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European Journal of Operational Research 177 (2007) 1333–1352

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The affect heuristic q

Paul Slovic *, Melissa L. Finucane, Ellen Peters, Donald G. MacGregor

Decision Research Inc., 1201 Oak Street, Suite 200, Eugene, OR 97401, USA

Available online 16 October 2006

Abstract

This paper introduces a theoretical framework that describes the importance of affect in guiding judgments and deci-sions. As used here, ‘‘affect’’ means the specific quality of ‘‘goodness’’ or ‘‘badness’’ (i) experienced as a feeling state(with or without consciousness) and (ii) demarcating a positive or negative quality of a stimulus. Affective responsesoccur rapidly and automatically—note how quickly you sense the feelings associated with the stimulus word ‘‘treasure’’or the word ‘‘hate’’. We argue that reliance on such feelings can be characterized as ‘‘the affect heuristic’’. In this paperwe trace the development of the affect heuristic across a variety of research paths followed by ourselves and many oth-ers. We also discuss some of the important practical implications resulting from ways that this heuristic impacts ourdaily lives.� 2002 Cambridge University Press. Published by Elsevier B.V.

Keywords: Affect heuristic; Judgment; Decision making; Risk perception

1. Background

Although affect has long played a key role inmany behavioral theories, it has rarely been recog-

0377-2217/$ - see front matter � 2002 Cambridge University Press. Pdoi:10.1016/j.ejor.2005.04.006

q Reprinted from Gilovich, T., Griffin, D., Kahneman, D.(Eds.), 2002. Heuristics and Biases: The Psychology of IntuitiveJudgment. Cambridge University Press, New York. pp. 397–420. � Cambridge University Press 2002. Reprinted with per-mission. Financial support for the writing of this paper wasprovided by the National Science Foundation under Grant SES9876587.

* Corresponding author. Tel.: +1 541 485 2400; fax: +1 541485 2403.

E-mail address: [email protected] (P. Slovic).URL: http://www.decisionresearch.org (P. Slovic).

nized as an important component of human judg-ment and decision making. Perhaps befitting itsrationalistic origins, the main focus of descriptivedecision research has been cognitive, rather thanaffective. When principles of utility maximizationappeared to be descriptively inadequate, Simon(1956) oriented the field toward problem solvingand information-processing models based uponbounded rationality. The work of Tversky andKahneman (1974) and Kahneman et al. (1982)demonstrated how boundedly rational individualsemploy heuristics such as availability, representa-tiveness, and anchoring and adjustment to makejudgments and how they use simplified strategiessuch as ‘‘elimination by aspects’’ to make choices

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http://www.decisionresearch.org

1334 P. Slovic et al. / European Journal of Operational Research 177 (2007) 1333–1352

(Tversky, 1972). Other investigators elaborated thecognitive strategies underlying judgment andchoice through models of constructed preferences(Slovic, 1995; Payne et al., 1993), dominance struc-turing (Montgomery, 1983), and comparativeadvantages (Shafir et al., 1989). In 1993, the entirevolume of the journal Cognition was dedicated tothe topic, Reason-Based Choice, in which it wasargued that ‘‘Decisions . . . are often reached byfocusing on reasons that justify the selection ofone option over another’’ (Shafir et al., 1993, p.34). Similarly, a state-of-the-art review by Buse-meyer et al. (1995) was titled ‘‘Decision Makingfrom a Cognitive Perspective’’. In keeping withits title, it contained almost no references to theinfluence of affect on decisions.

Despite this cognitive emphasis, the importanceof affect is being recognized increasingly by deci-sion researchers. A limited role for affect wasacknowledged by Shafir et al. (1993) who concededthat ‘‘People’s choices may occasionally stem fromaffective judgments that preclude a thorough eval-uation of the options’’ (p. 32, emphasis added).

A strong early proponent of the importance ofaffect in decision making was Zajonc (1980), whoargued that affective reactions to stimuli are oftenthe very first reactions, occurring automaticallyand subsequently guiding information processingand judgment. According to Zajonc, all percep-tions contain some affect. ‘‘We do not just see ‘ahouse’: We see a handsome house, an ugly house,or a pretentious house’’ (p. 154). He later adds,‘‘We sometimes delude ourselves that we proceedin a rational manner and weight all the pros andcons of the various alternatives. But this is proba-bly seldom the actual case. Quite often ‘‘I decidedin favor of X’’ is no more than ‘‘I liked X . . .’’ Webuy the cars we ‘‘like’’, choose the jobs and houseswe find ‘‘attractive’’, and then justify these choicesby various reasons. . .’’ (p. 155).

Affect also plays a central role in what havecome to be known as ‘‘dual-process theories’’ ofthinking, knowing, and information processing.As Epstein (1994), has observed,

There is no dearth of evidence in every day life thatpeople apprehend reality in two fundamentally dif-ferent ways, one variously labeled intuitive, auto-

matic, natural, nonverbal, narrative, andexperiential, and the other analytical, deliberative,verbal, and rational. (p. 710)

One of the characteristics of the experientialsystem is its affective basis. Although analysis iscertainly important in some decision-making cir-cumstances, reliance on affect and emotion is aquicker, easier, and more efficient way to navigatein a complex, uncertain, and sometimes dangerousworld. Many theorists have given affect a directand primary role in motivating behavior. Epstein’s(1994) view on this is as follows:

The experiential system is assumed to be intimatelyassociated with the experience of affect, . . . whichrefer[s] to subtle feelings of which people are oftenunaware. When a person responds to an emotion-ally significant event . . . the experiential systemautomatically searches its memory banks forrelated events, including their emotional accompa-niments . . . If the activated feelings are pleasant,they motivate actions and thoughts anticipated toreproduce the feelings. If the feelings are unpleas-ant, they motivate actions and thoughts antici-pated to avoid the feelings. (p. 716)

Also emphasizing the motivational role ofaffect, Mowrer (1960a,b) conceptualized condi-tioned emotional responses to images as prospec-tive gains and losses that directly ‘‘guide andcontrol performance in a generally sensible adap-tive manner’’ (1960a, p. 30). He criticized theoristswho postulate purely cognitive variables such asexpectancies (probabilities) intervening betweenstimulus and response, cautioning that we mustbe careful not to leave the organism at the choicepoint ‘‘lost in thought’’. Mowrer’s solution wasto view expectancies more dynamically (as condi-tioned emotions such as hopes and fears) servingas motivating states leading to action.

One of the most comprehensive and dramatictheoretical accounts of the role of affect in decisionmaking is presented by the neurologist, AntonioDamasio (1994), in his book Descartes’ Error:Emotion, Reason, and the Human Brain. Damasio’stheory is derived from observations of patientswith damage to the ventromedial frontal corticesof the brain that has left their basic intelligence,

P. Slovic et al. / European Journal of Operational Research 177 (2007) 1333–1352 1335

memory, and capacity for logical thought intactbut has impaired their ability to ‘‘feel’’—that is,to associate affective feelings and emotions withthe anticipated consequences of their actions.Close observation of these patients combined witha number of experimental studies led Damasio toargue that this type of brain damage induces aform of sociopathy (Damasio et al., 1990) thatdestroys the individual’s ability to make rationaldecisions; that is, decisions that are in his or herbest interests. Persons suffering this damagebecame socially dysfunctional even though theyremain intellectually capable of analyticalreasoning.

