not go after tenured faculty (except perhaps because many libertarians are
academics). We saw that companies can go bust, while governments remain.
But while governments remain, civil servants can be demoted and
congressmen and senators can be eventually voted out of office. In academia
a tenured faculty is permanent—the business of knowledge has permanent
"owners." Simply, the charlatan is more the product of control
than the result of freedom and lack of structure.
Prediction and Free Will
If you know all possible conditions of a physical system you can, in theory
(though not, as we saw, in practice), project its behavior into the future.
But this only concerns inanimate objects. We hit a stumbling block when
social matters are involved. It is another matter to project a future when
humans are involved, if you consider them living beings and endowed
with free will.
If I can predict all of your actions, under given circumstances, then you
may not be as free as you think you are. You are an automaton responding
to environmental stimuli. You are a slave of destiny. And the illusion
of free will could be reduced to an equation that describes the result of interactions
among molecules. It would be like studying the mechanics of a
1 8 4 WE J U S T C A N ' T PREDICT
clock: a genius with extensive knowledge of the initial conditions and the
causal chains would be able to extend his knowledge to the future of your
actions. Wouldn't that be stifling?
However, if you believe in free will you can't truly believe in social science
and economic projection. You cannot predict how people will act.
Except, of course, if there is a trick, and that trick is the cord on which
neoclassical economics is suspended. You simply assume that individuals
will be rational in the future and thus act predictably. There is a strong
link between rationality, predictability, and mathematical tractability. A
rational individual will perform a unique set of actions in specified circumstances.
There is one and only one answer to the question of how "rational"
people satisfying their best interests would act. Rational actors must
be coherent: they cannot prefer apples to oranges, oranges to pears, then
pears to apples. If they did, then it would be difficult to generalize their behavior.
It would also be difficult to project their behavior in time.
In orthodox economics, rationality became a straitjacket. Platonified
economists ignored the fact that people might prefer to do something
other than maximize their economic interests. This led to mathematical
techniques such as "maximization," or "optimization," on which Paul
Samuelson built much of his work. Optimization consists in finding the
mathematically optimal policy that an economic agent could pursue. For
instance, what is the "optimal" quantity you should allocate to stocks? It
involves complicated mathematics and thus raises a barrier to entry by nonmathematically
trained scholars. I would not be the first to say that this
optimization set back social science by reducing it from the intellectual
and reflective discipline that it was becoming to an attempt at an "exact
science." By "exact science," I mean a second-rate engineering problem
for those who want to pretend that they are in the physics department—
so-called physics envy. In other words, an intellectual fraud.
Optimization is a case of sterile modeling that we will discuss further
in Chapter 17. It had no practical (or even theoretical) use, and so it became
principally a competition for academic positions, a way to make
people compete with mathematical muscle. It kept Platonified economists
out of the bars, solving equations at night. The tragedy is that Paul
Samuelson, a quick mind, is said to be one of the most intelligent scholars
of his generation. This was clearly a case of very badly invested intelligence.
Characteristically, Samuelson intimidated those who questioned his
techniques with the statement "Those who can, do science, others do
methodology." If you knew math, you could "do science." This is reminisHOW
TO LOOK FOR B I R D POOP 1 85
cent of psychoanalysts who silence their critics by accusing them of having
trouble with their fathers. Alas, it turns out that it was Samuelson and
most of his followers who did not know much math, or did not know how
to use what math they knew, how to apply it to reality. They only knew
enough math to be blinded by it.
Tragically, before the proliferation of empirically blind idiot savants,
interesting work had been begun by true thinkers, the likes of J . M.
Keynes, Friedrich Hayek, and the great Beno?t Mandelbrot, all of whom
were displaced because they moved economics away from the precision of
second-rate physics. Very sad. One great underestimated thinker is G.L.S.
Shackle, now almost completely obscure, who introduced the notion of
"unknowledge," that is, the unread books in Umberto Eco's library. It is
unusual to see Shackle's work mentioned at all, and I had to buy his books
from secondhand dealers in London.
Legions of empirical psychologists of the heuristics and biases school
have shown that the model of rational behavior under uncertainty is not
just grossly inaccurate but plain wrong as a description of reality. Their results
also bother Platonified economists because they reveal that there are
several ways to be irrational. Tolstoy said that happy families were all
alike,, while each unhappy one is unhappy in its own way. People have been
shown to make errors equivalent to preferring apples to oranges, oranges
to pears, and pears to apples, depending on how the relevant questions are
presented to them. The sequence matters! Also, as we have seen with the
anchoring example, subjects' estimates of the number of dentists in Manhattan
are influenced by which random number they have just been presented
with—the anchor. Given the randomness of the anchor, we will
have randomness in the estimates. So if people make inconsistent choices
and decisions, the central core of economic optimization fails. You can no
longer produce a "general theory," and without one you cannot predict.
You have to learn to live without a general theory, for Pluto's sake!
THE GRUENESS OF EMERALD
Recall the turkey problem. You look at the past and derive some rule
about the future. Well, the problems in projecting from the past can be
even worse than what we have already learned, because the same past data
can confirm a theory and also its exact opposite! If you survive until tomorrow,
it could mean that either a) you are more likely to be immortal or
b) that you are closer to death. Both conclusions rely on the exact same
1 8 6 WE J U S T C A N ' T P R E D I CT
FIGURE 3
2.4 ; i * ? ? j
O 2.2 - ?
< 2 ?
Q- ?
O 1.8 :
1.6 ; ?
?
1.4
5 10 15 20
Y E A R S
A series of a seemingly growing bacterial population (or of sales records, or of
any variable observed through time—such as the total feeding of the turkey in
Chapter 4).
