Ethical decision-making research has centered on Rest’s framework that represents a rational, nonaffective model for ethical decision making. However, research in human cognition suggesting a “dual-processing” framework, composed of both rational and affective components, has been relatively ignored in the ethical decision-making literature. Examining dual-processing literature, it seems affect might be an important factor in decision making when a person’s mood is congruent with the task or situational context frame. Given that ethical decisions are serious and complex tasks, it is (...) proposed here that inducing a negative affective state might produce mood congruence, reinforce the salience of emotion for ethical decision makers, and lead to differences in decision processing. Evidence is presented documenting differences in the decisions made by ethical decision makers in a negative affective state as compared to those in either a positive or neutral affective state. (shrink)

Philosophers and psychologists alike have argued recently that relatively abstract beliefs or cognitive categories like those regarding race can influence the perceptual experience of relatively low-level visual features like color or lightness. Some of the proposed best empirical evidence for this claim comes from a series of experiments in which White faces were consistently judged as lighter than equiluminant Black faces, even for racially ambiguous faces that were labeled ‘White’ as opposed to ‘Black’ (Levin and Banaji 2006). The latter result (...) is considered especially indicative of cognitive penetration, based on the reasoning that the relevant distortions were a function of lexical labeling, and hence the effect must have been mediated by categorization at the cognitive level. I argue that this reasoning is flawed, and that the assumptions on which it relies are questionable on both empirical and theoretical grounds. I propose an alternative, low-level explanation of the phenomena, which I argue is empirically more plausible and abductively preferable to the cognitive-penetration account. The upshot is that cognitively impenetrable perceptual systems may be psychologically more plastic and hence philosophically more significant than is nowadays commonly assumed. (shrink)

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic (...) transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category-exemplar, mediated and backward prime-target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model. (shrink)

I criticize the idea that theories of ‘fragmented’ or ‘compartmentalized’ belief (as found in, e.g., Lewis 1982, Egan 2008) can help to account for the puzzling phenomena they are often taken to account for. After introducing fragmentationalism and a paradigm case that purportedly motivates it, I criticize the view primarily on the grounds that the models and explanations it offers are at best trivial—as witnessed by examples of over-generation—and should be seen as merely re-describing in figurative terms the phenomena it (...) is designed to account for. I also point out that fragments, as used in these theories, are not likely to be psychologically real in any robust sense and so cannot be appealed to on such grounds. (shrink)

In this paper we investigate how the dynamic nature of words’ meanings plays a role in a philosophical theory of meaning. For ‘dynamic nature’ we intend the characteristic of being flexible, of changing according to many factors (speakers, contexts, and more). We consider meaning as something that gradually takes shape from the dynamic processes of communication. Accordingly, we present a draft of a theory of meaning that, on the one hand, describes how a private meaning is formed as a mental (...) state of individual agents during a lifetime of experiences, and, on the other hand, shows how a public meaning emerges from the interaction of agents. When communicating with each other, agents need to converge on a shared meaning of the words used, by means of a negotiation process. A public meaning is the abstract product of many of these processes while, at the same time, the private meanings are continually reshaped by each negotiation. Exploring this dynamics, we have been looking at the work done by computer scientists dealing with problems of heterogeneity of sources of information. We argue that a suitable solution for both disciplines lies in a systematic characterization of the processes of meaning negotiation. (shrink)

The computational paradigm, which has dominated psychology and artificial intelligence since the cognitive revolution, has been a source of intense debate. Recently, several cognitive scientists have argued against this paradigm, not by objecting to computation, but rather by objecting to the notion of representation. Our analysis of these objections reveals that it is not the notion of representation per se that is causing the problem, but rather specific properties of representations as they are used in various psychological theories. Our analysis (...) suggests that all theorists accept the idea that cognitive processing involves internal information-carrying states that mediate cognitive processing. These mediating states are a superordinate category of representations. We discuss five properties that can be added to mediating states and examine their importance in various cognitive models. Finally, three methodological lessons are drawn from our analysis and discussion. (shrink)

Two experiments are reported which demonstrated intransitivity in category judgments, thus challenging a widely held assumption that the relation between categorized sets is one of class inclusion. Subjects consistently accepted the truth of certain category statements, in spite of being aware of the existence of counterexamples. Implications for semantic memory theory are discussed.

