Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is (...) about fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)

Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must meet to achieve these objectives as predictive robustness—predictive reliability over large domains. Drawing on the results of an ethnographic investigation and various studies in the systems biology literature, I explore four current obstacles to (...) achieving predictive robustness; data constraints, parameter uncertainty, collaborative constraints and system-scale requirements. I use a case study and the commentary of systems biologists themselves to show that current practices in the field, rather than pursuing these goals, frequently use models heuristically to investigate and build understanding of biological systems that do not meet standards of predictive robustness but are nonetheless effective uses of computation. A more heuristic conception of modeling allows us to interpret current practices as ways that manage these obstacles more effectively, particularly collaborative constraints, such that modelers can in the long-run at least work towards prediction and control. (shrink)

Surrogates’ decisions to withhold or withdraw life-sustaining treatments (LSTs) are pervasive. However, the factors influencing surrogates’ decisions to initiate LSTs are relatively unknown. We present evidence from two experiments indicating that some surrogates’ decisions about when to initiate LSTs can be predictably manipulated. Factors that influence surrogate decisions about LSTs include the patient’s cognitive state, the patient’s age, the percentage of doctors not recommending the initiation of LSTs, the percentage of patients in similar situations not wanting LSTs, and default treatment (...) settings. These results suggest that some people may use heuristics when making these important life-and-death decisions. These findings may have important moral implications for improving surrogate decisions about LSTs and reconsidering paternalism. (shrink)

The book examines metaphilosophical issues and contemporary philosophy, in particular such movements as hermeneutics, pragmatism, structuralism and deconstructionism. The author calls the new project of philosophical and metaphilosophical investigations which his work aims to present «philosophical heuristics».

Despite the increasing recognition that heuristics may be involved in myriad scientific activities, much about how to use them prudently remains obscure. As typically defined, heuristics are efficient rules or procedures for converting complex problems into simpler ones. But this increased efficiency and problem-solving power comes at the cost of a systematic bias. As Wimsatt showed, biased modelling heuristics can conceal errors, leading to poor decisions or inaccurate models. This liability to produce errors presents a fundamental challenge (...) to the philosophical value of heuristic analyses. Heuristics may be powerful and efficient procedures, but their practical value for science and epistemology is significantly mitigated if we do not have a principled methodology for knowing how to use them wisely. In this essay, I extend Wimsatt’s analyses to argue that this challenge for a heuristic methodology can be met by appealing to second-order, or meta-, heuristics—that is, practical guidelines that prescribe the appropriate conditions for a first-order heuristic’s use. 1 Introduction2 Background3 Heuristics and Meta-heuristics4 A Hierarchical Model and Three Applications4.1 Decision making in emergency medicine4.2 Mathematical explanation in physics4.3 Resilience in ecological management5 Conclusion. (shrink)

While there is abundant research on innovations, we know little about why and when the commercialization of highly contested innovations, such as genetically modified (GM) crops, is approved by governments. In this paper, we argue that governments' decision to approve the commercialization of GM crops is influenced by heuristics based on the decisions of other governments with which they have greater trade, the gap between country performance and aspiration, and governments' prior decisions on GM crops field trials. We further (...) propose that the effect of these heuristics weakens when the government operates in countries with higher governance quality. Using data on approval of GM crop commercialization between 1991 and 2016, we found support for these arguments and suggest the joint effects of heuristics based on the decisions of trade partners and governance quality on governments' approval of GM crop commercialization. (shrink)

