Pragmatic Thinking and Learning
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can construct a wide array of larger struc-
tures. Plato’s ideal forms work in a similar fashion; they are simpli-
fied building blocks of reality. But this approach of reducing real-
ity into an idealized form leaves a hole, called the platonic fold. An
awful lot can hide in this hole, and we get blindsided by these kinds
of unexpected events.
The concept of the platonic fold, described in The Black Swan: The
Impact of the Highly Improbable [Tal07], emphasizes that humans
are really bad at trying to extrapolate future events from previous
events. We assume that events form a more or less stable, linear
progression, with easily defined cause and effect.
They don’t. That’s why we fail to predict the future in so many
cases. In fact, because of our blind spots—including the platonic
fold—it turns out that all consequential events in history come from
the wholly unexpected.
That’s where the book’s titular “black swan”
comes from. For many years, it was assumed that
swans could only be white. Because no one had
ever seen a black swan, its existence was thought
to be impossible by the scientific community—
until a black swan showed up.
As a group, we tend to miss important
developments because we’re focused on Unexpected events
the wrong thing or are asking the wrong change the game.
questions. For example, I was cleaning my
office last year when I stumbled upon a stack of magazines dating
from the early to mid-1990s (I also found a 14.4 modem in the
middle of a tangle of active cables, but that’s another story).
The magazines made a convenient time capsule. Cover after cover
fanned the ferocious debate over the most important issue of the
day: who would win the desktop wars? Would the interface to con-
quer the desktop be based on Open Look or on Motif?
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Correlation vs. Causation
Scientific studies can be easily misinterpreted; most of us
are not well versed in the science of statistical analysis. One
of the most popular misconceptions arises from declaring
a cause and effect when there’s only a correlation.
Just because two variables are correlated does not mean
that either causes the other. For instance, consider reports
of high incidences of leukemia for families living under
power lines. The headline might even report that power
lines cause cancer.
They well might, but this single correlation doesn’t prove
that at all. There are many other possible variables: prop-
erty under power lines is cheaper, so these are poorer fam-
ilies, which may negatively affect diet, health care, early
detection, and so on. Determining causation is a different
beast than observing a correlation.
In addition, causality in the real world isn’t usually as sim-
ple as “event x causes event y.” Instead, it’s common that
x triggers y, which reinforces x, which then strengthens y,
and so on. It’s more a case of “both x and y” rather than
“either x or y.” Events can contribute to the causality in dif-
fering amounts, and they have different reinforcing proper-
ties. Even the same kind of event, observed over time, may
have completely different causes in each instance.
It was the wrong question, as it turned out, and Windows—which
wasn’t even considered one of the contenders—took over. Then
there was the middleware war; who would win? RMI or CORBA?
It was the wrong question again, because the growth of the Web
largely made the issue moot. The Web was a classic black swan,
an unanticipated development that changed the rules of the game
completely. And on it went: pages and pages of analysis and specu-
lation, forecasting and fretting, almost always over the wrong ques-
tion. Our biases make it nearly impossible to predict the future and
very difficult to navigate in the present.
As you can see, just because you “think so” doesn’t make it right.
Recognizing and overcoming your own cognitive bias is surely eas-
ier said than done. But here are a few suggestions that might help.
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“Rarely” Doesn’t Mean “Never”
“Astronomically unlikely coincidences happen daily.”6 Recently,
we’ve witnessed all manner of devastation from 500-year floods to
100-year storms, but geologically speaking that’s just a drop in the
bucket—these events are not that rare. They may freak people out
because they haven’t happened within their memory or the mem-
ory of their parents (or even grandparents). But that doesn’t mean
they can’t happen, and it doesn’t prevent them from happening
three times in a row.
