Critique of Emotional Reason
Paul Thagard
Philosophy Department
University of Waterloo
pthagard@uwaterloo.ca
Introduction
In the title of her most recent book, Susan Haack (1998) describes
herself as a passionate moderate. With eloquence and
verve, she ably defends the rationality of science and philosophy
against a host of post-modernist critics. Haack (p. 49) approvingly
quotes Peirce's descriptions of the scientific attitude as "a
craving to know how things really are," "an intense
desire to find things out," and "a great desire to
learn the truth". But despite the passion evident in her
own arguments and in her citations of Peirce, Haack's explicit
epistemology is emotion-free: the word "emotion" does
not appear in the index of her treatise on epistemology (Haack,
1993). She does however remark in her later book on the "misconception
of the emotions as brutally irrational" (Haack, 1998, p.
142).
In this chapter I want to address the question of how emotions
are relevant to rationality. Answering this question should
further the development of theories of theoretical and practical
reason that take seriously the pervasive role of emotions in human
thinking. I want to reject both the classical view that
emotions are primarily an impediment to reason and the romantic
view that emotionality is inherently superior to reason.
Instead, I develop a critical view that delineates the
ways in which emotions contribute to reason as well as the ways
in which emotions can impede reason. My title uses the term
"critique" to mean not criticism but assessment. I
will argue that emotional cognition can provide a useful supplement
to Haack's "foundherentist" epistemology, and also extend
her discussion of the practical question of affirmative action.
Theoretical and Practical Reason
Emotion is relevant to theoretical reason, which concerns
what to believe, and to practical reason, which concerns what
to do. The main kind of theoretical reason I want to discuss
is what Peirce called abduction, the formation and acceptance
of explanatory hypotheses. Abductive inference has two phases:
the generation of hypotheses and then their evaluation,
ideally leading to the acceptance of hypotheses that
are part of the best explanation of the evidence. Abduction
is common in everyday life, for example when I make inferences
about why my car fails to start or why a friend is in a bad mood;
but it is also central to scientific theorizing, for example in
the generation and evaluation of hypotheses concerning the causes
of disease. My aim is to lay out ways in which emotions affect
the generation and evaluation of scientific hypotheses.
Practical reasoning also has two phases: the generation of possible
actions and their evaluation, ideally leading to choice of those
actions that best satisfy the goals relevant to the decision.
For example, when members of an academic department make a hiring
decision, they have to choose whom to appoint from the typically
large number of candidates for the position. I will discuss
how emotions affect both the generation and evaluation of actions.
Finally, I will try to generalize concerning how emotions do
and should affect theoretical and practical reason.
Theoretical Reason: Generation
As Peirce (1931-1958, 5.591) noted, and as Fodor (2000) recently
reiterated, it is a puzzle why and how abductive inference is
ever successful. There is a huge range of facts that people
might try to explain, and for each fact there is a huge range
of hypotheses that might explain it. Fodor throws up his hands
and says that abduction is a terrible problem for cognitive science,
while Peirce postulates an innate ability, derived by evolution,
for forming and choosing good hypotheses. Preferable to both
these rather desperate conclusions is the attempt to specify the
cognitive mechanisms by which explanatory hypotheses are generated
(see, for example: Thagard 1988; Josephson and Josephson 1994).
Little noticed has been the fact that these mechanisms are
in part emotional.
Consider first the problem of deciding what to attempt to explain.
As Peirce observed, abductive inference is usually prompted
by surprise, the emotional reaction that occurs when our expectations
are violated. Most of the facts that we encounter are not surprising,
in that they fit perfectly well with what we already believe.
Occasionally, however, we encounter facts that do not fit with
our beliefs, generating surprise by a process of emotional incoherence
(Thagard 2000, p. 194). Hence we substantially focus our abductive
activity by narrowing it down to events that have the emotional
character of being surprising. Other emotions that stimulate
explanatory activity include curiosity, in which people have the
emotional drive to find out answers to questions that interest
them. For example, Watson and Crick had a passion to find out
the structure of DNA (Thagard, forthcoming). In addition to
surprise and curiosity, abductive inference can be emotionally
prompted by practical need, for example when a doctor urgently
tries to find a diagnosis that explains the symptoms of a seriously
sick patient. Thus we do not try to explain everything, just
those events and facts that we care about.
