Maps facilitate the orientation in complex worlds, and the target article by Bentley et al. provides an excellent map to the world of human decision behavior. But maps are more than descriptive tools; they coin entities and influence the way the map makers think about the world – the information maps provide feedback to those who have been mapped. Ian Hacking established the term “looping effect” to convey the notion that when humans (as opposed to, say, molecules) are the object of investigation, they consciously react to both the process and the product of investigation.
Famously, Hacking (Reference Hacking1992) illustrated the principle of looping by pointing out the influence of medical-psychological classification systems on the prevalence of certain health-related conditions. For instance, in North America the condition labeled “multiple personality disorder” appeared to explode in frequency after the medical community accepted it as a disease, devoted scientific conferences to the topic, and had findings and opinions regarding it disseminated among the general public. In the United Kingdom, where the same condition was regarded as an iatrogenic madness of the crowd, multiple personalities remained rare. Hacking's point was that illnesses can be transient and regional just like the classification manuals of mental diseases are bound to certain times and places. Mapping diseases is not principally different from mapping healthy human behavior, from sexual orientation to attitudes toward poverty, immigration, and violence (Hacking Reference Hacking, Sperber, Premack and Premack1995), but also to first-name or Facebook popularity.
Given the undeniable fact that, in social research, the product of investigation thus influences the object of investigation, in what ways could looping shape the map proposed by Bentley and colleagues to describe human collective behavior? When people know that their behavior is in the southeast (using Bentley et al.’s terminology), what effect would this knowledge have? We suggest that this kind of information adds a third dimension to the map that may be captured by the analogy of height (or contour lines on geographical maps) indicating the degree of self-reflection the observed agents have upon their behavior. Even if you are in the same quadrant of the map – it is quite a different situation to be deep in a valley lacking “looping-related” insights compared to being on top of a hill indicating a high degree of self-reflection the agent (or system of agents) has with respect to their knowledge of what they know about themselves or others know about them.
We suggest that such looping-related insights indicating the degree of self-reflection refer to two types of knowledge that are related to two ambiguities inherent to the dimensions of the map proposed by Bentley et al. Their first dimension concerns the degree of social influence on the decision of the agent, with complete independence attainable at the far western side of their map and a pronounced susceptibility to mirror social expectancies at the far eastern side of their map. Going from west to east thus denotes an increase in social influence, which is associated with the ability to discern social behaviors and options associated with others’ behaviors and to adopt the own behavior through mechanisms such as, for instance, imitation. The perspective of looping, however, adds an additional knowledge component to this picture, because people make models (simple theories) based on themselves as well as on other people with respect to mechanisms driving their behaviors. People may copy the behavior of others without knowing anything about why they display a particular behavior, or by having an accurate model of the mechanisms that drive their own and others’ decisions. Although this modeling does not directly change observed behavior patterns, it will have an impact, as outlined below.
The second dimension in Bentley et al.’s map captures the transparency in the payoffs and risks associated with the decisions agents make. In the far north, people have full transparency on what options are available and what their associated payoffs are. In the deep south, options and their consequences are opaque. But again, we need to consider an orthogonal dimension associated with this north–south axis, one that takes looping into account. That is, it critically matters whether an agent is aware of whether his or her knowledge of option payoffs is accessible to third parties, too. People may have no transparency with respect to payoffs and know that others also lack this transparency – or they may not know to what extent the others know the payoffs. Again, the opacity of the payoff for each person is the same, but the two situations drastically differ.
If we quantify effects of looping as the degree of self-reflection along the two dimensions just outlined, we do not expect that the major characteristics of the behavioral pattern in terms of output distributions change (e.g., Gaussian in the northwest versus long-tailed in the southeast). However, we suggest that this additional dimension helps one to understand the dynamics on this map. In a nutshell, we believe that a higher degree of self-reflection will allow for quicker movements on the map, that is, make behavioral patterns more unstable.
Having accurate knowledge (and models) of what drives others’ decisions will allow for strategic decisions which – just as the “invention” of new diseases has shown – may then change the behavioral mechanisms of others, by providing novel “identities” for persons: that is, a mechanism of de-stabilization. In contrast, not knowing that others also don't know enhances the opacity of payoffs and may contribute to pluralistic ignorance. This would stabilize social dynamics, if often only in a suboptimal state. Elaborating the map analogy a bit further: A higher degree of self-reflection means standing on a mountain with a view, but risking falling down (and consequently to be relocated on the map). Finally, this analogy points to an additional aspect when taking looping into account: Increased self-reflection – also by reading sociologists’ behavioral maps – may not be a positive exercise in all cases. While many situations may require an increase in self-reflection, in other situations (supported, e.g., by privacy arguments) too much self-reflection may lend a disservice to the agent (Christen et al. Reference Christen, Alfano, Bangerter, Lapsley, Rahman and Ramos2013).
