The Devil You (Expect to) Know: Political Polarization
In his final speech in office, President Obama remarked on the growing level of extreme polarization, particularly in online interactions, by telling those in attendance “[i]f you’re tired of arguing with strangers on the internet, try to talk with one in real life.” As the rise of social media has highlighted (if not exacerbated) political divides in modern society — enabling us to seek echo chambers among those with whom we agree, and to antagonize our adversaries from the relative security of a world mediated by screens — the President’s advice seemed to point to some deeper truth of human interaction: it is harder to demonize someone we know.
"“[i]f you’re tired of arguing with strangers on the internet, try to talk with one in real life.”"
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The Effects of Mere-Exposure
Indeed, a host of psychological research supports this intuitive claim. Beginning with Zajonc’s[1] (1968) demonstration of the attitudinal effect of “mere exposure” — that simply becoming familiar with some stimulus (a person, animal, object, etc.) is enough to positively influence our attitudes toward that thing — researchers have found the effect present in as diverse contexts as racial attitudes (Zebrowitz, White, & Wieneke, 2008) and tastes for tropical juice (Pliner, 1982). There are two main explanations for how this works: misattribution (i.e., subjects mistake the cognitive and perceptual fluency that comes with exposure to a stimulus for liking that stimulus) and uncertainty reduction (i.e., not knowing about a stimulus causes cognitive stress, which familiarity with that stimulus naturally moderates) (c.f. Lee, 2001). Weighing the evidence for each, Lee (2001) contends that, while misattribution may explain changes in cognitive judgments, only uncertainty reduction can explain how exposure impacts our affective judgments. That is, how much we like or dislike something or someone. Of course, a change in how we affectively judge our political opponents is what President Obama was suggesting could improve discourse. The more we view our adversaries with negative affect, such as contempt, the less likely we are to consider their perspectives.
Berger and Calabrese (1975) provide further axioms for understanding how uncertainty reduction affects interpersonal interactions. Notably, they suggest “similarities between persons reduce uncertainty” (axiom 6) and “decreases in uncertainty level produce increases in liking” (axiom 7). If we meet our adversaries in person, our uncertainty about them decreases — and as this happens, so too should our disdain dissipate. Anecdotally, this phenomenon should resonate with many of us: are not a great deal of our social interactions based on proximity and familiarity?
Short of arranging in-person meetings for all social media squabblers, what can this literature tell us about engendering understanding in political discourse? In her authoritative overview of motivated reasoning, Kunda (1990) further highlights how even anticipated interactions improve our perception of others. In one example, participants in a study observed a taped discussion between three individuals, and were told they would go on a date with one of the three. When asked to rate those three individuals, participants projected onto their hypothetical dates higher scores for personality and perceived likability, and expressed a greater degree of confidence in their projections (Berscheid, Graziano, Monson, & Dermer, 1976; c.f. Kunda, 1990). As Kunda writes, participants’ desire to expect a pleasant interaction positively biased their perceptions of the individuals.
Imagined Contact Hypothesis
More recently, a robust strain of literature has emerged to examine this effect of imagined contact. Making use of insights from mere exposure and contact hypothesis, Crisp and Turner (2009) set out to examine how even a hypothetical interaction with an individual affects one’s perception of her. There are two critical insights from this research: first, that even imagined contact leads to an increase in positive affect for the hypothesized individual (Crisp & Turner, 2009); and second, perhaps even more critically, that this effect is greater when the imagined contact is with an out-group member (Stathi & Crisp, 2008). That is, the benefits of hypothetical interaction are even greater when it is with a person outside of one’s familiar social “in-group” (i.e., age, race, gender, sexual orientation, political party, etc.). Moreover, this effect persisted regardless of whether the interaction had positive or neutral valence — so that any anticipated exposure had a positive impact on behavior.
How We View Our Political Rivals
In the context of uncertainty reduction, this all seems to make sense. We already know that people in our in-group (e.g., members of our political party) share at least some of our own characteristics or beliefs. Thus, imagining contact with them should do little to change our perception. Conversely, people in out-groups inherently have some element of foreignness (this is why they’re not in our in-group), which makes us uncertain about them. By exposing ourselves to them (whether in person or in our imaginations), we are forced to face this unfamiliarity, and in doing so we naturally look for points of similarity. This in turn reduces our perceived uncertainty about them, and causes us to like them more.
The AI Governance Challenge
The mechanism by which this change happens is as follows: with no expectation to meet another individual, I will simply rely on my predominant stereotype in making my judgment of her; however, if I expect to meet that individual — and thus have the directional goal of a pleasant interaction — I will draw more selectively from my cognitive heuristics and memory to construct a more likable picture of the individual.
What all of this suggests is that we desperately need to humanize our politics. The insight that something so small as expecting to meet an individual can meaningfully change our beliefs about and behavior towards them should be a powerful tool for social interventions aimed at reconciliation. Recognizing the person on the other end of that Twitter argument as a human being — with thoughts and feelings, and perhaps even friends and a family — could be a powerful antidote to widespread demonization of our political rivals.
References
Berger, C. R., & Calabrese, R. J. (1975). Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication. Human communication research, 1(2), 99-112.
Berscheid, E., Graziano, W., Monson, T., & Dermer, M. (1976). Outcome dependency: Attention, attribution, and attraction. Journal of Personality and Social Psychology, 34(5), 978.
Crisp, R. J., & Turner, R. N. (2009). Can imagined interactions produce positive perceptions?: Reducing prejudice through simulated social contact. American Psychologist, 64(4), 231.
Kunda, Z. (1990). The case for motivated reasoning. Psychological bulletin, 108(3), 480.
Lee, A. Y. (2001). The mere exposure effect: An uncertainty reduction explanation revisited. Personality and Social Psychology Bulletin, 27(10), 1255-1266.
Pliner, P. (1982). The effects of mere exposure on liking for edible substances. Appetite, 3(3), 283-290.
Stathi, S., & Crisp, R. J. (2008). Imagining intergroup contact promotes projection to outgroups. Journal of Experimental Social Psychology, 44(4), 943-957.
Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of personality and social psychology, 9(2p2), 1.
Zebrowitz, L. A., White, B., & Wieneke, K. (2008). Mere exposure and racial prejudice: Exposure to other-race faces increases liking for strangers of that race. Social cognition, 26(3), 259-275.
[1] Or, as some scholars cite it, with Fechner (1876) or Titchener (1910)
About the Author
Andrew Lewis
Andrew is a writer and behavioral scientist focused on belief construction and how people evaluate new information. He is a PhD candidate in Politics at the University of Oxford, and a doctoral researcher at its Centre for Experimental Social Science (CESS). He was previously at Carnegie Mellon University where he worked at the BEDR Policy Lab and Center for Behavioral and Decision Research (CBDR), and was a research and teaching assistant to George Loewenstein.