Bridging Causal and Explanatory Reasoning: Normative and Empirical Consideration

• Applicant: Dr. Matteo Colombo
• Subject Area: Theoretical Philosophy
• Term: from 2011 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 201291989

In the first phase of the SPP, we explored how probabilistic information affects explanatory judgments, and investigated whether probability is a suitable overarching framework for inductive and explanatory-abductive reasoning. Now, we would like to extend these results and proceed to a systematic, comparative, investigation of causal and explanatory reasoning, broadly embedded into a probabilistic framework. Although there are several theories and models of how humans reason about causality, and of how causality should ground scientific explanation, there are several outstanding issues concerning the relationship between causal and explanatory reasoning. In particular, relatively little is known about: (i) the conditions under which causal considerations should inform assessments of explanatory value; (ii) the relationship between the quantitative dimensions of explanatory and causal reasoning; (iii) how explanatory and causal considerations can be unified, and how they can be applied to important philosophical problems like the learning of conditional information. Our project aims to address exactly these three sets of issues. We shall proceed in three steps. First, we shall revisit the relationship between causal and explanatory reasoning, hypothesizing that specific patterns of probabilistic cues are sufficient to warrant a causal understanding of an explanation, and that causality not always informs folks assessment of explanatory value. This step will proceed by surveying, analyzing, and testing experimentally differences between causal and explanatory judgments. Second, we shall examine how different measures of causal strength should be classified and evaluated, and how they relate to existing measures of explanatory power. Specifically, we shall develop a quantitative, probabilistic explication of causal strength, based on the interventionist account of causation, and relate it to the notion of explanatory power. Third, we shall ask the general question: Can causal and explanatory reasoning be unified in a Bayesian framework, or should they be regarded as independent modes of inference? As a way to begin address this general question, we focus on the learning of conditional information. We conjecture that learning of conditional information depends on specific causal and explanatory relations between the relevant propositions. In the light of the case of learning of conditional information and of the results from the first two steps of our project, we shall put forward a formally-sound and empirically-informed account of how causal and explanatory reasoning should be bridged. We expect that the results of our project will contribute to the overall goals of the SPP1516 New Frameworks of Rationality priority program not only by making disagreements about different accounts of explanatory value more tractable, but also by helping us make a significant step toward a better understanding of the rational dimensions of explanation.

• DFG Programme: Priority Programmes
• Subproject of: SPP 1516: New Frameworks of Rationality
• International Connection: Netherlands
• Participating Person: Professor Dr. Jan Michael Sprenger