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::: center home >> events >> annual lecture series >> lectures 2012-13 |
53rd annual lecture series, 2012-13
Abstract: The philosophical literature on modeling tends to focus on modeling in the context of established theory. My talk will address how models are constructed and used in discovery processes. My analysis draws from twelve years of empirical research on modeling practices in pioneering bioengineering sciences research laboratories, where biological research is conducted in the context of application. An interesting feature of research in these domains is that because ethical issues or control considerations rule out the possibility of experimenting on the target phenomena, a major creative strategy involves researchers building physical and computational simulation models to serve as analogical source domains for target problems. The standard notion of analogy assumes a source domain from which one retrieves a ready-to-hand solution that can serve as the basis of inference. However, in these (and many other) areas of creative research, the base representation itself needs to be constructed. Information from a source domain is not mapped directly to the target problem; rather, constraints drawn from both domains are used for constructing intermediary hybrid models, which possess their own model constraints. The problem solver thinks and reasons through these intermediary models. After illustrating how this occurs though a case example, I consider implications of this practice for the philosophy of science more broadly. Why Children Actually Might be Better Scientists than Scientists Are Abstract: Over the past 10 years a large and productive research program uniting philosophy and developmental psychology has explored whether children’s learning can be understood as the construction and testing of probabilistic models. A large body of evidence shows that children can use statistical evidence to choose accurately among alternative hypotheses. However, this work raises the question of how this can be done at the algorithmic level. It also raises the question of whether there are developmental changes in the ways that this learning takes place. I will report several empirical studies from our lab suggesting that children may be using an algorithmic process of hypothesis sampling, similar to sampling techniques in machine learning. I will also suggest that children may be performing “higher-temperature” searches than adults do, and will report on studies showing that four-year-olds are actually better at learning low-probability hypotheses than adults are. In the Beginning There was Information? Abstract: New co-evolutionary models of sign production and use have consequences for a range of philosophical questions about information, representation, and belief. Causation: Interactions Between Philosophical Theories and Empirical Research Abstract: This talk will explore some of the interactions, actual and potential, between theoretical/philosophical/normative/ computational theorizing (hereafter “theoretical” work) about causal learning and judgment and experimental investigations of causal learning and judgment. My guiding idea is that work in each of these areas can inform the other. Theoretical work can help to suggest experiments (and also that certain experiments are not worth doing or should not be interpreted in the way that they commonly are.) More controversially, empirical work can sometimes help to motivate new theoretical ideas. I will provide illustrations from a variety of sources including some experimental work in which I have been involved concerning causal inferences in young children, experimental results concerning judgments about double prevention relations due to Tania Lombrozo and, time permitting, some experiments concerning subject’s preferred level of abstraction or explanation in causal judgment. I will try to show that causal cognition is a central and important aspect of human cognition that is worthy of scientific investigation in its own right and that this is a task to which both philosophers and behavioral scientists can contribute. What is Ontic Structural Realism? Abstract: What is, for Kant, a law of Nature? Abstract: In this paper I explore what Kant’s understanding of a law of nature is. I begin by reviewing Kant’s explicit statements about what a law is in general before describing an important challenge to the very idea of a law of nature that emerges from the conjunction of the natural law tradition and laws of nature in the early modern period. I then articulate how Kant can respond to that challenge in an interesting way by noting how he can draw on a univocal concept of law, one involving necessity and legislation, in articulating his accounts of laws of nature and the moral law. In this way, we not only come to a better appreciation of Kant’s views on the laws of nature, but also see more clearly some significant structural similarities between his theoretical and practical philosophies as a whole.
Abstract: In this talk, I explore whether certain constitutive equations of continuum
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