How Affective Intelligence Theory Can Help Us Understand Politics


George E. Marcus, Department of Political Science, Williams College

February 2017 – What follows is the story of how the Affective Intelligence Theory came into being and of how it can be used to better understand the dynamic changes of political systems. It is a personal narrative because I played a critical role in developing the theory and because I am understandably invested in its success. I proceed by telling why the theory came to be. Thereafter I shall give some examples of its payoffs to date.

To forestall misunderstandings, let me first emphasize that Affective Intelligence Theory and the theory of emotional intelligence, the latter developed by Peter Salovey and Jack Mayer (1990), are fundamentally different in their history and objectives. That also applies to a comparison of cognitive appraisal theories and the Affective Intelligence Theory. As to the first comparison, the impetus for Mayer and Salovey’s theory of emotional intelligence came from trying to understand whether there is a specific type of ability that enables some to more accurately identify emotions in oneself and in others. Those who had that ability could make use thereof to better manage one’s actions. All of this is described in their seminal 1990 piece “Emotional Intelligence”. One of their primary concerns was to provide a measure with good psychometric properties that could do for emotional intelligence what IQ measures have done for general intelligence. As I hope will become clear, the Affective Intelligence Theory has a quite different focus.

Additionally, many understand the Affective Intelligence Theory as being one of various cognitive appraisal theories. Clore and Ortony (2008) lay out the respective terrains of Affective Intelligence Theory and cognitive appraisal theories as follows. They note that some affect processes are “fast, automatic, and perceptual” while others, those that largely fall within the focus of cognitive appraisal theories, focus on “full-blown emotional states” (Clore and Ortony, 2008, p. 638).  Affective Intelligence Theory is focused on the “fast, automatic, and perceptual”. To expand on that comparison, Affective Intelligence Theory is concerned with accounting for what lays before the later cognitive appraisal processes that seek to explain emotion as it is expressed within consciousness. Another way to put it is that Affective Intelligence Theory focuses on the preconscious, understood as what comes before consciousness in the temporal order.

The impetus for Affective Intelligence Theory came from the then sterile debate taking place among American political scientists concerning the question of whether the American electorate was competent to make collective action political decisions (Bartels, 1996; Converse, 2000; Erikson, 2007; Key Jr. & Cummings, 1966; Lau & Redlawsk, 1997; Schudson, 1998; Smith, 1989). Much of the debate presupposed a crude reason-passion dichotomy which saw passion as a threat to competence, and dispassionate reason as the principal conduit to competence. Below is a fine example on the conventional view that emerged of the public’s performance. It was, and remains, the dominant view. In a study of how Californians came to pass a referendum in 1978 to limit property tax increases, Proposition 13, the two scholars explained its passage thusly (Sears and Citrin, 1982, pp 222-223):

“[A] surge of recklessness, a period of nearly blind emotion, surrounding the passage of Proposition 13, when anger at the government seemed to dominate the public’s thinking. The usual explanations for the voters’ choices still held sway, but this added hostility proved a potent weapon for the tax revolt. At this point, the tide of anti-government emotion eroded stable attitudes about what government should do. The public’s desire for maintaining the status quo of services plummeted, their perceptions of government inefficiency rose considerably, and their anger focused on the ‘bureaucrats.”

My primary concern was to re-examine the ancient and persistent dichotomy between reason and passion exemplified by this passage. The longstanding presumption has been that emotion is, by definition, the opposite of reason. Much of the political science research on voters’ competence in democratic societies fell into one of two camps. The first largely ignored emotion while the second used emotion to blame the electorate for its failure to make the correct judgment (as in the case given above, i.e., to reject Proposition 13). I thought it was time to see if emotion re-imagined could prove useful to better understand all forms of political behaviors.

The Reason-Passion Dichotomy

Survey research became available in the 40s and 50s. This enabled collecting systematic empirical data that could be used to examine what the American public knew and how voters went about making political decisions (Lazarsfeld, Berelson, & Gaudet, 1944; Campbell, Converse, Miller, & Stokes, 1960). The portrait of the American electorate that emerged was largely dystopic. The public was understood as poorly informed, largely moved by partisan affiliations rather than reliance on fulsome understanding and consideration of the dominant public issues of the day (Converse, 1964; Converse & Markus, 1979; Delli Carpini & Keeter, 1996, Lodge & Taber, 2013). Other scholars and theorists attacked this dystopian view, suggesting that the electorate was not entirely prey to irrational forces and gullible to misinformation (Page & Shapiro, 1992; Popkin, 1991). The debate has continued with little in the way of change or movement (Converse, 2000; Converse, 2006; Achen, 2016).

