David Pietraszewski's proposal for a computational theory of social groups is a significant original contribution to psychology, cognitive science, and the social sciences, as it offers a non-tautological and relational understanding of social groups by means of a finite collection of cognitive primitives. What I find most commendable in the target article is the attempt to develop a relational account of social groups without compromising the epistemic virtues of precision and clarity: for context, in my home discipline of human geography, relational understandings of social and spatial phenomena too often have come at the high price of imprecise, unclear, and metaphor-laden jargon (cf. Malpas, Reference Malpas2012). Interestingly, Pietraszewski's incisive critique of the still-dominant theorizing of groups as containers in which agents are somehow placed (cf. sect. 8.2, paras. 2–4) and the proposed redefinition of group membership as a relational property parallels recent critiques in human geography of (social) space itself as container and its rethinking in relational terms (Simandan, Reference Simandan2019a, Reference Simandan2020).
Even though the author acknowledges the tentative nature of the theory and the multiple lines of adjacent research needed to flesh it out, he insists without much warrant that the finite set of primitives he identified in sections 3 (paras. 3–4) and 4 (paras. 2–3) is necessary and sufficient for defining social groups in the context of conflict. In the remainder of this commentary, I expose three interrelated conundrums that undermine this simplistic presumption.
The first is the underappreciated role of delays in the computational problem of representing and reasoning about groups. Although the author briefly mentions that “contingent cost-infliction is often a drawn-out process, with many gaps and lulls between interactions” (sect. 6, para. 3) and that “therefore, delays between cost inflictions will have to be allowed for” (sect. 6, para. 3), he fails to develop the logical implications of this observation for how we make sense of groups-in-conflict. To appreciate this point, we need a more elaborate vocabulary for conceptualizing delays in the context of intergroup conflict (cf. Simandan, Reference Simandan2018, Reference Simandan2019b, Reference Simandan2019c). To begin with, a group's response to a particular challenge or move by a rival group can be immediate or delayed. This basic distinction is complicated by the fact that even apparently immediate reactions always involve a number of unavoidable delays pertaining to observation (delay between the emergence of a relevant signal in the environment and one's taking notice of that information), initial insight or coup d'oeil (delay between being aware of disparate signals and their subsequent juxtaposition into an incipient mental schema), full mental model development (delay between initial inchoate insight and its gradual development into a full representation of the group conflict situation), intragroup communication or reporting delays, group decision-making delays, initiation or launching (delay between a group's decision to respond to a rival group's move and the actual moment when that response is carried out), and material delays (the irreducible gap between launching a given response and the time it takes for it to generate results). The formal analysis of the dynamics of intergroup conflict requires dedicated attention to teasing apart unavoidable delays from premeditated or deliberate delays in move-countermove sequences. It also requires a more explicit acknowledgment that delays are a fundamental category that needs to be accounted for in any attempt to formalize the meaning of social groups beyond natural language understanding. This latter point unintentionally transpires even from Pietraszewski's proposed formalism (sects. 3 and 4): Indeed, although he builds his definition of groups-in-conflict by relying on the four triadic primitives of generalization (“A attacks B, then A attacks C”), alliance (“A attacks B, then C attacks B”), displacement (“A attacks B, then B attacks C”), and defense (“A attacks B, then C attacks A”), one of the common threads linking these triadic primitives is that they all function with delays, as signaled by the marker “then” (my emphasis).
The second conundrum results from Pietraszewski's glib relegation of proximity to the status of a mere ancillary attribute of social groups (cf. sect. 8.1, para. 2, and again in sect. 9.2, para. 2). I argue that once we take into account the multidimensional understandings of proximity/distance developed in construal-level theory and evolutionary geography, it becomes apparent that proximity is a strong candidate for inclusion in the set of primitives that defines what a social group is (cf. Simandan, Reference Simandan2016). Construal-level theory (Trope & Liberman, Reference Trope and Liberman2010) has advanced a subjective account of proximity whereby distance is a metric that tracks how far removed from the self-in-the-here-and-now an item is alongside the four interrelated dimensions of space, time, uncertainty, and sociality. Evolutionary geography (Boschma, Reference Boschma2005) has also moved toward a multidimensional conceptualization of proximity, identifying no less than five types: cognitive (degree of overlap between the dominant mental representations of two groups or organizations), geographical (physical objective distance), organizational (extent of shared history or past cooperation between two groups), institutional (degree of overlap between the cultures of two groups), and social proximity (intensity of social and kinship ties between two agents or groups). Both of the aforementioned theories identify social proximity as one of the crucial dimensions of proximity. In natural language, we use the vocabularies of social proximity and social groups seamlessly and often interchangeably: I would therefore urge Pietraszewski to develop his formal account of groups by exploring ways to upgrade proximity (understood multidimensionally) from ancillary to central status.
Finally, Pietraszewski's proposed building blocks for a computational account of social groups reveal repeatedly that the problematic of loyalty and disloyalty seems to be inextricably intertwined with how agents make inferences about groups (e.g., sect. 8.2, para. 6 and sect. 8.3, para. 2; sect. 8.4, para. 3). Which brings out the question: What would a computational theory of group loyalty itself look like? The philosophical literature on loyalty may not offer useful starting points because it often frames this topic as “an important area of the normative” (Oldenquist, Reference Oldenquist1982, p. 173). A more promising starting point seems to be appraising the dynamic relationship between social proximity and loyalty, and thereby pushing the relational understanding of social groups one step further.