Once emotion initiates the attempt to generate explanatory hypotheses,
it can also serve to focus the search for them. Scientists often
get excited about particular lines of thinking and as a result
pursue them intensively. As Peirce noticed, there is no way that
a person could do an exhaustive search of all possible explanatory
hypotheses for a set of data. Moreover, it has been proven
that abduction is computationally intractable, in the sense that
the time required to assemble a set of hypotheses to explain data
grows exponentially with the number of propositions involved (Bylander
et al., 1991), so no computer could do an exhaustive search either.
However, human thinking and current computational models use
heuristic techniques such as backward chaining of rules and spreading
activation of concepts to narrow search for hypotheses.
I conjecture that emotion is a valuable part of heuristic search
in humans. Once a fact to be explained is tagged as emotionally
important, then concepts and rules relevant to explaining it can
also be tagged as emotionally important. For example, when Watson
and Crick were working to find the structure of DNA, they got
excited about ideas such as the double helix that seemed most
relevant to divining the structure. Abduction is sometimes described
as having the structure:
E is to be explained.
H could cause E.
So maybe H.
This structure obscures the fact that considerable thinking goes
into putting together the hypothesis H. To take a simple example,
the ancient Greeks came up with the wave theory of sound to explain
various properties of sound, such as propagation and echoing.
The hypothesis that sound consists of waves requires the linkage
of three concepts: sound, waves, and consists. For
these concepts to be assembled into a proposition, they need to
be simultaneously active in working memory. Emotion may help
to bring potentially useful combinations into juxtaposition.
Chrysippus, the Greek stoic who first constructed the wave theory
of sound, was probably puzzled by the behaviors of sounds. When
something about water waves caught his attention, he was able
to generate the hypothesis that sound consists of waves. Emotional
involvement with a concept, either moderately as interest or more
passionately as excitement, focuses attention on it. When interest
in one concept gives rise to interest in another relevant one,
as when sound gets linked to wave, there emerges
the powerful excitement that signals a discovery.
Emotions are also relevant to guiding the finding of analogies
that often contribute to scientific discovery (see Holyoak and
Thagard, 1995, ch. 8). For example, if the fact to be explained
F1 is analogous to another fact F2 that has already been explained,
and if scientists has a positive emotional attitude toward the
kind of hypothesis H2 that explains F2, then they may get excited
about finding an analog of H2 to explain F1. Thus analogy can
transfer positive emotions from one theory to another similar
one that is judged to be promising (Thagard and Shelley, 2001).
Analogy can also transfer negative emotions, for example when
a potential research program is compared to cold fusion and thereby
discouraged.
Thus emotion seems to be an important part of the generation of
explanatory hypotheses, both in selecting what is to be explained
and in guiding the search for useful hypotheses. On the negative
side, emotions may unduly narrow the search for fruitful explanations.
If scientists become obsessed with a particular kind of hypothesis,
they may be blinded from discovering a very different kind of
hypothesis needed to explain some particularly puzzling fact.
Emotions serve a valuable cognitive function in narrowing the
search for hypotheses, but like any heuristic mechanism they can
take the search in undesirable directions. Misdirection can
occur especially if the goals that provoke emotional excitement
are personal rather than intellectual ones. If scientists get
excited about a particular kind of hypothesis because it might
make them rich and famous, they may be blinded from searching
for less lucrative hypotheses that have greater explanatory potential.
Theoretical Reason: Evaluation
Someone who wants to maintain the classical position that
emotion should not be part of theoretical reason might respond
to the previous section as follows: Granted, emotion has
a useful role to play in the context of discovery, but it must
be kept out of the context of justification, which it can only
distort. To be sure, there are a variety of ways that emotions
can distort theoretical reason in general and abductive inference
in particular, as I will shortly describe. But there is an argument
consistent with Haack's epistemology that shows a crucial role
for emotion in the evaluation of explanatory hypotheses.
Haack (1993) defended a powerful and plausible epistemological
position she dubbed foundherentism. It combines the foundationalist
insight that empirical evidence has a special role to play in
justifying theories with the coherentist insight that such evidence
cannot be taken as given but must be assessed with respect to
overall explanatory integration. Haack uses the apt analogy
of a crossword puzzle, in which there must be an integration of
entries and clues, to indicate how in abductive inference there
must be a coherence of hypotheses and evidence. She does not,
however, provide a method or algorithm for assessing the success
of such integration in particular cases. How do people judge
that they have a good fit in their answers to a crossword puzzle,
and how do scientists decide that one theory fits better with
the evidence than its competitors?
