2. Paul F. Lazarsfeld, “The American Solidier—An Expository Review,” Public Opinion Quarterly 13, no. 3 (1949): 377–404.
3. Daphna Baratz, How Justified Is the “Obvious” Reaction? (Stanford University, 1983).
Part D
Mysterious Answers
30
Fake Explanations
Once upon a time, there was an instructor who taught physics students. One day the instructor called them into the classroom and showed them a wide, square plate of metal, next to a hot radiator. The students each put their hand on the plate and found the side next to the radiator cool, and the distant side warm. And the instructor said, Why do you think this happens? Some students guessed convection of air currents, and others guessed strange metals in the plate. They devised many creative explanations, none stooping so low as to say “I don’t know” or “This seems impossible.”
And the answer was that before the students entered the room, the instructor turned the plate around.1
Consider the student who frantically stammers, “Eh, maybe because of the heat conduction and so?” I ask: Is this answer a proper belief? The words are easily enough professed—said in a loud, emphatic voice. But do the words actually control anticipation?
Ponder that innocent little phrase, “because of,” which comes before “heat conduction.” Ponder some of the other things we could put after it. We could say, for example, “Because of phlogiston,” or “Because of magic.”
“Magic!” you cry. “That’s not a scientific explanation!” Indeed, the phrases “because of heat conduction” and “because of magic” are readily recognized as belonging to different literary genres. “Heat conduction” is something that Spock might say on Star Trek, whereas “magic” would be said by Giles in Buffy the Vampire Slayer.
However, as Bayesians, we take no notice of literary genres. For us, the substance of a model is the control it exerts on anticipation. If you say “heat conduction,” what experience does that lead you to anticipate? Under normal circumstances, it leads you to anticipate that, if you put your hand on the side of the plate near the radiator, that side will feel warmer than the opposite side. If “because of heat conduction” can also explain the radiator-adjacent side feeling cooler, then it can explain pretty much anything.
And as we all know by this point (I do hope), if you are equally good at explaining any outcome, you have zero knowledge. “Because of heat conduction,” used in such fashion, is a disguised hypothesis of maximum entropy. It is anticipation-isomorphic to saying “magic.” It feels like an explanation, but it’s not.
Suppose that instead of guessing, we measured the heat of the metal plate at various points and various times. Seeing a metal plate next to the radiator, we would ordinarily expect the point temperatures to satisfy an equilibrium of the diffusion equation with respect to the boundary conditions imposed by the environment. You might not know the exact temperature of the first point measured, but after measuring the first points—I’m not physicist enough to know how many would be required—you could take an excellent guess at the rest.
A true master of the art of using numbers to constrain the anticipation of material phenomena—a “physicist”—would take some measurements and say, “This plate was in equilibrium with the environment two and a half minutes ago, turned around, and is now approaching equilibrium again.”
The deeper error of the students is not simply that they failed to constrain anticipation. Their deeper error is that they thought they were doing physics. They said the phrase “because of,” followed by the sort of words Spock might say on Star Trek, and thought they thereby entered the magisterium of science.
Not so. They simply moved their magic from one literary genre to another.
*
1. Search for “heat conduction.” Taken from Joachim Verhagen, http://web.archive.org/web/20060424082937/http://www.nvon.nl/scheik/best/diversen/scijokes/scijokes.txt, archived version, October 27, 2001.
31
Guessing the Teacher’s Password
When I was young, I read popular physics books such as Richard Feynman’s QED: The Strange Theory of Light and Matter. I knew that light was waves, sound was waves, matter was waves. I took pride in my scientific literacy, when I was nine years old.
When I was older, and I began to read the Feynman Lectures on Physics, I ran across a gem called “the wave equation.” I could follow the equation’s derivation, but, looking back, I couldn’t see its truth at a glance. So I thought about the wave equation for three days, on and off, until I saw that it was embarrassingly obvious. And when I finally understood, I realized that the whole time I had accepted the honest assurance of physicists that light was waves, sound was waves, matter was waves, I had not had the vaguest idea of what the word “wave” meant to a physicist.
There is an instinctive tendency to think that if a physicist says “light is made of waves,” and the teacher says “What is light made of?,” and the student says “Waves!,” then the student has made a true statement. That’s only fair, right? We accept “waves” as a correct answer from the physicist; wouldn’t it be unfair to reject it from the student? Surely, the answer “Waves!” is either true or false, right?
Which is one more bad habit to unlearn from school. Words do not have intrinsic definitions. If I hear the syllables “bea-ver” and think of a large rodent, that is a fact about my own state of mind, not a fact about the syllables “bea-ver.” The sequence of syllables “made of waves” (or “because of heat conduction”) is not a hypothesis, it is a pattern of vibrations traveling through the air, or ink on paper. It can associate to a hypothesis in someone’s mind, but it is not, of itself, right or wrong. But in school, the teacher hands you a gold star for saying “made of waves,” which must be the correct answer because the teacher heard a physicist emit the same sound-vibrations. Since verbal behavior (spoken or written) is what gets the gold star, students begin to think that verbal behavior has a truth-value. After all, either light is made of waves, or it isn’t, right?