We propose that human reasoning relies on an inherence heuristic, an implicit cognitive process that leads people to explain observed patterns (e.g., girls wear pink) in terms of the inherent features of their constituents (e.g., pink is an inherently feminine color). We then demonstrate how this proposed heuristic can provide a unified account for a broad set of findings spanning areas of research that might at first appear unrelated (e.g., system justification, nominal realism, is–ought errors in moral reasoning). By revealing (...) the deep commonalities among the diverse phenomena that fall under its scope, our account is able to generate new insights into these phenomena, as well as new empirical predictions. A second main goal of this paper, aside from introducing the inherence heuristic, is to articulate the proposal that the heuristic serves as a foundation for the development of psychological essentialism. More specifically, we propose that essentialism—which is the common belief that natural and social categories are underlain by hidden, causally powerful “essences”—emerges over the first few years of life as an elaboration of the earlier, and more open-ended, intuitions supplied by the inherence heuristic. In the final part of the paper, we distinguish our proposal from competing accounts (e.g., Strevens' K-laws) and clarify the relationship between the inherence heuristic and related cognitive tendencies (e.g., the correspondence bias). In sum, this paper illuminates a basic cognitive process that emerges early in life and is likely to have profound effects on many aspects of human psychology. (shrink)

Is our case strong enough to go to trial? Will interest rates go up? Can I trust this person? Such questions - and the judgments required to answer them - are woven into the fabric of everyday experience. This book, first published in 2002, examines how people make such judgments. The study of human judgment was transformed in the 1970s, when Kahneman and Tversky introduced their 'heuristics and biases' approach and challenged the dominance of strictly rational models. Their work (...) highlighted the reflexive mental operations used to make complex problems manageable and illuminated how the same processes can lead to both accurate and dangerously flawed judgments. The heuristics and biases framework generated a torrent of influential research in psychology - research that reverberated widely and affected scholarship in economics, law, medicine, management, and political science. This book compiles the most influential research in the heuristics and biases tradition since the initial collection of 1982. (shrink)

Balancing the pros and cons of two options is undoubtedly a very appealing decision procedure, but one that has received scarce scientific attention so far, either formally or empirically. We describe a formal framework for pros and cons decisions, where the arguments under consideration can be of varying importance, but whose importance cannot be precisely quantified. We then define eight heuristics for balancing these pros and cons, and compare the predictions of these to the choices made by 62 human (...) participants on a selection of 33 situations. The Levelwise Tallying heuristic clearly emerges as a winner in this competition. Further refinements of this heuristic are considered in the discussion, as well as its relation to Take the Best and Cumulative Prospect Theory. (shrink)

An influential suggestion about the relationship between Bayesianism and inference to the best explanation holds that IBE functions as a heuristic to approximate Bayesian reasoning. While this view promises to unify Bayesianism and IBE in a very attractive manner, important elements of the view have not yet been spelled out in detail. I present and argue for a heuristic conception of IBE on which IBE serves primarily to locate the most probable available explanatory hypothesis to serve as a working hypothesis (...) in an agent’s further investigations. Along the way, I criticize what I consider to be an overly ambitious conception of the heuristic role of IBE, according to which IBE serves as a guide to absolute probability values. My own conception, by contrast, requires only that IBE can function as a guide to the comparative probability values of available hypotheses. This is shown to be a much more realistic role for IBE given the nature and limitations of the explanatory considerations with which IBE operates. (shrink)

What is heuristic inquiry, anyway? -- Locating heuristic inquiry within contemporary qualitative research -- Philosophical and theoretical foundations of heuristic inquiry -- Heuristic processes and phases -- Heuristic research design -- Heuristic data collection, organization, and analysis -- Relationality, reflexivity, and meaning-making -- Evaluating the research: a collaborative process -- Writing a living manuscript: an embodied relational approach -- Ethics of heuristic research -- Universal applications of heuristic inquiry: bridging research and living experience -- An ending, beginning.