Commenting on one particularly significantcase, Damasio observes:

The instruments usually considered necessary andsufficient for rational behavior were intact inhim. He had the requisite knowledge, attention,and memory; his language was flawless; he couldperform calculations; he could tackle the logic ofan abstract problem. There was only one signifi-cant accompaniment to his decision-making fail-ure: a marked alteration of the ability toexperience feelings. Flawed reason and impairedfeelings stood out together as the consequencesof a specific brain lesion, and this correlation sug-gested to me that feeling was an integral compo-nent of the machinery of reason. (p. XII)

In seeking to determine ‘‘what in the brainallows humans to behave rationally’’, Damasioargues that thought is made largely from images,broadly construed to include sounds, smells, realor imagined visual impressions, ideas, and words.A lifetime of learning leads these images to become‘‘marked’’ by positive and negative feelings linkeddirectly or indirectly to somatic or bodily states(Mowrer and other learning theorists would callthis conditioning): ‘‘In short, somatic markers

are . . . feelings generated from secondary emotions.

These emotions and feelings have been connected,by learning, to predicted future outcomes of certain

scenarios’’ (Damasio, 1994, p. 174). When a nega-tive somatic marker is linked to an image of afuture outcome it sounds an alarm. When a posi-tive marker is associated with the outcome image,it becomes a beacon of incentive. Damasio con-

cludes that somatic markers increase the accuracyand efficiency of the decision process and theirabsence degrades decision performance.

Damasio tested the somatic marker hypothesisin a decision making experiment in which subjectsgambled by selecting cards from any of four decks.Turning each card resulted in the gain or loss of asum of money, as revealed on the back of the cardwhen it was turned. Whereas normal subjects andpatients with brain lesions outside the prefrontalsectors learned to avoid decks with attractive largepayoffs but occasional catastrophic losses, patientswith frontal lobe damage did not, thus losing agreat deal of money. Although these patientsresponded normally to gains and losses when theyoccurred (as indicated by skin conductanceresponses immediately after an outcome was expe-rienced) they did not seem to learn to anticipate

future outcomes (e.g., they did not produce nor-mal skin conductance responses when contemplat-ing a future choice from a dangerous deck). Inother words, they failed to show any proper antic-ipatory responses, even after numerous opportuni-ties to learn them.

Despite the increasing popularity of affect inresearch programs and recent attempts toacknowledge the importance of the interplaybetween affect and cognition, further work isneeded to specify the role of affect in judgmentand decision making. The ideas articulated beloware intended as a step toward encouraging thedevelopment of theory about affect and decisionmaking and demonstrating how such a theorycan be tested.

The basic tenet of this paper is that images,marked by positive and negative affective feelings,guide judgment and decision making. Specifically,it is proposed that people use an affect heuristic tomake judgments. That is, representations ofobjects and events in people’s minds are taggedto varying degrees with affect. In the process ofmaking a judgment or decision, people consult orrefer to an ‘‘affect pool’’ containing all the positiveand negative tags consciously or unconsciouslyassociated with the representations. Just as imagi-nability, memorability, and similarity serve as cuesfor probability judgments (e.g., the availabilityand representativeness heuristics), affect may serve


as a cue for many important judgments. Using anoverall, readily available affective impression canbe far easier—more efficient—than weighing thepros and cons or retrieving from memory manyrelevant examples, especially when the requiredjudgment or decision is complex or mentalresources are limited. This characterization of amental short-cut leads to labeling the use of affecta ‘‘heuristic’’.

2. Empirical evidence

2.1. Manipulating preferences through controlled

exposures

The fundamental nature and importance ofaffect has been demonstrated repeatedly in aremarkable series of studies by Robert Zajoncand his colleagues (see, e.g., Zajonc, 1968). Theconcept of stimulus exposure is central to all ofthese studies. The central finding is that, whenobjects are presented to an individual repeatedly,the ‘‘mere exposure’’ is capable of creating a posi-tive attitude or preference for these objects.

In the typical study, stimuli such as nonsensephrases, or faces, or Chinese ideographs are pre-sented to an individual with varying frequencies.In a later session, the individual judges these stim-uli on liking, or familiarity, or both. The more fre-quent the prior exposure to a stimulus, the morepositive the response. A meta-analysis by Born-stein (1989) of mere exposure research publishedbetween 1968 and 1987 included over 200 experi-ments examining the exposure–affect relationship.Unreinforced exposures were found to reliablyenhance affect toward visual, auditory, gustatory,abstract, and social stimuli.

Winkielman et al. (1997) demonstrated thespeed with which affect can influence judgmentsin studies employing a subliminal priming para-digm. Participants were ‘‘primed’’ through expo-sure to a smiling face, a frowning face, or aneutral polygon presented for 1/250 of a second,an interval so brief that there is no recognitionor recall of the stimulus. Immediately followingthis exposure, an ideograph was presented fortwo seconds, following which the participant rated

the ideograph on a scale of liking. Mean liking rat-ings were significantly higher for ideographs pre-ceded by smiling faces. This effect was lasting. Ina second session, ideographs were primed by the‘‘other face’’, the one not associated with the stim-ulus in the first session. This second priming wasineffective because the effect of the first primingremained.

It is not just subliminal smiles that affect ourjudgment. La France and Hecht (1995) found thatstudents accused of academic misconduct whowere pictured as smiling received less punishmentthan nonsmiling transgressors. Smiling personswere judged as more trustworthy, good, honest,genuine, obedient, blameless, sincere, and admira-ble than nonsmiling targets.

The perseverance of induced preferences wastested by Sherman et al. (1998) who asked partic-ipants to study Chinese characters and their Eng-lish meanings. Half of the meanings were positive(e.g., beauty), half were negative (e.g., disease).Then participants were given a test of these mean-ings followed by a task in which they were givenpairs of characters and were asked to choose theone they preferred. Participants preferred charac-ters with positive meaning 70% of the time. Next,the characters were presented with neutral mean-ings (desk, linen) and subjects were told that thesewere the ‘‘true’’ meanings. The testing procedurewas repeated and, despite learning the new mean-ings, the preferences remained the same. Charac-ters that had been initially paired with positivemeanings still tended to be preferred.

These various studies demonstrate that affect isa strong conditioner of preference, whether or notthe cause of that affect is consciously perceived.They also demonstrate the independence of affectfrom cognition, indicating that there may be con-ditions of affective or emotional arousal that donot necessarily require cognitive appraisal. Thisaffective mode of response, unburdened by cogni-tion and hence much faster, has considerableadaptive value.

2.2. Evaluating gambles

The affect heuristic can explain a finding thathas intrigued and perplexed the first author since

MeanPrice

MeanRating (0–20 scale)

29/36 to win $2 $1.25 13.27/36 to win $9 $2.11 7.5


he first observed it in 1984. Slovic and Amos Tver-sky were reexamining the early studies of Slovicand Lichtenstein (1968) and Lichtenstein and Slo-vic (1971, 1973), which pointed at compatibilitybetween stimulus attributes and response scalesas an explanation for preference reversals. Suchreversals were exhibited when an individual choseGamble A (with a high probability of winning amodest amount of money) over Gamble B (witha smaller probability of a larger payoff) butassigned a larger monetary value (buying price orselling price) to Gamble B. Presumably the rever-sal occurred because the gamble payoffs were givenmore weight in the pricing response mode than inchoice, due to the compatibility between prices andpayoffs, both of which were measured in dollars.

Tversky and Slovic decided to replicate the ear-lier reversal studies with three changes:

1. The complexity of the gamble was minimizedby eliminating losses. Each gamble consistedmerely of a stated probability of winning a givenamount. There was no possible loss of money.

