
but here it will be important to pick out just the right things to
say to make sense of anomalous behaviour. These sorts of
statements are crucial in such pursuits as public policy writing, and
a variety of other forms of public recommendation. Essentially, the
task is to say why you expect one thing to follow another
when, to a particular audience, the step does not go without
In general, our expectations can either be satisfied or unmet.
Satisfied expectations, bundled together, are the foundations for reliable predictions, which we’ll treat in the chapter on recommendations. This, in turn, is the foundation for concepts, which we’ll treat as a special topic in a later chapter.
For example, whenever I ride my bicycle to the supermarket my mood improves. I expect a bicycle ride to improve my mood, so I predict this ride will do the same.
Expectations come from somewhere, and that somewhere is our experiences in the world. We naturally notice patterns in the weather, in traffic conditions on Lake Road, in the times of year that birds migrate. Patterns are reasons to think that the same thing will happen again, under the same or relevantly similar conditions.
Of course, we write off details when we notice patterns. For example, there’s always traffic just after 4 PM on Lake Road, but it’s not the same cars every time. Despite not being the same cars, it’s the same pattern, and this generalisation is the foundation of our expectation that, around 4 PM, you’ll find a long line of cars, but not specific cars, on Lake Road.
These general patterns are conclusions to what we call inductive arguments. An inductive argument is a non-deductive argument whose reasons to think a conclusion is true are uninterrupted series of similar events. A year ago, I rode my bike and I noticed my mood improved. The next time I rode my bike, my mood improved again. And again. And again. And so on without exception. These instances are reasons to think that riding my bike improves my mood.
At the same time, this conclusion is a reason to think that, next time I ride my bike, my mood will improve. All of this is to say: patterns can operate as both conclusions and as reasons to think, depending on circumstances. But we must be careful how we express the pattern and the conditions that lead to our belief that the pattern will hold, uninterrupted, into the future.
Unmet expectations signal either unreasonable standards, or failed actions. When we investigate unmet expectations, we must determine first whether our standards (or characterisation of the circumstances) were reasonable. If they were reasonable, then we determine how a failure came about. Otherwise, we need to revisit our expectations.
For example, there was a day when I rode my bicycle to the supermarket and my mood didn’t improve. There was heavy traffic and rain that day. This suggests that the characterisation of my expectation in the first example was not sufficiently nuanced or accurate to be used as a reason to think some prediction would come to pass. It never occurred to me that sunny days made a difference until I rode on a not-sunny day.
Context and contrasts do much of the work in explanations, and so we must be cautious about our sensitivity to appropriate level of detail and accuracy.