Transitive inference (TI) refers to social cognition that facilitates the discernment of unknown relationships between individuals using known relationships. It is extensively reported that TI evolves in animals living in a large group because TI could assess relative rank without deducing all dyadic relationships, which averts costly fights. The relationships in a large group become so complex that social cognition may not be developed adequately to handle such complexity. If members apply TI to all possible members in the group, TI (...) requires extremely highly developed cognitive abilities especially in a large group. Instead of developing cognitive abilities significantly, animals may apply simplified TI we call reference TI in this study as heuristic approaches. The reference TI allows members to recognize and remember social interactions only among a set of reference members rather than all potential members. Our study assumes that information processes in the reference TI comprises (1) the number of reference members based on which individuals infer transitively, (2) the number of reference members shared by the same strategists, and (3) memory capacity. We examined how information processes evolve in a large group using evolutionary simulations in the hawk–dove game. Information processes with almost any numbers of reference members could evolve in a large group as long as the numbers of shared reference member are high because information from the others’ experiences is shared. TI dominates immediate inference, which assesses relative rank on direct interactions, because TI could establish social hierarchy more rapidly applying information from others’ experiences. (shrink)

The presented analyses are focusing on three predominant theoretical approaches in the philosophy of science and technology: technoscience (STS), technology assessment (TA) and converging technologies (NBIC). On this base are extrapolated the coordinates of the heuristics of technosciences.

Approaching science by considering the epistemological virtues which scientists see as constitutive of good science, and the way these virtues trade-off against one another, makes it possible to capture action that may be lost by approaches which focus on either the theoretical or institutional level. Following Wimsatt (1984) I use the notion of heuristics and biases to help explore a case study from the history of biology. Early in the 20th century, mutation theorists and natural historians fought over the (...) role that isolation plays in evolution. This debate was principally about whether replication was the central scientific virtue (and hence the ultimate goal of science to replace non-experimental evidence with experimental evidence) or whether consilience of inductions was the central virtue (and hence, as many kinds of evidence as possible should be pursued). (shrink)

We consider a special case of heuristics, namely numeric heuristic evaluation functions, and their use in artificial intelligence search algorithms. The problems they are applied to fall into three general classes: single-agent path-finding problems, two-player games, and constraint-satisfaction problems. In a single-agent path-finding problem, such as the Fifteen Puzzle or the travelling salesman problem, a single agent searches for a shortest path from an initial state to a goal state. Two-player games, such as chess and checkers, involve an adversarial (...) relationship between two players, each trying to win the game. In a constraint-satisfaction, problem, such as the 8-Queens problem, the task is to find a state that satisfies a set of constraints. All of these problems are computationally intensive, and heuristic evaluation functions are used to reduce the amount of computation required to solve them. In each case we explain the nature of the evaluation functions used, how they are used in search algorithms, and how they can be automatically learned or acquired. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant (...) value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Mental arithmetic is characterised by a tendency to overestimate addition and to underestimate subtraction results: the operational momentum effect. Here, motivated by contentious explanations of this effect, we developed and tested an arithmetic heuristics and biases model that predicts reverse OM due to cognitive anchoring effects. Participants produced bi-directional lines with lengths corresponding to the results of arithmetic problems. In two experiments, we found regular OM with zero problems but reverse OM with non-zero problems. In a third experiment, we (...) tested the prediction of our model. Our results suggest the presence of at least three competing biases in mental arithmetic: a more-or-less heuristic, a sign-space association and an anchoring bias. We conclude that mental arithmetic exhibits shortcuts for decision-making similar to traditional domains of reasoning and problem-solving. (shrink)

There are parallels between Gigerenzer et al.'s emphasis on the rationality of adults' reasoning in terms of simple heuristics and developmental researchers' emphasis on the rationality of children's reasoning in terms of intuitive theories. Indeed, just as children become better at using their theories, so might some people, experts, become better at using simple heuristics.