In 2004, your odds of being killed by lightning in the United States
were around 1 in 6,383,844.7 That sounds like pretty good odds,
right? But forty-six people died that year from lightning, despite the
six-million-to-one odds. And you had sixteen times greater odds of
dying from falling out of bed, although that’s probably not some-
thing you’d think of as particularly dangerous. Even though it’s
rare, it still happens. On a more positive note, you can expect to
experience a one-in-a-million miracle about once a month.8
The black swan cautions us not to discount unobserved or rare
phenomena as impossible.
Truly random events form a mix of values that are clumped
together as well as lone values; homogeneity and randomness are
different things. It’s perfectly valid in a completely random sample
to have three Category Five hurricanes in a row, for instance.
TIP 18
Watch the outliers: “rarely” doesn’t mean “never.”
Look into the platonic fold, and think about what you might be
missing. Any one of those minor elements that you overlooked can
be the one that changes history.
Take time to examine the “crazy” out-
liers or those “impossible,” astronomically Never say never.
unlikely events. If any of those actually did
happen, what would it mean to you? What would you do differ-
ently because of it? What concerns wouldn’t matter anymore, and
6.
Michael T. Nygard in Release It!: Design and Deploy Production-Ready Soft-
ware [Nyg07].
7.
According to the National Safety Council, http://nsc.org.
8.
See Littlewood’s Law for the math.
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Figure 5.2: Project knowledge over time
which would become prominent? Remember, these are still unlikely
events, so don’t start stocking up on canned food or Hazmat suits
just yet. But never say never.
Defer Closure
Our need for closure means we are driven to try to eliminate
uncertainty—ready or not. But fixing on a decision prematurely
reduces your options, perhaps to the point of eliminating the suc-
cessful choice.
On a software project, as with an exploratory or inventive project
in any discipline, it’s a given that you’ll learn a little bit more every
day. You’ll learn more about the users, the project itself, your team,
and the technology, as shown in Figure 5.2.
That means you’ll be at your peak of intelligence at the very end of
the project and at your most ignorant at the very beginning. So, do
you want to make decisions early on? No; you want to defer closure
for as long as possible in order to make a better decision later. But
that means critical issues may stay unsettled for a long time, which
makes many people acutely uncomfortable.
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Resist the pressure. Know that you will reach a decision, and the
matter will be settled, just not today.
TIP 19
Be comfortable with uncertainty.
Agile software development embraces the idea of working with
uncertainty. Early on, you don’t know what the project end date
will really be. You’re not 100 percent certain which features will be
present in the next iteration. You don’t know how many iterations
there will be. And that’s perfectly OK: that’s the sort of uncertainty
you want to be comfortable with. You’ll find answers as you go
along, and by the end, everything will have been answered.
You can, of course, take some concrete steps to try to reduce uncer-
tainty. You might talk the matter over with peers, google around
for more information, or build a prototype—that sort of thing. But
although these steps might help a little or a lot, they’re not a cure.
There will always be elements that are just plain uncertain, and
that’s not a bad thing. Chip away at it, but don’t be in a rush to
nail down details if it’s not ready yet. Be comfortable with the fact
you don’t know.
For something you don’t know but that
has to be known by others, such as a go-
Guess with explicit
live date, you can express it as a “target” probabilities.
date along with an indication of your con-
fidence in the estimate. That is, you might report a target date
such as Oct. 1, with a 37 percent chance of making that date. But
be careful when reporting a date with an 80 percent probability.
Folks may tend to hear that as “nearly certain” without appreci-
ating there’s a 20 percent chance it won’t happen. At least you’re
being up front about the inherent uncertainty.
But realize that it can be really, really hard for other folks in
the organization to be comfortable with these ideas. They are
programmed to seek closure at all costs and will try to do so at
every turn. Educate them as best you can, but be prepared for
resistance.
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You Can’t Recall
Finally, remember that you don’t remember very well. Memory is
unreliable, and old memories will change over time, which just
reassures you that your misconceptions and prejudices are valid.
Don’t rely exclusively on your memory. The Chinese proverb is cor-
rect: the palest ink is better than the best memory.
