Do people tend to be overconfident? Many think so. They’ve run studies on whether people are calibrated: whether their average confidence in their opinions matches the proportion of those opinions that are true. Under certain conditions, people are systematically ‘over-calibrated’—for example, of the opinions they’re 80% confident in, only 60% are true. From this empirical over-calibration, it’s inferred that people are irrationally overconfident. My question: When and why is this inference warranted? Answering it requires articulating a general connection between being (...) rational and being right—something extant studies have not done. I show how to do so using the notion of deference. This provides a theoretical foundation for calibration research, but also reveals a flaw: the connection between being rational and being right is much weaker than is standardly assumed, since rational people can often be expected to be miscalibrated. Thus we can’t test whether people are overconfident by simply testing whether they are over-calibrated; instead, we must try to predict the rational deviations from calibration, and then compare those predictions to people’s performance. I show how this can be done—and that doing so complicates the interpretation of robust empirical effects. (shrink)

Previous studies have shown that people often use heuristics in making inferences and that subjective memory experiences, such as recognition or familiarity of objects, can be valid cues for inferences. So far, many researchers have used the binary choice task in which two objects are presented as alternatives (e.g., “Which city has the larger population, city A or city B?”). However, objects can be presented not only as alternatives but also in a question (e.g., “Which country is city X in, (...) country A or country B?”). In such a situation, people can make inferences based on the relationship between the object in the question and each object given as an alternative. In the present study, we call this type of task a “relationships‐comparison task.” We modeled the three inference strategies that people could apply to solve it (familiarity‐matching [FM; a new heuristic we propose in this study], familiarity heuristic [FH], and knowledge‐based inference [KI]) to examine people's inference processes. Through Studies 1, 2, and 3, we found that (a) people tended to rely on heuristics, and that FM (inferences based on similarity in familiarity between objects) well explained participants' inference patterns; (b) FM could work as an ecologically rational strategy for the relationships–comparison task since it could effectively reflect environmental structures, and that the use of FM could be highly replicable and robust; and (c) people could sometimes use a decision strategy like FM, even in their daily lives (consumer behaviors). The nature of the relationships–comparison task and human cognitive processes is discussed. (shrink)

The purpose of the study was to investigate how numeracy and acuity of the approximate number system (ANS) relate to the calibration and coherence of probability judgments. Based on the literature on number cognition, a first hypothesis was that those with lower numeracy would maintain a less linear use of the probability scale, contributing to overconfidence and nonlinear calibration curves. A second hypothesis was that also poorer acuity of the ANS would be associated with overconfidence and non-linearity. A third hypothesis, (...) in line with dual-systems theory (e.g., Kahneman and Frederick, 2002 ) was that people higher in numeracy should have better access to the normative probability rules, allowing them to decrease the rate of conjunction fallacies. Data from 213 participants sampled from the Swedish population showed that: (i) in line with the first hypothesis, overconfidence and the linearity of the calibration curves were related to numeracy, where people higher in numeracy were well calibrated with zero overconfidence. (ii) ANS was not associated with overconfidence and non-linearity, disconfirming the second hypothesis. (iii) The rate of conjunction fallacies was slightly, but to a statistically significant degree decreased by numeracy, but still high at all numeracy levels. An unexpected finding was that participants with better ANS acuity gave more realistic estimates of their performance relative to others. (shrink)

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the (...) authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures. The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. (shrink)

According to Jon Elster, mechanisms are frequently occurring and easily recognizable causal patterns that are triggered under generally unknown conditions or with indeterminate consequences. In the absence of laws, moreover, mechanisms provide explanations. In this paper I argue that Elster’s view has difficulties with progressing knowledge. Normally, filling in the causal picture without revising it should not threaten one’s explanation. But this seems to be Elster’s case. The critique is constructive in the sense that it is built up from a (...) discussion of a mechanism that might explain ‘unwarranted’ risk taking in connection with swimming—a mechanism that is mirrored in the proverb: The best swimmers drown. (shrink)

