Thagard, P. (2001). How to make decisions: Coherence, emotion, and practical inference. In E. Millgram (Ed.), Varieties of practical inference . Cambridge, MA: MIT Press. 355-371.
Students face many important decisions: What college or university should I attend? What should I study? What kind of job should I try to get? Which people should I hang out with? Should I continue or break off a relationship? Should I get married? Should I have a baby? What kind of medical treatment should I use? A theory of practical reasoning should have something to say about how students and other people can improve their decision making.
I regularly teach a first-year course on critical thinking intended
to help students improve their reasoning about what to believe
and about what to do. After spending about two thirds of the course
on ways of improving judgments about the truth and falsity of
controversial claims in areas such as medicine and pseudoscience,
I devote the last third to practical reasoning, with the focus
on how people can make better decisions. I discuss both the kinds
of erroneous reasoning that decision makers commonly fall into,
and some systematic models that have been proposed by psychologists,
economists, and philosophers to specify how people should
make decisions.
Many students in the course dislike these models, and resist the
claim that using them is preferable to making decisions simply
by intuition. They trust their "gut feelings" more than
they trust the analytical methods that require a systematic and
mathematical comparative assessment of competing actions that
satisfy multiple criteria. The textbooks I use (most recently
Gilovich 1991, Russo and Schoemaker 1989, Schick and Vaughn 1999)
encourage people to avoid the use of intuition and instead to
base their judgments and decisions on reasoning strategies that
are less likely to lead to common errors in reasoning. From this
perspective, decision making should be a matter of calculation,
not intuition.
While I agree that intuition-based decision making can lead to
many problems, I also think that calculation-based decision making
of the sort recommended by psychologists and economists has some
serious pitfalls. In this chapter, I will try to offer a synthesis
and partial reconciliation of intuition and calculation models
of decision, using a recently developed theory of emotional coherence
(Thagard in press). This theory builds on a previous coherence-based
theory of decision making developed in collaboration with Elijah
Millgram. Understanding decision making in terms of emotional
coherence enables us to appreciate the merits of both intuition
and calculation as contributors to effective practical reasoning.
Suppose you are a student trying to decide whether to study
(1) an Arts subject such as philosophy or art history in which
you have a strong interest or (2) a subject such as economics
or computer science which may lead to a more lucrative career.
To make this decision intuitively is just to go with the option
that is supported by your emotional reactions to the two alternatives.
You may have a strongly positive gut feeling toward the more interesting
subject along with a strongly negative feeling about the more
career-oriented one, or your feelings may be just the opposite.
More likely is that you feel positive feelings toward both alternatives,
along with accompanying anxiety caused by your inability to see
a clearly preferable option. In the end, intuitive decision makers
choose an option based on what their emotional reactions tell
them is preferable.
There is much to be said for intuitive decision making. One obvious
advantage is speed: an emotional reaction can be immediate and
lead directly to a decision. If your choice is between chocolate
and vanilla ice cream, it would be pointless to spend a lot of
time and effort deliberating about the relative advantages and
disadvantages of the two flavors. Instead, an emotional reaction
such as "chocolate yum!" can make for a quick and
appropriate decision. Another advantage is that basing your decisions
on emotions helps to ensure that the decisions take into account
what you really care about. If you are pleased and excited about
a possible action, that is a good sign that the action promises
to accomplish the goals that are genuinely important to you. Finally,
decisions based on emotional intuitions lead directly to action:
the positive feeling toward an option will motivate you to carry
it out.
But emotion-based intuitive decision making can also have some
serious disadvantages. An option may seem emotionally appealing
because of failure to consider other available options. Intuition
may suggest buying chocolate ice cream only because you have failed
to consider a lower-fat alternative that would be a healthier
choice. Intuition is also subject to the intense craving that
drug addicts call "jonesing". If you are jonesing for
cocaine, or for a pizza, or for a Mercedes-Benz convertible, your
intuition will tell you to choose what you crave, but only because
the craving has emotionally swamped other desires that you will
be more aware of when the craving is less intense.
