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Automatic Evaluation
Melissa J. Ferguson and Vivian Zayas
Cornell University
ABSTRACT—Humans continuously evaluate aspects of their environment (people, objects, places) in an automatic fashion (i.e., unintentionally, rapidly). Such evaluations can be highly adaptive, triggering behavioral responses away from threats and toward rewards in the environ- ment. Even in the absence of immediate threats and fleeting rewards, the ability to automatically evaluate aspects of the environment enables individuals to effortlessly make sense of their world without depleting limited and valuable cognitive resources. We discuss two lines of research on automatic evaluation: The first demonstrates that people can evaluate a stimulus even when they are not conscious of the stimulus and thus unaware of having evaluated it. The second line of work shows that even when people are con- scious of a stimulus, they may evaluate it without intending to do so. We end by discussing current theoretical questions regarding this topic.
One of the most essential abilities of any organism is the ability to evaluate aspects of the environment as threatening or re- warding. Indeed, a wide range of living things—from amoebas to humans—possess at least some rudimentary form of this ca- pacity. Amoebas, for instance, move away from bright lights, demonstrating behaviorally their detection of a harmful pres- ence. Since the mid-1980s, researchers interested in human information processing have been investigating whether- evaluation of environmental stimuli can proceed automati- cally—that is, extremely rapidly (within milliseconds); without intention; and, at times, without awareness that the evaluation occurred or even of the stimulus being evaluated (see De Houwer, Teige-Mocigemba, Spruyt, & Moors, 2009; Petty, Fazio, & Brin˜ol, 2009). The ability to evaluate stimuli automatically is crucial for acting quickly in response to threats and rewards. Consider the benefit of being able to remove one’s hand from a hot stove even before consciously realizing the hotness, and even before con- sciously registering that one is touching a stove. Automatic evaluations provide this kind of highly relevant, quickly deliv-
ered information about appropriate behavioral responses to our environment. The tendency to evaluate stimuli rapidly and un- intentionally can be viewed as a background monitoring system operating even while individuals are engaged in some other task. From an evolutionary account, such an ability presumably en- abled ancestral humans to engage in one task, such as enjoying food, while also being able to respond to a quickly approaching predator. Even in more mundane situations, the automatic evaluation of stimuli is instrumental in helping individuals make sense of their world. It can facilitate decision making, for example, by allowing people to assess which aspects of the environment offer sufficient rewards to justify spending the effort and energy necessary to obtain them (e.g., Bijleveld, Custers, & Aarts, in press). Empirical evidence on automatic evaluation comes from two largely separate literatures. The literature on subliminal per- ception demonstrates that even when people do not consciously perceive a given stimulus, they evaluate it. In such cases, the evaluation must by necessity be unintentional given that the person is unaware of the stimulus itself. This research provides quintessential evidence that evaluative processes can unfold automatically—rapidly and without the person’s intention to evaluate. The second line of work comes from the attitudes lit- erature. This work also speaks to the automaticity of evaluative processes by showing that when people consciously perceive a stimulus they evaluate it even when not intending to do so.
EVALUATING NONCONSCIOUSLY PERCEIVED STIMULI
Behavioral Evidence Research on subliminal perception provides empirical support that people can evaluate the goodness or badness of a subliminal (i.e., consciously unidentifiable) stimulus. For example, in the widely used sequential evaluative priming paradigm (Fazio, Sanbonmatsu, Powell, & Kardes, 1986), participants are shown a series of trials, each of which consists of the presentation of a prime stimulus followed by a target stimulus. The target is se- mantically unrelated to the prime and is unambiguously positive or negative in connotation (e.g., words such as ‘‘delightful’’ or ‘‘painful’’). Participants’ task is to classify the valence of the
Address correspondence to Melissa J. Ferguson, 211 Uris Hall, Psy- chology Department, Cornell University, Ithaca, NY 14850; e-mail: [email protected].
CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE
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target. Research using this paradigm has shown evidence of evaluative priming; namely, the classification of targets is easier (i.e., faster, more accurate, or both) when targets share (versus do not share) the same valence with primes. The evaluative priming phenomenon is commonly interpreted as showing that primes are automatically evaluated and that these evaluations in turn influence the classification of subsequently presented targets. In research that examines the evaluation of subliminal stim- uli, primes are rendered consciously imperceptible by using a number of techniques (e.g., masks, short prime exposure). Even though primes are imperceptible, they influence the ease with which targets are classified, suggesting that the primes have indeed been evaluated. The evaluation of subliminal stimuli not only occurs for words but extends to human faces and images of objects, and it affects a range of subsequent outcomes such as mood states, behaviors, and judgments.