This paper argues that emotions can play an epistemic role as justifiers of evaluative beliefs. It also presents the heuristics theory of emotion as an empirically informed explanation of how emotions can play such a role and why they in practice usefully complement non-affective evaluative judgments. As such, the heuristics theory represents a form of moderate rationalism: it acknowledges that emotions can be epistemically valuable, even privileged in some sense, but denies that they would be uniquely privileged. I (...) argue that judgments and emotional responses pick out different but correlated kinds of evaluative properties and therefore emotional responses and non-affective evaluative judgments play mutually complementary rather than mutually exclusive roles. It follows that emotional responses can be legitimately drawn upon to support evaluative beliefs, but they lack supreme epistemic authority. (shrink)

The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...) representations in the epistemic practices of mechanism discovery and mechanism description. These examples also indicate that the scope of mechanistic explanation must be re-examined: With new and increasingly powerful methods of discovery and description comes the possibility of describing mechanisms far more complex than traditionally assumed. (shrink)

: This paper develops four related claims: 1. Critical thinking should focus more on decision making, 2. the heuristics and bias literature developed by cognitive psychologists and behavioral economists provides many insights into human irrationality which can be useful in critical thinking instruction, 3. unfortunately the “rational choice” norms used by behavioral economists to identify “biased” decision making narrowly equate rational decision making with the efficient pursuit of individual satisfaction; deviations from these norms should not be treated as an (...) irrational bias, 4. a richer, procedural theory of rational decision making should be the basis for critical thinking instruction in decision making. (shrink)

This chapter focuses on one of the common fallacies in Western philosophy called ' representative heuristic'. A heuristic is a shortcut rule, or guide, by which one tries to organize one's understanding of the world. The representative heuristic is the rule that suggests we should associate things that are alike, grouping them together, usually invoking “the principle that members of a category should resemble a prototype”. A way the representative heuristic leads us astray is by making us apt to think (...) that causes and their effects must resemble each other – that like causes like. This is most striking in the realm of alternative and “natural” medicine, where certain physical qualities of objects are thought to be transferable to those who ingest them. (shrink)

Proofs are central to mathematical practice in large part due to the heuristic role that some of them play. Not only do they help establish a result, but often provide new avenues of mathematical research. Jody Azzouni has argued that underlying the practice of creating mathematical proofs there is a very specific norm: to each proof there should be a corresponding algorithmic derivation, a derivation in an algorithmic system. Here a framework is provided to classify and assess mathematical proofs. It (...) is argued that there is a plurality of kinds of proofs in mathematics and a plurality of roles these proofs play. In the end, mathematical practice is far less unified in this respect than it may seem to be. (shrink)

The scope of a heuristic decision making rule is a product of its fit to the context, the extension to which a heuristic can be applied successfully. To achieve effective outcomes, decision makers may use a few heuristics with large scopes or many with narrow scopes. Through a directed review of the literature combined with ethnographic research, this paper contributes to the debate on the problem of scope in three types of heuristics, namely, multipliers, thresholds, and calends. The (...) scope of heuristic rules can be explored from different aspects, including the field in which a heuristic rule is applied and specific parameters that are used in a heuristic decision making process. The three types of heuristic rules we analyze were encountered in our ethnographic research, that was based on phenomenological interviews and observations. For these heuristics we discuss their scopes in through to the following organizing structures: the exploration of the adaptive tool-box, the role of ethnographic methodologies, and the categorization of heuristics. (shrink)

Intelligence on mass media audiences was founded on representative statistical samples, analysed by statisticians at the market departments of media corporations. The techniques for aggregating user data in the age of pervasive and ubiquitous personal media build on large aggregates of information analysed by algorithms that transform data into commodities. While the former technologies were built on socio-economic variables such as age, gender, ethnicity, education, media preferences, Big Data technologies register consumer choice, geographical position, web movement, and behavioural information in (...) technologically complex ways that for most lay people are too abstract to appreciate the full consequences of. The data mined for pattern recognition privileges relational rather than demographic qualities. We argue that the agency of interpretation at the bottom of market decisions within media companies nevertheless introduces a ‘heuristics of the algorithm’, where the data inevitably becomes translated into social categories. In the paper we argue that although the promise of algorithmically generated data is often implemented in automated systems where human agency gets increasingly distanced from the data collected, one can observe a felt need among media users and among industry actors to ‘translate back’ the algorithmically produced relational statistics into ‘traditional’ social parameters. The tenacious social structures within the advertising industries work against the techno-economically driven tendencies within the Big Data economy. (shrink)