Starting from Marr's ideas about levels of explanation, a theory of the data structures and access processes in human memory is demonstrated on 10 tasks. Functional characteristics of human memory are captured implementation-independently. Our theory generates a multidimensional task classification subsuming existing classifications such as the distinction between tasks that are implicit versus explicit, data driven versus conceptually driven, and simple associative (two-way bindings) versus higher order (threeway bindings), providing a broad basis for new experiments. The formal language clarifies the (...) binding problem in episodic memory, the role of input pathways in both episodic and semantic (lexical) memory, the importance of the input set in episodic memory, and the ubiquitous calculation of an intersection in theories of episodic and lexical access. (shrink)

This study assessed whether real-life stimulus material can elicit conscious and unconscious priming. A typical masked priming paradigm was used, with brand logo primes. We used a rigorous method to assess participants’ awareness of the subliminal information. Our results show that shortly presented and masked brand logos have the power to prime their brand names and, remarkably, words associated to the brand . However, this only occurred when the logos could be categorized clearly above the consciousness threshold. Once the primes (...) were presented close to the consciousness threshold, no subliminal influences on behavior were observed. (shrink)

Correspondences and similarities between ideas in shamanism and ideas in contemporary cognitive science are considered. The importance of interconnectedness in the web of life worldview characteristic of shamanism and in connectionist models of semantic memory in cognitive science, and the extension of meaning to elements of the natural world in shamanism and indistributed cognition, are considered. Cognitive consequences of such an extension (e.g., use of representativeness and intentional stance heuristics, magical thinking, social attribution errors, and social in‐group/out‐group differences) are discussed. (...) It is suggested that attributions of mental states, beliefs, and desires to a computer on the basis of behavioral measures (e.g., the Turing test) is consistent with the extension of meaning and intentionality to nonhuman elements of the natural world in shamanism. In general, the existence of such correspondencesand similarities suggests that elements of shamanism may reflect cognitive structures and processes that are also used by nonshamans and in nonshamanic settings. (shrink)

This paper reports a psychological study of human categorization that looked at the procedures used by expert scientists when dealing with puzzling items. Five professional botanists were asked to specify a category from a set of positive and negative instances. The target category in the study was defined by a feature that was unusual, hence situations of uncertainty and puzzlement were generated. Subjects were asked to think aloud while solving the tasks, and their verbal reports were analyzed. A number of (...) problem solving strategies were identified, and subsequently integrated in a model of knowledge‐guided inductive categorization. Our model proposes that expert knowledge influences the subjects' reasoning in more complex ways than suggested by earlier investigations of scientific reasoning. As in previous studies, domain knowledge influenced our subjects' hypothesis generation and testing; but, additionally, it played a central role when subjects revised their hypotheses. (shrink)

Question processing involves parsing, memory retrieval, question categorization, initiation of appropriate answer‐retrieval heuristics, answer formulation, and output. Computational and psychological models have traditionally treated these processes as separate, sequential, independent, and in pursuit of a single answer type at a time. Here this view is challenged and the implications of a theory in which question processes operate simultaneously on multiple question interpretations are explored. A highly interactive model is described in which an expectation‐driven parser generates multiple question candidates, including partially‐specified (...) candidates. Question candidates act as constraints for a matcher which activates memory items. An answer retrieval process examines question candidates and the active portions of memory in an attempt to generate answer candidates. Answer candidates are examined by an output process that derives the final answer. These processes run simultaneously and interact. Three experiments on human question answering are also described which provide evidence that working memory load during question reading is affected by processes related to answer retrieval. (shrink)

