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.

For decades, interdisciplinary research efforts have accumulated insights that diminish the significance of the classic nature versus nurture dichotomy, instead calling for a nuanced, multifactorial approach to ontogeny. Similarly, the role of genes in both phylogeny and ontogeny, once seen as rather deterministic, is now conceptualized as highly dependent on environmental factors, including behavior. Linguistic theories have, in principle, made an effort to incorporate these changing views. However, the central claim of the given paper is that this apparent compliance with (...) biological insights remains superficial. As such, considerable disconnects between linguistic theory and what is known about the biological underpinnings of complex traits persist, negatively impacting pertinent views on language acquisition, language universals and the evolution of language. Given the breadth of these fields of study, the aim of this paper is to tackle the root of the problem: It begins by sketching out linguistic nativism as conceptualized within generativism, pointing to aspects within this position that stand in conflict with the interdisciplinary literature. It will then review select areas of research in a succinct manner in order to substantiate the criticism and characterize the counterposition as found within the biological sciences. The paper will culminate in addressing these disconnects on conceptual grounds, i.e. invoking the term emergence as employed in neuroscience as a possible means to reconcile those biological insights with linguistic nativism. (shrink)

Empirically-informed approaches to emotion often construe our emotions as modules: systems hardwired into our brains by evolution and purpose-built to generate certain coordinated patterns of expressive, physiological, behavioural and phenomenological responses. In ‘Against Modularity’ (2008), de Sousa argues that we shouldn’t think of our emotions in terms of a limited number of modules because this conflicts with our aspirations for a life of greater emotional richness. My aim in this paper is to defend de Sousa’s critique of modular emotion taxonomies (...) from some obvious rejoinders, and to develop his positive proposal as to how we might reconcile the evidence for emotional modularity with an attitude of disapproval towards rigid emotion taxonomies. (shrink)

The general process view of learning, which guided research into learning for the first half of this century, has come under attack in recent years from several quarters. One form of criticism has come from proponents of the so-called biological boundaries approach to learning. These theorists have presented a variety of data showing that supposedly general laws of learning may in fact be limited in their applicability to different species and learning tasks, and they argue that the limitations are drawn (...) by the nature of each species' adaptation to the particular requirements of its natural environment. The biological boundaries approach has served an important critical function in the move away from general process learning theory, but it is limited in its ability to provide an alternative to the general process approach. In particular, the biological boundaries approach lacks generality, it is in some respects subservient to the general process tradition, and its ecological content is in too many cases limited toex post factoadaptive explanations of learning skills. A contrasting, ecological approach to learning, which can provide a true alternative to general process theory, is presented. The ecological approach begins by providing an ecological task description for naturally occurring instances of learning; this step answers the question:Whatdoes this animal learn to do? The next step is an analysis of the means by which learning occurs in the course of development, answering the question:Howdoes the animal learn to do this? On the basis of such analyses, local principles of adaptation are formulated to account for the learning abilities of individual species. More global principles are sought by generalization among these local principles and may form the basis for a general ecological theory of learning. (shrink)

A motivational system approach to avoidance behavior is presented. According to this approach, a motivational state increases the probability of relevant response patterns and establishes the appropriate or “ideal” consummatory stimuli as positive reinforcers. In the case of feeding motivation, for example, hungry rats are likely to explore and gnaw, and to learn to persist in activities correlated with the reception of consummatory stimuli produced by ingestion of palatable substances. In the case of defense motivation, fearful rats are likely to (...) flee or freeze, and to learn to persist in activities correlated with consummatory stimuli produced by flight from a dangerous place. Defense system activation is distinct from alarm reactions. The latter prepare the animal for probable noxious events, involve relatively intense negative affect and extinguish rapidly in situations where the noxious event no longer occurs. In contrast, defense system activation potentiates innate and modified defense reactions, thus preparing the animal for possible, but not necessarily probable, noxious events; it involves little or no negative affect and extinguishes very slowly when the noxious event no longer occurs. With these assumptions and the resulting model we attempt to resolve several long-standing problems in avoidance learning, including the low correlation between negative affect and avoidance performance, differential rates of extinction for avoidance performance and conditioned emotional responses, and evidence that some avoidance responses are much more easily learned than others. In addition, the model has implications for the study of parallels between appetitive and aversive motivation, sign tracking in aversive conditioning, and orientation of flight responses. Historical antecedents and alternative approaches are discussed. (shrink)

