If citizens’ behavior threatens to harm others or seems not to be in their own interest, it is not uncommon for governments to attempt to change that behavior. Governmental policy makers can apply established tools from the governmental toolbox to this end. Alternatively, they can employ new tools that capitalize on the wealth of knowledge about human behavior and behavior change that has been accumulated in the behavioral sciences. Two contrasting approaches to behavior change are nudge policies and boost policies. (...) These policies rest on fundamentally different research programs on bounded rationality, namely, the heuristics and biases program and the simple heuristics program, respectively. This article examines the policy–theory coherence of each approach. To this end, it identifies the necessary assumptions underlying each policy and analyzes to what extent these assumptions are implied by the theoretical commitments of the respective research program. Two key results of this analysis are that the two policy approaches rest on diverging assumptions and that both suffer from disconnects with the respective theoretical program, but to different degrees: Nudging appears to be more adversely affected than boosting does. The article concludes with a discussion of the limits of the chosen evaluative dimension, policy–theory coherence, and reviews some other benchmarks on which policy programs can be assessed. (shrink)
Some theorists, ranging from W. James to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies on (...) systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds. (shrink)
This target article is concerned with the implications of the surprisingly different experimental practices in economics and in areas of psychology relevant to both economists and psychologists, such as behavioral decision making. We consider four features of experimentation in economics, namely, script enactment, repeated trials, performance-based monetary payments, and the proscription against deception, and compare them to experimental practices in psychology, primarily in the area of behavioral decision making. Whereas economists bring a precisely defined “script” to experiments for participants to (...) enact, psychologists often do not provide such a script, leaving participants to infer what choices the situation affords. By often using repeated experimental trials, economists allow participants to learn about the task and the environment; psychologists typically do not. Economists generally pay participants on the basis of clearly defined performance criteria; psychologists usually pay a flat fee or grant a fixed amount of course credit. Economists virtually never deceive participants; psychologists, especially in some areas of inquiry, often do. We argue that experimental standards in economics are regulatory in that they allow for little variation between the experimental practices of individual researchers. The experimental standards in psychology, by contrast, are comparatively laissez-faire. We believe that the wider range of experimental practices in psychology reflects a lack of procedural regularity that may contribute to the variability of empirical findings in the research fields under consideration. We conclude with a call for more research on the consequences of methodological preferences, such as the use on monetary payments, and propose a “do-it-both-ways” rule regarding the enactment of scripts, repetition of trials, and performance-based monetary payments. We also argue, on pragmatic grounds, that the default practice should be not to deceive participants. Key Words: behavioral decision making; cognitive illusions; deception; experimental design; experimental economics; experimental practices; financial incentives; learning; role playing. (shrink)
What motivates grandparents to their altruism? We review answers from evolutionary theory, sociology, and economics. Sometimes in direct conflict with each other, these accounts of grandparental investment exist side-by-side, with little or no theoretical integration. They all account for some of the data, and none account for all of it. We call for a more comprehensive theoretical framework of grandparental investment that addresses its proximate and ultimate causes, and its variability due to lineage, values, norms, institutions (e.g., inheritance laws), and (...) social welfare regimes. This framework needs to take into account that the demographic shift to low fecundity and mortality in economically developed countries has profoundly altered basic parameters of grandparental investment. We then turn to the possible impact of grandparental acts of altruism, and examine whether benefits of grandparental care in industrialized societies may manifest in terms of less tangible dimensions, such as the grandchildren's cognitive and verbal ability, mental health, and well-being. Although grandparents in industrialized societies continue to invest substantial amounts of time and money in their grandchildren, we find a paucity of studies investigating the influence that this investment has on grandchildren in low-risk family contexts. Under circumstances of duress there is converging evidence that grandparents can provide support that helps to safeguard their children and grandchildren against adverse risks. We conclude by discussing the role that grandparents could play in what has been referred to as Europe's demographic suicide. (shrink)
