Reductive, naturalistic psychosemantic theories do not have a good track record when it comes to accommodating the representation of kinds. In this paper, I will suggest a particular teleosemantic strategy to solve this problem, grounded in the neurocomputational details of the cerebral cortex. It is a strategy with some parallels to one that Ruth Millikan has suggested, but to which insufficient attention has been paid. This lack of attention is perhaps due to a lack of appreciation for the severity of (...) the problem, so I begin by explaining why the situation is indeed a dire one. One of the main tasks for a naturalistic psychosemantic theory is to describe how the extensions of mental representations are determined. (Such a theory may also attempt to account for other aspects of the “meaning” of mental representations, if there are any.) Some mental representations, e.g. the concept of water, denote kinds (I shall be assuming this is non-negotiable). How is this possible? Unfortunately, I haven’t the space to canvass all the theories out there and show that each one fails to accommodate the representation of kinds, but I will point out the major types of problems that arise for the kinds of theories that, judging by the literature, are considered viable contenders.1 In general, the theories either attempt and fail to account for the representation of kinds, or they fall back on something like an intention to refer to a kind – not exactly the most auspicious move for a reductive theory. There are a number of problems that prevent non-teleosemantic theories from explaining how it is possible to represent kinds. A concept of a kind K must.. (shrink)

Certain philosophical arguments apparently show that the having of beliefs is tied conceptually to rationality. Such a view, however, seems at odds both with the possibility of irrational belief and with recent empirical discoveries in the psychology of reasoning. The aim of this paper is to move toward a reconciliation of these apparently conflicting perspectives by distinguishing between internalist and externalist conceptions of rationality. It is argued that elements of each are required for a satisfactory theory, one that allows for (...) the possibility of irrationality and makes sense of empirical findings without violating conditions on belief ascription. Normative theories, on this view, constrain the latter while remaining silent on the character of actual psychological mechanisms. (shrink)

This article addresses the question whether we can know on the basis of folk intuitions that we have character traits. I answer in the negative, arguing that on any of the primary theories of knowledge, our intuitions about traits do not amount to knowledge. For instance, because we would attribute traits to one another regardless of whether we actually possessed such metaphysically robust dispositions, Nozickian sensitivity theory disqualifies our intuitions about traits from being knowledge. Yet we do think we know (...) that we have traits, so I am advancing an error theory, which means that I owe an account of why we fall into error. Why do we feel so comfortable navigating the language of traits if we lack knowledge of them? To answer this question, I refer to a slew of heuristics and biases. Some, like the fundamental attribution error, the false consensus effect, and the power of construal, pertain directly to trait attributions. Others are more general cognitive heuristics and biases whose relevance to trait attributions requires explanation and can be classed under the headings of input heuristics and biases and processing heuristics and biases. Input heuristics and biases include selection bias, availability bias, availability cascade, and anchoring. Processing heuristics and biases include disregard of base rates, disregard of regression to the mean, and confirmation bias. (shrink)

In this paper, I will introduce you to a new theory of mental representation, emphasizing two important features. First, the theory coheres very well with folk psychology; better, I believe, than its competitors (e.g. Cummins, 1996; Dretske, 1988; Fodor, 1987 and Millikan, 1989, with which it has the most in common), though I will do little by way of direct comparison in this paper. Second, it receives support from current neuroscience. While other theories may be consistent with current neuroscience, none (...) that I know of actually receives some degree of confirmation from it. There are many different kinds of representations. Some examples are maps, words, meter and gauge readings, diagrams, pictures, scale models, computer simulations, blueprints, charts, musical notation, smoke signals, semaphore, and computer data structures. Qua representations, they all possess intentionality, or aboutness: maps are about places, most words are about the entities they refer to, meters and gauges are about the quantities they measure, etc. However, it seems they have little in common beyond this aboutness (Millikan, 1984, p. 85). Therefore we should be open to the possibility that the aboutness of different representations is ultimately to be explained in different ways. It is becoming increasingly popular to understand the aboutness of a large class of these representations in terms of function.1 For example, a tire gauge represents one of the properties that it indicates or carries information about, namely air pressure. However, it also carries information about other quantities. If the pressure and volume of the tire are kept constant, the tire gauge will indicate the temperature of the air inside the tire, and if the temperature and pressure are kept constant, the gauge will indicate the tire volume. However, although the tire gauge indicates these things, it does not represent them. It only.. (shrink)

"Blocking" refers to judgments of a moderate contingency being lowered when contrasted with a strong contingency. The Rescorla-Wagner model and causal model theory account for blocking through different mechanisms. To examine the predictions from these two models, seven experiments tested the extent to which "causal scenario" and "causal order" would influence whether blocking was observed in human contingency learning tasks. "Causal scenario" was manipulated by contrasting responses to two causes of one effect or to one cause of two effects; "causal (...) order" was defined as causes preceding effects or effects preceding causes. The four conjunctions of these two factors were investigated separately in Experiments 1 to 5. In Experiments 1 and 2, two causes preceded one effect and two effects preceded one cause, respectively. Blocking was observed regardless of whether the predictors were causes or effects. In Experiments 3, 4 and 5, participants were presented with one antecedent cue and made separate predictions about each of the trial's two outcomes. Blocking was not observed, irrespective of whether the antecedent cue was a cause or an effect. These initial results were consistent with the Rescorla-Wagner model. An alternative explanation was that blocking failed to occur in Experiments 3 to 5 because participants were asked questions between the predictor and two outcomes. Predicting the outcomes might have implicitly led participants to monitor them separately and to report on subsets of the data at the time of judgment. To address this issue, the volunteers in Experiment 6 observed the events on each trial but did not make any predictions about the outcomes. Blocking was observed, signifying that the intervening questions between the antecedent and consequent cues constitute an important variable influencing cue competition effects. In Experiment 7, all four conjunctions of causal scenario and causal order were tested simultaneously. Furthermore, participants w. (shrink)