How do you know?

We live in an age that craves precision and proposes to measure information scientifically. Yet, it is precisely in an environment dominated by junk information that it is most appropriate to ask: how do I know what I think I know?

We’re born with instinct and quickly develop an ingrained trust of our senses and other faculties. We naturally believe that reality is what our eyes show us. For, how can we know how to act in a given situation unless it’s clear what the situation is? Yet, reality is not naturally clear. We see things a definite way because ambiguous perception would be useless, leaving one confused, wavering in doubt. We trust our feelings because they provide an instant assessment and ready-made behavior, especially when delay could be fatal. But precisely because they are hasty and automatic, perception, instinct, and feeling can be wrong. Fortunately we have reason as well. But how reliable is it?

One likes to think that logical reasoning leads to truth. That is because the truths of logic are independent of particular facts, which are always subject to error. However, the sure steps of logical reasoning are merely stepping stones from presumed facts to action. They are only reliable if we know where to step in the first place. To arrive with certainty, you have to begin with certainty. Much of our reasoning is now done for us by computers, which are logic machines. But like us, their output is only as reliable as their input.

Logic forces the issue of certainty, because it is based on language rather than on reality. Logical propositions are statements defined to be either true or false. By formulating propositions, reason misleads us to believe that we can know things to be clearly one way or another. We are even trained in school to answer “true or false” questions on examinations. But only statements are true or false, not reality itself. It may seem evident, in a given time and place, that the statement “it is raining” is either true or false. But when you step outdoors and feel a single, barely discernible tingle of cool moisture on the skin of your face, is it then raining or not? The question may only matter if you are trying to decide whether to take your umbrella or even whether to go out at all. And that is the crux of the matter: the point of certainty is to decide, to know what to do next.

We are all familiar with the maddening limitations of public surveys, which ask us to rate our degree of accord with various propositions. In effect, these are “multiple choice” questions, also familiar from school days. Expanding the number of categories beyond the true/false dichotomy may seem like an improvement, but in fact all categories are arbitrary divisions. In the case of surveys our replies are used by others to make decisions that matter to them. Perhaps such information is reliable to the extent that people actually behave in ways that correspond to how they answer. But, haven’t you felt that the questions are misleading in the first place, and wished you could give more nuanced answers? In some ways, the public survey is an apt metaphor for our own internal thought processes. We query ourselves in order to decide some issue that could require action. How we reason, the questions we pose, the options we imagine, and the sort of answers we expect are shaped by language—our self-talk. We tend to think in words, which means in propositions and categories.

The digital age reflects this inborn propositional thinking. The essence of digital processing is ‘yes’ or ‘no’, ‘either/or’. In logic this is formally known as the law of excluded middle: there is no ground between true and false. But true and false are artificially sharp categories designed to generate the certainty upon which to act decisively. In many cases this works and serves us well. Even if we cannot predict the weather perfectly, we send spacecraft millions of miles to rendezvous precisely with a location as elusive as the proverbial needle in a haystack. The mathematics based on the law of excluded middle, and digital computers in particular, enable us to do this because the truths of mathematics, as of logic, are certain by definition. Yet, no plan or theory ever corresponds perfectly to reality, which is always more nuanced and may include unforeseeable surprises. Calculations are no more accurate than the data on which they are based. If you start with a false assumption, only by sheer luck can you arrive at a true conclusion.

Probability, statistics, and “fuzzy” logic have developed to compensate for the limitations of conventional reasoning as it applies to the naturally ambiguous real world. The probability that it will rain in the next minute refers in a fundamental way to similar situations in the past, of which a record has been kept. If it rained in 60 out of 100 past situations where similar conditions prevailed, then it is fair to claim there is a “60% chance” that it is about to rain now. Yet, even statistics deals with definable events, which are presumed either to have happened or not. (Was it indeed raining in each of those 60 cases? On what criterion was that decided?) And any logic, even fuzzy, depends on concepts, operations and conditions that are clearly defined to begin with. Thought aims toward clarity, but also presupposes it.

The truth is that truth is not a property of reality, but of statements or thoughts. Certainty is a state of mind, not a state of the world. We hope to feel certain, especially when we need to act, because being wrong (or failing to act) can have dire consequences for which we loathe to be responsible. Yet, however certain we feel, mistakes with dire consequences are possible. Sometimes (but not always, of course) it is better to do nothing than to act prematurely. In some situations, especially when time allows, it is wise to doubt what the situation actually is, because the reality is never as clear and simple as human accounts of it. There is room for a middle ground between true and false, which are categories that unrealistically presuppose well-defined situations. Yet, navigating the no-man’s-land between true and false is psychologically challenging—perhaps especially for action-oriented men. Remaining in doubt goes against the fundamental instinct to be decisive and ready to act. Not acting in that instance requires a different sort of action: to take the stance of unknowing.

As a septuagenarian male, I like to think I know my way around. While I generally trust my mind and my perceptions, I’ve also learned to know better. Experience has demonstrated that I can be wrong, and I sometimes find myself misjudging situations. I consider myself lucky when these errors are revealed before they are compounded by further action. I do not envy people in positions of responsibility who must make weighty decisions, which are unavoidably based on imperfect information. My own errors of judgment usually involve false assumptions. These may be based on poor information (for example, rumor), but the underlying problem is that I can trust my judgment inappropriately. And sometimes that is because I haven’t sufficiently questioned my own motivations, which underlie how I perceive the situation.

This is where the stance of unknowing comes in. It insists on taking time to self-examine and to question appearances. I have to remind myself that I may be making assumptions that are unjustified or that I am not even aware of making. I need to clearly understand and acknowledge my emotional stake in the situation. I have to ask myself how I know what I think I know. I may still be required to act, to come to a decision. But honoring the place of doubt may result in a better decision. In most cases, little is lost but time and a spurious sense of certainty. Henry Ford observed that time wasted is forever lost. But time lost is not necessarily wasted. Ford was a headstrong man whose self-confidence led to great success in early life. The same certainty led to regret in later life.