This is of course a highly simplified characterization of the state of play. A more nuanced and precise account can be in Marcus (2000) (see also Brader, Marcus, & Miller, 2011; Brader & Marcus, 2013). In effect, much of the political science discipline has taken to being critical of the public’s competence while giving but momentary attention to the many repeated signs of elite incompetence. Beating up on the plebeians is an old game, currently played by both intellectuals and conservatives (the former to display their intellectual pretensions, the latter to resist democratic oversight of the established hierarchies of wealth and social station).

But all parties to the debate bought into the idea that the competence of the electorate hinged on the relative influence of reason and emotion: the more influential reason and the less influential emotion is, the more the electorate is competent. This is the very presupposition we challenge in our Affective Intelligence Theory (Marcus, 2002). Nonetheless, the reason-passion dichotomy remains influential. Just to pick an example from among many, consider this letter to the editor published in The New Yorker (Clow, 2016):

“It seems that [Bernie] Sanders finds all these Trump supporters silly. But, in nominating Trump, Republicans have thrown out the whole epistemology of governing by facts in favor of governing by assertions. And Trump’s assertions aren’t empty: they’re weapons against reason, which means they’re attacks on the ideas of justice, science, and culture. His assertions are promises to wreck those things if voters fail to deliver Hillary Clinton to those who want her head. When passion is the medium for political participation, not reason, the result isn’t “ungentleness” as Sanders describes but mob behavior, barely in check.” David Clow, Los Angeles, California.

Here we find the ancient tropes. Reason and passion are assigned their familiar roles with the former presumed to enable fact-based deliberation and autonomous action while the latter is assigned the role of instigating turbulent irrationality and mob action.

In 1984-85, I was invited to spend a sabbatical year at the University of Minnesota. For a while I had been wondering whether giving emotion a reconsideration might offer a way out of the sterile debate on electorate competence. However, I had no particular insights as to how to do so. As it turned out a casual discussion about my hopes for the year with Prof. Auke Tellegen, who is a psychologist at the University of Minnesota, led to a momentous recommendation to read neuroscientist Jeffrey Gray’s work. That I did immediately after our conversation by taking a trip to the library, devouring first Gray’s work in affective neuroscience (Gray, 1970; Gray, 1981; Gray, 1985) and then later expanding my focus to Edmund Rolls’ theory of affect (Rolls, 1992; Rolls, 1999; Rolls, 2005).

This literature offers a new and more complex account of emotion and of reason. This led to a critical insight that in turn was instrumental in generating Affective Intelligence Theory as a dual process model. In dual process models humans are understood to have two modes of judgment. The first, the normal default mode of judgment is often labeled intuitive, automatic, or system 1. The second is often labeled deliberative, rational, or system 2 (Haidt, 2001; Kahneman, 2001; Chaiken and Trope, 1999; Sherman, Gawronski & Trope, 2014). Crucially, emotion is involved in both modes of judgment, with anxiety playing a pivotal role in triggering when people depart from reliance on the default mode to take up the reasoning mode. Similarly, our understanding of reasoning is also reshaped by this formulation, with reasoning serving different functions in each of the two modes of judgment. In what follows, I will provide some of the missing details.

The Lesson from Neuroscience: Consciousness as the “Tip of an Iceberg”

I was of course familiar with Freud’s claim that consciousness is just the tip of the mental iceberg, with the bulk of mental processes occurring below the surface of consciousness. The work of Benjamin Libet established to my satisfaction that conscious volition is not the sole place to focus on to understand political behavior but that many of the appraisals that orient our political behaviors are preconscious. Libet’s research demonstrated that it takes about 500 milliseconds after the sensory and somatosensory electrical signals arrive in the brain for the brain to construct consciousness (Libet et al., 1979, Libet et al., 1983, Libet, 1985, Libet, 2004). Crucially, within this 500 millisecond period the brain is already making lots of determinations and lots of fast flowing decisions. For example, we appraise the sexual orientation of a person, male or female, within 50 milliseconds even though we do not visually, consciously, see someone until the 500 milliseconds (Rule and Ambady, 2008; Rule et al., 2009).