I have developed a theory of explanatory coherence that shows
how the best explanation can be efficiently computed with artificial
neural networks (Thagard, 1992). I have also argued that this
theory, which gives a degree of priority to empirical evidence
while maintaining a coherentist perspective, implements and naturalizes
Haack's foundherentism (Thagard, 2000). I will not repeat that
argument here, but want to draw a conclusion concerning the role
of emotions.
Suppose I am right that foundherentist abductive inference is
accomplished in humans by a neural network that performs parallel
constraint satisfaction in a way that maximizes explanatory coherence.
People have no conscious access to this process: when you
realize you prefer one theory over another, you do not really
know why, although you may be able to retrace your intellectual
history of acquiring the various hypotheses and evidence that
contributed to your preference. All you can say is that one
theory "makes more sense" to you than the other.
This is not to say that inferences based on explanatory coherence
are irrational, since they may well involve maximization of coherence
with respect to the available hypotheses and evidence. But given
the limited access to mental processes, there is no way you can
directly know that you have maximized coherence.
This is where emotions are crucial. According to my recent theory
of emotional coherence, the way you know that you have achieved
explanatory coherence is by a feeling of happiness that emerges
from the satisfaction of many constraints in your neural network
(Thagard 2000, p. 194ff.) Highly coherent theories are praised
by scientist for their elegance and beauty. Because we cannot
extract from our brains judgments such as "Acceptance of
theory T1 satisfies .69 of the relevant constraints", we
have to fall back on the overall emotional judgment such as "T1
just makes sense." Thus the feeling of happiness that emerges
from a coherence judgment is part of our ability to assess scientific
theories. Ideally, a good theory generates a kind of emotional
gestalt that signals its coherence with the evidence and the rest
of our beliefs. Negative emotions attached to a theory signal
that it does not fit with our other beliefs, and a general feeling
of anxiety may signal that none of the available theories is very
coherent. Such anxiety may trigger a search for new hypotheses.
So a gut feeling that represents an emotional gestalt may be
a valid sign of a highly coherent evaluation of competing hypotheses.
The problem is that such a feeling may instead signal a different
kind of coherence based on wishful thinking or motivated inference
rather than fit with the evidence. I once got a letter from
someone urging me to send my explanatory coherence computer program
to him right away, because he had a theory of the universe that
no one else believed, and my program might help him convince other
people. Presumably his attachment to his theory was based more
on satisfaction of personal goals than on it providing the best
explanation of all the evidence. Noting the role of emotion
in appreciating coherence may seem to endorse the romantic view:
If it feels good, believe it.
I know of no psychological way of distinguishing between the positive
emotion of emotional coherence from the similar emotion of self-promotion.
Here it is important that science is a social as well as an
individual process. Scientists know that the fact that they
like their own theories cuts no ice with other scientists with
different personal motivations. In order to publish their work
or to get grants to continue it, scientists' hypotheses must stand
up to peer review, where the peers are people familiar with the
relevant hypotheses and evidence and not moved by the personal
goals of the submitting scientist. Awareness of this scrutiny
requires scientists to calibrate their coherence judgments against
what the scientific community is likely to accept, and influences
them to make their own assessments on the basis of explanatory
coherence rather than personal expedience. In everyday life,
people encounter less social pressure to reason in accord with
evidence and explanatory coherence, so they are more likely to
succumb to evidence-poor but personally-coherent hypotheses such
as conspiracy theories. Even in science there is the danger
that the emotional bias of one individual may spread to associates
by a kind of emotional contagion.
I will use the term emotional skewer for a factor that
is so vivid and affectively intense that it can produce an emotional
gestalt that does not reflect the maximal satisfaction of the
relevant and appropriate constraints. Such factors skew the
coherence calculation by placing too much weight on epistemically
irrelevant factors such as self-promotion. We will see that
emotional skewers also are a threat to rational judgment in practical
reasoning.
Practical Reason: Generation
In order to decide what to do, we need to generate a set
of possible actions and then choose the best. 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.
Then pick the alternative with the highest expected value.
But experts on decision making usually take for granted step
4, in which alternative actions are generated. Creative decision
making often involves not just choosing the best among available
alternatives, but in expanding the range of alternatives. Consider,
for example, hiring decisions in academic departments. The usual
course of action is something like:
1. Assess the needs of the department and establish the area
or areas in which to hire. Then advertise a position in these
areas.
2. Examine all applications and choose a short list for further
discussion.
3. Choose a few applicants to invite to campus.
4. Select a candidate to receive a job offer.
Emotions play a major role in all of these stages.
