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AbstractTwo concepts shaped and continue to shape the discussion on the limits of a liberal and democratic state. First, Mill's harm principle, according to which the fundamental justification for a state exercising power over individuals is to prevent harm being done to others. Second, the distinction between the public sphere, where liberal democracies can intervene, and the private sphere, where individuals are, in principle, free to do as they like. I argue that both concepts have to be revisited in the context of today's 'ultra-processed' world, in which sophisticated technologies and highly engineered products reach deep into the private sphere, exploiting human psychology and jeopardizing citizens' health and welfare in the interest of maximizing profit. In this ultra-processed world, where the distinction between the public and the private spheres is blurred, systemic interventions such as regulation and taxation, often criticized as paternalistic, are necessary to minimize harm. However, they must be complemented by interventions informed by behavioural science that modify and guide individual behaviours. Beyond the soft paternalism of nudging, people can be empowered to self-nudge – a non-paternalistic approach that enables them to design and structure their own decision environments and choice architectures as they see fit.

AbstractIn recent years, public officials have shown a growing interest in using evidence from the behavioural sciences to promote policy goals. Much of the discussion of behaviourally informed approaches has focused on 'nudges'; that is, non-fiscal and non-regulatory interventions that steer (nudge) people in a specific direction while preserving choice. Less attention has been paid to boosts, an alternative evidence-based class of non-fiscal and non-regulatory intervention. The goal of boosts is to make it easier for people to exercise their own agency in making choices. For instance, when people are at risk of making poor health, medical or financial choices, the policy-maker – rather than steering behaviour through nudging – can take action to foster or boost individuals' own decision-making competences. Boosts range from interventions that require little time and cognitive effort on the individual's part to ones that require substantial amounts of training, effort and motivation. This article outlines six rules that policy-makers can apply in order to determine under which conditions boosts, relative to nudges, are the preferable form of non-fiscal and non-regulatory intervention. The objective is not to argue that boosts are better than nudges or vice versa, but to begin to spell out the two approaches' respective conditions for success.

AbstractThis 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.

AbstractDespite 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.

Abstract. The layperson's view associates aging with biological and cognitive losses, which could be associated with decrements in work productivity and overall contributions to society. In turn, ecological approaches to life span development suggest that successful performance can result from an adaptive employment of an individual's physical, cognitive, or social capital in the appropriate environment. This ecological framework suggests that one must understand the demands of particular ecologies (i.e., niches) to predict whether aging is associated with failure, maintenance, or even improvements in performance. We provide examples that illustrate the importance of an ecological approach to understanding adaptation to challenging decision tasks both in the laboratory and in the wild. Overall, we propose that there are specific strategies and niches that can help older adults thrive and that more work is needed to understand the exact characteristics that lead to good performance in old age.

<i>Objectives:</i> Our aim is to provide an overview of key research findings from cognitive psychology regarding effective ways of communicating statistical information, and to point out the implications of these findings for genetic testing. <i>Method:</i> We review the literature on the presentation of statistical information in diagnostic test results, discuss various representations that invite misunderstandings, and propose alternative representations that foster understanding. <i>Results:</i> Single-event probabilities, conditional probabilities and relative risks are easily misunderstood. Specifying the class of events to which a probability refers and using natural frequency statements improve understanding. <i>Conclusions:</i> Cognitive psychology has identified simple and effective tools for improving statistical reasoning. They can help to improve the public's understanding of diagnostic test results.

ABSTRACT
Thaler and Sunstein (2008) advance the concept of 'nudge' policies—non-regulatory and non-fiscal mechanisms designed to enlist people's cognitive biases or motivational deficits so as to guide their behaviour in a desired direction. A core assumption of this approach is that policymakers make artful use of people's cognitive biases and motivational deficits in ways that serve the ultimate interests of the nudged individual. We analyse a model of dynamic policymaking in which the policymaker's preferences are not always aligned with those of the individual. One novelty of our set-up is that the policymaker has the option to implement a 'boost' policy, equipping the individual with the competence to overcome the nudge-enabling bias once and for all. Our main result identifies conditions under which the policymaker chooses not to boost in order to preserve the option of using the nudge (and its associated bias) in the future—even though boosting is in the immediate best interests of both the policymaker and the individual. We extend our analysis to situations in which the policymaker can be removed (e.g., through an election) and in which the policymaker is similarly prone to bias. We conclude with a discussion of some policy implications of these findings.

The Internet has evolved into a ubiquitous digital environment in which people communicate, seek information, and make decisions. Online environments are replete with smart, highly adaptive choice architectures designed primarily to maximize commercial interests, capture and sustain users' attention, monetize user data, and predict and influence future behavior. This online landscape holds multiple negative consequences for society, such as a decline in human autonomy, rising incivility in online conversation, the facilitation of political extremism, and the spread of disinformation. Benevolent choice architects working with regulators may curb the worst excesses of manipulative choice architectures, yet the strategic advantages, resources, and data remain with commercial players. One way to address this imbalance is with interventions that empower Internet users to gain some control over their digital environments, in part by boosting their information literacy and their cognitive resistance to manipulation. Our goal is to present a conceptual map of interventions that are based on insights from psychological science. We begin by systematically outlining how online and offline environments differ despite being increasingly inextricable. We then identify four major types of challenges that users encounter in online environments: persuasive and manipulative choice architectures, AI-assisted information architectures, distractive environments, and false and misleading information. Next, we turn to how psychological science can inform interventions to counteract these challenges of the digital world. After distinguishing between three types of behavioral and cognitive interventions—nudges, technocognition, and boosts—we focus in on boosts, of which we identify two main groups: (1) those aimed at enhancing people's agency in their digital environments (e.g., self-nudging, deliberate ignorance) and (2) those aimed at boosting competences of reasoning and resilience to manipulation (e.g., simple decision aids, inoculation). These cognitive tools are designed to foster the civility of online discourse and protect reason and human autonomy against manipulative choice architectures, attention-grabbing techniques, and the spread of false information.

ABSTRACTWe investigate what processes may underlie heterogeneity in social preferences. We address this question by examining participants' decisions and associated response times across 12 mini‐ultimatum games. Using a finite mixture model and cross‐validating its classification with a response time analysis, we identified four groups of responders: one group takes little to no account of the proposed split or the foregone allocation and swiftly accepts any positive offer; two groups process primarily the objective properties of the allocations (fairness and kindness) and need more time the more properties need to be examined; and a fourth group, which takes more time than the others, appears to take into account what they would have proposed had they been put in the role of the proposer. We discuss implications of this joint decision–response time analysis. Copyright © 2013 John Wiley & Sons, Ltd.