This suggests that unconscious neural activity is actually in charge of much of human behavior, with conscious processes commonly serving to provide post-hoc semantic accounts (Kunst-Wilson & Zajonc, 1980; Zajonc, 1980). And, for these forms of pre-conscious appraisals and executive control, affect plays an essential role (Bechara, et. al, 1997, 2005) in that affect is the principal mechanism by which the preconscious realm influences behavior in human and non-human animals (see also, Aglioti et al., 1995). The recognition that consciousness is too slow and inaccurate to have granular control of actions suggests that consciousness, in the words of Jeffrey Gray, is an “error correcting space”, with most actions commonly under the control of preconscious systems (Gray, 2004). The “preconscious system” has since been labeled in a variety of roughly equivalent ways, including the “intuitive system” (Haidt, 2001), the “automatic system” (Bargh & Pietromonaco, 1982; Bargh, Chaiken, Govender, & Pratto, 1992; Bargh & Chartrand, 1999) or simply “system 1” (Kahneman, 2011).

As has long been known, much of that process of construction is largely hidden, not below consciousness as standard conventions would have it but before consciousness. The question is: how can we map what is happening in the actions that take place before consciousness? That is the task of the theory of affective intelligence. But before turning to that theory I most likely need to convince you that the hidden is actually there, a task difficult because the brain artfully generates consciousness with a sense of immediacy and veracity that makes us all not just dubious but even resentful when the claim that the preconscious is fundamental is advanced.

I use the following simple demonstration that you can each execute to make the hidden apparent. Take one of your forefingers and touch your nose. How many touches do you feel? For most the correct answer is one. That is, subjectively we experience a single touch. But the brain actually records two touches. The first touch is generated by the nerve signals that arrive from the nose. This signal arrives well before the nerve signals that arrive from the forefinger, since the former have far less distance to travel. But what does the brain do with these two separate ‘touches’? It hides that two-touch experience. Rather, it generates a convergent subjective experience, the ‘single’ touch that what we experience in consciousness. This simple trial shows that the brain actively manages consciousness. It is also important to note that the brain falsifies our sense of time by generating the sense that the single touch is instantaneous with the event. Beyond that, none of have access to the actual way the brain manages the movement of our forefingers to accurately and lightly touch our noses so that we don’t miss, and poke an eye instead.

But if the preconscious is so demonstrably influential, then why then do we have consciousness? This seems an especially important question given that consciousness, the so-called seat of our “higher cognitive functions”, has a very high caloric demanding capacity. Why invest so much energy if that capacity offers but a rarely used standby capacity? Jeff Gray in his last posthumous book, offers the best explanation: consciousness is an error correcting space (Gray, 2004, p. 312). By that Gray meant that not all circumstances are well suited to the “automaticity” of the preconscious. More specifically, when humans confront novel and unfamiliar settings, prior habits are most likely to lead to error. In sum, when we face the unusual, we are best served by having our conscious capacities take over. Affective Intelligence Theory serves to account for when we rely on the preconscious capacities we all have and when we shift to conscious deliberation (Marcus, 1988). Here then is a brief overview the Affective Intelligence model that my colleagues Michael MacKuen, W. Russell Neuman and I have developed (MacKuen, Marcus, Neuman, & Keele, 2007; Marcus, 2013a, 2013b; MacKuen, Wolak, Keele, & Marcus, 2010). And, following that description I shall describe some of the new understandings of political behavior and judgment that were uncovered thereby.

The Theory of Affective Intelligence

The first important axiom of Affective Intelligence theory (AIT) is that in a normal wakeful state multiple affect-eliciting appraisals are active at the same time, generating rapid shifts in strategic assessments of the world allowing early control over those actions that are then underway. Because these appraisals occur well before conscious awareness, only those that are sufficiently robust and persistent become subjectively available. Affective Intelligence Theory is primarily concerned with the functional dynamics associated with each of three ongoing preconscious appraisals. Each appraisal uses a specific affect to assay one of three distinct strategic tasks (Marcus, 2013a; Marcus, 2013b; Marcus, 2013c). These tasks are shown below.

