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Michael Strevens (NYU)

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NYUAD InstituteNYUAD InstituteThe Highly Effective Irrationality of ScienceModern science has done amazing things: creating covid vaccines, sending humans to the moon, finding the ultimate nature of light. What makes it so powerful—and so different from the attempts to understand nature made by the philosophers and monks of old? Vaulting from Aristotle to gravitational waves, Michael Strevens argues that much of science’s power derives from an epistemic limitation that can only be understood as irrational. The paradigmatic scientist is a paradigmatic reasoner in many ways, but in at least one way, their perfection as a scientist lies in the deliberate cultivation of a gaping intellectual blind spot...2024-05-1645 minNeoAcademiaNeoAcademia18. Imperial Empiricism w/ Michael StrevensOn this episode of NeoAcademia Michael and I discussed society’s perception of science and his book The Knowledge Machine. Michael is a professor of philosophy at NYU Micahel keeps pretty busy working on complex systems, probabilities, causation, and the philosophy of science, the sociology of science. Subscribe to the Newsletter for show notes, the Big Nerve link, and more. Video episode available here. 2023-10-051h 17Thing in itselfThing in itselfMichael Strevens on explanation and modern scientific knowledgeMichael Strevens is professor of philosophy at NYU working in the philosophy of science. His research interests include explanation, complex systems, probability, confirmation, and the social structure of science and its role in science’s success; the psychology of concepts; and the philosophical applications of cognitive science, including philosophical methodology.2022-10-061h 31MCMP – Philosophy of ScienceMCMP – Philosophy of ScienceIdealization, Prediction, Difference-MakingMichael Strevens (NYU) gives a talk at the 6th Munich-Sydney-Tilburg Conference on "Models and Decisions" (10-12 April, 2013) titled "Idealization, Prediction, Difference-Making". Abstract: Every model leaves out or distorts some factors that are causally connected to its target phenomena – the phenomena that it seeks to predict or explain. If we want to make predictions, and we want to base decisions on those predictions, what is it safe to omit or to simplify, and what ought a causal model to capture fully and correctly? A schematic answer: the factors that matter are those that make a difference to the target phenomena. There ar...2019-04-1941 minMCMP – Philosophy of ScienceMCMP – Philosophy of ScienceThe Mathematical Route to Causal UnderstandingMichael Strevens (NYU) gives a talk at the MCMP Colloquium (30 April, 2015) titled "The Mathematical Route to Causal Understanding". Abstract: Causal explanation is a matter of isolating the elements of the causal web that make a difference to the explanandum event or regularity (so I and others have argued). Causal understanding is a matter of grasping a causal explanation (so says what I have elsewhere called the "simple theory" of understanding). It follows that causal understanding is a matter of grasping the facts about difference-making, and in particular grasping the reasons why some properties of the web are difference-makers and some...2015-05-1147 minConcrete CausationConcrete CausationUnifying Causal and Non-Causal KnowledgeMichael Strevens (NYU) meets Roland Poellinger (MCMP/LMU) in a joint session on "Unifying Causal and Non-Causal Knowledge" at the MCMP workshop "Bridges 2014" (2 and 3 Sept, 2014, German House, New York City). The 2-day trans-continental meeting in mathematical philosophy focused on inter-theoretical relations thereby connecting form and content of this philosophical exchange. Idea and motivation: We use theories to explain, to predict and to instruct, to talk about our world and order the objects therein. Different theories deliberately emphasize different aspects of an object, purposefully utilize different formal methods, and necessarily confine their attention to a distinct field of interest. The desire...2014-10-2056 minMCMP – Philosophy of ScienceMCMP – Philosophy of ScienceUnifying Causal and Non-Causal KnowledgeMichael Strevens (NYU) meets Roland Poellinger (MCMP/LMU) in a joint session on "Unifying Causal and Non-Causal Knowledge" at the MCMP workshop "Bridges 2014" (2 and 3 Sept, 2014, German House, New York City). The 2-day trans-continental meeting in mathematical philosophy focused on inter-theoretical relations thereby connecting form and content of this philosophical exchange. Idea and motivation: We use theories to explain, to predict and to instruct, to talk about our world and order the objects therein. Different theories deliberately emphasize different aspects of an object, purposefully utilize different formal methods, and necessarily confine their attention to a distinct field of interest. The desire...2014-10-0656 min