I conceptualise the role of dualities in quantum gravity, in terms of their functions for theory construction. I distinguish between two functions of duality in physical practice: namely, discovering and describing ‘equivalent physics’, versus suggesting ‘new physics’. I dub these the ‘theoretical’ versus the ‘heuristic’ functions of dualities. The distinction seems to have gone largely unnoticed in the philosophical literature: and it exists both for dualities, and for the more general relation of theoretical equivalence. The paper develops the heuristic function (...) of dualities: illustrating how they can be used, if one has any luck, to find and formulate new theories. I also point to the different physical commitments about the theories in question that underlie these two functions. I show how a recently developed schema for dualities articulates the differences between the two functions. (shrink)

We examine two major perspectives in the literature on domain specificity in cognition: in one of them cognitive modules are "intuitive theories"; in the other they are dispositional structures. Both of these positions accept that there is a continuous line from ordinary to scientific reasoning; nevertheless they interpret this continuity differently. We propose an alternative way of understanding the relation between ordinary and scientific reasoning: the continuity thesis holds because heuristic structures play a fundamental role in both types of reasoning. (...) Our main contention is that cognitive modules can be thought of as heuristic structures and that, since science is a complex of practices that embody different heuristic structures, science should be understood as a complex of cognitive modules. (shrink)

Heuristics can be regarded as justifying the actions and beliefs of problem-solving agents. I use an analysis of heuristics to argue that a symbiotic relationship exists between traditional epistemology and contemporary artificial intelligence. On one hand, the study of models of problem-solving agents usingquantitative heuristics, for example computer programs, can reveal insight into the understanding of human patterns of epistemic justification by evaluating these models'' performance against human problem-solving. On the other hand,qualitative heuristics embody the justifying (...) ability of defeasible rules, the understanding of which is provided by traditional epistemology. (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)

The paper assumes that fear presents a certain degree of ambivalence. To say it with Hans Jonas (1903-1993), fear is not only a negative emotion, but may teach us something very important: we recognize what is relevant when we perceive that it is at stake. Under this respect, fear may be assumed as a guide to responsibility, a virtue that is becoming increasingly important, because of the role played by human technology in the current ecological crisis. Secondly, fear and responsibility (...) concern both dimensions of human action: private-individual and public-collective. What the ‘heuristics of fear’ teaches us, is to become aware of a deeper ambivalence, namely the one which characterizes as such human freedom, which may aim to good or bad, to self-preservation or self-destruction. Any public discussion concerning political or economic issues related with human action (at an individual or collective level) ought not to leave this essential idea out of consideration. (shrink)

To be able to make “change” happen in the lives of patients entrusted to his care, Watzlawick says he tried to produce a theory about it. He was forced to acknowledge that the mechanisms of change resist systematization and, therefore, all wishes to elicit them as well.Well-being is to therapy what discovery is to thought and the event is to History: the position – unforeseen, unforeseeable – in reality of what did not hitherto exist. And heuristics would be, if (...) not a science, since there could be no science of change, then at least the name given to reflection on its mystery. (shrink)