Another problem with intuition is that it may be based on inaccurate
or irrelevant information. Suppose you need to decide whom to
hire for a job. If you are prejudiced against people of a particular
sex, race, or ethnicity, then your intuition will tell you not
to hire them, even if they have better qualifications for doing
the job well. It is difficult to determine introspectively whether
your intuitions derive from reliable and relevant information.
Finally, intuitive reasoning is problematic in group situations
where decisions need to be made collectively. If other people
disagree with your choices, you cannot simply contend that your
intuitions are stronger or better than the intuitions of others.
Defending your emotional reactions and attempting to reach a consensus
with other people requires a more analytical approach than simply
expressing your gut feelings.
Experts on decision making recommend a more systematic and calculating
approach. For example, Bazerman (1994, p. 4) says that rational
decision making should include the following six steps:
1. Define the problem, characterizing the general purpose of your
decision.
2. Identify the criteria, specifying the goals or objectives that
you want to be able to accomplish.
3. Weight the criteria, deciding the relative importance of the
goals.
4. Generate alternatives, identifying possible courses of action
that might accomplish your various goals.
5. Rate each alternative on each criterion, assessing the extent
to which each action would accomplish each goal.
6. Compute the optimal decision, evaluating each alternative by
multiplying the expected effectiveness of each alternative with
respect to a criterion times the weight of the criterion, then
adding up the expected value of the alternative with respect to
all criteria.
We can then pick the alternative with the highest expected value
and make a decision based on calculation, not on subjective emotional
reactions. Using slightly different terminology, Russo and Shoemaker
(1989, ch. 6) recommend essentially the same kind of decision
making process based on multiple weighted factors.
Some students dismiss this kind of process as robot-like, and
find it offensive that important decisions in their lives might
be made mathematically. A cartoon in the New Yorker (Jan. 10,
2000, p. 74) shows a man sitting at a computer and saying to a
woman: "I've done the numbers, and I will marry you."
Some decisions, at least, seem inappropriately based on doing
the numbers. But is the emotional dismissal of Bazerman's 6-step
calculation method justified? We can certainly see some notable
advantages of the calculation method over the intuition method.
First, it is set up to avoid neglecting relevant alternatives
and goals. Second, it makes explicit the consideration of how
the various alternatives contribute to the various goals. Third,
it puts the decision making process out in the open, enabling
it to be carefully reviewed by a particular decision maker and
also by others involved in a group decision process.
However, the calculation method of decision making may be more
difficult and less effective than decision experts claim. Suppose
you are trying to decide between two courses of study, say philosophy
versus computer science, and you systematically list all the relevant
criteria such as how interesting you find the subjects and how
well they fit with your career plans. You then weight the criteria
and estimate the extent to which each option satisfies them, and
proceed to a calculation of the expected value of the competing
choices. Having done this, you find that the expected value of
one option, say philosophy, exceeds that of the other. But what
if you then have the reaction "I don't want to do that!"
Your emotional reaction need not be crazy, because it may be that
the numerical weights that you put on your criteria do not reflect
what you really care about. Moreover, your estimates about the
extent to which different actions accomplish your goals may be
very subjective and fluid, so that your unconscious estimation
is at least as good as your conscious one. I once knew someone
who told me that she made decisions by first flipping a coin,
with heads for one option and tails for another. When the coin
came up heads, she would note her emotional reaction, which gave
her a better idea of whether she really wanted the option associated
with heads. She then used this emotional information to help her
make a choice between the two options.
There is empirical evidence that calculation may sometimes be
inferior to intuition in making good judgments. Damasio (1994)
describes people with injuries that have disconnected the parts
of their brains that perform verbal reasoning and numerical calculation
from emotional centers such as the amygdala. With their abstract
reasoning abilities intact, you might think that the patients
become paragons of rationality, like Spock or Data in Star
Trek. On the contrary, these patients tend to make poor interpersonal
decisions. Damasio conjectures that the deficiencies arise because
the brain damage prevents the patients from making emotional evaluations
that involve somatic markers, bodily states that indicate
the positive or negative emotional value of different possibilities.