Figure 1: The Theory of Affective Intelligence: Three Concurrent Parallel Preconscious Appraisals

As shown in Figure 1, at any given instance all three appraisals are ongoing. Two of the appraisals are concerned with the swift assessment and control of actions that implement familiar goal seeking routines. We understand these as habits, habits that can be relied on to manage the familiar recurring tasks of life. Most of what we do requires little in the way of active conscious control (James, 1890). That is the case for driving and it is true for voting (Spezio, et al., 2008; Willis & Todorov, 2006). The first appraisal uses the affective range that goes from depression to elation, to which we assign the rubric enthusiasm. The neural system which makes use of this range does so by monitoring and managing the progress of and adjustments to the actions meant to secure rewards by means previously learned. As reward seeking actions unfold successfully, this neural process generates greater levels of enthusiasm. And, to the extent these efforts prove less successful we feel greater frustration and even depression. When the actions are social, as is often the case in politics, enthusiasm manages our in-group actions (as it does our less social habits).

The second appraisal process uses the affective range we assign the rubric “aversion” to monitor and manage the progress and adjustments of actions meant to protect and minimize punishments by means previously learned. Just a few examples of the latter should suffice. We each have practiced routines to manage the various familiar grievances, minor and major. We all rely on this neural program because it swiftly identifies the presence of normative violations by increasing states of aversion or anger (bitterness or contempt for more modest levels and anger and hatred for the most compelling instance). This neural program also has access to procedural memory which then enables it to then actuate and monitor the appropriate routinized habits that manage the affair. Among these might be a grimace, a public display of disdain, a scornful comment directed at a target, or increased solidarity with partisans to marshal a more effective riposte. Anger also leads to defensive retrenchment, and as a result makes people more reliant on preexisting convictions and less open to change.

Because the human species is notably mobile and because we live in a world that has, and likely will, change in ways visible and not, we have a third appraisal to help us adapt to novel and uncertain conditions if and when we encounter them. The third appraisal uses the affective range we assign the rubric “anxiety” or “fear” to scan for the unexpected. As uncertainty and anxiety increase, reliance on convictions decreases, and in the public sphere, solidarity among in-group members goes down. And, also with greater anxiety, interest in and attention to new information goes up along with a willingness to find a compromise that will resolve the anxiety-producing uncertainty. Of great interest from the outset is the anticipation of what has come to be called the dual process model of decision-making or judgment (Chaiken & Trope, 1999; Kruglanski & Gigerenzer, 2011; Mukherjee, 2010; Smith & DeCoster, 2000).

Notably then, two of the affect channels posited by Affective Intelligence Theory, enable deft articulation of recurring actions that take place in the preconscious realm (various named as ‘intuitive,’ ‘automatic,’ or ‘system 1’) while appraisal 3 serves to inhibit reliance on fast automaticity so as to enable thoughtful deliberation to have executive capability (Marcus, 1988; Marcus & MacKuen, 1993). In sum, why are we sometimes committed to a cause while at other times willing to engage in compromise? AIT offers some testable hypotheses that my colleagues and I have been exploring over the past two plus decades. Ted Brader and I offer a recent summary overview (Brader & Marcus, 2013). I focus on two of them below.

The Benefits of AIT

For my colleagues and I, the appeal of this theory is that it offers new and unexpected lines of inquiry, and with this the possibility of new insights, especially on long established received wisdom (MacKuen et al., 2007; MacKuen et al., 2010; Neuman et al., 2007). I’ve chosen two of these. The first has to do with understanding how people go about voting. The second has to do with a longstanding claim that what animates conservatives is fear of change, one the core epistemic motives currently understood as the foundation of the conservative personality (Robin, 2004; Jost et al., 2003; Hibbing et al., 2014).

Let’s begin with voting (at least as practiced in the United States). From scholars at the University of Michigan came the Normal Vote model (Converse, 1966): a now well-known and widely accepted portrait describing public ignorance of the major candidates and where they stood with respect to the predominant issues of the day. The Normal Vote model advances the claim that partisan voting decisions are derived from a robust reliance on partisanship, whereas the voting decisions of independents results from responsiveness to “short-term” forces (hence the colloquial name “swing voters”). The Rational Choice account arrived shortly afterward from economics. In its initial formulation, rational choice held that voters engaged in a rational consideration of the alternatives presented to them, choosing that which best served their interests (Downs 1957).

