What follows will be a bit out of the ordinary—OK, a lot out of the ordinary—for regular readers of Adam Smith, Esq., but there’s a cold, hard, important, gem of truth in it for lawyers, our firms, and our bedrock assumptions about the way things ought to work (which is precisely the same way they’ve always worked).
Adam Gopnik, a gifted, prolific, and curious writer (The New Yorker, among other places) chooses from a broad and catholic selection of topics, but in A Point of View: Science, magic, and madness (BBC News Magazine), he wrote a few weeks ago about the large epistemological question of how people know what they think they know. Reeling us right in, he began:
When you write for a living, over time you learn that certain subjects will get set responses. You’re resigned to getting the responses before you write the story.
If you write something about Shakespeare, you will get many letters and emails from what we call the cracked (and I think you call the barking), explaining that Shakespeare didn’t write the plays that everyone who was alive when he was, said he had.
If you write something about the scandal of American prisons, you will be sent letters, many heartbreaking, from those wrongly imprisoned – and you will also get many letters from those who you’re pretty sure couldn’t possibly be more rightfully imprisoned. Sorting out what to say to each kind is a big job. (My wife has a simple rule – be nice to the ones who are going to be getting out).
The oddest response, though, is if you write making an obvious point about an historical period or historical figure, you will get lots of letters and emails insisting that the obvious thing about the guy or his time is completely wrong.
If you write about Botticelli as a painter of the Italian Renaissance, you’ll be told sapiently that there was never really a renaissance in Italy for him to paint in. If you write about Abraham Lincoln and emancipation, you’ll be bombarded, on a Fort Sumter scale, with people telling you that the American Civil War wasn’t really fought over slavery. The Spanish Inquisition was a benevolent, fact-checking organisation, Edmund Burke was no conservative… On and on it goes.
Now these letters and emails come more often from the half-bright, some of them professional academics, than from the fully bonkers or barking.
You can tell the half-bright from the barking because the barking don’t know how little they know, while the half-bright know enough to think that they know a lot, but don’t know enough to know what part of what they know is actually worth knowing.
Thus we are brought to Galileo, who was by no means always right about the universe (he was often wrong, notes Gopnik), but Galileo believed in trying to verify his beliefs in the real world by finding out what would happen if he were wrong.
The key thing about experiments is that good ones almost always take thought and effort. Firstly, we have to establish our hypothesis in a form that is amenable to experimentation. If we think of our school-boy version of Galileo at Pisa, this may seem simple, but if even that were so simple, why did it take so long to happen in a form that could be analyzed? Then we have to undertake a step that is much harder than it seems: we need to determine what will count as an answer to the question. Then we need to work out how we will measure the outcomes, including whether we think this is a strictly deterministic system, or (surely, more likely) whtether the experiment will be present a range of outcomes. This has deep implications for experimental design, such as the need for replication and selecting methods for analyzing results. Finally, we assemble the plan for the experiment. And almost always we find that the first experimental approach did not go as well as we would really have liked, so we probably will need to tinker with our design a bit.
Does that mean it is all too hard? Not at all. As many people have pointed out, the greatest improvement in understanding comes with the first increment of new information. Provided of course that the information is well posed with respect to the decision you need to make. In physical science and engineering, we believe strongly in experimentation as a basis for generating knowledge. We also believe, as my Dad had it: measure twice and cut once when it comes to designing and executing experiments.
Mark