The problem is that the patients just do not know what they care
about. Wilson and Schooler (1991) report research that shows that
there are domains where people's intuitive judgments may be more
effective than their more systematic, deliberative ones. They
studied college students' preferences for brands of strawberry
jams and for college courses, and found that students who were
asked to analyze the reasons for their preferences ended up with
choices that corresponded less with expert opinion than did the
choices of less analytical students. Wilson and Schooler conjecture
that this happens because analyzing reasons can focus people's
attention on relatively unimportant criteria. Lieberman (2000)
argues that intuitions are often based on unconscious learning
processes that can be interfered with by attempts at explicit
learning.
It seems, therefore, that we need a model of decision making that
is both more psychologically natural and more normatively effective
than the calculation model. I will now argue that we can get better
accounts both of how decisions are made and of how they should
be made by understanding practical inference in terms of emotional
coherence.
Decision making is a kind of inference, but what is inference?
Many philosophers have taken deductive logic as the model for
inference. Here is a sort of deductive practical inference:
Whenever you want ice cream, you should order chocolate.
You want ice cream.
Therefore, you should order chocolate.
Unfortunately, we rarely have general rules that tell us exactly
what to do, so deduction is not a good model for practical inference.
A second familiar model of inference is calculation, useful for
example in solving arithmetical problems and working with probability
theory. But there is a third general model of inference that advocates
the following rule: Accept a representation if and only if it
coheres maximally with the rest of your representations. Many
philosophers have advocated coherence theories of inference but
have left rather vague how to maximize coherence (e.g. Harman
1986, Brink 1989, and Hurley 1989). A precise and general model
of coherence-based inference can be constructed in terms of constraint
satisfaction (Thagard and Verbeurgt 1998, Thagard in press).
When we make sense of a text, a picture, a person, or an event,
we need to construct an interpretation that fits with the available
information better than alternative interpretations. The best
interpretation is one that provides the most coherent account
of what we want to understand, considering both pieces of information
that fit with each other and pieces of information that do not
fit with each other. For example, when we meet unusual people,
we may consider different combinations of concepts and hypotheses
that fit together to make sense of their behavior.
Coherence can be understood in terms of maximal satisfaction of
multiple constraints, in a manner informally summarized as follows:
1. Elements are representations such as concepts, propositions,
parts of images, goals, actions, and so on.
2. Elements can cohere (fit together) or incohere (resist fitting
together). Coherence relations include explanation, deduction,
facilitation, association, and so on. Incoherence relations include
inconsistency, incompatibility, and negative association.
3. If two elements cohere, there is a positive constraint between
them. If two elements incohere, there is a negative constraint
between them.
4. Elements are to be divided into ones that are accepted and
ones that are rejected.
5. A positive constraint between two elements can be satisfied
either by accepting both of the elements or by rejecting both
of the elements.
6. A negative constraint between two elements can be satisfied
only by accepting one element and rejecting the other.
7. The coherence problem consists of dividing a set of elements
into accepted and rejected sets in a way that satisfies the most
constraints.
Computing coherence is a matter of maximizing constraint satisfaction,
and can be accomplished approximately by several different algorithms.
The most psychologically appealing models of coherence optimization
are provided by connectionist algorithms. These use neuron-like
units to represent elements and excitatory and inhibitory links
to represent positive and negative constraints. Settling a connectionist
network by spreading activation results in the activation (acceptance)
of some units and the deactivation (rejection) of others. Coherence
can be measured in terms of the degree of constraint satisfaction
accomplished by the various algorithms. In general, the computational
problem of exactly maximizing coherence is very difficult, but
there are effective algorithms for approximating the maximization
of coherence construed as constraint satisfaction (Thagard and
Verbeurgt 1998).
I will now make this account of coherence more concrete by showing
how it applies to inference about what to do. Elijah Millgram
and I have argued that practical inference involves coherence
judgments about how to fit together various possible actions and
goals; (Millgram and Thagard 1996, Thagard and Millgram 1995).
