Polymath, and also political scientist, Herbert Simon dared to point out that the amounts of time, information, computation, and other resources required for maximizing utility far exceed what is possible when real people have to make real decisions in the real world. In psychology, there are two main approaches to studying actual human judgment and decision making—the heuristics-and-bias and the fast-and-frugal-heuristics research programs. A distinctive characteristic of the fast-and-frugal-heuristics program is that it specifies formal models of heuristics and attempts to determine when people use them and what performance they achieve. These models rely on a few pieces of information that are processed in computationally simple ways. The information and computation are within human reach, which means that people rely on information they have relatively easy access to and employ simple operations such as summing or comparing numbers. Research in the laboratory and in the wild has found that most people use fast and frugal heuristics most of the time if a decision must be made quickly, information is expensive financially or cognitively to gather, or a single/few attributes of the problem strongly point towards an option. The ways in which people switch between heuristics is studied in the framework of the adaptive toolbox. Work employing computer simulations and mathematical analyses has uncovered conditions under which fast and frugal heuristics achieve higher performance than benchmarks from statistics and machine learning, and vice versa. These conditions constitute the theory of ecological rationality. This theory suggests that fast and frugal heuristics perform better than complex optimization models if the available information is of low quality or scarce, or if there exist dominant options or attributes. The bias-variance decomposition of statistical prediction error, which is explained in layperson’s terms, underpins these claims. Research on fast and frugal heuristics suggests a governance approach not based on nudging, but on boosting citizen competence.
Konstantinos V. Katsikopoulos
Brooke N. Shannon, Zachary A. McGee, and Bryan D. Jones
Bounded rationality conceives of people engaging in politics as goal oriented but endowed with cognitive and emotional architectures that limit their abilities to pursue those goals rationally. Political institutions provide the critical link between micro- and macro-processes in political decision-making. They act to (a) compensate for those bounds on rationality; (b) make possible cooperative arrangements not possible under the assumptions of full or comprehensive rationality; and (c) fall prey to the same cognitive and emotional limits or canals that individual humans do. The cognitive limitations that hamper individuals are not only replicated at the organizational level but are in fact causal.
Cognitive theory encompasses mental activities such as the observation of different stimuli in an environment; the memorization and recall of information; pattern recognition and problem representation; and complex activities like social judgments, analytic reasoning, and learning. Cognitive psychology also highlights the constraints that prevent individuals from acting as utility-maximizing, fully rational decision-makers. These constraints lead people to rely on a regularly occurring set of cognitive mechanisms to simplify the decision-making process. Scholars of foreign policy have drawn from several prominent areas of cognitive psychology to inform their research. One such area looks at the beliefs and belief systems that are the building blocks for most judgments. Researchers have also examined how actors use cognitive biases and heuristics to cope with uncertainty, which is abundant in foreign policy settings. An important set of cognitive mechanisms examined in Foreign Policy Analysis (FPA) relates to judgments about policy risks and costs. Factors that facilitate and inhibit learning are crucial for understanding the conditions under which such judgments may improve over time. No cognitive process operates in a vacuum; instead these processes are moderated by an individual’s group context and emotions. There are several challenges in applying cognitive theory to FPA. Such theories are biased toward populations that are Western, educated, industrialized, rich, and democratic. They are usually first tested using controlled experiments that measure group-level differences; whereas FPA scholars are often interested in the cognitive processes of individual leaders operating in chaotic environments. Individual-level psychological mechanisms may augment or offset one another, as well as interact with variables at the governmental, societal, and international levels of analysis in unpredictable ways. In light of these challenges, FPA scholars who employ cognitive psychology may wish to conceive of their enterprise as a historical science rather than a predictive one.
Behavioral public administration is an interdisciplinary research field that studies public administration topics by connecting insights from public administration with psychology and, more broadly, the behavioral sciences. Behavioral public administration scholars study important public problems such as discrimination, corruption, and burnout. Various public administration scholars—including Herbert Simon—have stressed the importance of connecting psychology and public administration. Yet until the early 2010s, public administration did not work systematically on this connection. This has changed profoundly with the development of various overview articles, dedicated special issues in general public administration journals, and development of new journals. Behavioral public administration has several uses. First, behavioral public administration tests and extends theories and concepts from psychology in political-administrative settings. Examples include tests of prospect theory and the choice overload hypothesis in public-administrative settings. Second, it tests and extends the micro-foundations of public administration theories and concepts, such as concerning co-production and isomorphism. Third, behavioral public administration scholars develop new theories and concepts. This has probably been less widespread than the previous two uses, but is nonetheless already apparent in, for instance, concepts such as public service motivation, policy alienation, and administrative burden. Fourth, behavioral public administration can help in tackling practical public problems. Insights from behavioral public administration have been used to increase diversity within public organizations and reduce burnout. The field of behavioral public administration can develop further. The field could move beyond one-shot single studies and aim to build cumulative knowledge. This can be done via large-scale collaborations and replications. In addition, it is also beneficial if behavioral public administration scholars broaden their methodological toolkit to answer different kinds of research questions. It should not only focus on causal inference questions but also on questions concerning description of societal problems (e.g. via representative surveys) or concerning prediction (e.g. by using machine learning).