Rational choice posits an attentive and thoughtful electorate that makes explicit comparisons and adjudicates among them through rational evaluation of their respective costs and benefits. Unfortunately this model has a remarkable lack of empirical support (Quattrone and Tversky 1988). Both conventional approaches find that the public does not satisfy the common normative standards held up for assessing the capacity of the public to serve as empowered citizens. If democracy requires an attentive and politically learned electorate and requires voters to give at least modest attention and thoughtful consideration to the policy and leadership choices before them, then neither account suffices.

AIT argues that the Normal Vote Model and the Rational Choice Model have both gotten something right, but share a similar error by taking a special case of political judgment and treating it as if it were the general case. How can it be that the Normal Vote and Rational Choice models are special cases, that is, theoretical specifications that apply only in some rather than in all circumstances? The two established theories presume that voters have invariant patterns of judgment and behavior. In the case of the Normal Vote account, voters are either partisan or not, and these immutable qualities fully control what people do, for example, whether they will pay attention (partisans do, independents do not), when they decide for whom to vote (partisans early in campaigns and nonpartisans late), and so forth.

Partisans have certain qualities and they consistently display them, just as nonpartisans display their characteristic qualities (as we shall see, a similar case can be made for ideology as a stable defining quality). In the case of Rational Choice theory (or its more recent variant, bounded rationality), voters think and act rationally all the time and in every circumstance so long as at least minimal stakes are in play. The orienting insight of Affective Intelligence Theory is that voters shift between different decision strategies, roughly along the lines suggested by the dual process understanding of human judgment.

The theory, as shown in figure 1, demonstrates how we can integrate the Normal vote and Rational Choice accounts (with one important change to the latter). When people feel they are in familiar circumstances, engaged in recurring previously learned habits, they will act as partisans (voting their ideological and partisan predilections). However, when they feel themselves in novel, unfamiliar settings, they will abandon – at least temporarily – those convictions (both implicit and explicit). Instead, feeling anxious, they will seek to learn more about the candidates and more about where they stand on the issues of the day. And, they will then vote based on what they learn (Marcus and MacKuen, 1993). Thus, they act under the guidance of the “system 1” intuitive mode of judgment when conditions are familiar, but under the guidance of the “system 2” deliberative mode of judgment when conditions are uncertain (MacKuen et al. 2007, 2010).

In sum, the theory of Affective Intelligence leads us to reject both the dystopic portrait of the ill-informed and irrational public and the more utopian aspiration for the full-time rational citizen. Instead, we arrive at a more complex and a more dynamic understanding in which citizens display shapeshifting capacities, moving, on occasion from steadfast partisan determination to deliberate consideration freed from convictions (Marcus, 2013b). An important corollary of this analysis is that, contrary to common belief, it is not the case that reason and emotions are in complete conflict. Fear of the uncertain is clearly an emotion and yet, according to AIT, it is involved in the engagement of a system 2 process (Appraisal 3 in Figure 1).

This shows that the ability to have emotions may be an essential part of the very ability to reason (on this topic, see also influential work by Bechara and colleagues (1997; 2005)). On the other hand, the AIT model also accounts for the role emotions play in non-deliberative system 1 processes, which are often related to the emotions of enthusiasm (Appraisal 1 in Figure 1) and anger (Appraisal 2 in Figure 1). If AIT is on the right track, the reason-passion dichotomy is a coarse and inappropriate tool for making sense of political behavior, because it hides from view the complex role emotions pay in sometimes facilitating and sometimes hindering rational deliberation.

The second conventional wisdom has to do with conservatism. The “conservative mind” has long been of interest to scholars, pundits, and academic scholars (Adorno et al, 1950; Jost, 2003; Robin, 2004, 2011; Wilson, 1973). A popular account in the academy puts fear at the center of why some adopt conservative views and values and others progressive (or liberal) views and values. Standard accounts, both old and more recent, have argued that it is fear that drives the public towards nationalist, often xenophobic and authoritarian parties (Adorno, Frenkel-Brunswick, Levinson, & Sanford, 1950; Fromm, 1965; Wilson, 1973; Jost, Glaser, Kruglanski, & Sulloway, 2003; Landau et al., 2004). And, central to this line of inquiry are two fundamental points.

