Mind Matters - June 3, 2008

Of Two Minds When Making a Decision
We may make snap judgments, or mull things carefully. Why and when do
we use the
brain systems behind these decision-making styles?
By Alan G. Sanfey and Luke J. Chang

One of the more enduring ideas in psychology, dating back to the time
of William
James a little more than a century ago, is the notion that human
behavior is not
the product of a single process, but rather reflects the interaction
of
different specialized subsystems. These systems, the idea goes,
usually interact
seamlessly to determine behavior, but at times they may compete. The
end result
is that the brain sometimes argues with itself, as these distinct
systems come
to different conclusions about what we should do.

The major distinction responsible for these internal disagreements is
the one
between automatic and controlled processes. System 1 is generally
automatic,
affective and heuristic-based, which means that it relies on mental
"shortcuts."
It quickly proposes intuitive answers to problems as they arise.
System 2, which
corresponds closely with controlled processes, is slow, effortful,
conscious,
rule-based and also can be employed to monitor the quality of the
answer
provided by System 1. If it's convinced that our intuition is wrong,
then it's
capable of correcting or overriding the automatic judgments.

One way to conceptualize these systems is to think of the processes
involved in
driving a car: the novice needs to rely on controlled processing,
requiring
focused concentration on a sequence of operations that require mental
effort and
are easily disrupted by any distractions. In contrast, the well-
practiced
driver, relying on automatic processes, can carry out the same task
efficiently
while engaged in other activities (such as chatting with a passenger
or tuning
in to a radio station). Of course, he or she can always switch to more
deliberative processing when necessary, such as conditions of extreme
weather,
heavy traffic or mechanical failure.

In terms of decision-making, the description of System 2 bears a close
resemblance to the rational, general-purpose processor presupposed by
standard
economic theory. Although these economic models have provided a strong
and
unifying foundation for the development of theory about decision-
making, several
decades of research on these topics has produced a wealth of evidence
demonstrating that, in practice, these models do not provide a
satisfactory
description of actual human behavior. For instance, it's been
recognized for
several decades the people are more sensitive to losses than to gains,
a
phenomenon known as loss aversion. This doesn't fit with economic
theory, but it
appears to be hard-wired into the brain.

A major cause of these observed idiosyncrasies of decision-making may
be that
controlled processing accounts for only part of our overall behavioral
repertoire, and in some circumstances can face stiff competition from
domain-specific automatic processes that are part of System 1. One
recent
compelling demonstration of this phenomenon comes from Princeton
University
psychologist Adam Alter and colleagues, who examined how subtle
changes in
contextual cues, such as altering the legibility of a font, can
facilitate
switching between System 1 and System 2 processing.

In a series of clever experiments, the authors manipulated the
"perceptual
fluency" of various sets of stimuli. In other words, they made it
harder for
people to understand or decipher the scenarios they were asked to
judge. For
example, in one experiment participants were asked a series of
questions, known
as the Cognitive Reflection Test, designed to assess the degree to
which System
1 intuitive processes are engaged in decision-making. In this test the
gut
reaction answer is invariably incorrect. (An example: if a bat and a
ball
together cost $1.10, and the bat costs $1 more than the ball, how much
does the
ball cost? If you find yourself wanting to shout out "10 cents, of
course," then
you're in the majority, but sadly also wrong.) Alter et al. found that
by making
the problem simply more difficult to read (by using grayed-out,
reduced-size
font), participants seemed to shift to more considered, System 2
responses, and
as a result answered more of the questions correctly.

The authors repeated this effect in various situations. For example
they
degraded the byline of the author on a review of an MP3 player. As a
result,
participants were less influenced by the apparent competence of the
reviewer,
which would have been based on viewing a picture of him or her, and
more by the
actual content of the review. In an additional scenario, they ask
participants
to either furrow their brow or puff their cheeks while assessing
statistical
information. The former activity is a cue for cognitive effort and as
such led
to decreased reliance on (incorrect) intuition, and more on
dispassionate
analytic thinking.

These examples are important for several reasons. Most trivially, they
are a
good example of the ingenuity of researchers in finding interesting
new ways to
demonstrate the existence of the two purported systems. More important
however,
they begin to address the issue, largely ignored until now, of exactly
why and
when the various systems are employed in judgments. The work can lead
towards
more accurate predictions of when the respective Systems may be
engaged.

Finally, the examples illustrated here have the potential to
contribute to how
these systems may be usefully applied to construct environments that
foster more
sensible decisions. In a similar vein, a recent movement in behavioral
economics
seeks to acknowledge the limitations of everyday decision-making (such
as the
apparent reluctance of workers to contribute to 401K plans) and
therefore design
institutions in such a way as to 'encourage' better choices (such as
introducing
default options for retirement savings). Work led by Richard Thaler
has
demonstrated that, when people are asked to commit to saving money in
the
distant future (as opposed to right now), they end up making much more
economically rational decisions. This is because System 2 seems to be
in charge
of making decisions that concern the future, while System 1 is more
interested
in the present moment.

Of course, there are still many outstanding questions regarding the
multiple-system model, not least the degree to which these proposed
systems
actually exist and are truly separable. The welcome integration of
neuroscience
with traditional experimental psychology has led to some debate about
how, and
where, exactly, these systems are instantiated in the brain. Although
there is a
good deal of evidence for some level of dissociation between multiple
systems
that approximate controlled and automatic processing respectively,
with parts of
the brain such as areas of frontal cortex (controlled) and limbic
regions
(automatic) implicated in these processes, it seems highly unlikely
that there
are dedicated, independent, sub-systems at the neural level that are
specific to
these modes of processing. Therefore, one important question is
whether the
types of systems that have been described at the psychological level
are a good
analogue for the way information is organized and processed in the
brain.
Research such as Alter et al.'s work points to the importance of
becoming
increasingly more specific about the situations and conditions that
engage these
distinct systems, which will prove to be essential in understanding
how these
multiple systems interact at a neural level.

Mind Matters is edited by Jonah Lehrer, the science writer behind the
blog The
Frontal Cortex and the book Proust was a Neuroscientist

Source: Scientific American
http://www.sciam.com/article.cfm?id=of-two-minds-when-making&sc=WR_20080603