TIP 20
Trust ink over memory; every mental read is a write.
Instead, augment your memory with some kind of reality check.
Whether it’s notes that you keep or a conversation with someone
else with their own memories, you need something to help keep
your memories from drifting too far from reality.
Next Actions
! List the cognitive biases you recognize in yourself. We all have
our favorites. Which ones are you particularly susceptible to?
! Notice how many astronomically unlikely events you have wit-
nessed in your career. How unlikely were they in hindsight?9
! Start and maintain an engineer’s log of notes from design
meetings, coding questions and solutions, and so on. Put a
mark next to older entries any time you have to go back and
use it.
5.2 Recognize Your Generational Affinity
Anything that is in the world when you’re born is normal and
ordinary and is just a natural part of the way the world works.
Anything that’s invented between when you’re fifteen and
thirty-five is new and exciting and revolutionary and you can
probably get a career in it. Anything invented after you’re thirty-five
is against the natural order of things.
Douglas Adams, The Salmon of Doubt
9.
While pondering this, remember that most of the world’s data is now stored on hard drives with a ninety-day limited warranty.
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We’ve looked at cognitive biases so far in a sort of static light. But
of course, nothing is static. The biases you fell for several years
ago are probably different from your current faves. But they might
have a lot in common with your peers along the way, and they
might differ dramatically from folks who are a little older or a little
younger than you are.
As Douglas Adams points out, the biases you form change over
time, and taken as a whole, the biases that drive any particular
generation will be different from the biases that drive you and your
peers.
Some folks value the stability of their job at the expense of any
amount of abuse from their boss. Other folks will pack up and quit
at the slightest perceived offense. Folks who are driven to work all
hours can’t understand the folks who cheerfully pack up at 5 p.m.
and head home to be with their family, and vice versa.
These are more insidious forms of bias than the bugs we’ve looked
at so far—values and attitudes that are so ingrained you wouldn’t
even think to question them. But they can dramatically affect your
judgment and your perception.
Have you ever pondered why you value those things you value? Are
they the values your parents instilled in you? Or are they a reaction
against those who raised you? Did you ever sit down and deliber-
ately decide to be liberal, conservative, libertarian, or anarchist? A
workaholic or a slacker?
Or were you just born that way? Well,<
br />
partly. We’ll look at the “just born that Consider the context.
way” factors in the next section. But
remembering that context is king, let’s look at you in the context of
your peers and your environment.
You are a product of your times—perhaps much more so than you
think. The attitudes, philosophies, and values of your parents and
your cohort (those born about the same time as you; your peers
throughout school and in the workplace; members of your gener-
ation) have a tremendous impact on your values, attitudes, and
perceptions.
You and the rest of your cohort are united by shared memories,
common habits, and popular styles, as well as your age and station
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in life at that time. For instance, the terrorist attacks of 9/11 were
a major, shared global event, affecting everyone. But depending on
whether you are in your 20s, your 40s, or your 60s, your reaction
to those events will differ—and align more closely with everyone
else who is in your similar age bracket.
How might your attitudes differ? Here are a couple of axes I can
think of:
• Risk taker vs. risk adverse
• Individualism vs. teamwork
• Stability vs. freedom
• Family vs. work
Different generations inherently have different values, and your
own attitudes and concerns change as you age as well.
As you and your cohort age, you begin to fulfill roles vacated by
the previous generation, but you’ll adapt the situation to your own
outlook.
Here’s a quick synopsis10 of the last several generations in America,
including the approximate birth years for each generation. These
ranges are necessarily fuzzy; if you are born near one of the inflec-
tion points, you may find yourself identifying more with an adjacent
bracket than with your nominal one.
And of course, these are broad general-
These are broad
izations at best. So, it’s not to say that if
generalizations.
you’re born in these years that you have
these traits, rather that taken as a whole,
these cohorts tend to exhibit these traits. Remember these aren’t
laws or set-in-stone prescriptions; these are useful abstractions to