74 research outputs found
Interview with Dunja Šešelja, Samuli Reijula, and Matteo Michelini
No full textThis interview discusses the use of agent-based modelling in philosophy of science with leading scholars in the field, Dunja Šešelja, Samuli Reijula, and Matteo Michelini
Nudge, boost, or design? Limitations of behaviorally informed policy under social interaction
No full textNudge and boost are two competing approaches to applying the psychology of reasoning and decision making to improve policy. Whereas nudges rely on manipulation of choice architecture to steer people towards better choices, the objective of boosts is to develop good decision-making competences. Proponents of both approaches claim capacity to enhance social welfare through better individual decisions. We suggest that such efforts should involve a more careful analysis of how individual and social welfare are related in the policy context. First, individual rationality is not always sufficient or necessary for improving collective outcomes. Second, collective outcomes of complex social interactions among individuals are largely ignored by the focus of both nudge and boost on individual decisions. We suggest that the design of mechanisms and social norms can sometimes lead to better collective outcomes than nudge and boost, and present conditions under which the three approaches (nudge, boost, and design) can be expected to enhance social welfare
How could a rational analysis model explain?
No full textRational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances
How could a rational analysis model explain?
No full textRational analysis is an influential but contested account of how probabilistic modeling can be used to construct non mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordance
Self-nudging and the citizen choice architect
No full textThis article argues that nudges can often be turned into self-nudges: empowering interventions that enable people to design and structure their own decision environments—that is, to act as citizen choice architects. Self-nudging applies insights from behavioral science in a way that is practicable and cost-effective but that sidesteps concerns about paternalism or manipulation. It has the potential to expand the scope of application of behavioral insights from the public to the personal sphere (e.g., homes, offices, families). It is a tool for reducing failures of self-control and enhancing personal autonomy; specifically, self-nudging can mean designing one’s proximate choice architecture to alleviate the effects of self-control problems, engaging in education to understand the nature and causes of self-control problems and employing simple educational nudges to improve goal attainment in various domains. It can even mean self-paternalistic interventions such as winnowing down one’s choice set by, for instance, removing options. Policy makers could promote self-nudging by sharing knowledge about nudges and how they work. The ultimate goal of the self-nudging approach is to enable citizen choice architects’ efficient self-governance, where reasonable, and the self-determined arbitration of conflicts between their mutually exclusive goals and preferences
Social categories in the making: construction or recruitment?
No full textReal kinds, both natural and social categories, are characterized by rich inductive potential. They have relatively stable sets of conceptually independent projectable properties. Somewhat surprisingly, even some purely social categories (e.g., ethnicity, gender, political orientation) show such multiple projectability. The article explores the origin of the inductive richness of social categories and concepts. I argue that existing philosophical accounts provide only a partial explanation, and mechanisms of boundary formation and stabilization must be brought into view for a more comprehensive account of inductively rich social categories.Peer reviewe
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