This paper focuses on the opposition between two contemporary research programs in economics: behavioral economics (BE) and experimental market economics (EME). Our claim is that the arguments of this opposition can be clarified through the lens of another opposition in the philosophy of probability and in probability theory, between Bayesianism and frequentism. We show how this probabilistic opposition has indirectly shaped a controversy in psychology that opposes two research programs – Heuristics and Biases and Ecological Rationality – which play respective (...) roles in the foundations of individual rationality in BE and EME. To understand these theoretical interrelationships, we investigate the 1996 controversy between Kahneman, Tversky, and Gigerenzer. Those psychologists held different views on how probabilistic representations influence the context-dependency of rationality. This provides a rationale to suggest that a probabilistic ghost may be haunting the experimental machine in economics, and explai.. (shrink)

Koriat & Goldsmith's abstract correspondence metaphor is unlikely to prove useful to memory science. It aims to motivate and inform the investigation of everyday memory, but that movement has prospered without it. The irrelevance of its competitor – the more concrete storehouse metaphor – as a guiding force in memory research presages a similar fate for the correspondence perspective.

Any instance (i.e., event, behavior, trait) belongs to infinitely many reference classes, hence there are infinitely many base rates from which to choose. People clearly do not entertain all possible reference classes, however, so something must be limiting the search space. We suggest some possible mechanisms that determine which reference class is evoked for the purpose of judgment and decision.

Consistent with Koehler's position, we propose a generalization of the base rate fallacy and earlier conservatism literatures. In studies using both traditional tasks and new tasks based on ecologically valid base rates, our subjects typically underweight individuating information at least as much as they underweight base rates. The implications of cue consistency for averaging heuristics are discussed.

When base rates are learned and used in an experiential manner subjects show better base rate use, perhaps because the implicit learning system is engaged. A causal framework in which base rates are relevant might also be necessary. Humans might thus perform better on more ecologically valid tasks, which are likely to contain those three components.

The distinction that Koriat & Goldsmith have drawn between laboratory and naturalistic research is largely valid, but the metaphor they have chosen to characterize the latter may not be optimal. The “correspondence” approach is vulnerable on conceptual grounds and is not applicable to significant portions of empirical research.

Philosophers commonly define knowledge as justified true beliefs. A heated debate exists, however, about what makes a belief justified. In this article, we examine the question of belief justification from a psychological perspective, focusing on the subjective confidence in a belief that the person has just formed. Participants decided whether to accept or reject a proposition depicting a social belief, and indicated their confidence in their choice. The task was repeated six times, and choice latency was measured. The results were (...) analyzed within a Self-Consistency Model of subjective confidence. According to SCM, the decision to accept or reject a proposition is based on the on-line sampling of representations from a pool of representations associated with the proposition. Respondents behave like intuitive statisticians who infer the central tendency of a population based on a small sample. Confidence depends on the consistency with which the belief was supported across the sampled representations, and reflects the likelihood that a new sample will yield the same decision. The results supported the assumption of a commonly shared population of representations associated with each proposition. Based on this assumption, analyses of within-person consistency and cross-person consensus provided support for the model. As expected, choices that deviated from the person’s own modal judgment or from the consensually held judgment took relatively longer to form and were associated with relatively lower confidence, presumably because they were based on non-representative samples. The results were discussed in relation to major epistemological theories – foundationalism, coherentism and reliabilism. (shrink)

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the (...) fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality. (shrink)

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point (...) estimates, decisions, and probability assessments by human participants. The best fit is obtained for a version that weights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implements speed and frugality in a psychologically plausible way. (shrink)

People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do; they are subject to an illusion—an illusion of explanatory depth. The illusion is far stronger for explanatory knowledge than many other kinds of knowledge, such as that for facts, procedures or narratives. The illusion for explanatory knowledge is most robust where the environment supports real‐time explanations with visible mechanisms. We demonstrate the illusion of depth with explanatory knowledge in Studies 1–6. Then we show (...) differences in overconfidence about knowledge across different knowledge domains in Studies 7–10. Finally, we explore the mechanisms behind the initial confidence and behind overconfidence in Studies 11 and 12, and discuss the implications of our findings for the roles of intuitive theories in concepts and cognition. (shrink)