On our account, the elements are actions and goals, the positive
constraints are based on facilitation relations (the action of
going to Paris facilitates my goal of having fun), and the negative
constraints are based on incompatibility relations (you cannot
go to Paris and London at the same time). Deciding what to do
is based on inference to the most coherent plan, where coherence
involves evaluating goals as well as deciding what to do.
More exactly, deliberative coherence can be specified by the following
principles:
Principle 1. Symmetry. Coherence and incoherence are symmetrical
relations: If a factor (action or goal) F1 coheres with a factor
F2, then F2 coheres with F1.
Principle 2. Facilitation. Consider actions A1 ... An that
together facilitate the accomplishment of goal G. Then
(a) each Ai coheres with G,
(b) each Ai coheres with each other Aj, and
(c) the greater the number of actions required, the less the coherence
among actions and goals.
Principle 3 . Incompatibility.
(a) If two factors cannot both be performed or achieved, then
they are strongly incoherent.
(b) If two factors are difficult to perform or achieve together,
then they are weakly incoherent.
Principle 4. Goal priority. Some goals are desirable for
intrinsic or other non-coherence reasons.
Principle 5. Judgment. Facilitation and competition relations
can depend on coherence with judgments about the acceptability
of factual beliefs.
Principle 6. Decision. Decisions are made on the basis
of an assessment of the overall coherence of a set of actions
and goals.
In order to assess overall coherence, we can use the computer
program DECO (short for "Deliberative Coherence"). DECO
represents each element (goal or action) by a neuron-like unit
in an artificial neural network and then spreads activation through
the network in a way that activates some units and deactivates
others. At the end of the spread of activation, the active units
represent elements that are accepted, while the deactivated ones
represent elements that are rejected. DECO provides an efficient
and usable way to compute the most coherent set of actions and
goals.
At first glance, deliberative coherence might seem like a variant
of the calculation model of decision making. Figuring out which
action best coheres with your goals sounds like Bazerman's calculation
of the expected value of alternatives based on the extent to which
they satisfy weighted criteria. But there are some crucial differences.
Unlike Bazerman's proposal, the deliberative coherence model of
decision does not take the weights of the goals as fixed. In DECO,
units representing some of the goals get initial activation in
accord with principle 4, goal priority, but their impact depends
on their relation to other goals: even a basic goal can be deactivated,
at least partially, by other goals. The impact of goals on decision
making depends on their activation, which depends on their relation
to other goals and to various actions. For example, students trying
to decide what to do on the weekend might start off thinking that
what they most want to do is to have fun, but realize that having
fun is not so important because it conflicts with other goals
such as studying for an important exam or saving money to pay
next term's tuition.
Psychologically, decision as coherence is very different from
decision as calculation. Calculations are conscious and explicit,
displayable to everyone on pencil and paper. In contrast, if coherence
maximization in human brains is similar to what happens in the
artificial neural networks used in DECO, then assessment of coherence
is a process not accessible to consciousness. What comes to consciousness
is only the result of the process of coherence maximization: the
realization that a particular action is the one I want to perform.
Thus, as an account of how decisions are made by people, deliberative
coherence is closer to the intuition model of decision than to
the calculation model. Coherence is not maximized by an explicit,
consciously accessible calculation, but by an unconscious process
whose output is the intuition that one action is preferable to
others. There is, however, a major difference between the deliberative
coherence account of decision making and the intuition account:
intuitions about what to do are usually emotional, involving feelings
that one action is a good thing to do and that alternatives are
bad things to do. Fortunately, coherence theory can naturally
be extended to encompass emotional judgments.
In the theory of coherence stated above, elements have the epistemic
status of being accepted or rejected. We can also speak of degree
of acceptability, which in artificial neural network models of
coherence is interpreted as the degree of activation of the unit
that represents the element. I propose that elements in coherence
systems have, in addition to acceptability, an emotional valence,
which can be positive or negative. Depending on the nature of
what the element represents, the valence of an element can indicate
likability, desirability, or other positive or negative attitude.
For example, the valence of Mother Theresa for most people is
highly positive, while the valence of Adolf Hitler is highly negative.