2. Following Goldstein (later Goldstein andEinhorn, 1987), who observed reversals with rat-ings and prices, we included ratings of a gamble’sattractiveness along with choices and pricing asmethods of eliciting preferences. The attractivenessscale ranged between 0 (not at all attractive) and20 (very attractive).

3. To ensure the strategic equivalence of ourthree elicitation procedures, we devised a methodfor linking preferences to outcomes that was iden-tical across all conditions. Subjects were told that apair of bets would be selected and the bet thatreceived the higher attractiveness rating (or thehigher price, or that was preferred in the choicetask) would be the bet they would play. Conse-quently, the preferences elicited by prices and rat-ings should not differ from each other or from thepreferences elicited by direct choices. Some of thegambles were, in fact, actually played.

Using this design, we observed strong differ-ences between response modes, leading to manypreference reversals. Particularly striking was thedifference between ratings and prices. Ratings pro-duced an overwhelming dominance of high proba-bility bets over high payoff bets (the bet withhigher probability of winning had the higher

attractiveness rating 80–90% of the time, but wasassigned a higher price only 10–15% of the time).The mean evaluations of the following two betswere typical:

Seeking to explain these results in terms of com-patibility, we linked the compatibility effect to theease of mapping the stimulus component of a gam-ble onto the response scale. The easier it is to exe-cute such a mapping, the greater the weight giventhe component. In principle, a gamble’s payoff ismore compatible with a price response than witha rating, because prices and payoffs are bothexpressed in dollars. Hence payoffs should getgreater weight in pricing than in rating. The extre-mely high weight given probabilities when ratingattractiveness may be explained by the fact thatthe probabilities are more readily coded as attrac-tive or unattractive than are the payoffs. Forexample, 29 out of 36 chances to win are veryattractive odds. On the other hand, a $9 payoffmay be harder to map on a rating scale becauseits attractiveness depends on what other payoffsare available.

According to this explanation, if we could makea gamble’s payoff more compatible with the attrac-tiveness rating, we would presumably enhance theweight given to payoff in the rating response mode.We attempted to do this in a new experiment,focusing on the gamble 7/36 to win $9. To makethe payoff more compatible with regard to thescale of attractiveness, we added a very small loss(5¢) to the gamble

7=36 win $9;

29=36 lose 5!.

Whereas the attractiveness of $9 might not bereadily apparent, we reasoned that a bet offering$9 to win and only 5¢ to lose should appear tohave a very attractive payoff ratio. This led us to


predict that one might increase the attractivenessof a gamble (p to win X) by adding a loss compo-nent to it.

The results exceeded our expectations. Thegamble with no loss had the lower attractivenessrating (mean = 9.4 on the 0–20 scale). Adding a5¢ loss led to a much higher attractiveness rating(mean = 14.9). Even the bet

7=36 win $9;

29=36 lose 25!.

was judged more attractive (mean = 11.7) than thebet with no loss.

Would adding a small loss to the gambleenhance its attractiveness in choice as it did in rat-ing? We recently addressed this question by asking96 University of Oregon students to choosebetween playing a gamble, and receiving a gainof $2. For half of the students, the gamble was7/36 to win $9; for the others, the gamble hadthe 5¢ loss. Whereas only 33.3% chose the $9 gam-ble over the $2, 60.8% chose the ($9; �5¢) gambleover the $2. A replication study with $4 as thealternative to the gamble produced similar results.The enhancement produced by adding a small lossthus holds for choices as well as for ratingresponses.

The enhanced attractiveness produced by smalllosses was originally predicted and explained interms of compatibility, and we now see it also asan example of the affect heuristic. This broaderperspective was induced, in part, by resultsobtained later by Mellers et al. (1992) and Hsee(1995, 1996a,b, 1998) and by our own subsequentstudies of imagery, affect, and decision making.These convergent streams of research are describedin the following sections.

2.3. Image, affect, and decision making

The early anomalous findings with gambleswere laid aside while other means of explainingthe differences between ratings, choices, and pric-ing responses were developed (see Tversky et al.,1990). At the same time, Slovic and colleagues atDecision Research embarked on a research pro-gram designed to test whether introducing a haz-

ardous facility into a region might stigmatizethat region and cause people to avoid going thereto recreate, retire, or do business. Believing self-report to be unreliable (‘‘If they build it, will younot come?’’), research on stigmatization was con-ducted through a number of empirical studiesdesigned to examine the relationship betweenimagery, affect, and decision making. After con-ducting these studies, we learned that they fit clo-sely with a large body of existing theory andresearch such as the work of Damasio, Mowrer,and Epstein, described earlier.

Several empirical studies have demonstrated astrong relationship between imagery, affect, anddecision making. Many of these studies used aword-association technique. This method involvespresenting subjects with a target stimulus, usuallya word or very brief phrase, and asking them toprovide the first thought or image that comes tomind. The process is then repeated a number oftimes, say three to six, or until no further associa-tions are generated. Following the elicitation ofimages, subjects are asked to rate each image theygive on a scale ranging from very positive (e.g.,+2) to very negative (e.g., �2), with a neutral pointin the center. Scoring is done by summing or aver-aging the ratings to obtain an overall index.

This imagery method has been used successfullyto measure the affective meanings that influencepeople’s preferences for different cities and states(Slovic et al., 1991), as well as their support oropposition to technologies such as nuclear power(Peters and Slovic, 1996).

Table 1 illustrates the method in a task whereone respondent was asked to give associations toeach of two cities and, later, to rate each imageaffectively. The cities in this example show a clearaffective preference for San Diego over Denver.Slovic et al. (1991) showed that summed imagescores such as these were highly predictive ofexpressed preferences for living in or visiting cities.In one study they found that the image score pre-dicted the location of actual vacations during thenext 18 months.

Subsequent studies have found affect-ladenimagery elicited by word associations to be predic-tive of preferences for investing in new companieson the stock market (MacGregor et al., 2000) and

Table 1Images, ratings, and summation scores for one respondent

Stimulus Imagenumber

Image Imagerating

San Diego 1 Very nice 2San Diego 2 Good beaches 2San Diego 3 Zoo 2San Diego 4 Busy freeway 1San Diego 5 Easy to find way 1San Diego 6 Pretty town 2

Sum = 10

Denver 1 High 2Denver 2 Crowded 0Denver 3 Cool 2Denver 4 Pretty 1Denver 5 Busy airport �2Denver 6 Busy streets �2

Sum = 1

Note: Based on these summation scores, this person’s predictedpreference for a vacation site would be San Diego. Source:Slovic et al. (1991).

Table 2Attributes of two dictionaries in Hsee’s study

Year ofpublication

Number ofentries

Any defects?

Dictionary A 1993 10,000 No, it’s like newDictionary B 1993 20,000 Yes, the cover is

torn; otherwise it’slike new

Source: Adapted from Hsee (1998).


predictive of adolescents’ decisions to take part inhealth-threatening and health-enhancing behav-iors such as smoking and exercise (Benthin et al.,1995).

2.4. Evaluability

The research with images points to the impor-tance of affective impressions in judgments anddecisions. However, the impressions themselvesmay vary not only in their valence but in the pre-cision with which they are held. It turns out thatthe precision of an affective impression substan-tially impacts judgments.