David Pietraszewski's proposal for a computational theory of social groups is a significant original contribution to psychology, cognitive science, and the social sciences, as it offers a non-tautological and relational understanding of social groups by means of a finite collection of cognitive primitives. What I find most commendable in the target article is the attempt to develop a relational account of social groups without compromising the epistemic virtues of precision and clarity: for context, in my home discipline of human geography, relational understandings of social and spatial phenomena too often have come at the high price of imprecise, unclear, and metaphor-laden jargon (cf. Malpas, Reference Malpas2012). Interestingly, Pietraszewski's incisive critique of the still-dominant theorizing of groups as containers in which agents are somehow placed (cf. sect. 8.2, paras. 2–4) and the proposed redefinition of group membership as a relational property parallels recent critiques in human geography of (social) space itself as container and its rethinking in relational terms (Simandan, Reference Simandan2019a, Reference Simandan2020).
Even though the author acknowledges the tentative nature of the theory and the multiple lines of adjacent research needed to flesh it out, he insists without much warrant that the finite set of primitives he identified in sections 3 (paras. 3–4) and 4 (paras. 2–3) is necessary and sufficient for defining social groups in the context of conflict. In the remainder of this commentary, I expose three interrelated conundrums that undermine this simplistic presumption.
The first is the underappreciated role of delays in the computational problem of representing and reasoning about groups. Although the author briefly mentions that “contingent cost-infliction is often a drawn-out process, with many gaps and lulls between interactions” (sect. 6, para. 3) and that “therefore, delays between cost inflictions will have to be allowed for” (sect. 6, para. 3), he fails to develop the logical implications of this observation for how we make sense of groups-in-conflict. To appreciate this point, we need a more elaborate vocabulary for conceptualizing delays in the context of intergroup conflict (cf. Simandan, Reference Simandan2018, Reference Simandan2019b, Reference Simandan2019c). To begin with, a group's response to a particular challenge or move by a rival group can be immediate or delayed. This basic distinction is complicated by the fact that even apparently immediate reactions always involve a number of unavoidable delays pertaining to observation (delay between the emergence of a relevant signal in the environment and one's taking notice of that information), initial insight or coup d'oeil (delay between being aware of disparate signals and their subsequent juxtaposition into an incipient mental schema), full mental model development (delay between initial inchoate insight and its gradual development into a full representation of the group conflict situation), intragroup communication or reporting delays, group decision-making delays, initiation or launching (delay between a group's decision to respond to a rival group's move and the actual moment when that response is carried out), and material delays (the irreducible gap between launching a given response and the time it takes for it to generate results). The formal analysis of the dynamics of intergroup conflict requires dedicated attention to teasing apart unavoidable delays from premeditated or deliberate delays in move-countermove sequences. It also requires a more explicit acknowledgment that delays are a fundamental category that needs to be accounted for in any attempt to formalize the meaning of social groups beyond natural language understanding. This latter point unintentionally transpires even from Pietraszewski's proposed formalism (sects. 3 and 4): Indeed, although he builds his definition of groups-in-conflict by relying on the four triadic primitives of generalization (“A attacks B, then A attacks C”), alliance (“A attacks B, then C attacks B”), displacement (“A attacks B, then B attacks C”), and defense (“A attacks B, then C attacks A”), one of the common threads linking these triadic primitives is that they all function with delays, as signaled by the marker “then” (my emphasis).
The second conundrum results from Pietraszewski's glib relegation of proximity to the status of a mere ancillary attribute of social groups (cf. sect. 8.1, para. 2, and again in sect. 9.2, para. 2). I argue that once we take into account the multidimensional understandings of proximity/distance developed in construal-level theory and evolutionary geography, it becomes apparent that proximity is a strong candidate for inclusion in the set of primitives that defines what a social group is (cf. Simandan, Reference Simandan2016). Construal-level theory (Trope & Liberman, Reference Trope and Liberman2010) has advanced a subjective account of proximity whereby distance is a metric that tracks how far removed from the self-in-the-here-and-now an item is alongside the four interrelated dimensions of space, time, uncertainty, and sociality. Evolutionary geography (Boschma, Reference Boschma2005) has also moved toward a multidimensional conceptualization of proximity, identifying no less than five types: cognitive (degree of overlap between the dominant mental representations of two groups or organizations), geographical (physical objective distance), organizational (extent of shared history or past cooperation between two groups), institutional (degree of overlap between the cultures of two groups), and social proximity (intensity of social and kinship ties between two agents or groups). Both of the aforementioned theories identify social proximity as one of the crucial dimensions of proximity. In natural language, we use the vocabularies of social proximity and social groups seamlessly and often interchangeably: I would therefore urge Pietraszewski to develop his formal account of groups by exploring ways to upgrade proximity (understood multidimensionally) from ancillary to central status.
Finally, Pietraszewski's proposed building blocks for a computational account of social groups reveal repeatedly that the problematic of loyalty and disloyalty seems to be inextricably intertwined with how agents make inferences about groups (e.g., sect. 8.2, para. 6 and sect. 8.3, para. 2; sect. 8.4, para. 3). Which brings out the question: What would a computational theory of group loyalty itself look like? The philosophical literature on loyalty may not offer useful starting points because it often frames this topic as “an important area of the normative” (Oldenquist, Reference Oldenquist1982, p. 173). A more promising starting point seems to be appraising the dynamic relationship between social proximity and loyalty, and thereby pushing the relational understanding of social groups one step further.
Financial support
This research received no specific grant from any funding agency, commercial, or not-for-profit sectors
Conflict of interest
None.