We have previously argued thatbehavioral scientists have been testing and advocating individualistic (i-frame) solutions to policy problems that have systemic (s-frame) causes and require systemic solutions. Here, we consider the implications of adopting an s-frame approach for research. We argue that an s-frame approach will involve addressing different types of questions, which will, in turn, require a different toolbox of research methods.

It is widely agreed upon that morality guides people with conflicting interests towards agreements of mutual benefit. We therefore might expect numerous proposals for organizing human moral cognition around the logic of bargaining, negotiation, and agreement. Yet, while “contractualist” ideas play an important role in moral philosophy, they are starkly underrepresented in the field of moral psychology. From a contractualist perspective, ideal moral judgments are those that would be agreed to by rational bargaining agents—an idea with wide-spread support in philosophy, psychology, economics, biology, and cultural evolution. As a practical matter, however, investing time and effort in negotiating every interpersonal interaction is unfeasible. Instead, we propose, people use abstractions and heuristics to efficiently identify mutually beneficial arrangements. We argue that many well-studied elements of our moral minds, such as reasoning about others’ utilities (“consequentialist” reasoning) or evaluating intrinsic ethical properties of certain actions (“deontological” reasoning), can be naturally understood as resource-rational approximations of a contractualist ideal. Moreover, this view explains the flexibility of our moral minds—how our moral rules and standards get created, updated and overridden and how we deal with novel cases we have never seen before. Thus, the apparently fragmentary nature of our moral psychology—commonly described in terms of systems in conflict—can be largely unified around the principle of finding mutually beneficial agreements under resource constraint. Our resulting “triple theory” of moral cognition naturally integrates contractualist, consequentialist and deontological concerns.

Our target article distinguishes between policy approaches that seek to address societal problems through intervention at the level of the individual (adopting the “i-frame”) and those that seek to change the system within which those individuals live (adopting the “s-frame”). We stress also that a long-standing tactic of corporations opposing systemic change is to promote the i-frame perspective, presumably hoping that i-frame interventions will be largely ineffective and more importantly will be seen by the public and some policy makers as a genuine alternative to systemic change. We worry that the i-frame focus of much of behavioral science has inadvertently reinforced this unhelpful focus on the individual. In this response to commentators, we identify common themes, build on the many constructive suggestions to extend our approach, and reply to concerns. We argue, along with several commentators, that a key role of behavioral public policy is to clarify how to build support for systemic reforms for which there is a broad consensus in the policy community, but which are opposed by powerful special interests.

Johnson et al. make a persuasive case that qualitative, story-like reasoning plays a crucial role in everyday thought and decision-making. This commentary questions the cohesiveness of this type of reasoning and the representations that generate it. Perhaps narratives do not underpin, but are ephemeral products of thought, created when we need to justify our actions to ourselves and others.

We agree with Heintz & Scott-Phillips that pragmatics does not supplement, but is prior to and underpins, language. Indeed, human non-linguistic communication is astonishingly rich, flexible, and subtle, as we illustrate through the game of charades, where people improvise communicative signals when linguistic channels are blocked. The route from non-linguistic charade-like communication to combinatorial language involves (1) local processes of conventionalization and grammaticalization and (2) spontaneous order arising from mutual constraints between different communicative signals.

We report an experiment exploring sequential context effects on strategy choices in one-shot Prisoner’s Dilemma (PD) game. Rapoport and Chammah (1965) have shown that some PDs are cooperative and lead to high cooperation rate, whereas others are uncooperative. Participants played very cooperative and very uncooperative games, against anonymous partners. The order in which these games were played affected their cooperation rate by producing perceptual contrast, which appeared only between the trials, but not between two separate sequences of games. These findings suggest that people may not have stable perceptions of absolute cooperativeness. Instead, they judge the cooperativeness of each fresh game only in relation to the previous game. The observed effects suggest that the principles underlying judgments about highly abstract magnitudes such as cooperativeness may be similar to principles governing the perception of sensory magnitudes.