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Maps facilitate the orientation in complex worlds, and the target article by Bentley et al. provides an excellent map to the world of human decision behavior. But maps are more than descriptive tools; they coin entities and influence the way the map makers think about the world – the information maps provide feedback to those who have been mapped. Ian Hacking established the term “looping effect” to convey the notion that when humans (as opposed to, say, molecules) are the object of investigation, they consciously react to both the process and the product of investigation.
Famously, Hacking (Reference Hacking1992) illustrated the principle of looping by pointing out the influence of medical-psychological classification systems on the prevalence of certain health-related conditions. For instance, in North America the condition labeled “multiple personality disorder” appeared to explode in frequency after the medical community accepted it as a disease, devoted scientific conferences to the topic, and had findings and opinions regarding it disseminated among the general public. In the United Kingdom, where the same condition was regarded as an iatrogenic madness of the crowd, multiple personalities remained rare. Hacking's point was that illnesses can be transient and regional just like the classification manuals of mental diseases are bound to certain times and places. Mapping diseases is not principally different from mapping healthy human behavior, from sexual orientation to attitudes toward poverty, immigration, and violence (Hacking Reference Hacking, Sperber, Premack and Premack1995), but also to first-name or Facebook popularity.
Given the undeniable fact that, in social research, the product of investigation thus influences the object of investigation, in what ways could looping shape the map proposed by Bentley and colleagues to describe human collective behavior? When people know that their behavior is in the southeast (using Bentley et al.’s terminology), what effect would this knowledge have? We suggest that this kind of information adds a third dimension to the map that may be captured by the analogy of height (or contour lines on geographical maps) indicating the degree of self-reflection the observed agents have upon their behavior. Even if you are in the same quadrant of the map – it is quite a different situation to be deep in a valley lacking “looping-related” insights compared to being on top of a hill indicating a high degree of self-reflection the agent (or system of agents) has with respect to their knowledge of what they know about themselves or others know about them.
We suggest that such looping-related insights indicating the degree of self-reflection refer to two types of knowledge that are related to two ambiguities inherent to the dimensions of the map proposed by Bentley et al. Their first dimension concerns the degree of social influence on the decision of the agent, with complete independence attainable at the far western side of their map and a pronounced susceptibility to mirror social expectancies at the far eastern side of their map. Going from west to east thus denotes an increase in social influence, which is associated with the ability to discern social behaviors and options associated with others’ behaviors and to adopt the own behavior through mechanisms such as, for instance, imitation. The perspective of looping, however, adds an additional knowledge component to this picture, because people make models (simple theories) based on themselves as well as on other people with respect to mechanisms driving their behaviors. People may copy the behavior of others without knowing anything about why they display a particular behavior, or by having an accurate model of the mechanisms that drive their own and others’ decisions. Although this modeling does not directly change observed behavior patterns, it will have an impact, as outlined below.
The second dimension in Bentley et al.’s map captures the transparency in the payoffs and risks associated with the decisions agents make. In the far north, people have full transparency on what options are available and what their associated payoffs are. In the deep south, options and their consequences are opaque. But again, we need to consider an orthogonal dimension associated with this north–south axis, one that takes looping into account. That is, it critically matters whether an agent is aware of whether his or her knowledge of option payoffs is accessible to third parties, too. People may have no transparency with respect to payoffs and know that others also lack this transparency – or they may not know to what extent the others know the payoffs. Again, the opacity of the payoff for each person is the same, but the two situations drastically differ.
If we quantify effects of looping as the degree of self-reflection along the two dimensions just outlined, we do not expect that the major characteristics of the behavioral pattern in terms of output distributions change (e.g., Gaussian in the northwest versus long-tailed in the southeast). However, we suggest that this additional dimension helps one to understand the dynamics on this map. In a nutshell, we believe that a higher degree of self-reflection will allow for quicker movements on the map, that is, make behavioral patterns more unstable.
Having accurate knowledge (and models) of what drives others’ decisions will allow for strategic decisions which – just as the “invention” of new diseases has shown – may then change the behavioral mechanisms of others, by providing novel “identities” for persons: that is, a mechanism of de-stabilization. In contrast, not knowing that others also don't know enhances the opacity of payoffs and may contribute to pluralistic ignorance. This would stabilize social dynamics, if often only in a suboptimal state. Elaborating the map analogy a bit further: A higher degree of self-reflection means standing on a mountain with a view, but risking falling down (and consequently to be relocated on the map). Finally, this analogy points to an additional aspect when taking looping into account: Increased self-reflection – also by reading sociologists’ behavioral maps – may not be a positive exercise in all cases. While many situations may require an increase in self-reflection, in other situations (supported, e.g., by privacy arguments) too much self-reflection may lend a disservice to the agent (Christen et al. Reference Christen, Alfano, Bangerter, Lapsley, Rahman and Ramos2013).