Most investigations into how people make risky choices have employed a simple drosophila: monetary gambles involving stated outcomes and probabilities. People are asked to make decisions from description . When people decide whether to back up their computer hard drive, cross a busy street, or go out on a date, however, they do not enjoy the convenience of stated outcomes and probabilities. People make such decisions either in the void of ignorance or in the twilight of their own often limited (...) experience of such real-world options. In the latter case, they make decisions from experience . Recent research has consistently documented that decisions from description and decisions from experience can lead to substantially different choices. Key in this description–experience gap is people’s treatment of rare events. In this paper, I briefly review studies that have documented the description–experience gap, offer several explanations for this gap, and discuss to what extent people’s decisions from experience are in conflict with benchmarks of rationality. (shrink)
The classical view that equates rationality with adherence to the laws of probability theory and logic has driven much research on inference. Recently, an increasing number of researchers have begun to espouse a view of rationality that takes account of organisms' adaptive goals, natural environments, and cognitive constraints. We argue that inference is carried out using boundedly rational heuristics, that is, heuristics that allow organisms to reach their goals under conditions of limited time, information, and computational capacity. These heuristics are (...) ecologically rational in that they exploit aspects of both the physical and social environment in order to make adaptive inferences. We review recent work exploring this multifaceted conception of rationality. (shrink)
In psychology, deception is commonly used to increase experimental control. Yet, its use has provoked concerns that it raises participants' suspicions, prompts second-guessing of experimenters' true intentions, and ultimately distorts behavior and endangers the control it is meant to achieve. Over time, these concerns regarding the methodological costs of the use of deception have been subjected to empirical analysis. We review the evidence stemming from these studies.
Despite the ubiquity of uncertainty, scientific attention has focused primarily on probabilistic approaches, which predominantly rely on the assumption that uncertainty can be measured and expressed numerically. At the same time, the increasing amount of research from a range of areas including psychology, economics, and sociology testify that in the real world, people’s understanding of risky and uncertain situations cannot be satisfactorily explained in probabilistic and decision-theoretical terms. In this article, we offer a theoretical overview of an alternative approach to (...) uncertainty developed in the framework of the ecological rationality research program. We first trace the origins of the ecological approach to uncertainty in Simon’s bounded rationality and Brunswik’s lens model framework and then proceed by outlining a theoretical view of uncertainty that ensues from the ecological rationality approach. We argue that the ecological concept of uncertainty relies on a systemic view of uncertainty that features it as a property of the organism–environment system. We also show how simple heuristics can deal with unmeasurable uncertainty and in what cases ignoring probabilities emerges as a proper response to uncertainty. (shrink)
This response reinforces the major themes of our target article. The impact of key methodological variables should not be taken for granted. Rather, we suggest grounding experimental practices in empirical evidence. If no evidence is available, decisions about design and implementation ought to be subjected to systematic experimentation. In other words, we argue against empirically blind conventions and against methodological choices based on beliefs, habits, or rituals. Our approach will neither inhibit methodological diversity nor constrain experimental creativity. More likely, it (...) will promote both goals. (shrink)
This response outlines more reasons why we need the integrative framework of grandparental investments and intergenerational transfers that we advocated in the target article. We discusses obstacles that stand in the way of such a framework and of a better understanding of the effects of grandparenting in the developed world. We highlight new research directions that have emerged from the commentaries, and we end by discussing some of the things in our target article about which we may have been wrong.
A key premise of the heuristics-and-biases program is that heuristics are “quite useful.” Let us now pay more than lip service to this premise, and analyse the environmental structures that make heuristics more or less useful. Let us also strike from the long list of biases those phenomena that are not biases and explore to what degree those that remain are adaptive or can be understood as by-products of adaptive mechanisms.
Campbell's target article is a stimulating attempt to extend our understanding of sex differences in risk-taking behaviors. However, Campbell does not succeed in demonstrating that her account adds explanatory power to those (e.g., Daly & Wilson 1994) previously proposed. In particular, little effort was made to explore the causal links between survival (staying alive) and reproduction.
The notion of “cognitive ability” leads to paradoxical conclusions when invoked to explain Inhelder and Piaget's research on class inclusion reasoning and research on the inclusion rule in the heuristics-and-biases program. The vague distinction between associative and rule-based reasoning overlooks the human capacity for semantic and pragmatic inferences, and consequently, makes intelligent inferences look like reasoning errors.