We shall refer to the distributional qualities ofaffective impressions and responses as ‘‘affectivemappings’’. Consider, for example, some questionsposed by Mellers et al. (1992): ‘‘How much wouldyou like a potential roommate if all you knewabout her was that she was said to be intelligent?’’Or, ‘‘Suppose, instead, all you knew about her wasthat she was said to be obnoxious?’’ Intelligence isa favorable trait but it is not very diagnostic (e.g.,meaningful) for likeableness, hence its affectivemap is rather diffuse. In contrast, obnoxiousnesswill likely produce a more precise and more nega-tive impression.

How much would you like a roommate said tobe both intelligent and obnoxious? Anderson(1981) has shown that the integration of multiplepieces of information into an impression of thissort can be described well by a weighted averagemodel where separate weights are given to intelli-gence and obnoxiousness, respectively. Mellerset al. (1992) further showed that the weights insuch integrative tasks are inversely proportionalto the variance of the impressions. Thus we wouldexpect the impression produced by the combina-tion of these two traits to be closer to the impres-sion formed by obnoxiousness alone, reflectinggreater weight given to obnoxiousness due to itssmaller variance (more precise affective mapping).The meaning of a stimulus image appears to bereflected in the precision of the affective feelingsassociated with that image. More precise affectiveimpressions reflect more precise meanings andcarry more weight in impression formation, judg-ment, and decision making.

Hsee (1996a,b, 1998) has developed the notionof evaluability to describe the interplay betweenthe precision of an affective impression and itsmeaning or importance for judgment and decisionmaking. Evaluability is illustrated by an experi-ment in which Hsee asked people to assume theywere music majors looking for a used music dictio-nary. In a joint-evaluation condition, participantswere shown two dictionaries, A and B (see Table2), and asked how much they would be willing topay for each. Willingness-to-pay was far higherfor Dictionary B, presumably because of its greaternumber of entries. However, when one group ofparticipants evaluated only A and another groupevaluated only B, the mean willingness to paywas much higher for Dictionary A. Hsee explains


this reversal by means of the evaluability principle.He argues that, without a direct comparison, thenumber of entries is hard to evaluate, because theevaluator does not have a precise notion of how

good or how bad 10,000 (or 20,000) entries is. How-ever, the defects attribute is evaluable in the sensethat it translates easily into a precise good/badresponse and thus it carries more weight in theindependent evaluation. Most people find a defec-tive dictionary unattractive and a like-new oneattractive. Under joint evaluation, the buyer cansee that B is far superior on the more importantattribute, number of entries. Thus number ofentries becomes evaluable through the comparisonprocess.

According to the evaluability principle, theweight of a stimulus attribute in an evaluativejudgment or choice is proportional to the ease orprecision with which the value of that attribute(or a comparison on the attribute across alterna-tives) can be mapped into an affective impression.In other words, affect bestows meaning on infor-mation (cf., Osgood et al., 1957; Mowrer,1960a,b) and the precision of the affective meaninginfluences our ability to use information in judg-ment and decision making. Evaluability can thusbe seen as an extension of the general relationshipbetween the variance of an impression and itsweight in an impression-formation task (Mellerset al., 1992).

Hsee’s work in evaluability is noteworthybecause it shows that even very important attri-butes may not be used by a judge or decisionmaker unless they can be translated precisely intoan affective frame of reference. As described inthe next section, Hsee finds evaluability effectseven with familiar attributes such as the amountof ice cream in a cup (Hsee, 1998). We will alsodemonstrate similar effects with other familiar con-cepts such as amounts of money or human lives.

2.5. Proportion dominance

In situations that involve uncertainty aboutwhether we will win or lose or that involve ambi-guity about some quantity of something (i.e.,how much is enough), there appears to be oneinformation format that is highly evaluable, lead-

ing it to carry great weight in many judgmenttasks. This is a representation characterizing anattribute as a proportion or percentage of some-thing, or as a probability. At the suggestion ofChris Hsee (personal communication), we shallrefer to the strong effects of this type of represen-tation as ‘‘proportion dominance’’.

Proportion (or probability) dominance was evi-dent in the studies of gambles described at thebeginning of this paper. Ratings of a gamble’sattractiveness tend to be determined far morestrongly by the probabilities of winning and losingthan by the monetary payoffs. The curious findingthat adding a small loss to a gamble increases itsrated attractiveness, explained originally as a com-patibility effect, can now be seen to fit well with thenotions of affective mapping and evaluability.

According to this view, a probability maps rel-atively precisely onto the attractiveness scalebecause probability has a lower and upper bound(0 and 1) and a midpoint below which a probabil-ity is ‘‘poor’’ or ‘‘bad’’ (i.e., has worse than an evenchance) and above which it is ‘‘good’’ (i.e., has abetter than even chance). People know where agiven value, such as 7/36, falls within the bounds,and exactly what it means—‘‘I’m probably notgoing to win’’. In contrast, the mapping of a dollaroutcome (e.g., $9) onto the attractiveness scale isdiffuse, reflecting a failure to know how good orbad or how attractive or unattractive $9 is. Thus,the impression formed by the gamble offering $9to win with no losing payoff is dominated by therelatively precise and unattractive impression pro-duced by the 7/36 probability of winning. How-ever, adding a very small loss to the payoffdimension brings the $9 payoff into focus and thusgives it meaning. The combination of a possible $9gain and a 5¢ loss is a very attractive win/loss ratio,leading to a relatively precise mapping onto theupper end of the scale. Whereas the imprecisemapping of the $9 carries little weight in the aver-aging process, the more precise and now favorableimpression of ($9; �5¢) carries more weight, thusleading to an increase in the overall favorabilityof the gamble.

The effect of adding a small loss to the gamblecan also be explained by norm theory (Kahnemanand Miller, 1986). But a norm-theoretical explana-

Fig. 1. Stimuli in ice cream study by Hsee (1998). Participantswere given the sizes of the cups and the amounts of ice cream.


tion is consistent with an affective account. Itasserts that the gamble with no loss is a relativelymediocre representative of the set of all positivegambles whereas the gamble with a small loss isa relatively attractive member of the class of mixed(win/loss) gambles.

Proportion dominance surfaces in a powerfulway in a very different context, the life-saving inter-ventions studied by Fetherstonhaugh et al. (1997),Baron (1997), Jenni and Loewenstein (1997) andFriedrich et al. (1999). For example, Fetherston-haugh et al. found that people’s willingness to inter-vene to save a stated number of lives wasdetermined more by the proportion of lives savedthan by the actual number of lives that would besaved. However, when two or more interventionswere directly compared, number of lives savedbecome more important than proportion saved.Thus, number of lives saved, standing alone,appears to be poorly evaluable, as was the casefor number of entries in Hsee’s music dictionaries.With a side-by-side comparison, the number of livesbecame clearly evaluable and important, as alsohappened with the number of dictionary entries.

Slovic (unpublished), drawing upon proportiondominance and the limited evaluability of numbersof lives, predicted (and found) that people, in abetween-groups design, would more strongly sup-port an airport-safety measure expected to save98% of 150 lives at risk than a measure expectedto save 150 lives. Saving 150 lives is diffusely good,hence only weakly evaluable, whereas saving 98%of something is clearly very good because it is soclose to the upper bound on the percentage scale,

Table 3Proportion dominance and airport safety

Potential benefit

Save 150 lives Save 98%

Mean supporta 10.4 13.6Mediana 9.8 14.3% of ratings P 13 37 75

Saving a percentage of 150 lives receives higher support ratings thana Cell entries in these rows describe mean and median responses t

measure to purchase the new equipment?’’ (Critics argue that the moaspects of airport safety). The response scale ranged from 0 (would noresulted in F4200 = 3.36, p = .01. The save 98% and save 95% condcondition at p < .05, Tukey HSD test.

and hence is readily evaluable and highly weightedin the support judgment. Subsequent reduction ofthe percentage of 150 lives that would be saved to95%, 90%, and 85% led to reduced support for thesafety measure but each of these percentage condi-tions still garnered a higher mean level of supportthan did the save 150 lives condition (see Table 3).