When departments decide in which areas to hire, there is often
a conflict based on the differing goals of individual members.
Professors typically value their own specialties over those of
their colleagues, so they often have an emotional bias towards
hiring in their own areas. But a thorough assessment of the pedagogical
and research needs of a department should lead to a more reasonable
choice of areas. No data are available on the role of emotions
in generating alternatives for decision making, but I expect that
the cognitive process is similar to that involved in generating
hypotheses in abductive reasoning. There are routine cognitive
processes such as backward chaining that uses rule-like knowledge
of action-goal connections. For example, if the department members
know that there is a ethics course that needs teaching, then they
might think of hiring someone in ethics. But hiring priorities
might also be based on more amorphous considerations, such as
ideas about what areas are emerging as important. Diffuse mechanisms
such as spreading activation among concepts may contribute, but
would be little use in focusing the search for good ideas.
As with the search for hypotheses, emotions are a useful way to
focus the search for decision alternatives. Certain ideas may
get high positive valence and suggest other ideas with positive
valence. For example, my own department recently learned that
Waterloo is getting a very well funded new institute in theoretical
physics, so it occurred to some of us that it might be desirable
to hire someone in philosophy of physics to provide a connection
with this institute. The occurrence was based on excitement
about the new institute which spurred excitement about connecting
philosophy with it which spurred excitement about the possibility
of adding a department member with the relevant specialty.
In academic hiring, the set of applicants is usually determined
by the advertisement, so at this stage the range of alternatives
is fixed. But more creative hiring often involves actively searching
out candidates rather than just passively waiting for the applications
to come in. Once again emotions play a role: people tend to
think of potential candidates whose work they like or whom they
like personally. Of course, emotions can also work negatively,
ruling out people whose work is not respected or whose personalities
are suspect. But emotions can be useful in the process of headhunting,
i.e. trying to identify candidates to urge to apply rather than
simply waiting to see who applies. Of course, emotions can also
prevent options from being generated, as when a name evokes an
"over my dead body" response.
Practical Reason: Evaluation
Once a range of alternative actions is identified, for example
a list of job applicants, then the department must decide whom
to hire. In contrast to the systematic approach to decision making
recommended by Bazerman, department members usually proceed in
a quite haphazard fashion. Members of the hiring committee look
over the applications, and select a small number to comprise a
short list. This selection is both an individual and a group
process, as committee members first make their own short lists
and then meet to agree upon a common short list. Ideally, the
members individually and cooperatively work with a set of criteria,
such as:
1. Research quality, as shown by publications and letters of
reference.
2. Teaching ability, as shown by experience and student course
evaluations.
However, such objectivity may go out the window when candidates
come to campus for personal interviews. Then personal interactions
and quality of performance in the job talk may swamp the more
extensive information contained in the applicants dossier. A
candidate with a charming personality may win out over an introvert
with a better academic record. On the other hand, the department
hiring may make a rational decision to choose the candidate who
best fits their reasonably established criteria.
In either case, I conjecture, the individuals in the department
reach their decisions by means of a kind of emotional gestalt
that summarizes how they feel about particular candidates. They
choose to hire candidates that they feel good about, and reject
candidates that they do not feel good about. As with hypothesis
evaluation in science, we have no direct access to the unconscious
mental processes that integrate various criteria to produce a
coherent decision. Decision making is a coherence process similar
in structure and processing to hypothesis evaluation (see the
DECO model of decision making in Thagard and Millgram, 1995, and
Thagard, 2000). One might try working with pencil-and-paper models
that implement the kind of decision-making procedure described
by Bazerman above, but doing so is difficult because it is hard
to ensure that the numerical weightings one applies actually correspond
to the importance one attaches to the various criteria. Moreover,
if one went through this exercise and found that it suggested
hiring someone with a negative emotional gestalt, it would not
be unreasonable to think that the numerical process had gone astray.
However, it must be admitted that practical reason is even more
susceptible to emotional skewers than is theoretical reason.
For example, a person trying to decide what to have for dinner
may want to make the decision based on a strong aim to eat healthy
foods, but be seduced by a menu into ordering a cheeseburger with
French fries. Here the momentary but intense desire for high-fat
food swamps the long-term interests of the eater and serves as
an emotional skewer. The familiar phenomena of weakness of will
and self deception can be best understood as the result of emotional
skewers.
Hiring decisions are unquestionably susceptible to emotional skewers.
