October 2016 Lunchtime Abstracts & Details

Simplicity and Unification in Cosmological Model Selection
Yann Benetreau-Dupin, Postdoc Fellow
University of Western Ontario
Tuesday, October 4, 2016
12:05 pm, 817R Cathedral of Learning

Abstract:  The criteria for model selection commonly used in cosmology tend to focus on optimizing the number of free parameters, so as to avoid overfitting. This is often justified by appealing to a sense of simplicity or ontological parsimony. I claim that, strictly speaking, it is not simplicity that these model selection criteria are after. Moreover, I show that statistical model selection methods in general are particularly problematic in cosmology due to the limited theoretical background and possibility for experimentation. I explore whether a Bayesian criterion of unification can be better suited to some probabilistic inferences in cosmology.

Science and Moral Imagination: Towards a New Ideal for Values in Science
Matthew Brown, Visiting Fellow
University of California, San Diego
Dept. of Logic and Philosophy of Science
Friday, October 7, 2016
12:05 pm, 817R Cathedral of Learning

Abstract:  The values in science debate has shifted ground, from arguments for and against the ideal of value-free science, to detailed arguments about normative guidance for value-laden science. For the most part, accounts that seek to replace the value-free ideal emphasize rules aimed at upholding the epistemic integrity and social responsibility of science. These accounts generally demand compliance with set rules or principles. While these are important desiderata for an ideal for values in science, I provide an alternative that emphasizes the positive aspects of the interaction of science and values, and provides primarily prospective guidance for scientists making ethically-loaded decisions *in situ*. According to the ideal of moral imagination, scientists should be encouraged to recognize decision-points in their research, creatively explore possible choices, empathetically recognize potential stakeholders, discover morally salient aspects and consequences of their decisions, and make decisions that harmonize across ethical and epistemic considerations as far as possible. This approach joins recent work in practical ethics that emphasizes ethical perception, insight, creativity, and bottom-up problem-solving over top-down compliance, and so avoids the problems with compliance-oriented accounts.

Mechanisms, Explanation, and Prediction
Viorel Pâslaru, Visiting Fellow
University of Dayton
Tuesday, October 11, 2016
12:05 pm, 817R Cathedral of Learning

Abstract: New mechanistic philosophy and recent proposals to augment qualitative descriptions of mechanisms with quantitative models based on the formal framework of causal graph theory have not examined in detail the role of mechanisms in formulating predictions. A common thesis that can be found in these approaches is that adequate descriptions of mechanisms can be used to make both explanations and predictions. I scrutinize this thesis and show that to formulate predictions based on mechanisms, qualitative descriptions of mechanisms and quantitative models must be accompanied by additional knowledge about the functioning of the mechanism, external influences, and its dynamics. I use cases from ecology to exemplify the additional knowledge required for mechanistic prediction and to shed light on its limits. In view of the foregoing examination of prediction based on descriptions of mechanisms I argue for reconsidering Hempel’s symmetry thesis.

Pragmatism about Causation and Chance
Alison Fernandes, Postdoc Fellow
Columbia University
Friday, October 14, 2016
12:05 pm, 817R Cathedral of Learning

Abstract:  Causation doesn’t fit easily into a scientific picture of the world. Fundamental physics makes no reference to causes, and seems radically at odds with the very idea of causation. Its laws don’t reflect causation’s temporal asymmetry, and don’t relate individual states. But we can explain causation’s place by relating it to deliberation. According to a ‘deliberative account’, causal relations correspond to the evidential relations we use when we decide on one thing in order to achieve another. Tamsin’s taking her umbrella, for example, counts as a cause of her staying dry if and only if her deciding to take her umbrella is grounds for thinking she’ll stay dry. Causal asymmetry can then be derived from temporally symmetric laws and features of deliberation. This approach demonstrates a broad pragmatist strategy for making sense of scientific relations: use agential standards to pick out objective relations, explain their temporal features, and reconcile them with fundamental physics. I’ll briefly consider how the strategy can be applied to chance.

Intuition and Visualization in Mathematics with Particular Reference to Felix Klein
Daniele Muttini, Visiting Fellow
University of Bologna
Tuesday, October 18, 2016
12:05 pm, 817R Cathedral of Learning

Abstract:  Because the idea of the “unreliability of intuition” was common in philosophy and mathematics in the late 19th century, as well as throughout much of the 20th century, research in the past few decades has aimed at rediscovering the role of intuition and visual thinking in mathematical practice.  The purpose of my work is thus to take part in the contemporary debate taking into account the “historical case” of Felix Klein.  The main part of my analysis aims to clarify the different meanings of the term “intuition” that Klein used in his works, in order to give a representative account of his epistemological view.  I demonstrate how his reflections provided a vision of the role of an intuitive approach to mathematics, one which, surprisingly, is reflected in some of the contemporary research being carried out in psychology and neuroscience, as well as providing arguments to effectively support the role of intuition in mathematics.

Explanatory Asymmetry and Inferential Practice
Kareem Khalifa, Visiting Fellow
Emory University
Tuesday, October 25, 2016
12:05 pm, 817R Cathedral of Learning

Abstract:  In this paper, I motivate and present a new account of explanation. Its guiding idea is that explanation is an inferential practice. While some have argued that explanations are inferences, and others have argued that explanations are practices, my view provides a unique combination of the two. Arguably, the most significant challenge to both inferential and pragmatic accounts of explanation is the problem of asymmetry. In short, both inferential and pragmatic approaches to explanation fail to capture the idea that, in general, if A explains B, then B does not explain A. I review how this problem has plagued my predecessors, while showing that my view readily solves this problem.