: Psychological explanations of philosophical intuitions can help us assess their evidentiary value, and our warrant for accepting them. To explain and assess conceptual or classificatory intuitions about specific situations, some philosophers have suggested explanations which invoke heuristic rules proposed by cognitive psychologists. The present paper extends this approach of intuition assessment by heuristics-based explanation, in two ways: It motivates the proposal of a new heuristic, and shows that this metaphor heuristic helps explain important but neglected intuitions: general factual (...) intuitions which have been highly influential in the philosophies of mind and perception but neglected in on-going debates in the epistemology of philosophy. To do so, the paper integrates results from three philosophically pertinent but hitherto largely unconnected strands of psychological research: research on intuitive judgement, analogy and metaphor, and memory-based processing, respectively. The paper shows that the heuristics-based explanation thus obtained satisfies the key requirements cognitive psychologists impose on such explanations, that it can explain the philosophical intuitions targeted, and that this explanation supports normative assessment of the intuitions' evidentiary value: It reveals whether particular intuitions are due to proper exercise of cognitive competencies or constitute cognitive illusions. (shrink)

I argue that an ecologically distributed conception of instrumental rationality can and should be extended to a socially distributed conception of instrumental rationality in social environments. The argument proceeds by showing that the assumption of exogenously fixed units of activity cannot be justified; different units of activity are possible and some are better means to independently given ends than others, in various circumstances. An important social heuristic, the mirror heuristic, enables the flexible formation of units of activity in game theoretic (...) situations, including collective units where these are instrumentally effective. In effect, the mirror heuristic makes the formation of units of activity endogenous to instrumental rationality. Moreover, the mirror heuristic is a conditional metaheuristic, which depends on mind reading of the heuristics of other players rather than on predictions of their behavior. Such mind reading can be regarded as emerging from an arms race between behavioral mimicry and ever smarter behavior reading. Even though unilateral mind reading may have benefits, the mirror metaheuristic illustrates that mutual mind reading has distinctive functions in responding to the challenges of social complexity. If simple heuristics can make us smart in the right environments, then social heuristics can make us smarter still. (shrink)

Seventy-three children between 6 and 7 years of age were presented with a problem having ambiguous subgoal ordering. Performance in this task showed reliable fingerprints: a non-monotonic dependence of performance as a function of the distance between the beginning and the end-states of the problem, very high levels of performance when the first move was correct, and states in which accuracy of the first move was significantly below chance. These features are consistent with a non-Markov planning agent, with an inherently (...) inertial decision process, and that uses heuristics and partial problem knowledge to plan its actions. We applied a statistical framework to fit and test the quality of a proposed planning model. Our framework allows us to parse out independent contributions to problem-solving based on the construction of the value function and on general mechanisms of the search process in the tree of solutions. We show that the latter are correlated with children's performance on an independent measure of planning, while the former is highly domain specific. (shrink)

Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or "shortcut" mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which "heuristic" is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This (...) dissertation seeks to remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data. (shrink)

(1995). Heuristics, hypotheses, and social influence: A new approach to the experimental simulation of social epistemology. Social Epistemology: Vol. 9, Simulating Science, pp. 57-69.

In response to the COVID‐19 pandemic philosophers and governments have proposed scarce resource allocation guidelines. Their purpose is to advise healthcare professionals on how to ethically allocate scarce medical resources. One challenging feature of the pandemic has been the large numbers of patients needing mechanical ventilatory support. Guidelines have paradigmatically focused on the question of what doctors should do if they have fewer ventilators than patients who need respiratory support: which patient should get the ventilator? There is, however, an important (...) higher level allocation problem. Namely, how are we to ethically distribute newly obtained ventilators across hospitals: which hospital should get the ventilator(s)? In this paper, we identify a set of principles for allocating newly obtained ventilators across hospitals. We focus particularly on low and middle income countries, who frequently have limited pre‐existing intensive care capacity, and have needed to source additional ventilators. We first provide some background. Second, we argue that the main population healthcare aim during the COVID‐19 pandemic should be to save the most lives. Next, we assess a series of potential heuristics or principles that could be used to guide allocation: allocation to the most densely populated cities, random allocation, allocation based on the ratio of patients to ICU personnel, prioritisation in terms of intrahospital mortality, prioritisation of younger populations, and prioritisation in terms of population mortality. We conclude by providing a plausible ranking of the principles, while noting a number of epistemological challenges, in terms of how they best further the aim of increasing the probability of saving the most lives. (shrink)