Many epistemologists use intuitive responses to particular cases as evidence for their theories. Recently, experimental philosophers have challenged the evidential value of intuitions, suggesting that our responses to particular cases are unstable, inconsistent with the responses of the untrained, and swayed by factors such as ethnicity and gender. This paper presents evidence that neither gender nor ethnicity influence epistemic intuitions, and that the standard responses to Gettier cases and the like are widely shared. It argues that epistemic intuitions are produced (...) by the natural ‘mindreading’ capacity that underpins ordinary attributions of belief and knowledge in everyday social interaction. Although this capacity is fallible, its weaknesses are similar to the weaknesses of natural capacities such as sensory perception. Experimentalists who do not wish to be skeptical about ordinary empirical methods have no good reason to be skeptical about epistemic intuitions. (shrink)

is normative in the sense that it aims to make recommendations for improving human judgment; it aims to have a practical impact on morally and politically significant human decisions and actions; and it studies normative, rational judgment qua rational judgment. These nonstandard ways of understanding ACP as normative collectively suggest a new interpretation of the strong replacement thesis that does not call for replacing normative epistemic concepts, relations, and inquiries with descriptive, causal ones. Rather, it calls for recognizing that the (...) aims and normative inquiries of epistemology and normative psychology have become intermutual in nature. Key Words: Heuristics and biases • applied cognitive psychology • normative psychology • rationality • naturalized epistemology • Epistemics • Applied Naturalized Epistemology • strong replacement • strategic reliabilism • ameliorative psychology. (shrink)

In this response, we clarify several misunderstandings of the understanding/acceptance principle and defend our specific operationalization of that principle. We reiterate the importance of addressing the problem of rational task construal and we elaborate the notion of computational limitations contained in our target article. Our concept of thinking dispositions as variable intentional-level styles of epistemic and behavioral regulation is explained, as is its relation to the rationality debate. Many of the suggestions of the commentators for elaborating two-process models are easily (...) integrated into our generic dual-process account. We further explicate how we view the relation between System 1 and System 2 and evolutionary and normative rationality. We clarify our attempt to fuse the contributions of the cognitive ecologists with the insights of the original heuristics and biases researchers. (shrink)

A working assumption that processes of natural and cultural evolution have tailored the mind to fit the demands and structure of its environment begs the question: how are we to characterize the structure of cognitive environments? Decision problems faced by real organisms are not like simple multiple-choice examination papers. For example, some individual problems may occur much more frequently than others, whilst some may carry much more weight than others. Such considerations are not taken into account when (i) the performance (...) of candidate cognitive mechanisms is assessed by employing a simple accuracy metric that is insensitive to the structure of the decision-maker's environment, and (ii) reason is defined as the adherence to internalist prescriptions of classical rationality. Here we explore the impact of frequency and significance structure on the performance of a range of candidate decision-making mechanisms. We show that the character of this impact is complex, since structured environments demand that decision-makers trade off general performance against performance on important subsets of test items. As a result, environment structure obviates internalist criteria of rationality. Failing to appreciate the role of environment structure in shaping cognition can lead to mischaracterising adaptive behavior as irrational. (shrink)

Airline pilots are attributed ultimate responsibility and final authority over their aircraft to ensure the safety and well-being of all its occupants. Yet, with the advent of automation technologies, a dissonance has emerged in that pilots have lost their actual decision-making authority as well as their ability to act in an adequate fashion towards meeting their responsibilities when unexpected circumstances or emergencies occur. Across the literature in human factor studies, we show how automated algorithmic technologies have wrestled control away from (...) airline pilots. The inter-related ethical and pragmatic consequences resulting from such a dissonance are presented. This includes pilots serving as ‘legal sponges’, being caught in ‘moral crumple zones’, as well as real impacts on safety and well-being of passengers and crew. One potential avenue presented in the literature involves a redistribution of responsibility towards all agential entities within the cockpit system. We discuss the possible pitfalls to this approach, including the reinforcement of pilot skills erosion as well as technology’s own limitations in adaptively dealing with unexpected circumstances. We justify our position by showing how algorithmic technology’s representational frames mask or severely limit the pilots’ natural reflex to ‘practically cope’ and gain an ‘optimal grip’ with a given context/situation at hand. Here, we present the concept of relevant or meaningful control, which pilots, when allowed to develop their natural brain-body reflexes, gain across gradual mastery of the aircraft. Finally, we propose a socio-technical design approach in which pilots can re-appropriate full human meaningful control of the aircraft, thus allowing them to meet their attributed responsibilities. (shrink)

