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)

This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples;optimalityis used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the (...) extreme flexibility of optimality considerations, including selective search for confirming vidence, ex post rationalization, and the confusion of prediction with explanation. Commentators are asked to reflect on the extent to which optimality is an organizing principle of nature, a set of relatively unconnected techniques of science, a normative principle for rational choice and social organization, a metaphysical way of looking at the world, or something else still. (shrink)

A lot of philosophy taught to science students consists of scientific methodology. But many philosophy of science textbooks have a fraught relationship with methodology, presenting it either a system of universal principles or entirely permeated by contingent factors not subject to normative assessment. In this paper, I argue for an alternative, heuristic perspective for teaching methodology: as fallible, purpose- and context-dependent, subject to cost-effectiveness considerations and systematically biased, but nevertheless subject to normative assessment. My pedagogical conclusion from this (...) perspective is that philosophers should aim to teach science students heuristic reasoning: strategies of normative method choice appraisal that are sensitive to purposes, contexts, biases and cost-effectiveness considerations; and that we should do so by teaching them exemplars of such reasoning. I illustrate this proposal at the hand of three such exemplars, showing how they help students to appreciate the heuristic nature of both methods and methodology, and to normatively assess method choice in such circumstances. (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)

The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...

Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of the system's parts if it depends upon their mode of organization--a view consistent with reduction. Emergence can be analyzed as a failure of aggregativity--a state in which "the whole is nothing more than the sum of its parts." Aggregativity requires four conditions, giving tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different (...) degrees, these conditions provide powerful evaluation criteria for choosing decompositions, and heuristics for detecting biases of vulgar reductionisms. This analysis of emergence is compatible with reduction. (shrink)

Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: the discovery of less-is-more effects; the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; an advancement from vague labels to computational models (...) of heuristics; the development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an “adaptive toolbox;” and the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people’s adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. (shrink)

The ecologist today finds scarce ground safe from controversy. Decisions must be made about what combination of data, goals, methods, and theories offers them the foundations and tools they need to construct and defend their research. When push comes to shove, ecologists often turn to philosophy to justify why it is their approach that is scientific. Karl Popper’s image of science as bold conjectures and heroic refutations is routinely enlisted to justify testing hypotheses over merely confirming them. One of (...) the most controversial theories in contemporary science is the Neutral Theory of Ecology. Its chief developer and proponent, Stephen Hubbell, presents the neutral theory as a bold conjecture that has so far escaped refutation. Critics of the neutral theory claim that it already stands refuted, despite what the dogmatic neutralists say. We see the controversy through a Popperian lens. But Popper’s is an impoverished philosophy of science that distorts contemporary ecology. -/- The controversy surrounding the neutral theory actually rests on a methodological fault. There is a strong but messy historical link between the concepts of being neutral and being null in biology, and Hubbell perpetuates this when he claims that the neutral theory is supplies the appropriate null for testing alternative theories. What method is being followed here? There are three contenders: -/- Null hypothesis testing tests for whether a there is a pattern to be explained. Null modeling tests for whether a process is causally relevant to a pattern. Baseline modeling apportions relative responsibility to multiple processes each relevant to a pattern. -/- Whether the neutral theory supplies an appropriate “null” depends upon whether null hypothesis, null modeling, or baseline model is intended. These methods prescribe distinct inference patterns. If they are null hypothesis testing or null modeling, the neutralists’s reasoning is invalid. If they are baseline modeling, the justification of a crucial assumption remains opaque. Either way, the neutral-null connection is being exploited rhetorically to privilege the neutral theory over its rivals. Clarifying the reasoning immunizes us against the rhetoric and foregrounds the underlying virtues of the neutralist approach to ecology. -/- The Popperian lens distorts theoretical development as dogmatism. Lakatos’s view of science as the development of research programmes clarifies the epistemology of the neutral theory. Focusing philosophical attention on the neutralist research programme illuminates (1) the synchronic uses of the neutral theory to make predictions and give descriptions and explanations; (2) its diachronic development in response to theoretical innovation and confrontation with data; (3) its complex relationships to alternative theories. For example, baseline modeling is now seen to be its primary explanatory heuristic. The justification for baseline modeling with the neutral theory, previously hidden from view, is seen in the logic of in the neutralist research programme. (shrink)