Turning to a more mundane form of proportiondominance, Hsee (1998) found that an overfilledice cream container with 7 oz. of ice cream was val-ued more highly (measured by willingness to pay)than an underfilled container with 8 oz. of icecream (see Fig. 1). This ‘‘less is better effect’’reversed itself when the options were juxtaposedand evaluated together. Thus, the proportion ofthe serving cup that was filled appeared to be moreevaluable (in separate judgments) than the abso-lute amount of ice cream.

2.6. Insensitivity to probability

Outcomes are not always affectively as vague asthe quantities of money, ice cream, and lives that

Save 95% Save 90% Save 85%

12.9 11.7 10.914.1 11.3 10.869 35 31

does saving 150 lives.o the question: ‘‘How much would you support this proposedney spent on this system could be better spent enhancing othert support at all) to 20 (very strong support). An overall ANOVAitions were both significantly different from the save 150 lives


were dominated by proportion in the above exper-iments. When consequences carry sharp andstrong affective meaning, as is the case with a lot-tery jackpot or a cancer, the opposite phenomenonoccurs—variation in probability often carries toolittle weight. As Loewenstein et al. (2001) observe,one’s images and feelings toward winning the lot-tery are likely to be similar whether the probabilityof winning is one in 10 million or one in 10,000.They further note that responses to uncertain situ-ations appear to have an all or none characteristicthat is sensitive to the possibility rather than theprobability of strong positive or negative conse-quences, causing very small probabilities to carrygreat weight. This, they argue, helps explain manyparadoxical findings such as the simultaneousprevalence of gambling and the purchasing ofinsurance. It also explains why societal concernsabout hazards such as nuclear power and exposureto extremely small amounts of toxic chemicals failto recede in response to information about thevery small probabilities of the feared consequencesfrom such hazards. Support for these argumentscomes from Rottenstreich and Hsee (2001) whoshow that, if the potential outcome of a gambleis emotionally powerful, its attractiveness or unat-tractiveness is relatively insensitive to changes inprobability as great as from 0.99 to 0.01.

2.7. Mid-course summary

We can now see that the puzzling finding ofincreased attractiveness for the gambles to whicha loss was appended is part of a larger story thatcan be summarized as follows:

1. Affect, attached to images, influences judg-ments and decisions.

2. The evaluability of a stimulus image isreflected in the precision of the affective feelingsassociated with that image. More precise affectiveimpressions reflect more precise meanings (i.e.,greater evaluability) and carry more weight inimpression formation, judgment, and decisionmaking.

3. The anomalous findings from the experi-ments with gambles, ice cream preferences, andlife-saving interventions suggest that, without acontext to give affective perspective to quantities

of dollars, ice cream, and lives, these quantitiesmay convey little meaning. Amounts of anything,no matter how common or familiar or intrinsicallyimportant, may in some circumstances not beevaluable.

4. Probabilities or proportions, on the otherhand, often are highly evaluable, reflecting the easewith which people recognize that a high probabil-ity of a desirable outcome is good and a low prob-ability is bad. When the quantities or outcomes towhich these probabilities apply are affectively pal-lid, probabilities carry much more weight in judg-ments and decisions. However, just the oppositeoccurs when the outcomes have precise and strongaffective meanings—variations in probability carrytoo little weight.

2.8. The affect heuristic in judgments of risk and

benefit

Another stream of research that, in conjunctionwith many of the findings reported above, led us topropose the affect heuristic, had its origin in theearly study of risk perception reported by Fisch-hoff et al. (1978). One of the findings in this studyand numerous subsequent studies was that percep-tions of risk and society’s responses to risk werestrongly linked to the degree to which a hazardevoked feelings of dread (see also Slovic, 1987).Thus activities associated with cancer are seen asriskier and more in need of regulation than activi-ties associated with less dreaded forms of illness,injury, and death (e.g., accidents).

A second finding in the study by Fischhoff et al.has been even more instrumental in the study ofthe affect heuristic. This is the finding that judg-ments of risk and benefit are negatively correlated.For many hazards, the greater the perceived bene-fit, the lower the perceived risk and vice versa.Smoking, alcoholic beverages, and food additives,for example, tend to be seen as very high in riskand relatively low in benefit, whereas vaccines,antibiotics, and X-rays tend to be seen as high inbenefit and relatively low in risk. This negativerelationship is noteworthy because it occurs evenwhen the nature of the gains or benefits from anactivity is distinct, and qualitatively different fromthe nature of the risks. That the inverse relation-

Perceivedbenefit

Perceivedrisk

Affect

Fig. 2. A model of the affect heuristic explaining the risk/benefit confounding observed by Alhakami and Slovic (1994).Judgments of risk and benefit are assumed to be derived byreference to an overall affective evaluation of the stimulus item.Source: Finucane et al. (2000).

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ship is generated in people’s minds is suggested bythe fact that risk and benefits generally tend to bepositively (if at all) correlated in the world. Activ-ities that bring great benefits may be high or low inrisk but activities that are low in benefit are unli-kely to be high in risk (if they were, they wouldbe proscribed).

A study by Alhakami and Slovic (1994) foundthat the inverse relationship between perceived riskand perceived benefit of an activity (e.g., using pes-ticides) was linked to the strength of positive ornegative affect associated with that activity. Thisresult implies that people base their judgments ofan activity or a technology not only on what theythink about it but also on what they feel about it. Ifthey like an activity, they are moved to judge therisks as low and the benefits as high; if they dislikeit, they tend to judge the opposite—high risk andlow benefit.

Alhakami and Slovic’s (1994) findings sug-gested that use of the affect heuristic guides percep-tions of risk and benefit as depicted in Fig. 2. If so,

C

A

Information says “Benefit is high”.

Risk inferredto be low

Nuclear Power

Positive

Information says “Benefit is low”.

Risk inferredto be high

I

Nuclear Power

Negative

Fig. 3. Model showing how information about benefit (A) or informatof nuclear power and lead to inferences about risk and benefit thinformation could decrease the overall affective evaluation of nuclear

providing information about risk should changethe perception of benefit and vice-versa (seeFig. 3). For example, information stating that riskwas low for some technology should lead to morepositive overall affect that would, in turn, increaseperceived benefit. Indeed, Finucane et al. (2000)

D

B

Information says “Risk is low”.

Benefits inferred to be

high

Nuclear Power

Positive

nformation says “Risk is high”.

Benefitinferred to be

low

Nuclear Power

Negative

ion about risk (B) could increase the overall affective evaluationat coincide affectively with the information given. Similarly,power as in C and D. Source: Finucane et al. (2000).

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conducted this experiment, providing four differ-ent kinds of information designed to manipulateaffect by increasing or decreasing perceived riskand increasing or decreasing perceived benefit. Ineach case there was no apparent logical relationbetween the information provided (e.g., informa-tion about risks) and the nonmanipulated variable(e.g., benefits). The predictions were confirmed.When the information that was provided changedeither the perceived risk or the perceived benefit,an affectively congruent but inverse effect wasobserved on the nonmanipulated attribute asdepicted in Fig. 3. These data support the theorythat risk and benefit judgments are causally deter-mined, at least in part, by the overall affectiveevaluation.