FIGURE 4
10 20 30 40 50 60
Y E A R S
Easy to fit the trend—there is one and only one linear model that fits the data. You
can project a continuation into the future
HOW TO LOOK FOR B I R D POOP 1 87
FIGURE 5
Y E A R S
We look at a broader scale. Hey, other models also fit it rather well.
FIGURE 6
z
O
2.5
<
= 2 ! ?
a.
O
Q. ? ...
?
1.5 ;
50 100 150 200
Y E A R S
And the real "generating process" is extremely simple but it had nothing to do with
a linear model! Some parts of it appear to be linear and we are fooled by extrapolating
in a direct line.*
These graphs also illustrate a statistical version of the narrative fallacy—you find a model that fits
the past. "Linear regression" or "R-square" can ultimately fool you beyond measure, to the point
where it is no longer funny. You can fit the linear part of the curve and claim a high R-square,
meaning that your model fits the data very well and has high predictive powers. All that off hot air:
you only fit the linear segment of the series. Always remember that "R-square" is unfit for Extremistan;
it is only good for academic promotion.
1 8 8 WE J U S T C A N ' T P R E D I CT
data. If you are a turkey being fed for a long period of time, you can either
naively assume that feeding confirms your safety or be shrewd and consider
that it confirms the danger of being turned into supper. An acquaintance's
unctuous past behavior may indicate his genuine affection for me
and his concern for my welfare; it may also confirm his mercenary and calculating
desire to get my business one day.
So not only can the past be misleading, but there are also many degrees
of freedom in our interpretation of past events.
For the technical version of this idea, consider a series of dots on a
page representing a number through time—the graph would resemble Figure
1 showing the first thousand days in Chapter 4. Let's say your high
school teacher asks you to extend the series of dots. With a linear model,
that is, using a ruler, you can run only a straight line, a single straight line
from the past to the future. The linear model is unique. There is one and
only one straight line that can project from a series of points. But it can get
trickier. If you do not limit yourself to a straight line, you find that there is
a huge family of curves that can do the job of connecting the dots. If you
project from the past in a linear way, you continue a trend. But possible
future deviations from the course of the past are infinite.
This is what the philosopher Nelson Goodman called the riddle of induction:
We project a straight line only because we have a linear model in
our head—the fact that a number has risen for 1,000 days straight should
make you more confident that it will rise in the future. But if you have a
nonlinear model in your head, it might confirm that the number should
decline on day 1,001.
Let's say that you observe an emerald. It was green yesterday and the
day before yesterday. It is green again today. Normally this would confirm
the "green" property: we can assume that the emerald will be green tomorrow.
But to Goodman, the emerald's color history could equally confirm
the "grue" property. What is this grue property? The emerald's grue
property is to be green until some specified date, say, December 3 1 , 2006,
and then blue thereafter.
The riddle of induction is another version of the narrative fallacy—you
face an infinity of "stories" that explain what you have seen. The severity
of Goodman's riddle of induction is as follows: if there is no longer even a
single unique way to "generalize" from what you see, to make an inference
about the unknown, then how should you operate? The answer, clearly,
will be that you should employ "common sense," but your common sense
may not be so well developed with respect to some Extremistan variables.
HOW TO LOOK FOR B I R D POOP 1 8 9
THAT GREAT ANTICIPATION MACHINE
The reader is entitled to wonder, So, NNT, why on earth do we plan?
Some people do it for monetary gain, others because it's "their job." But
we also do it without such intentions—spontaneously.
Why? The answer has to do with human nature. Planning may come
with the package of what makes us human, namely, our consciousness.
There is supposed to be an evolutionary dimension to our need to project
matters into the future, which I will rapidly summarize here, since it
can be an excellent candidate explanation, an excellent conjecture, though,
since it is linked to evolution, I would be cautious.
The idea, as promoted by the philosopher Daniel Dennett, is as follows:
What is the most potent use of our brain? It is precisely the ability
to project conjectures into the future and play the counterfactual game—
"If I punch him in the nose, then he will punch me back right away, or,
worse, call his lawyer in New York." One of the advantages of doing so is
that we can let our conjectures die in our stead. Used correctly and in place
of more visceral reactions, the ability to project effectively frees us from
immediate, first-order natural selection—as opposed to more primitive organisms
that were vulnerable to death and only grew by the improvement
in the gene pool through the selection of the best. In a way, projecting allows
us to cheat evolution: it now takes place in our head, as a series of
projections and counterf actual scenarios.
This ability to mentally play with conjectures, even if it frees us from
the laws of evolution, is itself supposed to be the product of evolution—it
is as if evolution has put us on a long leash whereas other animals live on
the very short leash of immediate dependence on their environment. For
Dennett, our brains are "anticipation machines"; for him the human mind
and consciousness are emerging properties, those properties necessary for
our accelerated development.
Why do we listen to experts and their forecasts? A candidate explanation
is that society reposes on specialization, effectively the division of
knowledge. You do not go to medical school the minute you encounter a
big health problem; it is less taxing (and certainly safer) for you to consult
someone who has already done so. Doctors listen to car mechanics (not
for health matters, just when it comes to problems with their cars); car mechanics
listen to doctors. We have a natural tendency to listen to the expert,
even in fields where there may be no experts.
Chapter Twelve
EPISTEMOCRACY, A DREAM
This is only an essay—Children and philosophers vs. adults and
nonphilosophers—Science as an autistic enterprise—The past too has a
past—Mispredict and live a long, happy life (if you survive)
Someone with a low degree of epistemic arrogance is not too visible, like
a shy person at a cocktail party. We are not predisposed to respect humble