We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along several (...) distinct dimensions. First, we show that words associated with an increase in quantity or number (e.g., add, addition, more, most) are more frequent than words associated with a decrease in quantity or number (e.g., subtract, subtraction, less, least). Second, we show that in binomial expressions, addition-related words are mentioned first, that is, add and subtract rather than subtract and add. Third, we show that the distributional semantics of verbs of change, such as to improve and to transform, overlap more with the distributional semantics of add/increase than subtract/decrease, which suggests that change verbs are implicitly biased toward addition. Fourth, addition-related words have more positive connotations than subtraction-related words. Fifth, we demonstrate that state-of-the-art large language models, such as the Generative Pre-trained Transformer (GPT-3), are also biased toward addition. We discuss the implications of our results for research on cognitive biases and decision-making. (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)

Mark Kelman’s recent book, The Heuristics Debate (HD), has two main goals. First, it seeks to reconstruct the controversy in decision science between Kahneman et al.’s heuristics-and-biases approach and Gigerenzer et al.’s fast-and-frugal heuristics approach. Second, it tries to discuss its implications for jurisprudence and policy-making. This study focuses on the first task only. The study attempts to show that, although HD has several important merits, its interpretation of the controversy misses some crucial aspects. Specifically, (...) HD fails to appreciate that the debate is fundamentally about what a “rational” judgment is in the first place. Moreover, because of this, HD also fails to acknowledge the interplay between normative and methodological considerations. With regard to this aspect, HD’s treatment of the controversy fits into a long tradition. This study takes the opportunity to rectify the error. (shrink)

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)

The simple heuristics that may indeed usually make us smart–or at least smart enough–in contexts of individual choice will sometimes make us dumb, especially in contexts of social choice. Here each individual choice (or vote) has little impact on the overall choice, although the overall choice is compounded out of the individual choices. I use an example (risk aversion) to illustrate the point.

There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision-making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One (...) region implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues. (shrink)

Dual-processes theories of cognition implicitly assume universality of the human mind. However, research has shown that large-scale differences exist in thinking styles across cultures. Thereby, the universality of the effects found in Western samples remains an open empirical question. Here, we explored whether effects predicted by prospect theory, such as the framing effect, would be observed in a sample of 312 Bulgarian students. Overall, the size of the framing effect was smaller than in the original studies. Most notably, we failed (...) to reproduce the framing effect in the famous Asian Disease problem, using a rating response format. In a between-subjects design, decision- making performance was completely independent of university admission grades. We propose that studying the size of the effects across cultures is needed in order to establish the effects’ level of universality. More broadly, we suggest ways in which knowledge of cultural settings can help elaborate or test dual-process predictions. (shrink)

This chapter investigates the extent to which claims of massive modular organization of the mind (espoused by some members of the evolutionary psychology research program) are consistent with the main elements of the simple heuristics research program. A number of potential sources of conflict between the two programs are investigated and defused. However, the simple heuristics program turns out to undermine one of the main arguments offered in support of massive modularity, at least as the latter is generally (...) understood by philosophers. So one result of the argument will be to force us to re-examine the way in which the notion of modularity in cognitive science should best be characterized, if the thesis of massive modularity isn’t to be abandoned altogether. What is at stake in this discussion, is whether there is a well-motivated notion of ‘module’ such that we have good reason to think that the human mind must be massively modular in its organization. I shall be arguing (in the end) that there is. (shrink)

The Adaptive Toolbox framework specifies heuristics for choice and categorisation that search through cues in previously learned orders (Gigerenzer & Todd, 1999). We examined the learning of three cue parameters defining different orders: discrimination rate (DR) (the probability that a cue points to a unique choice), validity (the probability of correct choice given that a cue discriminates), and success (the probability of correct choice). Success orderings are identical to those by expected information gain (Klayman & Ha, 1987). In two (...) experiments, participants made choices in real-world environments with objective outcome criteria. Participant ratings indicated some appropriate parameter learning when the relevant cue parameter values were highly dispersed. Rated orders of cue validity and DR were less distinct than the objective orders—learning one parameter may be biased towards success by variation in the other. Success ratings capture the variation in validity and DR as well as participants' perception of these parameters. (shrink)