The affect heuristic also predicts that using timepressure to reduce the opportunity for analyticdeliberation (and thereby allowing affective con-siderations freer rein), should enhance the inverserelationship between perceived benefits and risks.In a second study, Finucane et al. showed thatthe inverse relationship between perceived risksand benefits increased greatly under time pressure,as predicted. These two experiments with judg-ments of benefits and risks are important becausethey support the contention by Zajonc (1980) thataffect influences judgment directly and is not sim-ply a response to a prior analytic evaluation.

Further support for the model in Fig. 2 hascome from two very different domains—toxicol-ogy and finance. Slovic et al. (1999) surveyed mem-bers of the British Toxicological Society and foundthat these experts, too, produced the same inverserelation between their risk and benefit judgments.As expected, the strength of the inverse relationwas found to be mediated by these experts’ affec-tive reactions toward the hazard items beingjudged. In a second study, these same toxicologistswere asked to make a ‘‘quick intuitive rating’’ foreach of 30 chemical items (e.g., benzene, aspirin,second hand cigarette smoke, dioxin in food) onan affect scale (bad–good). Next, they were askedto judge the degree of risk associated with a very

small exposure to the chemical, defined as an expo-sure that is less than 1/100 of the exposure levelthat would begin to cause concern for a regulatoryagency. Rationally, because exposure was so low,

one might expect these risk judgments to be uni-formly low and unvarying, resulting in little orno correlation with the ratings of affect. Instead,there was a strong correlation across chemicalsbetween affect and judged risk of a very smallexposure. When the affect rating was strongly neg-ative, judged risk of a very small exposure washigh; when affect was positive, judged risk wassmall. Almost every respondent (95 out of 97)showed this negative correlation (the median cor-relation was �0.50). Importantly, those toxicolo-gists who produced strong inverse relationsbetween risk and benefit judgments in the firststudy also were more likely to exhibit a high corre-spondence between their judgments of affect andrisk in the second study. In other words, acrosstwo different tasks, reliable individual differencesemerged in toxicologists’ reliance on affective pro-cesses in judgments of chemical risks.

In the realm of finance, Ganzach (2001) foundsupport for a model in which analysts base theirjudgments of risk and return for unfamiliar stocksupon a global attitude. If stocks were perceived asgood, they were judged to have high return andlow risk, whereas if they were perceived as bad,they were judged to be low in return and high inrisk. However, for familiar stocks, perceived riskand return were positively correlated, rather thanbeing driven by a global attitude.

2.9. Judgments of probability, relative frequency,

and risk

The affect heuristic has much in common withthe model of ‘‘risk as feelings’’ proposed by Loe-wenstein et al. (2001) and with dual process theo-ries put forth by Epstein (1994), Sloman (1996),and others. Recall that Epstein argues that individ-uals apprehend reality by two interactive, parallelprocessing systems. The rational system is a delib-erative, analytical system that functions by way ofestablished rules of logic and evidence (e.g., prob-ability theory). The experiential system encodesreality in images, metaphors, and narratives towhich affective feelings have become attached.

To demonstrate the influence of the experientialsystem, Denes-Raj and Epstein (1994) showed that,when offered a chance to win a prize by drawing a


red jelly bean from an urn, subjects often elected todraw from a bowl containing a greater absolutenumber, but a smaller proportion, of red beans(e.g., 7 in 100) than from a bowl with fewer redbeans but a better probability of winning (e.g., 1in 10). For these individuals, images of 7 winningbeans in the large bowl appeared to dominate theimage of 1 winning bean in the small bowl.

We can characterize Epstein’s subjects as fol-lowing a mental strategy of ‘‘imaging the numera-tor’’ (i.e., the number of red beans) and neglectingthe denominator (the number of beans in thebowl). Consistent with the affect heuristic, imagesof winning beans convey positive affect that moti-vates choice.

Although the jelly bean experiment may seemfrivolous, imaging the numerator brings affect tobear on judgments in ways that can be both non-intuitive and consequential. Slovic et al. (2000)demonstrated this in a series of studies in whichexperienced forensic psychologists and psychia-trists were asked to judge the likelihood that amental patient would commit an act of violencewithin 6 months after being discharged from thehospital. An important finding was that clinicianswho were given another expert’s assessment of apatient’s risk of violence framed in terms of rela-tive frequency (e.g., of every 100 patients similarto Mr. Jones, 10 are estimated to commit an actof violence to others . . .’’) subsequently labeledMr. Jones as more dangerous than did clinicianswho were shown a statistically ‘‘equivalent’’ riskexpressed as a probability (e.g., ‘‘Patients similarto Mr. Jones are estimated to have a 10% chanceof committing an act of violence to others’’).

Not surprisingly, when clinicians were told that‘‘20 out of every 100 patients similar to Mr. Jonesare estimated to commit an act of violence’’, 41%would refuse to discharge the patient. But whenanother group of clinicians was given the risk as‘‘patients similar to Mr. Jones are estimated tohave a 20% chance of committing an act of vio-lence’’, only 21% would refuse to discharge thepatient. Similar results have been found byYamagishi (1997), whose judges rated a diseasethat kills 1286 people out of every 10,000 as moredangerous than one that kills 24.14% of thepopulation.

Unpublished follow-up studies showed that rep-resentations of risk in the form of individual prob-abilities of 10% or 20% led to relatively benignimages of one person, unlikely to harm anyone,whereas the ‘‘equivalent’’ frequentistic representa-tions created frightening images of violent patients(example: ‘‘Some guy going crazy and killingsomeone’’). These affect-laden images likelyinduced greater perceptions of risk in response tothe relative-frequency frames.

Although frequency formats produce affect-laden imagery, story and narrative formats appearto do even better in that regard. Hendrickx et al.(1989) found that warnings were more effectivewhen, rather than being presented in terms of rel-ative frequencies of harm, they were presented inthe form of vivid, affect-laden scenarios and anec-dotes. Sanfey and Hastie (1998) found that com-pared with respondents given information in bargraphs or data tables, respondents given narrativeinformation more accurately estimated the perfor-mance of a set of marathon runners. Furthermore,Pennington and Hastie (1993) found that jurorsconstruct narrative-like summations of trial evi-dence to help them process their judgments of guiltor innocence.

Perhaps the biases in probability and frequencyjudgment that have been attributed to the avail-ability heuristic may be due, at least in part, toaffect. Availability may work not only throughease of recall or imaginability, but because remem-bered and imagined images come tagged withaffect. For example, Lichtenstein et al. (1978)invoked availability to explain why judged fre-quencies of highly publicized causes of death(e.g., accidents, homicides, fires, tornadoes, andcancer) were relatively overestimated and under-publicized causes (e.g., diabetes, stroke, asthma,tuberculosis) were underestimated. The highlypublicized causes appear to be more affectivelycharged, that is, more sensational, and this mayaccount both for their prominence in the mediaand their relatively overestimated frequencies.

2.10. Further evidence

The studies described above represent only asmall fraction of the evidence that can be


marshaled in support of the affect heuristic.Although we have developed the affect heuristicto explain findings from studies of judgment anddecision making (e.g., the inverse relationshipbetween perceived risks and benefits), one can findrelated proposals in the literature of marketingand social cognition. For example, Wright (1975)proposed the ‘‘affect-referral heuristic’’ as a mech-anism by which the remembered affect associatedwith a product influences subsequent choice ofthat product (see also Pham, 1998).