And this leads into an even worse habit. Suppose the teacher presents you with a confusing problem involving a metal plate next to a radiator; the far side feels warmer than the side next to the radiator. The teacher asks “Why?” If you say “I don’t know,” you have no chance of getting a gold star—it won’t even count as class participation. But, during the current semester, this teacher has used the phrases “because of heat convection,” “because of heat conduction,” and “because of radiant heat.” One of these is probably what the teacher wants. You say, “Eh, maybe because of heat conduction?”
This is not a hypothesis about the metal plate. This is not even a proper belief. It is an attempt to guess the teacher’s password.
Even visualizing the symbols of the diffusion equation (the math governing heat conduction) doesn’t mean you’ve formed a hypothesis about the metal plate. This is not school; we are not testing your memory to see if you can write down the diffusion equation. This is Bayescraft; we are scoring your anticipations of experience. If you use the diffusion equation, by measuring a few points with a thermometer and then trying to predict what the thermometer will say on the next measurement, then it is definitely connected to experience. Even if the student just visualizes something flowing, and therefore holds a match near the cooler side of the plate to try to measure where the heat goes, then this mental image of flowing-ness connects to experience; it controls anticipation.
If you aren’t using the diffusion equation—putting in numbers and getting out results that control your anticipation of particular experiences—then the connection between map and territory is severed as though by a knife. What remains is not a belief, but a verbal behavior.
In the school system, it’s all about verbal behavior, whether written on paper or spoken aloud. Verbal behavior gets you a gold star or a failing grade. Part of unlearning this bad habit is becoming consciously aware of the difference between an explanation and a password.
&n
bsp; Does this seem too harsh? When you’re faced by a confusing metal plate, can’t “heat conduction?” be a first step toward finding the answer? Maybe, but only if you don’t fall into the trap of thinking that you are looking for a password. What if there is no teacher to tell you that you failed? Then you may think that “Light is wakalixes” is a good explanation, that “wakalixes” is the correct password. It happened to me when I was nine years old—not because I was stupid, but because this is what happens by default. This is how human beings think, unless they are trained not to fall into the trap. Humanity stayed stuck in holes like this for thousands of years.
Maybe, if we drill students that words don’t count, only anticipation-controllers, the student will not get stuck on “heat conduction? No? Maybe heat convection? That’s not it either?” Maybe then, thinking the phrase “heat conduction” will lead onto a genuinely helpful path, like:
“Heat conduction?”
But that’s only a phrase—what does it mean?
The diffusion equation?
But those are only symbols—how do I apply them?
What does applying the diffusion equation lead me to anticipate?
It sure doesn’t lead me to anticipate that the side of a metal plate farther away from a radiator would feel warmer.
I notice that I am confused. Maybe the near side just feels cooler, because it’s made of more insulative material and transfers less heat to my hand? I’ll try measuring the temperature . . .
Okay, that wasn’t it. Can I try to verify whether the diffusion equation holds true of this metal plate, at all? Is heat flowing the way it usually does, or is something else going on?
I could hold a match to the plate and try to measure how heat spreads over time . . .
If we are not strict about “Eh, maybe because of heat conduction?” being a fake explanation, the student will very probably get stuck on some wakalixes-password. This happens by default: it happened to the whole human species for thousands of years.
*
32
Science as Attire
The preview for the X-Men movie has a voice-over saying: “In every human being . . . there is the genetic code . . . for mutation.” Apparently you can acquire all sorts of neat abilities by mutation. The mutant Storm, for example, has the ability to throw lightning bolts.
I beg you, dear reader, to consider the biological machinery necessary to generate electricity; the biological adaptations necessary to avoid being harmed by electricity; and the cognitive circuitry required for finely tuned control of lightning bolts. If we actually observed any organism acquiring these abilities in one generation, as the result of mutation, it would outright falsify the neo-Darwinian model of natural selection. It would be worse than finding rabbit fossils in the pre-Cambrian. If evolutionary theory could actually stretch to cover Storm, it would be able to explain anything, and we all know what that would imply.
The X-Men comics use terms like “evolution,” “mutation,” and “genetic code,” purely to place themselves in what they conceive to be the literary genre of science. The part that scares me is wondering how many people, especially in the media, understand science only as a literary genre.
I encounter people who very definitely believe in evolution, who sneer at the folly of creationists. And yet they have no idea of what the theory of evolutionary biology permits and prohibits. They’ll talk about “the next step in the evolution of humanity,” as if natural selection got here by following a plan. Or even worse, they’ll talk about something completely outside the domain of evolutionary biology, like an improved design for computer chips, or corporations splitting, or humans uploading themselves into computers, and they’ll call that “evolution.” If evolutionary biology could cover that, it could cover anything.