With respect to questions of fact, people use heuristics – mental short-cuts, or rules of thumb, that generally work well, but that also lead to systematic errors. People use moral heuristics too – moral short-cuts, or rules of thumb, that lead to mistaken and even absurd moral judgments. These judgments are highly relevant not only to morality, but to law and politics as well. Examples are given from a number of domains, including risk regulation, punishment, reproduction and sexuality, (...) and the act/omission distinction. In all of these contexts, rapid, intuitive judgments make a great deal of sense, but sometimes produce moral mistakes that are replicated in law and policy. One implication is that moral assessments ought not to be made by appealing to intuitions about exotic cases and problems; those intuitions are particularly unlikely to be reliable. Another implication is that some deeply held moral judgments are unsound if they are products of moral heuristics. The idea of error-prone heuristics is especially controversial in the moral domain, where agreement on the correct answer may be hard to elicit; but in many contexts, heuristics are at work and they do real damage. Moral framing effects, including those in the context of obligations to future generations, are also discussed. (shrink)

I present two criticisms: (1) Merge is a model of performance in speech perception experiments but not an ecologically valid model integrating both word recognition and speech perception, and (2) Merge's implementation of the variability of lexical effects must be made more precise or the model is indistinguishable from its alternatives.

If A confirms H and B confirms H, it seems reasonable to infer that A&B confirms H. However, this inference is not valid; it is only a heuristic. I show that the level of confirmation A and B each give to H by itself implies nothing about the level of confirmation that A&B gives to H. Any combination of values is possible for P(H), P(H|A), P(H|B) and P(H|AB) is possible. Still, I show the heuristic leads from true premises to true (...) conclusions whenever A and B are statistically independent or correlated,which includes most situations where we evaluate evidence. There is risk, though, when one does not consider how A and B interact; one can miss anti-correlations that lead the heuristic to fail. The problem is exacerbated when groups of people are motivated to support a favored hypothesis. Each person finds evidence that confirms the hypothesis and contributes that evidence to the group’s discourse (e.g. through a climate change denial website). The temptation to focus solely on the number of individual pieces of evidence can lead people to ignore whether the evidence fits together. In combination with cognitive biases, this can lead to serious errors. (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)

Gigerenzer’s ‘external validity argument’ plays a pivotal role in his critique of the heuristics and biases research program (HB). The basic idea is that (a) the experimental contexts deployed by HB are not representative of the real environment and that (b) the differences between the setting and the real environment are causally relevant, because they result in different performances by the subjects. However, by considering Gigerenzer’s work on frequencies in probability judgments, this essay attempts to show that there (...) are fatal flaws in the argument. Specifically, each of the claims is controversial: whereas (b) is not adequately empirically justified, (a) is inconsistent with the ‘debiasing’ program of Gigerenzer’s ABC group. Therefore, whatever reason we might have for believing that the experimental findings of HB lack experimental validity, this should not be based on Gigerenzer’s version of the argument. (shrink)

Feminist philosophers have discussed the prospects for assessing values empirically, particularly given the ongoing threat of sexism and other oppressive values influencing science and society. Some advocates of such tests now champion a “values as evidence” approach, and they criticize Helen Longino’s contextual empiricism for not holding values to the same level of empirical scrutiny as other claims. In this paper, we defend contextual empiricism by arguing that many of these criticisms are based on mischaracterizations of Longino’s position, overstatements (...) of certain claims, and false dichotomies. Her contextual empiricism not only allows for the empirical support and disconfirmation of values, but Longino explicitly discusses when values can be empirically adjudicated and emphasizes the crucial role of the community for standards of evidence. We support contextual empiricism and elaborate a less direct account of “values as heuristics” by reviewing Longino’s theory of evidence and then using a case study from Elisabeth Lloyd on the biology of female orgasm, demonstrating the disconfirmation of androcentric values in evolutionary science. Within Longino’s and Lloyd’s contextual empiricism, values do not get treated as empirical evidence to be directly assessed by individuals, but rather values are heuristic tools to build models whose use can be validated or invalidated by communities based on their empirical fruitfulness in the logic and pragmatics of research questions in specific historical and cultural contexts. (shrink)

Sewall Wright's adaptive landscape is the most influential heuristic in evolutionary biology. Wright's biographer, Provine, criticized Wright's adaptive landscape, claiming that its heuristic value is dubious because of deep flaws. Ruse has defended Wright against Provine. Ruse claims Provine has not shown Wright's use of the landscape is flawed, and that, even if it were, it is heuristically valuable. I argue that both Provine's and Ruse's analyses of the adaptive landscape are defective and suggest a more adequate understanding of it.

Is human cognition best described by optimal models, or by adaptive but suboptimal heuristic strategies? It is frequently hard to identify which theoretical model is normatively best justified. In the context of information search, naoptimal” models.