Attitudes have long been recognized as having astrong evaluative component (see, e.g., Thurstone,1928 or Edwards, 1957). Pratkanis (1989) definedattitude as ‘‘a person’s evaluation of an object ofthought’’ (p. 72). He went on to propose that atti-tudes serve as heuristics, with positive attitudesinvoking a favoring strategy toward an objectand negative attitudes creating disfavoringresponse. More specifically, he defined the ‘‘atti-tude heuristic’’ as the use of the evaluative relation-ship as a cue for assigning objects to a favorableclass or an unfavorable class, thus leading toapproach or avoidance strategies appropriate tothe class. Pratkanis described numerous phenom-ena that could be explained by the attitude heuris-tic, including halo effects not unlike the consistencydescribed earlier between risk and benefit judg-ments (Finucane et al., 2000).

Other important work within the field of socialcognition includes studies by Fazio (1995) on theaccessibility of affect associated with attitudesand by Schwarz and Clore (1988) on the role ofaffect as information.

Returning to the recent literature on judgmentand decision making, Kahneman and colleagueshave demonstrated that responses as diverse aswillingness to pay for the provision of a publicgood (e.g., protection of an endangered species)or a punitive damage award in a personal injurylawsuit seems to be derived from attitudes basedon emotion rather than on indicators of economicvalue (Kahneman and Ritov, 1994; Kahnemanet al., 1998).

Hsee and Kunreuther (2000) have demon-strated that affect influences decisions aboutwhether or not to purchase insurance. In onestudy, they found that people were willing to pay

twice as much to insure a beloved antique clock(that no longer works and cannot be repaired)against loss in shipment to a new city than toinsure a similar clock for which ‘‘one does nothave any special feeling’’. In the event of loss,the insurance paid $100 in both cases. Similarly,Hsee and Menon (1999) found that students weremore willing to buy a warranty on a newly pur-chased used car if it was a beautiful convertiblethan if it was an ordinary looking station wagon,even if the expected repair expenses and cost ofthe warranty were held constant.

Loewenstein et al. (2001) provide a particularlythorough review and analysis of research that sup-ports their ‘‘risk-as-feelings hypothesis’’, a conceptthat has much in common with the affect heuristic.They present evidence showing that emotionalresponses to risky situations, including feelingssuch as worry, fear, dread, or anxiety, often divergefrom cognitive evaluations and have a different andsometimes greater impact on risk-taking behaviorthan do cognitive evaluations. Among the factorsthat appear to influence risk behaviors by actingon feelings rather than cognitions are backgroundmood (e.g., Johnson and Tversky, 1983; Isen,1993), the time interval between decisions and theiroutcomes (Loewenstein, 1987), vividness (Hend-rickx et al., 1989), and evolutionary preparedness.Loewenstein et al. invoke the evolutionary perspec-tive to explain why people tend to react with littlefear to certain types of objectively dangerous stim-uli that evolution has not prepared them for, suchas guns, hamburgers, automobiles, smoking, andunsafe sex, even when they recognize the threat ata cognitive level. Other types of stimuli, such ascaged spiders, snakes, or heights, which evolutionmay have prepared us to fear, evoke strong visceralresponses even when we recognize them, cogni-tively, to be harmless.

Individual differences in affective reactivity alsoare informative. Damasio relied upon brain-dam-aged individuals, apparently lacking in the abilityto associate emotion with anticipated outcomes,to test his somatic-marker hypothesis. Similarinsensitivity to the emotional meaning of futureoutcomes has been attributed to psychopathicindividuals and used to explain their aberrantbehaviors (Hare, 1965; Patrick, 1994). Using the


Damasio card-selection task, Peters and Slovic(2000) found that normal subjects who reportedthemselves to be highly reactive to negative eventsmade fewer selections from decks with large losingpayoffs. Conversely, greater self-reported reactiv-ity to positive events was associated with a greaternumber of selections from high-gain decks. Thusindividual differences in affective reactivity appearto play a role in the learning and expression ofrisk-taking preferences.

3. The downside of affect

Throughout this paper we have made manyclaims for the affect heuristic, portraying it as thecenterpiece of the experiential mode of thinking,the dominant mode of survival during the evolutionof the human species. But, like other heuristics thatprovide efficient and generally adaptive responsesbut occasionally lead us astray, reliance on affectcan also deceive us. Indeed, if it was always optimalto follow our affective and experiential instincts,there would have been no need for the rational/ana-lytic system of thinking to have evolved and becomeso prominent in human affairs.

There are two important ways that experien-tial thinking misguides us. One results from thedeliberate manipulation of our affective reactionsby those who wish to control our behaviors. Theother results from the natural limitations of theexperiential system and the existence of stimuli inour environment that are simply not amenable tovalid affective representation. Both types of prob-lems are discussed below.

3.1. Manipulation of affect in our daily lives

Given the importance of experiential thinking itis not surprising to see many forms of deliberateefforts being made to manipulate affect in orderto influence our judgments and decisions. Con-sider, for example, some everyday questions aboutthe world of entertainment and the world of con-sumer marketing:

1. Why do entertainers often change theirnames?

Answer: To make them affectively more pleas-ing. One wonders whether the careers of JohnDenver, Sandra Dee, and Judy Garland wouldhave been as successful had they performedunder their real names—Henry Deutschendorf,Alexandra Zuck, and Frances Gumm. Studentsof onomastics, the science of names, have foundthat the intellectual products of persons withless attractive names are judged to be of lowerquality (Harari and McDavid, 1973; Erwinand Calev, 1984) and some have even assertedthat the affective quality of a presidential candi-date’s name influences the candidate’s chancesof being elected (Smith, 1997).

2. Why do movies have background music? Afterall, can’t we understand the events we arewatching and the dialog we are hearing withoutmusic?Answer: Music conveys affect and thusenhances meaning even for common humaninteractions and events.

3. Why are all the models in the mail-order catalogsmiling?Answer: To link positive affect to the clothingthey are selling.

4. Why do packages of food products carry allthose little blurbs such as ‘‘new’’, ‘‘natural’’,‘‘improved’’, or ‘‘98% fat free’’?Answer: These are ‘‘affective tags’’ that enhancethe attractiveness of the product and increasethe likelihood it will be purchased, much asadding ‘‘Save 98%’’ increased the attractivenessof saving 150 lives.

Clearly entertainers and marketers of consumerproducts have long been aware of the powerfulinfluence of affect. Perhaps no corporate entitieshave more zealously exploited consumers’ affectivesensitivities than the tobacco companies. A recentad for Kool Natural Lights, for example, repeatsthe word ‘‘natural’’ thirteen times in a singlehalf-page advertisement. The attractive images ofrugged cowboys and lush waterfalls associated withcigarette ads are known to all of us. Indeed, affec-tive associations between cigarettes and positiveimages may begin forming in children as youngas three years old (Fischer, 1991). As Epstein(1994) observes, ‘‘Cigarette advertising agencies


and their clients are willing to bet millions of dol-lars in advertising costs that the . . . appeal of theirmessages to the experiential system will prevailover the verbal message of the Surgeon Generalthat smoking can endanger one’s life, an appealdirected at the rational system’’ (p. 712). Throughthe workings of the affect heuristic, as explicatedby Finucane et al. (2000), we now have evidencesuggesting that cigarette advertising designed toincrease the positive affect associated with smokingwill quite likely depress perceptions of risk. Thefactual (impassionate) appeal by the Surgeon Gen-eral will likely have little effect.