This article is concerned with how we make decisions based on how problems are presented to us and the effect that the framing of the problem might have on our choices. Current philosophical and psychological accounts of the framing effect in experiments such as the Asian Disease Problem concern reference points and domains. We question the importance of reference points and domains. Instead, we adopt a linguistic perspective focussing on the role of the evaluative polarity evoked by the words - (...) negativeand positive - used to describe the options in the decision problem. We show that the evaluative polarity of the different wordings in the ADP better explain participants’ behaviour than reference points and domains. We propose two models in which the values given to evaluative polarity words directly influence the strength of framing. The results indicate that linguistic considerations regarding evaluative polarity have to be considered in relation to the ADP. The account resembles Fuzzy-Trace-Theory but allows for thestrength of evaluative polarity to directly affect behaviour. In the discussion, we also assess how evaluative polarity relates to negation, antonyms and the communicative frame within which the choices are presented. (shrink)

In recent years, a plethora of high-profile scientific publications has been reporting about machine learning algorithms outperforming clinicians in medical diagnosis or treatment recommendations. This has spiked interest in deploying relevant algorithms with the aim of enhancing decision-making in healthcare. In this paper, we argue that instead of straightforwardly enhancing the decision-making capabilities of clinicians and healthcare institutions, deploying machines learning algorithms entails trade-offs at the epistemic and the normative level. Whereas involving machine learning might improve the accuracy of medical (...) diagnosis, it comes at the expense of opacity when trying to assess the reliability of given diagnosis. Drawing on literature in social epistemology and moral responsibility, we argue that the uncertainty in question potentially undermines the epistemic authority of clinicians. Furthermore, we elucidate potential pitfalls of involving machine learning in healthcare with respect to paternalism, moral responsibility and fairness. At last, we discuss how the deployment of machine learning algorithms might shift the evidentiary norms of medical diagnosis. In this regard, we hope to lay the grounds for further ethical reflection of the opportunities and pitfalls of machine learning for enhancing decision-making in healthcare. (shrink)

Decision-making competence in later adulthood is affected by declines in cognitive skills, and age-related changes in affect and experience can sometimes compensate. However, recent findings suggest that age-related changes in motivation also affect the extent to which adults draw from experience, affect, and deliberative skills when making decisions. To date, relatively little attention has been given to strategies for addressing age-related changes in motivation to promote better decisions in older adults. To address this limitation, we draw from diverse literatures to (...) suggest promising intervention strategies for motivating older recipients’ motivation to make better decisions. We start by reviewing the life-span developmental literature, which suggests that older adults’ motivation to put effort into decisions depends on the perceived personal relevance of decisions as well as their self-efficacy (i.e., confidence in applying their ability and knowledge). Next, we discuss two approaches from the health intervention design literature, the mental models approach and the patient activation approach, which aim to improve motivation for decision making by improving personal relevance or by building self-efficacy or confidence to use new information and skills. Using examples from these literatures, we discuss how to construct interventions to motivate good decisions in later adulthood. (shrink)

In two experiments, we investigated the relationship between confidence and accuracy in syllogistic reasoning. Participants judged the validity of conclusions and provided confidence ratings twice for each problem: once quickly and again after further deliberation. Correlations between confidence and accuracy were small or nonexistent. In addition, confidence and accuracy were mediated by different variables. Confidence judgments appeared to reflect external cues, so that confidence was greater when the participants were allowed additional time to think about the problem, as well as (...) when the conclusion was either believable or unbelievable, rather than neutral. In contrast, accuracy changed little as a function of the amount of time available and did not differ for believable and neutral problems. These data support a model in which initial decisions are made quickly, on the basis of heuristic cues, and analytic processes are used to justify or rationalize the earlier decision. (shrink)

This commentary deals with criteria for assigning truth values to memory contents. A parallel with perception shows how truth values can be assigned by considering subjects' beliefs about the truth state of the memory content. This topic is also relevant to the study of processes of control over retrieval.

Koriat & Goldsmith's thesis is provocative but has three problems: First, quantity and accuracy are not simply related, they are complementary. Second, the storehouse metaphor is not the driving force behind contemporary theories of memory and may not be viable. Third, the taxonomy is incomplete, leaving unclassified several extremely influential methods and measures, such as priming and response latency.

This commentary presents a self-assessment inventory that will allow readers to determine their own attitude toward the base rate fallacy and its literature. The inventory is scientifically valid but not Medicare/Medicaid reimbursable.