This lecture will deal with the heuristic power of the deductive method and its contributions to the scientific task of finding new knowledge. I will argue for a new reading of the term 'deductive method.' It will be presented as an architectural scheme for the reconstruction of the processes of gaining reliable scientific knowledge. This scheme combines the activities of doing science with the activities of presenting scientific results. It combines the heuristic and the deductive side of science. The heuristic (...) side is represented, e.g., by the creative methods to find the 'best' hypotheses, to design experimental systems for empirical research in order to formulate general laws, or to create axiomatic systems. The other side consists of the production of deductive knowledge. This combination leads to a clear hierarchy: the heuristic side provides the basic presuppositions from which the deductive side takes off. The former is used to make deductions possible. The deductive method can be presented as an analysis-synthesis scheme as it can be found, e.g., in the tradition of Kant, Jakob Friedrich Fries, and Leonard Nelson. Nelson's critical philosophy can be seen as a key for understanding the philosophy behind David Hilbert's early axiomatic method. This axiomatic method is usually restricted to a non-philosophical approach to pure mathematics. But Hilbert was not an exclusive formalist; he proposed a mathesis universalis in the Cartesian-Leibnizian sense according to which mathematics is the syntactical tool for a general philosophy of science, applicable to all scientific disciplines. In this function, mathematics takes its problems from the sciences. Hilbert did not deny that mathematics should play a role in explaining the world. The analysis-synthesis scheme helps to provide a consistent interpretation of these two sides of Hilbert's attitude towards his working field. (shrink)

Gigerenzer et al.'s is an extremely important book. The ecological validity of the key heuristics is strengthened by their relation to ubiquitous Poisson processes. The recognition heuristic is also used in conspecific cueing processes in ecology. Three additional classes of problem-solving heuristics are proposed for further study: families based on near-decomposability analysis, exaptive construction of functional structures, and robustness.

Philosophical analyses of scientific methodology have long understood intuition to be incompatible with a rule based reasoning that is often considered necessary for a rational scientific method. This paper seeks to challenge this contention by highlighting the indispensable role that intuition plays in the application of methodologies for scientific discovery. In particular, it seeks to outline a positive role for intuition and personal judgment in scientific discovery by exploring a comparison between the use of heuristic reasoning in scientific practice and (...) engineering design. While these discussions share many features, it will also be shown that the successful use of heuristics in engineering design is often considered to depend on a crucial factor that is markedly absent from accounts of the use of heuristics in scientific discovery; experienced judgment. In the final sections of this paper, I will compare attitudes to the role of computer analysis in scientific and engineering practices, with the aim of showing how the limitations of scientific discovery machines reveal the need for including intuition in philosophical accounts of heuristic reasoning in scientific discovery. (shrink)

After a few general observations on scientific activity, the author briefly comments on different versions of naturalism. Subsequently, he suggests that the birth of evolutionary biology and its successive developments may show how the natural world comes to be differently conceived as scientific advancements are accomplished. Then the main thesis is outlined by introducing the principles of a heuristic science-based naturalism not conclusively defining the real and the knowable. From the epistemological perspective, heuristic naturalism is meant to be framed in (...) critical realism, whereas from the ontological standpoint it may be framed in emergent monism, given that the latter can also underpin recent trends in investigation addressing human specificity. Finally, attention is turned to some implications of heuristically guided scientific activity with regard to the issues of divine action and of imago Dei. (shrink)