Many other researchers have previously proposed introducing emotion
into cognitive models by adding valences or affective tags (Bower
1981, 1991; Fiske and Pavelchak 1986; Lodge and Stroh 1993; Ortony,
Clore, and Collins 1988; Sears, Huddy, Schaffer 1986). Kahneman
(1999) reviews experimental evidence that evaluation on the good/bad
dimension is a ubiquitous component of human thinking.
Just as elements are related to each other by the positive and
negative deliberative constraints described in the last section,
they also can be related by positive and negative valence constraints.
Some elements have intrinsic positive and negative valences, for
example pleasure and pain. Other elements can acquire
valences by virtue of their connections with elements that have
intrinsic valences. These connections can be special valence constraints,
or they can be any of the constraints posited by the theory of
deliberative coherence. For example, if someone has a positive
association between the concepts of dentist and pain,
where pain has an intrinsic negative valence, then dentist
can acquire a negative valence. However, just as the acceptability
of an element depends on the acceptability of all the elements
that constrain it, so the valence of an element depends on the
valences of all the elements that constrain it.
The basic theory of emotional coherence can be summarized in three
principles analogous to the qualitative principles of coherence
above:
1. Elements have positive or negative valences.
2. Elements can have positive or negative emotional connections
to other elements.
3. The valence of an element is determined by the valences and
acceptability of all the elements to which it is connected.
As already mentioned, coherence can be computed by a variety of
algorithms, but the most psychologically appealing model, and
the model that first inspired the theory of coherence as constraint
satisfaction, employs artificial neural networks. In this connectionist
model, elements are represented by units, which are roughly analogous
to neurons or neuronal groups. Positive constraints between elements
are represented by symmetric excitatory links between units, and
negative constraints between elements are represented by symmetric
inhibitory links between units. The degree of acceptability of
an element is represented by the activation of a unit, which is
determined by the activation of all the units linked to it, taking
into account the strength of the various excitatory and inhibitory
links.
It is straightforward to expand this kind of model into one that
incorporates emotional coherence. In the expanded model, called
"HOTCO" for "hot coherence," units have valences
as well as activations, and units can have input valences to represent
their intrinsic valences. Moreover, valences can spread through
the system in a way very similar to the spread of activation,
except that valence spread depends in part on activation spread.
An emotional decision emerges from the spread of activation and
valences through the system because nodes representing some actions
receive positive valence while nodes representing other actions
receive negative valence. The gut feeling that comes to consciousness
is the end result of a complex process of cognitive and emotional
constraint satisfaction. Emotional reactions such as happiness,
anger, and fear are much more complex than positive and negative
valences, so HOTCO is by no means a general model of emotional
cognition. But it does capture the general production by emotional
inference of positive and negative attitudes toward objects, situations,
and choices.
It might seem that we can now abandon the cognitive theory of
deliberative coherence for the psychologically richer theory of
emotional coherence, but that would be a mistake for two reasons.
First, emotional coherence must interconnect with other kinds
of coherence that involve inferences about what is acceptable
as well as about what is emotionally desirable. The valence of
an element does not depend just on the valences of the elements
that constrain it, but also on their acceptability. Attaching
a negative valence to the concept dentist, if it does not
already have a negative valence from previous experience, depends
both on the negative valence for causes-pain and the acceptability
(confidence) of causes-pain in the current context.
The inferential situation here is analogous to expected utility
theory, in which the expected utility of an action is calculated
by summing, for various outcomes, the result of multiplying the
probability of the outcome times the utility of the outcome. The
calculated valence of an element is like the expected utility
of an action, with degrees of acceptability analogous to probabilities
and valences analogous to utilities. There is no reason, however,
to expect degrees of acceptability and valences to have the mathematical
properties that define probabilities and utilities. Because the
valence calculation depends on the acceptability of all the relevant
elements, it can be affected by other kinds of coherence. For
example, the inference concerning whether to trust someone depends
largely on the valence attached to them based on all the information
you have about them, where this information derives in part from
inferences based on explanatory, analogical, and conceptual coherence
(Thagard in press).