Neuroscience Evidence Research from cognitive neuroscience using functional mag- netic resonance imaging (fMRI) has routinely implicated the critical role of the amygdala in the evaluation of subliminal stimuli. The amygdala is best known for its role in the processing of emotion, especially (but not exclusively) fear. Studies have shown that subliminally presented fearful and angry faces (compared with neutral or happy faces) more strongly activate the amygdala, indicating evaluation in the absence of conscious awareness (e.g., Morris, O¨ hman, & Dolan, 1998). The amygdala appears to be crucial for initial evaluative judgments, as it is highly sensitive to cues of environmental threat as well as reward (Breiter et al., 1996). The amygdala’s connections to other brain regions involved in directing cogni- tive and motor processes (Armony & LeDoux, 2000) allows for these automatic evaluations to quickly translate into responsive behaviors (e.g., moving away from threat; Hyman, 1998). Ad- ditionally, the amygdala plays a significant role in the formation of memories and conditioned learning, especially that involving fear, which is highly relevant to automatic evaluations given that most preferences are learned rather than inborn (Rozin & Millman, 1987).
Assessing the Perceptibility of Prime Stimuli Although the most common approach for assessing whether a ‘‘subliminal’’ stimulus is in fact imperceptible is to ask partici- pants to state the content of the prime, such self-reports of perceptibility are limited. Commonly used presentation tech- niques (e.g., short prime durations, masking) make primes difficult to see. As a result, perceivers tend to be underconfident in their ability to accurately identify these stimuli, treating un- certainty as evidence of lack of perceptibility (e.g., Hannula, Simons, & Cohen, 2005). Thus, some studies claiming to show unconscious evaluation may be instead assessing evaluation at very low levels of conscious awareness. More rigorous behav-
ioral (rather than subjective) methods of assessing perceptibility to assess whether evaluation occurs without conscious aware- ness are needed.
EVALUATING CONSCIOUSLY PERCEIVED STIMULI
Behavioral Evidence Most of the work in the attitudes literature using the sequential priming paradigm (Fazio et al., 1986) presents primes supra- liminally (i.e., consciously visible). Even though participants are asked to ignore the primes, they show evidence of having evaluated them (via the evaluative priming effect). Because the time between the presentation of the prime and the target is too short (usually less than 300 milliseconds) to allow for strategic and effortful responding, it has been assumed that any effect of the prime on responses to the target is automatic. Other para- digms (e.g., the Implicit Association Test; Greenwald, McGhee, & Schwartz, 1998) that measure people’s automatic evaluation of stimuli yield similar evidence of unintentional evaluation. Even paradigms that do not explicitly ask participants to classify the evaluative meaning of targets, such as the lexical decision task, have produced similar results, providing further support that evaluation occurs without intention.
Neuroscience Evidence The recording of event related potentials (ERP) is a neuro- physiological technique that offers high temporal resolution, providing a millisecond-to-millisecond record of the brain’s neurophysiological responses associated with the processing of a stimulus. As such, this technique reveals how quickly the brain makes evaluative discriminations. This kind of research con- sistently finds that the valence of various types of stimuli (words, faces, objects), presented either subliminally or supraliminally, is encoded in under a quarter of a second after the onset of the prime (for a review, see Compton, 2003), with faces typically evaluated more quickly than objects, which in turn are evaluated more quickly than words.
OUTSTANDING QUESTIONS
Are Evaluations Themselves Nonconscious? Do the empirical findings described so far necessarily indicate that people are not conscious of evaluations triggered by stimuli? For example, even with subliminally presented stimuli, the person may experience a fleeting sense of the positivity or neg- ativity of each stimulus. Consistent with this possibility, work on subliminal face priming has found effects on a person’s mood state. Although the subliminal stimuli are evaluated without any conscious awareness, the evaluative response to those stimuli is consciously experienced and reportable, as evidenced by changes in reported mood. On the other hand, in work using the sequential priming paradigm and other commonly used para-
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underlying processes and triggering causes. Some social cog- nitive researchers have suggested that, generally speaking, de- liberate processes may occur in the same way as automatic processes, regardless of differences in awareness, intention, effort, and control. However, other work on varieties of non- conscious versus conscious processing would suggest that de- liberately making an evaluative judgment should (and perhaps must) introduce some differences at the subjective level, and possibly at the functional as well (see Dehaene et al., 2006). Consistent with this position, research shows that the way people automatically evaluate stimuli may at times be at odds with the way they would evaluate those same stimuli given more time and thought. For example, whereas people may exhibit initially negative reactions to stigmatized group members, their more intentional evaluations can be more positive. Research is on- going to examine the source(s) for such dissociations in measures of evaluations (e.g., see Petty et al., 2009). Dual-process theories (e.g., Gawronski & Bodenhausen,
- provide a framework for understanding both automatic and deliberative evaluations. According to such theories, eval- uations can emerge from one of two systems in the mind: a propositional (deliberative) system or an associative (automatic) system. Whereas evaluations that depend on propositional knowledge are often conscious, intentional, and endorsed by the person, evaluations that proceed from an associative system are often unconscious, unintentional, and sometimes at odds with the person’s more deliberate evaluations. Research from a va- riety of perspectives is investigating how both automatic and deliberate evaluations are generated (e.g., see Wojnowicz, Fer- guson, Dale, & Spivey, in press).
CONCLUSION
Automatic evaluations—those that occur unintentionally, rap- idly, and, at times, without conscious awareness—allow indi- viduals to respond quickly to threats and rewards present in an ever-changing environment. The next generation of empirical inquiry on automatic evaluation will require addressing when it happens, how it happens, what consequences it may have, how it interacts with other knowledge structures, and whether and how it can be controlled.