Probably an actual majority of the people who believe in evolution use the phrase “because of evolution” because they want to be part of the scientific in-crowd—belief as scientific attire, like wearing a lab coat. If the scientific in-crowd instead used the phrase “because of intelligent design,” they would just as cheerfully use that instead—it would make no difference to their anticipation-controllers. Saying “because of evolution” instead of “because of intelligent design” does not, for them, prohibit Storm. Its only purpose, for them, is to identify with a tribe.
I encounter people who are quite willing to entertain the notion of dumber-than-human Artificial Intelligence, or even mildly smarter-than-human Artificial Intelligence. Introduce the notion of strongly superhuman Artificial Intelligence, and they’ll suddenly decide it’s “pseudoscience.” It’s not that they think they have a theory of intelligence which lets them calculate a theoretical upper bound on the power of an optimization process. Rather, they associate strongly superhuman AI to the literary genre of apocalyptic literature; whereas an AI running a small corporation associates to the literary genre of Wired magazine. They aren’t speaking from within a model of cognition. They don’t realize they need a model. They don’t realize that science is about models. Their devastating critiques consist purely of comparisons to apocalyptic literature, rather than, say, known laws which prohibit such an outcome. They understand science only as a literary genre, or in-group to belong to. The attire doesn’t look to them like a lab coat; this isn’t the football team they’re cheering for.
Is there any idea in science that you are proud of believing, though you do not use the belief professionally? You had best ask yourself which future experiences your belief prohibits from happening to you. That is the sum of what you have assimilated and made a true part of yourself. Anything else is probably passwords or attire.
*
33
Fake Causality
Phlogiston was the eighteenth century’s answer to the Elemental Fire of the Greek alchemists. Ignite wood, and let it burn. What is the orangey-bright “fire” stuff? Why does the wood transform into ash? To both questions, the eighteenth-century chemists answered, “phlogiston.”
. . . and that was it, you see, that was their answer: “Phlogiston.”
Phlogiston escaped from burning substances as visible fire. As the phlogiston escaped, the burning substances lost phlogiston and so became ash, the “true material.” Flames in enclosed containers went out because the air became saturated with phlogiston, and so could not hold any more. Charcoal left little residue upon burning because it was nearly pure phlogiston.
Of course, one didn’t use phlogiston theory to predict the outcome of a chemical transformation. You looked at the result first, then you used phlogiston theory to explain it. It’s not that phlogiston theorists predicted a flame would extinguish in a closed container; rather they lit a flame in a container, watched it go out, and then said, “The air must have become saturated with phlogiston.” You couldn’t even use phlogiston theory to say what you ought not to see; it could explain everything.
This was an earlier age of science. For a long time, no one realized there was a problem. Fake explanations don’t feel fake. That’s what makes them dangerous.
Modern research suggests that humans think about cause and effect using something like the directed acyclic graphs (DAGs) of Bayes nets. Because it rained, the sidewalk is wet; because the sidewalk is wet, it is slippery:
From this we can infer—or, in a Bayes net, rigorously calculate in probabilities—that when the sidewalk is slippery, it probably rained; but if we already know that the sidewalk is wet, learning that the sidewalk is slippery tells us nothing more about whether it rained.
Why is fire hot and bright when it burns?
It feels like an explanation. It’s represented using the same cognitive data format. But the human mind does not automatically detect when a cause has an unconstraining arrow to its effect. Worse, thanks to hindsight bias, it may feel like the cause constrains the effect, when it was merely fitted to the effect.
Interestingly, our modern understanding of probabilistic reasoning about causality can describe precisely
what the phlogiston theorists were doing wrong. One of the primary inspirations for Bayesian networks was noticing the problem of double-counting evidence if inference resonates between an effect and a cause. For example, let’s say that I get a bit of unreliable information that the sidewalk is wet. This should make me think it’s more likely to be raining. But, if it’s more likely to be raining, doesn’t that make it more likely that the sidewalk is wet? And wouldn’t that make it more likely that the sidewalk is slippery? But if the sidewalk is slippery, it’s probably wet; and then I should again raise my probability that it’s raining . . .
Judea Pearl uses the metaphor of an algorithm for counting soldiers in a line.1 Suppose you’re in the line, and you see two soldiers next to you, one in front and one in back. That’s three soldiers, including you. So you ask the soldier behind you, “How many soldiers do you see?” They look around and say, “Three.” So that’s a total of six soldiers. This, obviously, is not how to do it.
A smarter way is to ask the soldier in front of you, “How many soldiers forward of you?” and the soldier in back, “How many soldiers backward of you?” The question “How many soldiers forward?” can be passed on as a message without confusion. If I’m at the front of the line, I pass the message “1 soldier forward,” for myself. The person directly in back of me gets the message “1 soldier forward,” and passes on the message “2 soldiers forward” to the soldier behind them. At the same time, each soldier is also getting the message “N soldiers backward” from the soldier behind them, and passing it on as “N + 1 soldiers backward” to the soldier in front of them. How many soldiers in total? Add the two numbers you receive, plus one for yourself: that is the total number of soldiers in line.
Rationality- From AI to Zombies Page 13