In the last decade, the study of moral heuristics has gained in importance. I argue that we can consider speciesism as a moral heuristic: an intuitive rule of thumb that substitutes a target attribute (that is difficult to detect, e.g. “having rationality”) for a heuristic attribute (that is easier to detect, e.g. “looking like a human being”). This speciesism heuristic misfires when applied to some atypical humans such as the mentally disabled, giving them rights although they lack rationality. But (...) I argue that it is not necessarily irrational or inconsistent to hold on to this heuristic rule, because we have to take time and knowledge constraints, uncertainty aversion and emotional costs into account. However, this “heuristic defense” of speciesism uses a target attribute (rationality) that has implications of disrespect towards some atypical humans. Therefore, based on notions of impartiality and compassion, I argue for a morally better target attribute: sentience (“having a sense of well-being”). “Being a vertebrate” is suitable as a corresponding heuristic attribute because it is easy to detect and has a strong correlation with the target attribute of sentience. (shrink)

In fantasy sports, the goal is to gain as many points as possible. To get there, users have to choose players with the optimal price-to-performance ratio. However, finding these optimal players requires a great amount of time and effort, in which the users might not be willing to invest. Instead, they can use heuristic strategies. This paper investigates one such strategy for choosing squads based on the assumption that athletes starting for the favourite team of the match would bring users (...) more points—in line with the representativeness heuristic. The data come from the Czech fantasy league according to the Premier League in the season 2015–16. The econometric model examines the percentage of squads a player was chosen into. The Ordinary Least Squares method used here uses control variables indicating performance, price, Czech nationality, and the game position of the athletes. The results show that users choose their squads primarily based on players’ past performances, but also take the favourite team into account. By applying the latter heuristic users aim to simplify the process decision-making but they overestimate the impact of belonging to a favourite team. (shrink)

Preferences for options that do not secure optimal outcomes, like the ones catalogued by Sunstein, derive from two sources: cognitive heuristics and deontological rules. Although rules may stem from automatic affective reactions, they are deliberately maintained. Because strongly held convictions have important behavioral implications, it may be useful to regard cognitive heuristics and deontological rules as separate sources of nonconsequential judgment in the moral domain.

The main aim of this book is to encourage philosophers to take a more sophisticated and scientific attitude to their handling of evidence, both in theory and in practice, by introducing two categories neglected in current metaphilosophy. The first category is that of heuristics. These are typically efficient ways of solving problems of some kind, quick and easy to use, and mostly but not always reliable. Those most probably central to philosophical methodology are more or less humanly universal general (...) cognitive heuristics which we employ without conscious reflection. In many plausible cases, they can be shown to be implicitly inconsistent, and so cannot be perfectly valid, though for evolutionary reasons they are likely to be fairly reliable in normal cases. Such heuristics may well generate false but convincing data as applied to some actual or hypothetical. Arguably, the heuristics also generate philosophical paradoxes, just as heuristics embedded in our perceptual systems generate perceptual illusions. The second category is that of overfitting. This is a recognized pathology in science, when models are allowed to become very complicated to achieve a close fit with data, and further complications typically keep having to be made as new data comes in. When the data contains errors, such theorizing provides little insight. Scientists guard against overfitting by strongly preferring comparatively simple models. Philosophers should learn to do the same. This approach is applied to debates between coarse-grained (intensionalist) and fine-grained (hyperintensionalist) theories of metaphysics, ascriptions of propositional attitudes, and other topics, in favour of intensionalism. (shrink)

A large body of the literature on sustainability indicators, assessments and reporting is currently available. However, sustainability performance measurement systems have an insubstantial presence in the literature. Invariably, a sustainability performance measurement system presents the potential for certain trade-offs or opportunity costs for organizations. Extant sustainability platforms and standards are largely silent about how to deal with trade-offs. Utilizing evidence from the literature, as well as contingency factors, this paper seeks to present a heuristic model for establishing trade-offs in corporate (...) sustainability performance measurement systems. Trade-offs in this area revolve around performance measurement, stakeholder management, competitive advantage, as well as the vertical and horizontal integration of the performance platform. This is particularly important for organizations seeking to establish, integrate or expand their environmental management systems into the area of sustainability. As yet, formalistic attempts to deal with trade-offs in sustainability performance measurement systems are infrequent and vague. (shrink)