Research heuristics—implicit rules used to guide work on a scientific problem—are explored for their role in guiding psychological research. Work on the psychology of creativity is used to illustrate how heuristics have guided research. We examine the influence of three heuristics: the trilogy-of-mind heuristic, the emotions-as-moods heuristic, and the analysis-of-variance heuristic. This analysis of multiple heuristics provides a new way to understand the state of research on creativity. In the discussion, the analysis is extended to other (...) heuristics and to how heuristics may help as well as hinder innovative research. (shrink)

One of our more fundamental beliefs is that causal chains are continuous in time: we believe that every influence from the past upon the future runs through the present. I argue that this tenet, given certain data, can force conceptual changes upon us. I attempt to formulate a heuristic for discovery, based as explicitly as possible upon this tenet, and illustrate it by means of several examples, one of which is Mendel's discovery of genes.

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.

The program of research now known as the heuristics and biases approach began with a study of the statistical intuitions of experts, who were found to be excessively confident in the replicability of results from small samples. The persistence of such systematic errors in the intuitions of experts implied that their intuitive judgments may be governed by fundamentally different processes than the slower, more deliberate computations they had been trained to execute. The ancient idea that cognitive processes can (...) be partitioned into two main families--traditionally called intuition and reason--is now widely embraced under the general label of dual-process theories. Dual-process models come in many flavors, but all distinguish cognitive operations that are quick and associative from others that are slow and governed by rules. To represent intuitive and deliberate reasoning, we borrow the terms "system 1" and "system 2" from Stanovich and West. In the following section, we present an attribute-substitution model of heuristic judgment, which assumes that difficult questions are often answered by substituting an answer to an easier one. Following sections introduce a research design for studying attribute substitution, as well as discuss the controversy over the representativeness heuristic in the context of a dual-system view that we endorse. The final section situates representativeness within a broad family of prototype heuristics, in which properties of a prototypical exemplar dominate global judgments concerning an entire set. (shrink)

By focusing on mistaken judgments, Sunstein provides a theory of performance errors without a theory of moral competence. Additionally, Sunstein's objections to thought experiments like the footbridge and trolley problems are unsound. Exotic and unfamiliar stimuli are used in theory construction throughout the cognitive sciences, and these problems enable us to uncover the implicit structure of our moral intuitions.

Although economists often model decision makers as rational actors, the heuristics and biases literature that springs from the work of Nobel Prize winner Daniel Kahneman and his late colleague Amos Tversky demonstrates that people make decisions that depart from the optimal model in systematic ways. These cognitive and behavioral limitations not only cause inefficient decision making, but also lead people to make decisions that are unethical. This article seeks to introduce a selected portion of the heuristics and (...) biases and related psychological literature, to highlight its implications for ethical decision making, and to serve as the basis for a lecture that could inform students regarding these matters. If business actors are on guard against errors in their own decision making processes, perhaps they can avoid some of the ethical pitfalls that recently put Enron and so many other companies in the news. (shrink)

Sensitivity-type principles are prominent in epistemology. They have the promise to explain our intuitive and considered reactions to a wide range of important cases in everyday life, science and philosophy. Despite this promise, philosophers have raised a number of very serious objections to the principles. Accordingly, I propose a different type of sensitivity account which, I believe, gets around these serious objections. An important feature of the new approach is that the principle I propose need not be true. Rather, (...) it should be understood as a cognitive heuristic that tells us when something is not known—a type of doubt. A second feature is that the principle does not care about what one’s belief would be like in counter-factual situations. Instead, it cares about what the bases or causes for the belief would be like in those situations. (shrink)

A survey of contemporary philosophical and scientific literatures reveals that different authors employ the term ‘heuristic’ in ways that deviate from, and are sometimes inconsistent with, one another. Given its widespread use in philosophy and cognitive science generally, it is striking that there appears to be little concern for a clear account of what phenomena heuristics pick out or refer to. In response, I consider several accounts of ‘heuristic’, and I draw a number of distinctions between different sorts (...) of heuristics in order to make sense of various research programmes. I then develop a working characterization of ‘heuristic’ which is shown to be coherent and robust enough to serve as a kind within philosophy and cognitive science broadly. My intent is not to pursue a unified account of ‘heuristic’, but to highlight some features of certain kinds of heuristics that are important for theorizing about cognition in order to proceed with a science of the mind/brain. 1 Why We Need an Appropriate Characterization of ‘Heuristic’2 Inadequate Definitions2.1 A positive attempt2.2 Heuristics versus guaranteed correct outcomes3 A Taxonomy of Heuristics3.1 Stimulus-driven versus heuristic3.2 Perceptual versus cognitive heuristics3.3 Computational versus cognitive heuristics3.4 Methodological versus inferential heuristics3.5 Summary of distinctions4 Characterizing Cognitive Heuristics4.1 Heuristics as rules of thumb4.2 Beyond rules of thumb: exploiting information5 Concluding Remarks. (shrink)