The first is that understanding the liberal mind need be of little interest, reflecting the Enlightenment presumption that a liberal mind is now the new normal orientation that humans will and should adopt. And, continuing, the conservative mind is thus viewed as retrograde (Marcus, 2008). But it is the second point that is best understood as perplexing from the perspective of the Affective Intelligence Theory. Is it plausible, in light of the Affective Intelligence Theory that what draws people to conservatism is the emotion of fear? Many, including Jost and colleagues argue yes: “people embrace political conservatism (at least in part) because it serves to reduce fear, anxiety, and uncertainty; to avoid change, disruption, and ambiguity” (Jost, 2003, p. 340).

From the perspective of the theory of affective intelligence, fear seems an unlikely basis for conservatism. Take another look at Figure 1 and note that anxiety and fear rise with one’s state of uncertainty. These emotions are driven by the unexpected, but the deliberative state that follows makes it unlikely that anxiety and fear drive support for conservatism. According to AIT, it is far more likely that the fundamental motivation for conservatism is anger. Anger arises when we face challenges to important norms that we find to be foundational to the social order. In other words, conservatives are not so much xenophobic (afraid of foreigners) as they are xenocholeric (angry at foreigners). My current research with colleagues Pavlos Vasilopoulos, Martial Foucault, and Nicholas Valentino, examines support for the Front National and authoritarian policies in France, and for Republicans and Donald Trump in the US.

What we have found is that anger fuels support for conservative policies and voting for conservative candidates, whereas anxiety undermines support for such policies and candidates. According to AIT, anger and anxiety will activate two distinct patterns of information processing. Heightened anger will make people use system 1 or intuitive judgments and make them reliant on their pre-existing convictions. Heightened anxiety will shift people to system 2, or deliberative reasoning and undermine the influence of pre-existing convictions. And in a number of unpublished studies we find precisely that (Vasilopoulos, et al, unpublished). As anger rises among conservatives, their convictions are strengthened. On the other hand, anxiety undermines conservatives’ reliance on their convictions. This happens because anxiety initiates a new judgment stance, that of deliberative reasoners interested in exploring collective action solutions that are not bound to or by our normally potent convictions.

Hence, in the main, the role of anxiety (fear) has been mis-judged as the principal motivator for support for authoritarian policies and leaders (Jost et al., 2003; Landau et al., 2004). Conversely, the crucial role of anger has been underestimated. In sum, we anticipate that generalized public anger – whatever its the target may be – explains why so many electorates are turning to the right.


It was the inspiration provided by Gray’s neuroscientific research on the importance of unconscious processes that led me to set aside the stale 1990s debate as to whether citizens are competent and eventually gain new insights about the way political decisions are made. The turn to emotions, understood in the context of a dual process model of decision-making, has led us to new understandings of politics. Voters, as it turns out, are neither so partisan as posited by the Normal Vote model nor so free from irrational influences as posited by the Rational Choice model.  They are complex creatures capable of both blind faith and rational assessment. This is why this new understanding is not utopian.

Humans are still bedeviled by lack of foresight (Hobbes, 1968), but they can at least temporarily engage in evidence-based deliberation. Affective Intelligence Theory, as a dual process model, offers an explanation of how humans, and likely other species, have adapted by having multiple available decision strategies. One the one hand, habituated processes are swiftly and deftly executed by reliance on the capabilities offered by neural systems that manage the familiar recurring tasks. But if that were the sole capacity available to humans we all would be vulnerable to anything that is unusual and unexpected.

Hence, the importance of having a neural system dedicated to early identification and assessment of the magnitude of the novelty. While complete foresight is not thereby obtained, heightened anxiety in the face of uncertainty alerts us to conditions that can benefit us from setting aside lessons that have most often served us well. That does not protect us against human fallibility. We may incorrectly understand the circumstances we face, acting as if circumstances are familiar when they are not or acting as it circumstances are uncertain when they are not. Nonetheless, having protean capacities would seem to give us greater adaptive flexibility.


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