Attempts at affective manipulation often workdirectly on language. Communicators desiring tochange attitudes toward stigmatized technologies,for example, created ‘‘nukespeak’’ to extol the vir-tues of ‘‘clean bombs’’ and ‘‘peacekeeper missiles’’,while promoters of nuclear power coined a newterm for reactor accidents: ‘‘excursions’’. Geneti-cally modified food has been promoted as‘‘enhanced’’ by proponents and ‘‘frankenfood’’by opponents.

Manipulation of attitudes and behavior by per-suasive argumentation is often quite effective, butat least it tends to be recognized as an attempt topersuade. Manipulation of affect is no less power-ful but is made more insidious by often takingplace without our awareness. It is unlikely thatHsee’s subjects recognized that what they werewilling to pay for the used music dictionary wasdetermined far more by the torn cover thanby the more important dimension, number ofentries.

Legal scholars such as Hanson and Kysar(1999a,b), paying close attention to research onaffect and other judgment heuristics, have begunto speak out on the massive manipulation of con-sumers by the packaging, marketing, and publicrelations practices of manufacturers. Such manip-ulation, they argue, renders ineffective three pri-mary forms of legal control over dangerousproducts—warning requirements, product liabilitysuits, and regulation of advertising. Hanson andKysar (2001) point to the need for new regulatorystrategies that would take into account the full lia-bility of manufacturers who manipulate consumersinto purchasing and using hazardous products.

3.2. Failures of the experiential system: The case

of smoking

Judgments and decisions can be faulty not onlybecause their affective components are manipula-ble, but also because they are subject to inherentbiases of the experiential system. For example,the affective system seems designed to sensitize usto small changes in our environment (e.g., the dif-ference between 0 and 1 deaths) at the cost of mak-ing us less able to appreciate and respondappropriately to larger changes (e.g., the differencebetween 570 deaths and 670 deaths). Fetherston-haugh et al. (1997) referred to this insensitivity as‘‘psychophysical numbing’’.

Similar problems arise when the outcomes thatwe must evaluate change very slowly over time, areremote in time, or are visceral in nature. The irra-tionality of decisions to smoke cigarettes providesdramatic examples of these types of failure (Slovic,2001).

Despite the portrayal of beginning smokers as‘‘young economists’’ rationally weighing the risksof smoking against the benefits when decidingwhether to initiate that activity (e.g., Viscusi,1992), recent research paints a different picture.This new account (Slovic, 2001) shows young smok-ers acting experientially in the sense of giving littleor no thought to risks or to the amount of smokingthey will be doing. Instead, they go with the affectiveimpulses of the moment, enjoying smoking as some-thing new and exciting, a way to have fun with theirfriends. Even after becoming ‘‘regulars’’, the greatmajority of smokers expect to stop soon, regardlessof how long they have been smoking, how many cig-arettes they currently smoke per day, or how manyprevious unsuccessful attempts they have experi-enced. Only a fraction actually quit, despite manyattempts. The problem is nicotine addiction, a con-dition that young smokers recognize by name as aconsequence of smoking but do not understandexperientially until they are caught up in it.

The process of becoming addicted appears tobegin surprisingly soon after one begins to smoke.Recent research indicates that adolescents begin toshow signs of nicotine dependence within days toweeks of the onset of occasional tobacco use (Di-Franza et al., 2000).


Loewenstein (1999) explains the process ofaddiction as being governed by immensely power-ful visceral factors or cravings that, from an expe-riential perspective, are very hard to anticipate andappreciate:

Unlike currently experienced visceral factors,which have a disproportionate impact on behav-ior, delayed visceral factors tend to be ignored orseverely underweighted in decision making.Today’s pain, hunger, anger, etc. are palpable,but the same sensations anticipated in the futurereceive little weight. (p. 240)

The failure of the experiential system to protectmany young people from the lure of smoking isnowhere more evident than in the responses to asurvey question that asks smokers: ‘‘If you had itto do all over again, would you start smoking?’’More than 85% of adult smokers and about 80%of young smokers (ages 14–22) answer ‘‘no’’ (Slo-vic, 2001). Moreover, the more individuals per-ceive themselves to be addicted, the more oftenthey have tried to quit, the longer they have beensmoking, and the more cigarettes they are smokingper day, the more likely they are to answer ‘‘no’’.

We can now address a central question posedby Viscusi (1992): ‘‘. . . at the time when individu-als initiate their smoking activity, do they under-stand the consequences of their actions and makerational decisions?’’ Viscusi went on to define theappropriate test of rationality in terms of‘‘. . . whether individuals are incorporating theavailable information about smoking risks andare making sound decisions, given their own pref-erences . . .’’ (p. 11).

The data indicate that the answer to Viscusi’squestion is ‘‘no’’. Most beginning smokers lackthe experience to appreciate how their future selveswill perceive the risks from smoking or how theywill value the tradeoff between health and the needto smoke. This is a strong repudiation of the modelof informed rational choice. It fits well with the find-ings indicating that smokers give little consciousthought to risk when they begin to smoke. Theyappear to be lured into the behavior by the pros-pects of fun and excitement. Most begin to thinkof risk only after starting to smoke and gainingwhat to them is new information about health risks.

These disturbing findings underscore the dis-tinction that behavioral decision theorists nowmake between decision utility and experience util-ity (Kahneman, 1997; Kahneman and Snell, 1992;Loewenstein and Schkade, 1999). Utility predictedor expected at the time of decision often differsgreatly from the quality and intensity of the hedo-nic experience that actually occurs.

4. Conclusion

We hope that this rather selective and idiosyn-cratic tour through a melange of experimentsand conjectures has conveyed the sense of excite-ment we feel toward the affect heuristic. This heu-ristic appears at once both wondrous andfrightening: wondrous in its speed, and subtlety,and sophistication, and its ability to ‘‘lubricatereason’’; frightening in its dependency upon con-text and experience, allowing us to be led astrayor manipulated—inadvertently or intentionally—silently and invisibly.

It is sobering to contemplate how elusive mean-ing is, due to its dependence upon affect. Thus theforms of meaning that we take for granted andupon which we justify immense effort and expensetoward gathering and disseminating ‘‘meaningful’’information may be illusory. We cannot assumethat an intelligent person can understand themeaning of and properly act upon even the sim-plest of numbers such as amounts of money, notto mention more esoteric measures or statistics,unless these numbers are infused with affect.

Contemplating the workings of the affect heu-ristic helps us appreciate Damasio’s (1994) conten-tion that rationality is not only a product of theanalytical mind, but of the experiential mind aswell:

The strategies of human reason probably did notdevelop, in either evolution or any single individ-ual, without the guiding force of the mechanismsof biological regulation, of which emotion andfeeling are notable expressions. Moreover, evenafter reasoning strategies become estab-lished . . . their effective deployment probablydepends, to a considerable extent, on a continuedability to experience feelings. (p. xii)


Ironically, the perception and integration ofaffective feelings, within the experiential system,appears to be the kind of high-level maximizationprocess postulated by economic theories since thedays of Jeremy Bentham. These feelings form theneural and psychological substrate of utility. Inthis sense, the affect heuristic enables us to berational actors in many important situations. Butnot in all situations. It works beautifully whenour experience enables us to anticipate accuratelyhow we will like the consequences of our decisions.It fails miserably when the consequences turn outto be much different in character than weanticipated.

The scientific study of affective rationality is inits infancy. It is exciting to contemplate whatmight be accomplished by future research designedto help humans understand the affect heuristic andemploy it beneficially.

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Anderson, N.H., 1981. Foundations of information integrationtheory. Academic, New York.

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