How do you know what’s true? I mean this in the most prosaic way you can imagine. As in, how do you know which conditions about the “real” world should inform your decisions? Your answer to this question will have a big impact on your life.
Imagine you’re walking in the dark and hit a wall. The pain you feel is a good sign that the wall is “true.” It’s unarguably there; you just ran into it. The bump proves it. There’s a baseline here: what your senses are reporting back to you. The pain is information. If you have any wits, you’ll avoid doing that again.
Not everything is as obviously true. Let’s take another example. Say you’re trying to manage your weight, so you step onto your bathroom scale. The number you read on the scale’s display, too, is information. By itself, it’s less obviously meaningful than the pain you feel from the wall. To begin with, it’s more abstract than the bump. To make sense of the number, you must know what it is and what it means. Is it higher or lower than “normal”? Well, that requires that you know what “normal” is. If this is the first time weighing yourself, you may not have anything to compare it to. So you may have data, but not necessarily information.
But let’s assume this is not the first time you weigh yourself. Imagine today’s number is higher than yesterday’s. The most obvious explanation for this is that today you’re actually heavier than yesterday. But that’s not the only viable explanation. For example, it could be that the scale is broken, or that today you’ve forgotten to take off your clothes. Whatever the case, the information you’re getting from the scale is less immediate — and thus, less trustworthy — than the one you got from the wall. You can be pretty sure that today you’re heavier, but you’re not 100% sure.
Both the scale and the wall provide you information about the world. The wall does so directly, while the scale does so indirectly. Both give you feedback. Hitting a wall is a good indication that your current trajectory is unsustainable. Seeing a higher number on the scale is pretty good feedback that you may be consuming more energy than you’re putting out. But it’s not as solid as the wall. Some doubt creeps in.
Now imagine that the scale doesn’t have a display; you step on it and get no immediate feedback at all. Instead, you receive a text message a few weeks from now with a reading of your weight. This reading is as true as the one you’d get if the scale had a display, but you’d probably be less likely to act on it. For one thing, time has passed between the time you took the reading and when you received the message. For another, there are more intermediaries between the measuring and the reporting of the information. Many things could’ve intruded in the reading. Were you wearing anything on that morning? Was that the day where you had that big dinner? Did you even weigh yourself then? What if the system mixed up your numbers with somebody else’s?
Now let’s complicate things further. Imagine that the system can’t measure your weight as an individual; it only measures the weight of the entire population of humans. (Ok, it’s starting to get silly — please bear with me.) This would make it very difficult for you to confidently state that that double bacon cheeseburger you ate two days ago had any impact on your weight.
There are now many layers of abstraction between the measuring and the reporting. Many things could’ve intruded between the moment the measurement was taken and when the result was reported back to you. What if the scale is broken? What if the databases that collect the data are broken? What if the algorithms that compute the results are flawed? What if the change the system is detecting is due to your neighbors’ overindulgence? What if the people who are managing the data have an agenda? Also, inevitably reporting at such scales will happen in very long cycles; you probably won’t see the impact of the cheeseburger (if at all) until many weeks or months from now, if at all.
Now imagine that you’re not getting the results back directly from the system that tracks them. Instead, you’re learning about the weight of the population not from the entity that is managing the weight-measurement system, but through indirect channels devoted to reporting on information about all sorts of other things. This is yet another layer of abstraction. (Remember: with each layer that stands between you and acquisition of the facts, the less confident you can be of the truth and relevance of the information.)
But wait, it gets worse. What if these indirect feedback mechanisms are financed by showing you information meant to persuade you to act in one way or another, alongside the information you actually need? For example, you could see an article that suggests you should eat more cheeseburgers alongside one reporting on the population’s creeping weight, with the former being the one that funds the operation. In some cases, these paid-for content items would be almost indistinguishable in form and tone from the ones meant to inform you about the state of the world. At this point, your confidence in the truth would probably be quite low.
The more layers of abstraction there are between the moment of measurement and the moment you learn about them, the less you trust the information. The more distant it is from you as an individual — both in scale and in layers of abstraction from the point of measurement — the less you trust the information. These factors add up to erode your confidence.
Getting your information in an environment designed to persuade you, and with no first-, second-, or even third-hand access to the facts, you leave the door open for all sorts of theories that attempt to explain away what the systems are reporting back to you. If you have a taste for cheeseburgers, you’ll justify them to yourself more easily. You’ll go on enjoying them indiscriminately — perhaps even ramping up your habit — right up until the massive heart attack kills you.
Ultimately it’s up to you to ascertain that you have a good “read” on what is true. (That is: one that helps you make good predictions about possible outcomes.) This sometimes requires that you be wary of the means by which you acquire information. But you should also be wary if you catch yourself explaining away what you’re hearing and seeing and feeling for ideological reasons. Reality doesn’t much care about your beliefs or how you came about them. At some point, you will hit a wall — a metaphorical one, in any case.
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