We report a study of the effects the choice set on financial decision making related to retirement savings and risky investment. The participants were presented with either a full range of choice options or a limited subset of the feasible options. The choices of saving and risk are affected by the position of each option in the range of presented options. This result demonstrated that the range of the options offered as possible saving rates and levels of investment risk influences decisions about saving and risk. The study was conducted on a sample of working people, and we controlled whether the participants can financially afford in their real life the decisions taken in the test. In addition, various measures of risk aversion did not account for the risk taken in each condition. Surprisingly, only the simplest and most direct risk preference measure was a significant predictor of the responses within a particular choice set context, although the actual choices were still very much influenced by the range. Thus, the results reported here suggest that financial judgments and choices are relative, which corroborates, in an important practical domain, previous related work with abstract gambles and hypothetical risky investments.

Vlaev and Chater (2006) demonstrated that the cooperativeness of previously seen prisoner’s dilemma games biases choices and predictions in the current game. These effects were: a) assimilation to the mean cooperativeness of the played games caused by action reinforcement, and b) perceptual contrast with the preceding games depending on the range and the rank order of their cooperativeness. We demonstrate that, when playing against choice strategies that are not biased by such factors, perceptual biases disappear and only assimilation bias caused by reinforcement persists. This suggests that reinforcement learning is a powerful source of inconsistency in strategic interaction, which may not be eliminated even if the other players are unbiased and the markets are efficient.

Bermúdez convincingly argues that framing effects are ubiquitous and that this is not a sign of human irrationality, but an unavoidable feature of any intelligent system. The commentary adds that framing effects arise even in formal domains, such as chess and mathematics, which appear paradigms of rational thought. Indeed, finding and attempting to resolve clashes between different frames is a major impetus for deliberative cognition.

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: To adopt what we call the “i-frame,” rather than the “s-frame.” The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contribute to public policy is by employing their skills to develop and implement value-creating system-level change.

Many proponents of behavioural public policy work within a broadly consequentialist framework. From this perspective, the ultimate aim of public policy is to maximise utility, happiness, welfare, the satisfaction of preferences, or similar; and the behavioural aspect of public policy aims to harness a knowledge of human psychology to make this maximisation more effective. In particular, behavioural insights may be crucial to help policy-makers ‘save us from ourselves’ by helping citizens avoid falling into non-rational choices, for example, through framing effects, failures of will-power, and so on. But an alternative reading of the psychological literature is that human thoughts and actions are not biased from a rational standard, but are simply systematically inconsistent. If so, then utility and similar notions are not well defined either for individuals or as an objective of public policy. I argue that a different, contractarian viewpoint is required: that the determination of public policy is continuous with the formation of agreements we make with each other at all scales, from momentary social interactions, to linguistic and social conventions, to collective decisions by groups and organisations. Behavioural factors do not over-ride, but can (among many other factors) inform, our collective decision-making process. The point of behavioural insights in public policy is primarily to inform and enrich public debate when deciding the rules by which we should like to live.

Resource rationality is useful for choosing between models with the same cognitive constraints but cannot settle fundamental disagreements about what those constraints are. We argue that sampling is an especially compelling constraint, as optimizing accumulation of evidence or hypotheses minimizes the cost of time, and there are well-established models for doing so which have had tremendous success explaining human behavior.

Frijters et al. make a powerful and lucid case for a top-down approach to government, in which the maximization of wellbeing should be the ultimate goal. I argue, by contrast, for a bottom-up approach: that the variety of goals, plans, norms and rules that govern our lives should be the starting point for political discussion. From this standpoint, the goal of individual and collective decision-making of all kinds is the reconciliation of conflicting objectives and priorities on a piecemeal basis. The distinction between top-down and bottom-up approaches in political decision-making parallels debates between ‘foundationalists’ and ‘coherentists’ in epistemology.

May provides a compelling case that reasoning is central to moral psychology. In practice, many morally significant decisions involve several moral agents whose actions are interdependent – and agents embedded in society. We suggest that social life and the rich patterns of reasoning that underpin it are ethical through and through.

Lake et al. argue persuasively that modelling human-like intelligence requires flexible, compositional representations in order to embody world knowledge. But human knowledge is too sparse and self-contradictory to be embedded in “intuitive theories.” We argue, instead, that knowledge is grounded in exemplar-based learning and generalization, combined with high flexible generalization, a viewpoint compatible both with non-parametric Bayesian modelling and with sub-symbolic methods such as neural networks.

The evaluation of magnitudes serves as a foundation not only for numerical and mathematical cognition, but also for decision making. Recent theoretical developments and empirical studies have linked numerical magnitude evaluation to a wide variety of core phenomena in decision making and challenge the idea that preferences are driven by an innate, universal, and stable sense of number or value.