The second reason for not completely replacing the cold (nonemotional)
theory of deliberative coherence with the hot theory of emotional
coherence is that people can sometimes come up with incompatible
hot and cold judgments about what to do. Unconsciously using deliberative
coherence may produce the judgment that you should not do something,
while emotional coherence leads you in a different direction.
For example, students seeing the first nice spring day at the
end of a long Canadian winter might decide emotionally to go outside
and enjoy it, while at the same time reasoning that the alternative
of finishing up overdue end-of-term projects is more coherent
with their central goals such as graduating from university. I
am not the only person capable of thinking: "The best thing
for me to do is X, but I'm going to do Y." Jonesing in reaction
to vivid stimuli can make emotional coherence swamp deliberative
coherence.
The theory of emotional coherence provides a psychologically realistic
way of understanding the role of intuition in decisions. My gut
feeling that I should go to Paris is the result of an unconscious
mental process in which various actions and goals are balanced
against each other. The coherence process involves both inferences
about what I think is true (e.g. I'll have fun in Paris) and inferences
about the extent to which my goals will be accomplished. But the
coherence computation determines not only what elements will be
accepted and rejected, but also an emotional reaction to the element.
It is not just "go to Paris yes" or "go to
Paris no", but "go to Paris yeah!"
or "go to Paris yuck!".
As we just saw, however, emotional coherence may be better as
a descriptive theory of how people make decisions than as a normative
theory of how people should make decisions. Judgments based on
emotional coherence may be subject to the same criticisms that
I made against intuitive decisions: susceptibility to jonesing
and to failure to consider the appropriate range of actions and
goals. I doubt, however, that people are capable of making decisions
without recourse to emotional coherence that is just how
our brains are constituted. For normative purposes, therefore,
the best course is to adopt procedures that interact with emotional
coherence to produce intuitions that are informed and effective.
The theory of emotional coherence shows how people's gut feelings
about what to do may sometimes emerge from integrative unconscious
judgments about the actions that might best accomplish their goals.
But it also applies to cases where people's intuitions are too
quick and uninformed. How can students and other people be helped
to ensure that their decisions are based on informed intuition?
For important decisions, I recommend that, rather than leaping
to an immediate intuitive choice, people should follow a procedure
something like the following:
Informed Intuition
1. Set up the decision problem carefully. This requires identifying
the goals to be accomplished by your decision and specifying the
broad range of possible actions that might accomplish those goals.
2. Reflect on the importance of the different goals. Such reflection
will be more emotional and intuitive than just putting a numerical
weight on them, but should help you to be more aware of what you
care about in the current decision situation. Identify goals whose
importance may be exaggerated because of jonesing or other emotional
distortions.
3. Examine beliefs about the extent to which various actions would
facilitate the different goals. Are these beliefs based on good
evidence? If not, revise them.
4. Make your intuitive judgment about the best action to perform,
monitoring your emotional reaction to different options. Run your
decision past other people to see if it seems reasonable to them.
This procedure combines the strengths and avoids the weaknesses
of the intuition and calculation models of decision making. Like
the intuition model, it recognizes that decision making is an
unconscious process that involves emotions. Like the calculation
model, it aims to avoid decision errors caused by unsystematic
and unexamined intuitions. One drawback of the Informed Intuition
procedure is that it is not so intersubjective as the calculation
model, in which the numerical weights and calculations can be
laid out on the table for all to see. It would certainly be a
useful exercise in many cases for people to go through the steps
of producing a calculation in order to provide some information
about how different people are seeing the situation. Ultimately,
however the individual decision makers will have to make decisions
based on their own intuitive judgments about what is the right
thing to do. The members of the group may be poor at specifying
the emotional weights they put on different goals, and they may
be unaware of their assumptions about the extent to which different
actions facilitate different goals. Achieving consensus among
a group of decision makers may require extensive discussion that
reveals the goals and beliefs of decision makers to themselves
as well as to others. It is much easier to identify jonesing and
other emotional distortions in others than in yourself. The discussion,
including the exercise of working through a calculation together,
may help the members of the group converge on evaluations of goal
importance and belief plausibility that produce a shared reaction
of emotional coherence. Scientific consensus concerning competing
scientific theories can emerge from a process of individual coherence
and interpersonal communication (Thagard 1999, ch. 7), but conflict
resolution concerning what to do requires a more complex process
of comparing and communicating the diverse goals driving the various
decision makers. A crucial part of this process is becoming aware
of the emotional states of others, which may benefit as much from
face-to-face interactions involving perception of people's physical
as from purely verbal communication.
