Commentary/Bentley et al.: Mapping collective behavior global games are modeled as fully rational, exogenous noise can push them into Bentley et al.'s southeast quadrant, leading to such phenomena as market bubbles and bank mns. Finally, microeconomic modeling of labor, product, and techno!ogy diffusion markets increasingly borrows network theory (Goyal 2007), the dominant mathematics of the souüieast. There is irony here. Behavioral economists criticize standard economics as, in Bentley et al.'s terms, stuck in the nortliwest. They then creep cautiously south, whue die economists they criticize range all over the map.
Understanding social networks requires more than two dimensions doi:10.1017/S0140525X13001878 Derek Ruths^ and Thomas Shultz" "School of Computer Science, Network Dynamics Lab, fVlcGill University, Montreal, Quebec, H3A 2A7, Canada; "Department of Psychology, Laboratory for Natural and Simulated Cognition, and School of Computer Science, McGill University, Montreal, Quebec H3A 1B1, Canada. [email protected] [email protected]
Abstract: The proposed framework is insufficient to categorize and understand current evidence on decision making. There are some amhiguiües in die que.stions asked that require additional distinctions hetween correctness and accuracy, decision tnaking and leaming, accuracy and confidence, and social influence and empowerment. Social leaming techniques are not all tlie same: Behavior copying is quite different frotn theory passing. Sigmoidal acqtjisition curves are not unique to social leaming and are often tiiistaken for otlier accelerating curves.
Bentley et al. address the issue of how people make decisions in the realm of large-scale social media. They propose an interesting two-dimensional framework in wlúch to classify major influences on decision making: an east-west axis reflecting the degree to wliich decisions are made individually versus socially influenced, and a north-south axis reflecting the degree of transparency of the payoffs and rislcs associated with particular decisions. This is a useful start, and Bendey et al. get a certain amount of mileage from considering decision making within this framework. However, it is already apparent to us diat diis framework is insufficient to categorize and undei-stand current ewdence on decision making. The question being asked. An issue diat overshadows the work is a lack of clarity as to what aspect of human decision making they want to approach. A model is best evaluated within the context of the question it is being used to answer. For example, two specific questions that seem relevant to the proposed framework are: (1) "How do social context and critical thinking interact in producing right or wrong thinking?" and (2) "What is the role of social engagement in decision making?" These questions are reasonable, but involve the use of the proposed model in different ways. Furtliermore, neither can be answered using the framework as proposed: For case 1, the model lacks a notion of correctness; for case 2, the model is unclear about modes of social interaction. In the target article text, the authors do not identify a particular, precise question that their approach addresses. This issue derives, in part, from ambiguity about how certain aspects of die proposed mode! shou!d be interpreted. We hig!dight three of these below. Decision making or learning? Despite their discussion of decision maldng in dieir introductory remarks, it is sometimes unclear which of these human processes Bentley et al. are applying their model to-decision making or leaming. Although decision making and leaming are related, they are distinct processes diat cannot be lightly interchanged (Busemeyer & Johnson 2006).
Accurate or confkient perception? The proposed north-south axis is described in terms of clarity of infomiation. But what is the nature of this clarity? Are we concemed with whether the indixidual feels confident about tlieir perception of risks and rewards, irrespective of whether their perception is correct; or are we concemed with whether the individual accurately perceives the risk/ rewards? The two are not the same tiling and may need to be separated into different axes. Social influence or empowerment? The social (east-west) axis characterizes an ambiguous social dimension. Does moving east involve odier people having increasing sway over what the individual believes (social influence) or odier people having increasing sway over whether an individuid acts on their belief (social empowerment)? Each of these is valid, but they reflect quite different and important aspects of decision making in a socia! context. Lumping together all social learning methods. Bendey et al lump a variety of social leaming techniques togedier under a high value of their/ parameter. However, tliere is now evidence that cultural transmission, deflned as dieory passing, has sharply different characteristics from imitation (Montrey & Shultz 2010). Imitation (defined as attempted copying of behavior) is a lossy way to transmit information and may quickly become outdated in rapidly changing en\dronments. In contrast, cultiira! transmission via passing of theories from one agent to another builds on existing knowledge, creating a strong ratchet effect with very little backsliding. In the Montrey and Shultz study, there were diree leaming methods in an agent-based model on a fuUy occupied lattice: imitation, exploration, and theoiy passing. Each leaming method was implemented as a variant of Bayesian leaming. As in previous work (Beppu & Griffiths 2009), three aUeles were compared: imitation alone (least adaptive), imitation plus exploration (moderately adaptive), and imitation plus exploration plus theory passing (most adaptive). Agents reproduced by cloning an offspring according to their own fitness. Shape of acquisition curve is not definitive. The authors use the shape of acquisition curves to unequivocally identify underlying leaming strategies. But this method is known to be difficult and often unreliable because the same shape can be consistent with more than one leaming method. For example, individual leaming typically produces a sigmoidal curve (Shultz 2003), a shape that Bentley et al. assume is a unique signature of social leaming. Not only is the overall acquisition curve often sigmoidal (basically, a spurt connecting two plateaus), but widi denser time sampling, numerous sigmoidal spurts can be found. Moreover, a number of different accelerating functions have been successfully fit to social leaming data (Reader 2004). Even if the underlying social leaming cui-ve is truly sigmoidal, it can be mistakenly viewed as accelerating if final data points are missed, or as decelerating if early data points are missed. Closing remarks. Despite the concems raised above, Bendey et al. meaningfully contribute on an important topic: how social, metJia, and intemal milieus interact to infomi human decision making. The problem is higlily dimensional, and Bendey et al. have provided a framework on which future work can productively budd.
The giobal shift: Shadows of identifiability doi:10.1017/S0140525X1300188X Colin T. Schmidt Head of Technology Appropriateness, ENSAM-ParisTech & Lavai Technical Institute, LeMans University, 53020 Laval, France. [email protected]
Abstract; The presence of ovei-whelming amounts of information in our hig-data era society is growing. Glohalisaüon is increasingly giving these solicitations (regarding information) a more social aspect causing BEHAVIORAL AND BRAIN SCIENCES (2014) 37:1
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