JoBeth Shafran, Bryan D. Jones, and Connor Dye
Bounded rationality is the notion that while humans want to be fully rational beings and weigh the costs and benefits when making a decision, they cannot do so due to cognitive and emotional limitations. The role of human nature in the study and design of organizations can be examined through three general approaches that are explained using metaphors: organization as machine, organization as hierarchy, and organization as canal. The organization-as-machine approach ignores the principles of bounded rationality by assuming the organizational members perform straightforward cost–benefit responses to the incentives put forward by the operators. Later developments in organizational scholarship incorporate elements of bounded rationality and allowed researchers to link human cognitive capacities to the basic organizational features, giving us two new conceptions of organization: organization as hierarchy and organization as canal. Organization as hierarchy focuses on the organization’s use of subunits to create divisions of labor to expand the capacity to process information and problem-solve. Organization as canal recognizes that the weaknesses of human cognition are still channeled into the organizational structure, making it difficult for organizations to update their preferences and assumptions as they receive new information. These principles of bounded rationality in organizational theory can be applied to policy-making institutions. Hierarchical organizations delegate information processing to the subunits, allowing them to attend to the various policy environments and process incoming information. While the collective organization attends to many issues at once, the rules and procedures that are present within the organization and the cognitive limits of decision makers, prevent proportional information processing. Political institutions are unable to respond efficiently to changes in the environment. Thus, organizational adjustment to the environment is characterized as disjointed and episodic as opposed to smooth and incremental. Punctuated equilibrium theory applies these tenets of bounded rationality to a theory of policy change. Congress has been a vehicle for studying bounded rationality in organizations and theories of policy change, as it is a formal institution with bureaucratic elements and is subject to the constraints faced by any formal organization.
The lexicographic decision rule is one of the simplest methods of choosing among decision alternatives. It is based on a simple priority ranking of the attributes available. According to the lexicographic decision rule, a decision alternative is better than another alternative if and only if it is better than the other alternative in the most important attribute on which the two alternatives differ. In other words, the lexicographic decision rule does not allow trade-offs among the various attributes. For example, if quality is considered to be more important than cost, no difference in price can compensate for a difference in quality: The lexicographic decision rule chooses the item with the best quality regardless of the cost. Over the years, the lexicographic decision rule has been compared to various statistical learning methods, including multiple linear regression, support vector machines, decision trees, and random forests. The results show that the lexicographic decision rule can sometimes compete remarkably well with more complex statistical methods, and even outperform them, despite its naively simple structure. These results have stimulated a rich scientific literature on why, and under what conditions, lexicographic decision rules yield accurate decisions. Due to the simplicity of its decision process, its fast execution time, and the robustness of its performance in various decision environments, the lexicographic decision rule is considered to be a plausible model of human decision making. In particular, the lexicographic decision rule is put forward as a model of how the human mind implements bounded rationality to make accurate decisions when information is scarce, time is short, and computational capacity is limited.
“Evidence-based policy making” (EBPM) has become a popular term to describe the need for more scientific and less ideological policy making. Some compare it to “evidence-based medicine,” which describes moves to produce evidence, using commonly-held scientific principles regarding a hierarchy of evidence, which can directly inform practice. Policy making is different: there is less agreement on what counts as good evidence, and more things to consider when responding to evidence. Our awareness of these differences between science and policy are not new. Current debates resemble a postwar policy science agenda, to produce more scientific and “rational” policy analysis, which faced major empirical and normative obstacles: the world is not that simple, and an overly technocratic approach to policy undermines much-needed political debate. To understand modern discussions of EBPM, key insights from previous discussions must be considered: policy making is both “rational” and “irrational”; it takes place in complex policy environments or systems, whose properties should be understood in some depth; and it can and should not be driven by “the evidence” alone.