Informed Intuition is a much more complicated process of decision
making than the practical syllogism commonly discussed by philosophers.
Millgram (1997, p. 41) gives the following example:
1. Delicious things should be eaten. [major premise]
2. This cake is delicious. [minor premise]
3. Eat the cake. [conclusion]
The practical syllogism gives an inadequate picture of decision
making, both descriptively and normatively. Descriptively it fails
to notice that the decision to eat cake is crucially influenced
by the emotional value of the action of eating cake. Normatively
it fails to see that deciding is a matter of deliberative coherence
which has to balance competing goals (e.g. eat something delicious,
be slim, be healthy) and to evaluate competing actions (e.g. eat
the cake, eat an apple, drink Perrier). On the coherence model
of inference, reasoning and inference are very different. Reasoning
is verbal and linear, like the practical syllogism and proofs
in formal logic. But inference is an unconscious mental process
in which many factors are balanced against each other until a
judgment is reached that accepts some beliefs and rejects others
in a way that approximately maximizes coherence.
This does not mean that practical and theoretical reasoning should
be sneered at. Reasoning is a verbal, conscious process that is
easily communicated to other people. People are rarely convinced
by an argument directly, but the fact that reasoning does not
immediately translate into inference does not make it pointless.
Making reasoning explicit in decisions helps to communicate to
all the people involved what the relevant goals, actions, and
facilitation relations might be. If communication is effective,
then the desired result will be that each decision maker will
make a better informed intuitive decision about what to do.
Improving inference is both a matter of recognizing good inference
procedures such as Informed Intuition and watching out for errors
that people commonly make. Such errors are usually called fallacies
by philosophers and biases by psychologists. Psychologists, economists,
and philosophers have identified a variety of error tendencies
in decision making, such as overrating sunk costs, using bad analogies,
and being overconfident in judgments. Noticing the role of emotional
coherence in decision making enables us to expand this list to
include emotional determinants of bad decision making such as
jonesing and failing to perceive the emotional attitudes of other
people. In this paper I have emphasized the positive strategy
of making decisions using a recommended procedure, Informed Intuition,
but a fuller account would also develop the negative strategy
of avoiding various tendencies that are natural to human thinking
and that often lead to poor decisions.
The coherence model of decision making allows goals to be adjusted
in importance while evaluating a decision, but it does not address
the question of how we adopt new goals. Millgram's (1997) account
of practical induction is useful for describing how people in
novel situations can develop new interests that provide them with
new goals. A full theory of decision making would have to include
an account of where human goals come from and how they can be
evaluated. People who base their decisions only on the goals of
sex, drugs, and rock and roll may achieve local coherence, but
they have much to learn about the full range of pursuits that
enrich human lives.
I have tried in this paper to provide students and other people
with a model of decision making that is both natural and effective.
Practical inference is not simply produced by practical syllogisms
or cost-benefit calculations, but requires assessment of the coherence
of positively and negatively interconnected goals and actions.
This assessment is an unconscious process based in part on emotional
valences attached to the various goals to be taken into consideration,
and yields a conscious judgment that is not just a belief about
what is the best action to perform but also a positive emotional
attitude toward that action. Reason and emotion need not be in
conflict with each other, if the emotional judgment that arises
from a coherence assessment takes into account the relevant actions
and goals and the relations between them. The procedure I recommend,
Informed Intuition, shows how decisions can be both intuitive
and reasonable.
Acknowledgments
This research is supported by the Natural Sciences and Engineering
Research Council of Canada. The sections on decision as coherence
and emotional coherence contain excerpts from Thagard (in press).
I am grateful to Elijah Millgram for comments on an earlier draft.
Various papers on coherence can be found on my Web site: http://cogsci.uwaterloo.ca.
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