Faced with hundreds of applicants for a job, it is natural for
members of a philosophy department to eliminate individuals on
the basis of solitary criteria: this one hasn't published, that
one has no teaching experience, and so on. There is nothing
wrong with such elimination if the criteria are the ones appropriate
for the position, but stereotypes and prejudices operating consciously
or unconsciously can have the same effect in normatively inappropriate
ways. They can lead, for example, to the summary rejection of
women with young children, or to gay or lesbian candidates who
just would not "fit in" with the department. Members
of an academic department may have an unconscious schema of the
appropriate sort of colleague to have, a schema that is based
in substantial part on themselves. Someone who does not fit
that schema because of features that are irrelevant for job performance
may nevertheless be considered just not right for the job.
The operation of emotional skewering shows why preferential hiring
is sometimes necessary. Like Haack, (1998, ch. 10), I would
much prefer a hiring process in which the best candidate for a
job is hired, which, given the plausible assumption that women
are as academically talented as men, would over time lead to the
elimination of gender bias in academic hiring. But there have
undoubtedly been departments where emotional skewers are so pronounced
that fair hiring is very unlikely. An American philosopher once
told about the difficulties that his illustrious department had
had in placing their female candidates. For example, the chair
of one hiring department told him: "Don't bother telling
us about your women students we don't have to hire a woman
yet." In such cases, administrative action to enforce hiring
of women is the only way to change the department in ways that
allow the development of fair hiring practices.
Haack (1998, p. 173) is well aware of the role of emotions in
hiring decisions, describing the hiring process as a combination
of greed and fear:
Greed: we want someone who will improve the standing of the department,
who has contacts from which we might benefit, who will willingly
do the teaching we'd rather not do, who will publish enough so
the tenure process will go smoothly. Fear: we don't want someone
so brilliant or energetic that they make the rest of us look bad,
or compete too successfully for raises and summer money, or who
will vote with our enemy on controversial issues.
Any of these greed factors and fear factors, alone or in combination,
can serve as emotional skewers that contribute to an emotional
gestalt that produces an unfair and suboptimal hiring decision.
So should we just try to turn off the emotional contribution
to decision making and proceed in as analytical a manner as possible
using something like Bazerman's procedure?
I doubt that it is possible or even desirable to turn hiring and
other decisions into matters of cold calculation (Thagard, 2001).
Our brains are wired with many interconnections between cognitive
areas such as the neocortex and emotional areas such as the amygdala
(Damasio, 1994). There is no way we can shut down the amygdala,
which contributes to emotional assessments via dense connections
with bodily states. Moreover, if Damasio's patients (who have
brain damage that interferes with neocortex-amygdala connections)
are a good indication, then shutting down the amygdala would worsen
rather than improve decision making. These patients have normal
verbal and mathematical abilities, but tend to be ineffective
and even irresponsible in their personal and social decisions.
Hence I do not think that we can write emotions out of the
practical reasoning process.
Still, there is lots of room for improvement in decisions based
on emotional intuitions. Thagard (2001) advocates the process
of 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 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 is obviously applicable to hiring decisions and
would, I hope lead to the hiring of the best person for the job.
This model of decision making applies to individual thinkers,
but much decision making is social, involving the need to accommodate
the views and preferences of various members in a group. Emotions
can definitely be a hindrance to social decision making, if some
members are irrationally exuberant about or obstinately resistant
to particular options. But emotions can also be valuable in
communicating people's preferences and evaluations. If I am
trying to coordinate with people and see that they are getting
very upset by a potential action such as hiring a candidate, I
can realize that their strong emotions signal a strong preference
against the action. Alternatively, if they are as enthusiastic
as I am, then together we can achieve a kind of group emotional
coherence is that is very good for social solidarity.
Conclusion
In sum, both theoretical and practical reason involve processes
of generating alternatives and evaluating them in order to select
the best. Both generation and evaluation involve emotions, and
the involvement is often positive, when emotions guide the search
for attractive alternatives and when they signal a gestalt that
marks the achievement of a maximally coherent state of mind.
There is no realistic prospect of stripping these emotional contributions
from generation and evaluation. I would not want it otherwise,
since passion adds much to science, philosophy, and everyday life.
But the involvement of emotions can also be negative, when emotional
skewers impede the generation of attractive alternatives and distort
the evaluation of which alternatives are the best. To overcome
these negative effects of emotions, we need to adopt procedures
such as informed intuition that recognize and encourage the contributions
of affect to theoretical and practical reason, while watching
for the presence of distortions. In addition to being passionately
moderate, one should aim to be moderately passionate.
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