Our response to this symposium on our 2006 paper centers on three questions. First, what motivations exist in the political wild, and do our experimental manipulations realistically capture them? We agree that strong accuracy motivations are likely (but not certain) to reduce biases, but we are not at all confident that the real world supplies stronger accuracy motivations than our subjects received. Second, how can we square our findings of stubbornly persistent beliefs and attitudes with the well-established literatures on framing (...) and persuasion, which find political opinion to be more malleable? We argue that our John Q. Public theory of political information accounts for both persistence and persuasion and explains when we should expect one or the other. Citizens will be more responsive to contextual information or persuasive appeals when prior feelings are weak, knowledge is sparse, and information is encountered outside of awareness. Resistance to information or arguments is most likely when prior feelings are strong, attitudes are embedded within dense knowledge networks, and appeals are consciously perceived. Third, is belief persistence driven by feelings and emotions, as we claim, or is it more the result of a conviction that one's priors are accurate? We suggest that the distinctions that stand behind this question are suspect. We see in some of our commentators a tendency to align accuracy motivation, central processing, and cognition on one side of the dual-processing framework, with directional motivation, peripheral processing, and feelings on the other side. On the contrary, we argue that beliefs in the truth of one's priors often result from feelings and wishes and are themselves sources of motivated bias in processing new information. Moreover, directional motivations are also often a source of central processing, so it is not easy to disentangle these processes. (shrink)

Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...) the representation of complex concepts. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

We advance a model of human probability judgment and apply it to the design of an extrapolation algorithm. Such an algorithm examines a person's judgment about the likelihood of various statements and is then able to predict the same person's judgments about new statements. The algorithm is tested against judgments produced by thirty undergraduates asked to assign probabilities to statements about mammals.

Contextual vocabulary acquisition (CVA) is the deliberate acquisition of a meaning for a word in a text by reasoning from context, where “context” includes: (1) the reader’s “internalization” of the surrounding text, i.e., the reader’s “mental model” of the word’s “textual context” (hereafter, “co-text” [3]) integrated with (2) the reader’s prior knowledge (PK), but it excludes (3) external sources such as dictionaries or people. CVA is what you do when you come across an unfamiliar word in your reading, realize that (...) you don’t know what it means, decide that you need to know what it means in order to understand the passage, but there is no one around to ask, and it is not in the dictionary (or you are too lazy to look it up). In such a case, you can try to figure out its meaning “from context”, i.e., from clues in the co-text together with your prior knowledge. Our computational theory of CVA—implemented in a the SNePS knowledge representation and reasoning system [28]—begins with a stored knowledge base containing SNePS representations of relevant PK, inputs SNePS representations of a passage containing an unfamiliar word, and draws inferences from these two (integrated) information sources. When asked to define the word, definition algorithms deductively search the resulting network for information of the sort that might be found in a dictionary definition, outputting a definition frame whose slots are the kinds of features that a definition might contain (e.g., class membership, properties, actions, spatio-temporal information, etc.) and whose slot-fillers contain information gleaned from the network [6–8,20,23,24]. We are investigating ways to make our system more robust, to embed it in a naturallanguage-processing system, and to incorporate morphological information. Our research group, including reading educators, is also applying our methods to the develop-. (shrink)

Measures and theories of information abound, but there are few formalised methods for treating the contextuality that can manifest in different information systems. Quantum theory provides one possible formalism for treating information in context. This paper introduces a quantum inspired model of the human mental lexicon. This model is currently being experimentally investigated and we present a preliminary set of pilot data suggesting that concept combinations can indeed behave non-separably.

Using a cross-modal semantic priming paradigm, both experiments of the present study investigated the link between the mental representations of iconic gestures and words. Two groups of the participants performed a primed lexical decision task where they had to discriminate between visually presented words and nonwords (e.g., flirp). Word targets (e.g., bird) were preceded by video clips depicting either semantically related (e.g., pair of hands flapping) or semantically unrelated (e.g., drawing a square with both hands) gestures. The duration of gestures (...) was on average 3,500 ms in Experiment 1 but only 1,000 ms in Experiment 2. Significant priming effects were observed in both experiments, with faster response latencies for related gesture–word pairs than unrelated pairs. These results are consistent with the idea of interactions between the gestural and lexical representational systems, such that mere exposure to iconic gestures facilitates the recognition of semantically related words. (shrink)