Peace, as this article reminds us, is nothing but a particular manifestation of a more general ability of humans to reap the benefits of mutually beneficial exchange – often called positive-sum relationships – instead of engaging in the war of all against all. Perhaps the most fundamental insight to be gained from this article is that the extent of this ability is supported by a highly complex culturally evolved system of institutions that incentivize cooperation by a great diversity of means. Cultural technologies like age-sets, peace ceremonies, efficient monitoring systems, or trading rituals are all highly complex, require very high levels of coordination, and typically emerge as a result of a long history of cultural accumulation over time (Alvard, Reference Alvard2003; Wiessner, Reference Wiessner2019; Wiessner & Tumu, Reference Wiessner and Tumu1998). In this commentary, we propose to extend the author's insight by highlighting how it can fit within the existing literature in social cognition and contribute further to this field.

Indeed, from an evolutionary perspective, the great variability in the ability of humans to achieve positive-sum relationships – that is, they sometimes achieve peace, but often cannot escape war – creates a selective pressure for an alliance detection system designed to keep track of the social relationships that structure one's particular social landscape. This includes both positive-sum relationships – for instance, the detection of friendships and coalitional alliances – and zero-sum ones – for instance, the detection of rivals or enemies (Liberman, Kinzler, & Woodward, Reference Liberman, Kinzler and Woodward2014; Pietraszewski, Cosmides, & Tooby, Reference Pietraszewski, Cosmides and Tooby2014; Pietraszewski, Curry, Petersen, Cosmides, & Tooby, Reference Pietraszewski, Curry, Petersen, Cosmides and Tooby2015).

This system is, of course, sensitive to direct evidence of positive-sum relationships, such as when people can directly observe instances of cooperation between individuals (Chalik & Rhodes, Reference Chalik and Rhodes2014; Kurzban, Tooby, & Cosmides, Reference Kurzban, Tooby and Cosmides2001; Liberman & Shaw, Reference Liberman and Shaw2017, Reference Liberman and Shaw2018). But, importantly, it also pays attention to indirect cues that are good predictors of social relationships: For instance, sharing goals, intentions, preferences, accents, or adhesion to norms can all facilitate cooperation and are indeed interpreted by human social cognition as predictors of social relationships (Basyouni & Parkinson, Reference Basyouni and Parkinson2022; Kinzler, Reference Kinzler2021; Liberman & Shaw, Reference Liberman and Shaw2017, Reference Liberman and Shaw2018; Liberman, Woodward, & Kinzler, Reference Liberman, Woodward and Kinzler2017; Liberman, Kinzler, & Woodward, Reference Liberman, Kinzler and Woodward2021; Liberman et al., Reference Liberman, Kinzler and Woodward2014; Noyes & Dunham, Reference Noyes and Dunham2017; Wilson, Bassiou, Denli, Dolan, & Watson, Reference Wilson, Bassiou, Denli, Dolan and Watson2018).

The insight that culturally evolved technologies are fundamental to stabilize positive-sum relationships thus has the potential to make a substantial contribution to the field of social cognition. Cultural technologies are not just abstract constructions that humans make, they should also constitute a major input for detecting group membership and cooperative networks in their environment. Observable cues suggesting that a group of individuals is embedded in a set of well-functioning institutions should trigger the alliance detection system and be encoded as a predictor of positive-sum relationships within the group.

This idea resonates with an already consistent body of evidence in the behavioral and political sciences suggesting that shared institutions play a fundamental role in group behavior (Bowles & Gintis, Reference Bowles and Gintis2004). Indeed, numerous lab experiments suggest that impartial and efficient sanctioning institutions can significantly increase social trust and prosocial behavior (Cassar, d'Adda, & Grosjean, Reference Cassar, d'Adda and Grosjean2014; Fabbri, Reference Fabbri2022; Hruschka et al., Reference Hruschka, Efferson, Jiang, Falletta-Cowden, Sigurdsson, McNamara and Henrich2014; Spadaro, Gangl, Van Prooijen, Van Lange, & Mosso, Reference Spadaro, Gangl, Van Prooijen, Van Lange and Mosso2020). Critically for the author's perspective, fair and effective institutions can even suppress prejudice between two rival groups (Bartoš & Levely, Reference Bartoš and Levely2021; Cassar et al., Reference Cassar, d'Adda and Grosjean2014; Fabbri, Reference Fabbri2022; Lin & Packer, Reference Lin and Packer2017; Van Bavel & Packer, Reference Van Bavel and Packer2021). Such institutions are usually operationalized as abstract entities that punish cheaters in lab experiments, or as state-like institutions in field studies. However, as Glowacki notes, institutions that favor the sanctioning of free-riders can take a wide variety of cultural forms – including much less formal ones. One important institutional strategy to stabilize cooperation is that societies tend to structure social networks in a way that facilitates the monitoring and sanctioning of cheaters, notably by encouraging the circulation of reputational information (Hechter, Reference Hechter1987; Ostrom, Reference Ostrom1990). In line with this idea, an influential field study in Uganda showed that ethnic preferences are merely a reflection of the belief in shared and efficient sanctioning institutions – typically through dense social networks that facilitate the detection of free-riders (Habyarimana, Humphreys, Posner, & Weinstein, Reference Habyarimana, Humphreys, Posner and Weinstein2007; see also Bartoš & Levely, Reference Bartoš and Levely2021, for a similar result in Afghanistan).

We invite researchers in social cognition to view this target article as an invitation to extend this line of research. More empirical work is needed to investigate how the presence of certain shared features – such as the presence of strong leaders, the existence of shared rituals, and other forms of cultural arrangements identified by Glowacki and others – can be used as cues by our social cognition to infer cooperative networks in our environment. This question is especially interesting when investigated from a “third-party” perspective (see, for instance, Noyes & Dunham, Reference Noyes and Dunham2020). For instance, are groups with effective leaders or with an institutionalized tradition of peace ceremonies perceived as more cohesive than groups without these features? Understanding how the perception of cultural technologies affects the way humans construct group boundaries has two important consequences.

First, it can contribute to understanding some peculiar cultural phenomena, such as why people often seem to take pride in the ancient roots of their culture (for illustrations of this tendency in modern nationalism, see Hobsbawm & Ranger, Reference Hobsbawm and Ranger1983). One answer may be that the ancient cultural history of a group signals that it has had the time to craft highly complex cultural technologies over the course of generations. A group that can claim ancient cultural roots may be perceived as having institutions that are better at solving the coordination and cooperation problems inherent in human social life, and thus at stabilizing positive-sum relationships.

Second, it can better guide the policy recommendations for peacebuilding. As noted by the author, many peacebuilding initiatives are attempts to create or rejuvenate cultural technologies that favor reconciliation and cooperation. Focusing on social cognition opens an additional avenue: Peace could be favored by exposing people to reliable cues that they evolve under cultural systems that are effective in resolving social dilemmas. For instance, making punishment, peace ceremonies, or any other functional institution more visible to citizens might considerably increase their willingness to interact peacefully.