Responses are strengthened by consequences having to do with the survival of individuals and species. With respect to the provenance of behavior, we know more about ontogenic than phylogenic contingencies. The contingencies responsible for unlearned behavior acted long ago. This remoteness affects our scientific methods, both experimental and conceptual. Until we have identified he variables responsible for an event, we tend to invent causes. Explanatory entities such as “instincts,” “drives,” and “traits” still survive. Unable to show how organisms can behave (...) effectively under complex circumstances, we endow them with special abilities permitting them to do so.Behavior exhibited by most members of a species is often accepted as inherited if all members were not likely to have been exposed to relevant ontogenic contingencies. When contingencies are not obvious, it is perhaps unwise to call any behavior either inherited or acquired, as the examples of churring in honey guides and following in imprinted ducklings show. Nor can the relative importance of phylogenic and ontogenic contingencies be argued from instances in which unlearned or learned behavior intrudes or dominates. Intrusions occur in both directions.Behavior influenced by its consequences seems directed toward the future, but only past effects are relevant. The mere fact that behavior is adaptive does not indicate whether phylogenic or ontogenic processes have been responsible for it. Examples include the several possible provenances of imitation, aggression, and communication. The generality of such concepts limits their usefulness. A more specific analysis is needed if we are to deal effectively with the two kinds of contingencies and their products. (shrink)

A review of data concerning the uneven distribution of phobias suggests that nonassociative, ethological models can account for most of tile important findings that cannot be attributed to expectancy biases. The origin of a variety of fears that appear in fixed developmental patterns across divergent cultures and species can best be explained by biological models.

In his critique of preparedness theory, Davey does not address the limitations of adaptationism. The purpose of this commentary is to outline problems that arise when one assumes that mental illness (e.g., phobic disorder)musthave had adaptive significance for it to have survived the vicissitudes of natural selection.

Most phobias are focussed on a small number of fear-inducing stimuli (e.g., snakes, spiders). A review of the evidence supporting biological and cognitive explanations of this uneven distribution of phobias suggests that the readiness with which such stimuli become associated with aversive outcomes arises from biases in the processing of information about threatening stimuli rather than from phylogenetically based associative predispositions or “biological preparedness.” This cognitive bias, consisting of a heightened expectation of aversive outcomes following fear-relevant stimuli, generates and maintains (...) robust learned associations between them. Some of the features of such stimuli which determine this expectancy bias are estimates of how dangerous they are, the semiotic similarity between them and their aversive outcomes, and the degree of prior fear they elicit. Ontogenetic and cultural factors influence these features of fear-relevant stimuli and are hence important in determining expectancy bias. The available evidence does not exclude the possibility that both expectancy biases and specific evolved predispositions coexist, but the former can explain a number of important findings that the latter cannot. (shrink)

Commentators agree that simple conclusions about a general base rate fallacy are not appropriate. It is more constructive to identify conditions under which base rates are differentially weighted. Commentators also agree that improving the ecological validity of the research is desirable, although this is less important to those interested exclusively in psychological processes. The philosophers and ecologists among the commentators offer a kinder perspective on base rate reasoning than the psychologists. My own perspective is that the interesting questions (both psychological (...) and normative/prescriptive) are best answered through empirical studies that use real-world performance standards. (shrink)

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)

Base rates have no necessary relation to judgments that are not themselves probabilities. There is no logical imperative, for instance, that behavioral base rates must affect causal attributions or that base rate information should affect judgments of legal liability. Decision theorists should be cautious in arguing that base rates place normative constraints on judgments of anything other than posterior probabilities.

Abstract(1) The miscitations of seminal experiments in the base rate literature adds to the existing database of systematic miscitations of wellknown psychological experiments. These miscitations may be caused by a process of reconstructive remembering. (2) Representative design should be the methodological core of Koehler's call for ecologically valid research. This approach can benefit both basic and applied research.

Koehler's summary and critique of research on the base rate fallacy is cogent and persuasive. However, he may have overstated the case, and his suggestions for future research may be too restrictive. We agree that methodological approaches to this topic should be broadened, but we argue that experimental laboratory research and the Bayesian normative standard are useful and should not be abandoned.

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.

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.