Cognitive algebra strongly disproved the representativeness heuristic almost before it was published; and therewith it also disproved the base rate fallacy. Cognitive algebra provides a theoretical foundation for judgment-decision theory through its joint solution to the two fundamental problems – true measurement of subjective values, and cognitive rules for integration of multiple determinants.

We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. At the empirical level, a thorough examination of the base rate literature (including the famous lawyer–engineer problem) does not support the conventional wisdom that people routinely ignore base rates. Quite the contrary, the literature shows that base rates are almost always used and that their degree of use depends on task structure and representation. Specifically, base rates play a relatively larger role (...) in tasks where base rates are implicitly learned or can be represented in frequentist terms. Base rates are also used more when they are reliable and relatively more diagnostic than available individuating information. At the normative level, the base rate fallacy should be rejected because few tasks map unambiguously into the narrow framework that is held up as the standard of good decision making. Mechanical applications of Bayes's theorem to identify performance errors are inappropriate when (1) key assumptions of the model are either unchecked or grossly violated, and (2) no attempt is made to identify the decision maker's goals, values, and task assumptions. Methodologically, the current approach is criticized for its failure to consider how the ambiguous, unreliable, and unstable base rates of the real world are and should be used. Where decision makers' assumptions and goals vary, and where performance criteria are complex, the traditional Bayesian standard is insufficient. Even where predictive accuracy is the goal in commonly defined problems, there may be situations (e.g., informationally redundant environments) in which base rates can be ignored with impunity. A more ecologically valid research program is called for. This program should emphasize the development of prescriptive theory in rich, realistic decision environments. (shrink)

Philosophical theorizing is often, either tacitly or explicitly, guided by intuitions about cases. Theories that accord with our intuitions are generally considered to be prima facie better than those that do not. However, recent empirical work has suggested that philosophically significant intuitions are variable and unstable in a number of ways. This variability of intuitions has led naturalistically inclined philosophers to disparage the practice of relying on intuitions for doing philosophy in general (e.g. Stich & Weinberg 2001) and for doing (...) moral philosophy in particular (Appiah 2008; Doris & Stich 2005; Horowitz 1998; Nadelhoffer & Feltz 2008; Sinnott Armstrong 2008). In this paper, we will draw on naturalistic considerations to offer some solace to philosophers who rely on intuitions. We wouldn’t call this a defense of intuitions, exactly, since we are sympathetic with much of the naturalists’ critique. But we want to introduce into the debate some neglected naturalistic reasons to be optimistic about intuitions, focusing especially on ethical intuitions. (shrink)

This article provides an overview of recent results on lexicographic, linear, and Bayesian models for paired comparison from a cognitive psychology perspective. Within each class, we distinguish subclasses according to the computational complexity required for parameter setting. We identify the optimal model in each class, where optimality is defined with respect to performance when fitting known data. Although not optimal when fitting data, simple models can be astonishingly accurate when generalizing to new data. A simple heuristic belonging to the class (...) of lexicographic models is Take The Best (Gigerenzer & Goldstein (1996) Psychol. Rev. 102: 684). It is more robust than other lexicographic strategies which use complex procedures to establish a cue hierarchy. In fact, it is robust due to its simplicity, not despite it. Similarly, Take The Best looks up only a fraction of the information that linear and Bayesian models require; yet it achieves performance comparable to that of models which integrate information. Due to its simplicity, frugality, and accuracy, Take The Best is a plausible candidate for a psychological model in the tradition of bounded rationality. We review empirical evidence showing the descriptive validity of fast and frugal heuristics. (shrink)

Over the past few decades, reasoning and rationality have been the focus of enormous interdisciplinary attention, attracting interest from philosophers, psychologists, economists, statisticians and anthropologists, among others. The widespread interest in the topic reflects the central status of reasoning in human affairs. But it also suggests that there are many different though related projects and tasks which need to be addressed if we are to attain a comprehensive understanding of reasoning.