Gigerenzer, Todd, and the ABC Research Group argue that optimisation under constraints leads to an infinite regress due to decisions about how much information to consider when deciding. In certain cases, however, their fast and frugal heuristics lead instead to an endless series of decisions about how best to decide.

The HeartMath system refers to various methods, tools and techniques developed by the HeartMath Institute, a global research and educational organization. Working from an interdisciplinary, scientific foundation, the institute has adopted a coherence model to promote its vision and mission of education and health. This model is based on empirical, predominantly natural scientific foundations. Although many, rigorous studies have provided a substantial evidence base of the science and praxis of personal, social and global coherence, the actual coherence experience has (...) not yet been investigated. To address this gap in the HeartMath research evidence, this heuristic phenomenological investigation was organized into three phases, with the goal of eliciting the essential structure of the coherence experience. The first phase consisted of a quantitatively orientated review of the author’s personal HeartMath practice records, with special focus on examples of highest coherence levels and achievement scores, as measured on HeartMath instruments, and as available on Heart Cloud records. In the second qualitatively orientated phase, ten selected descriptions, perceived to be good examples of coherence experiences, were synthesized into an essential review summary. The third, pilot study, phase explored the actual coherence experience of ten consecutive HeartMath sessions, varying with regard to context, duration, time, place and manner of practice. Essential summary findings of the coherence experience are discussed with regard to personal, social and global implications for research, education and health promotion. (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)

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. (...) 1999), we explore fast and frugal heuristics – simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data – that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program. Key Words: adaptive toolbox; bounded rationality; decision making; elimination models; environment structure; heuristics; ignorance-based reasoning; limited information search; robustness; satisficing; simplicity. (shrink)

Simple heuristics are clearly powerful tools for making near optimal decisions, but evidence for their use in specific situations is weak. Gigerenzer et al. (1999) suggest a range of heuristics, but fail to address the question of which environmental or task cues might prompt the use of any specific heuristic. This failure compromises the falsifiability of the fast and frugal approach.

An influential heuristic for thinking about climate adaptation asserts that “natural” adaptation strategies are the best ones. This heuristic has been roundly criticized but is difficult to dislodge in the absence of an alternative. We introduce a new heuristic that assesses adaptation strategies by looking at their maturity, power, and commitment. Maturity is the extent to which we understand an adaptation strategy’s effects. Power is the size of the effect an adaptation strategy will have. Commitment is the degree to which (...) an adaptation strategy is difficult to test or reverse. (shrink)

The science of consciousness has made great strides in recent decades. However, the proliferation of competing theories makes it difficult to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, agents artificial systems are capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to (...) artificial systems. With these challenges in mind, I propose that we look for ecumenical heuristics for artificial consciousness to enable us to make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such heuristics should have three main features: they should be (i) intuitively plausible, (ii) theoretically-neutral, and (iii) scientifically tractable. I claim that the concept of general intelligence — understood as a capacity for robust, flexible, and integrated cognition and behavior — satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious. -/- . (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)

A large campaign has sought to destigmatize psychiatric disorders by disseminating the view that they are in fact brain disorders. But when psychiatric disorders are associated with neurobiological correlates, laypeople's attitudes toward patients are harsher, and the prognoses seem poorer. Here, we ask whether these misconceptions could result from the essentialist presumption that brain disorders are innate. To this end, we invited laypeople to reason about psychiatric disorders that are diagnosed by either a brain or a behavioral test that were (...) strictly matched for their informative value. Participants viewed disorders as more likely to be innate and immutable when the diagnosis was supported by a brain test as compared to a behavioral test. These results show for the first time that people spontaneously essentialize psychiatric conditions that are linked to the brain, even when the brain probe offers no additional diagnostic or genetic information. This bias suggests that people consider the biological essence of living things as materially embodied. (shrink)