How Trust Impressions Influence Economic Choices

People often judge others based on their facial appearance. Research demonstrates that it takes incredibly low time and effort for people to decide whether someone is trustworthy, competent, dominant, or attractive. These face-based judgments have been shown to bias multiple real-life decisions, from the outcome of a political election to sentencing decisions. In the context of economics, it has been shown that trust impressions influence people's investing and gambling choices. However, there is sparse information about factors that modulate this trust bias. In the present project, we use a face trait rating task, a gambling task, and a set of personality assessments to test whether participants' empathy and sensibility to opponents' loss are modulators of the trust bias. While more research still needs to be done, the results of this project will have important implications to further understand the trust bias and design strategies to mitigate it. I. Background "Don't judge a book by its cover" is a popular idiom used to warn people from making premature decisions. Against this conventional wisdom, a vast body of research shows that people make precipitate decisions in numerous situations, using scant or dubious sources of information. One of these lines of research demonstrates that people often judge the personal and social character of others based on their facial appearance (Todorov et al., 2015). Remarkably, these judgments are made at high speed and low cognitive cost. After a brief presentation of a stranger's face, people take as short as 100 milliseconds to decide whether this person is trustworthy, competent, dominant, or attractive (Willis & Todorov, 2006; De Neys et al., 2017). Notably, face-based impressions can have a significant influence in multiple real-world settings. For instance, research shows defendants with untrustworthy-looking faces require less evidence to be determined guilty in a court of law (Porter et al., 2010). Similarly, competence impressions of political candidates are highly correlated with voting preferences in political elections (Antonakis & Dalgas, 2009). Since research demonstrates that faces are unreliable indicators of people's character, the consequential effects of face-based judgments pose a societal problem (Todorov et al., 2015). Accordingly, the scientific community has been discussing and trying to develop strategies to mitigate them (Olivola et al., 2014). Nevertheless, face-based biases are highly resistant; educating people about their inaccuracy and offering alternative sources of information does not reduce their effect (Rule et al., 2014; Jaeger et al., 2020). Hence, in order to develop effective mitigation strategies, it is crucial to further understand face-based judgments and factors that modulate their effects. The present project follows this motivation while narrowing its focus to facial biases in economic choices. Research on facial biases on economic choices has traditionally focused on trust impressions, as they seem to exert the strongest effect (Schlicht et al., 2010; Rezlescu et al., 2012;). Often, experiments consist of subjects playing an economic game against other players represented by faces with varying levels of trustworthiness (e.g., trustworthy, neutral, or untrustworthy). Two notable economic games featured in the research literature are the trust game and a poker game. Research using these economic games shows that the perceived trustworthiness of faces has a direct influence on the choices people make. The trust game is a two-player game, where participants play the role of the investor, and their co-players play the role of the splitter. Each round, participants are given a set amount of money. As investors, their job is to decide how much money they want to invest in their co-players. The experimenter will increment any amount they choose to invest. However, the game has a catch in that participants do not know how much money their co-players will send back. The co-player can split this incremented amount any way they want. They can send back to participants more or less than the initially invested money. Hence, participants have to balance how much they trust their co-player and how much risk they are willing to take. Studies using this game show a clear pattern of responses. There is a bias favoring trustworthy faces; compared to neutral and untrustworthy faces, trustworthy faces receive significantly larger investments (Stirrat & Perrett, 2010; Rezlescu et al., 2012; Tingley, 2014). For instance, Rezlescu et al. (2012) found that when relying on the partner's face as a sole source of information, trustworthy faces receive an average of 42% higher investments. Further, they showed that even when participants have additional sources of information, like their co-player's behavioral history, although reduced, the trust bias holds. Notably, this bias extends across age groups. Children and older adults have been recorded displaying this trust bias (Ewing et al., 2015; Bailey et al., 2016). The poker game is also a two-player game where participants play a simplified version of Texas Hold'em poker. Each round, participants play against an opponent represented by a face with varying degrees of trustworthiness. Participants receive a pair of cards and a set of poker chips and are required to place an initial bet. Then, their job is to assess the strength of their cards, guess their co-player's game, and decide whether to enter or abandon a gamble. Research using this type of game also shows the presence of a trust bias. Compared to neutral or untrustworthy faces, participants are less likely to accept gambles against trustworthy faces (Schlicht et al., 2010). Altogether, evidence indicates trust impressions exert a robust effect on economic choices. Surprisingly, there have been very few attempts to determine factors that modulate this trust bias. One notable attempt was made by Schlicht et al. (2010). This group of researchers used statistical modeling to determine if economic parameters modulated the trust bias in the poker game. They considered three economic parameters: loss aversion, risk aversion, and a sensitivity parameter. The loss aversion parameter measured the participants' aversion to losses compared to their like of proportional gains. The risk aversion parameter measured participants' willingness to take higher-paying risky gambles against lower-paying sure options. Last, the sensitivity parameter measures participants' choice consistency between sure and risky outcomes. The results from this group of researchers showed that, compared to neutral and untrustworthy faces, trustworthy faces were associated with higher levels of loss aversion. This implies that compared to neutral and untrustworthy faces, participants disliked losing more against trustworthy faces. Even though the results of Schlicht et al. (2010) are interesting, it would be a mistake to assume they present a complete account of the factors that modulate the trust bias in economic choices. The types of games used to study the trust bias indeed have a strong economic component. However, they also have a strong social component. Usually, the outcome of these games ends up affecting all parties involved. Further, the trust bias relies on human faces used as stimuli. These faces are representations of other human beings, which makes these games reduced representations of real-world social dynamics. Hence, there is reason to believe social factors can modulate the trust bias. Consistent with the idea that social factors might modulate the trust bias, research on altruism shows a link between altruistic behavior and empathy. This research indicates that empathy encompasses two distinct states: affective and cognitive (Shamay-Tsoory et al., 2009). Affective empathy refers to people's ability to sense or feel what another person is feeling. Alternatively, cognitive empathy refers to people's ability to understand another's intentions, beliefs, or perspective. Various results demonstrate a close connection between affective empathy and altruistic behavior. For instance, Edele et al. (2013) had subjects play economics games and fill personality questionnaires. They found that affective empathy but not cognitive empathy was correlated with altruistic choices. Similarly, Klimecki et al. (2016) explored whether an empathy intervention would influence subjects' choices in an economic game. Their results showed that eliciting affective empathy impacted subjects' choices, while a control intervention did not. Altogether, research indicates a strong relationship between affective empathy and economic choice. An alternative line of research also consistent with the idea that social factors might modulate the trust bias explores whether face-based impressions can elicit empathic responses. Neuroscientists have been working to understand how empathy is generated in the brain. Part of this research studies the temporal dynamics of empathy. Accordingly, scientists often rely on electroencephalographic recordings, as this technique has a high temporal resolution. To probe human empathy, subjects are shown empathy eliciting stimuli while researchers record their brain activity. This work has found that subjects' empathic response is characterized by an early and a late response. The early response, linked with components N1 and N2, is thought to reflect an automatic process associated with affective empathy. In contrast, the late response, linked to component P3, is thought to reflect a controlled process associated with cognitive empathy (Fan & Han, 2008; Li et al., 2019). Notably, a substantial part of this research has used human faces as empathy eliciting stimuli, and a subset of studies have explored the effects of face-based impressions. For instance, Kopiś et al. (2020) and Meng et al. (2020) have found that attractiveness impressions produced a greater signal in compo