During the last 25 years, researchers studying human reasoning and judgment in what has become known as the “heuristics and biases” tradition have produced an impressive body of experimental work which many have seen as having “bleak implications” for the rationality of ordinary people (Nisbett and Borgida 1975). According to one proponent of this view, when we reason about probability we fall victim to “inevitable illusions” (Piattelli-Palmarini 1994). Other proponents maintain that the human mind is prone to “systematic deviations from (...) rationality” (Bazerman & Neale 1986) and is “not built to work by the rules of probability” (Gould 1992). It has even been suggested that human beings are “a species that is uniformly probability-blind” (Piattelli-Palmarini 1994). This provocative and pessimistic interpretation of the experimental findings has been challenged from many different directions over the years. One of the most recent and energetic of these challenges has come from the newly emerging field of evolutionary psychology, where it has been argued that it’s singularly implausible to claim that our species would have evolved with no “instinct for probability” and, hence, be “blind to chance” (Pinker 1997, 351). Though evolutionary psychologists concede that it is possible to design experiments that “trick our probability.. (shrink)

Samuels and Stich explore the debate over the extent to which ordinary human reasoning and decision making is rational. One prominent cluster of views, often associated with the heuristics and biases tradition in psychology, maintains that human reasoning is, in important respects, normatively problematic or irrational. Samuels and Stich start by sketching some key experimental findings from this tradition and describe a range of pessimistic claims about the rationality of ordinary people that these and related findings are sometimes taken to (...) support. Such pessimistic interpretations of the experimental findings have not gone unchallenged however: Samuels and Stich outline some of the research on reasoning that has been done by evolutionary psychologists and sketch a cluster of more optimistic theses about ordinary reasoning that such psychologists defend. Although Samuels and Stich think that the most dire pronouncements made by writers in the heuristics and biases tradition are unwarranted, they also maintain that the situation is rather more pessimistic than sometimes suggested by evolutionary psychologists. They conclude by defending this “middle way” and sketch a family of “dual processing” theories of reasoning which, they argue, offer some support for the moderate interpretation they advocate. (shrink)

In this paper we contrast bounded and ecological rationality with a proposed alternative, generative rationality. Ecological approaches to rationality build on the idea of humans as “intuitive statisticians” while we argue for a more generative conception of humans as “probing organisms.” We first highlight how ecological rationality’s focus on cues and statistics is problematic for two reasons: the problem of cue salience, and the problem of cue uncertainty. We highlight these problems by revisiting the statistical and cue-based logic that underlies (...) ecological rationality, which originate from the misapplication of concepts in psychophysics. We then work through the most popular experimental task in the ecological rationality literature—the city size task—to illustrate how psychophysical assumptions have informally been linked to ecological rationality. After highlighting these problems, we contrast ecological rationality with a proposed alternative, generative rationality. Generative rationality builds on biology—in contrast to ecological rationality’s focus on statistics. We argue that in uncertain environments cues are rarely given or available for statistical processing. Therefore we focus on the psychogenesis of awareness rather than psychophysics of cues. For any agent or organism, environments “teem” with indefinite cues, meanings and potential objects, the salience or relevance of which is scarcely obvious based on their statistical or physical properties. We focus on organism-specificity and the organism-directed probing that shapes awareness and perception. Cues in teeming environments are noticed when they serve as cues-for-something, requiring what might be called a “cue-to-clue” transformation. In this sense, awareness toward a cue or cues is actively “grown.” We thus argue that perception might more productively be seen as the presentation of cues and objects rather than their representation. This generative approach not only applies to relatively mundane organism interactions with their environments—as well as organism-object relationships and their embodied nature—but also has significant implications for understanding the emergence of novelty in economic settings. We conclude with a discussion of how our arguments link with—but modify—Herbert Simon’s popular “scissors” metaphor, as it applies to bounded rationality and its implications for decision making in uncertain, teeming environments. (shrink)

ABSTRACTA cognitive autopoietic system is a dynamic, self-generating, organized and self-organizing thing which self-regulates with respect to an external medium. The present model of the effect of stress on a cognitive autopoietic system captures the notion of how a priori cognitive structures, combined with external sensations, constitute the basis for the development of cognitive structures and their architecture. The ESCA model integrates the fact that the mind–environment relation has a twofold effect: on one hand, it enables self-regulation of mind, but (...) on the other hand, it poses a potential perturbation on the same, which may result in the breakdown of the self-regulation of mind. The architecture of the CS developed on the basis of the ESCA model is consistent with the manifestations of the effect of stress on mind behavior at different levels. The ESCA model predicts that the faculty to concatenate... (shrink)