Recommended Reading De Houwer, J., Teige-Mocigemba, S., Spruyt, A., & Moors, A. (2009). (See References). A thorough overview of various theoretical and methodological issues concerning implicit measures of evaluation. Fazio, R.H., Sanbonmatsu, D.M., Powell, M.C., & Kardes, F.R. (1986). (See References). A historical classic—the first paper to empiri- cally demonstrate automatic evaluations. Petty, R.E., Fazio, R.H., & Brin˜ ol, P. (Eds.). (2009). (See References). A comprehensive review for readers who wish to expand their knowledge on automatic evaluations.
Wittenbrink, B., & Schwarz, N. (2007). Implicit measures of attitudes. New York: Guilford. A comprehensive review of the theory and research concerning the measures of automatic evaluations.
REFERENCES
Aarts, H., Dijksterhuis, A., & De Vries, P. (2001). The psychology of drinking: Being thirsty and perceptually ready. British Journal of Psychology, 92 , 631–642. Armony, J.L., & LeDoux, J.E. (2000). How danger is encoded: Toward a systems, cellular, and computational understanding of cognitive- emotional interactions in fear. In M.S. Gazzaniga (Ed.), The new cognitive neurosciences (2nd ed., pp. 1067–1079). Cambridge, MA: MIT Press. Bijleveld, E., Custers, R., & Aarts, H. (in press). The unconscious eye- opener: Pupil size reveals strategic recruitment of resources upon subliminal reward cues. Psychological Science. Breiter, H.C., Etcoff, N.L., Whalen, P.J., Kennedy, W.A., Rauch, S.L., Buckner, R.L., et al. (1996). Response and habituation of the human amygdala during visual processing of facial expression. Neuron, 17 , 875–887. Cacioppo, J.T., & Berntson, G.G. (1994). Relationship between atti- tudes and evaluative space: A critical review, with emphasis on the separability of positive and negative substrates. Psychological Bulletin, 115 , 401–423. Compton, R.J. (2003). The interface between emotion and attention: A review of evidence from psychology and neuroscience. Behavioral and Cognitive Neuroscience Reviews, 2 , 115–129. Dehaene, S., Changeux, J., Naccache, L., Sackur, J., & Sergent, C. (2006). Conscious, preconscious, and subliminal processing: A testable taxonomy. Trends in Cognitive Sciences, 10 , 204–211. De Houwer, J., Teige-Mocigemba, S., Spruyt, A., & Moors, A. (2009). Implicit measures: A normative analysis and review. Psychologi- cal Bulletin, 135 , 347–368. Dijksterhuis, A., & Aarts, H. (in press). Goals, attention, and (un)con- sciousness. Annual Review of Psychology. Fazio, R.H., Sanbonmatsu, D.M., Powell, M.C., & Kardes, F.R. (1986). On the automatic activation of attitudes. Journal of Personality and Social Psychology, 50 , 229–238. Ferguson, M.J. (2008). On becoming ready to pursue a goal you don’t know you have: Effects of nonconscious goals on evaluative readiness. Journal of Personality and Social Psychology, 95 , 1268–1294. Gawronski, B., & Bodenhausen, G.V. (2006). Associative and propo- sitional processes in evaluation: An integrative review of implicit and explicit attitude change. Psychological Bulletin, 132 , 692–
Greenwald, A.G., McGhee, D.E., & Schwartz, J.L.K. (1998). Measuring individual differences in implicit cognition: The Implicit Associ- ation Test. Journal of Personality and Social Psychology, 74 , 1464–1480. Hannula, D., Simons, D.J., & Cohen, N. (2005). Imaging implicit per- ception: Promise and pitfalls. Nature Reviews Neuroscience, 6 , 247–255. Hyman, S.E. (1998). A new image for fear and emotion. Nature, 393 , 417–418. Klauer, K.C., & Teige-Mocigemba, S. (2007). Controllability and re- source dependence in automatic evaluation. Journal of Experi- mental Social Psychology, 43 , 648–655.
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Morris, J.S., O¨ hman, A., & Dolan, R.J. (1998). Conscious and uncon- scious emotional learning in the human amygdala. Nature, 393 , 467–470. O¨ hman, A., & Soares, J.J.F. (1998). Emotional conditioning to masked stimuli: Expectancies for aversive outcomes following non-rec- ognized fear-relevant stimuli. Journal of Experimental Psychol- ogy: General, 127 , 69–82.
Petty, R.E., Fazio, R.H., & Brin˜ ol, P. (Eds.). (2009). Attitudes: Insights from the new implicit measures. New York: Psychology Press. Rozin, P., & Millman, L. (1987). Family environment, not heredity, accounts for family resemblances in food preferences and atti- tudes: A twin study. Appetite, 8 , 125–134. Wojnowicz, M., Ferguson, M.J., Dale, R., & Spivey, M. (in press). On the self-organization of explicit attitudes. Psychological Science.
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