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Michael Poznic
Universität Karlsruhe
  1.  95
    Machine Learning and the Future of Scientific Explanation.Florian J. Boge & Michael Poznic - 2021 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 52 (1):171-176.
    The workshop “Machine Learning: Prediction Without Explanation?” brought together philosophers of science and scholars from various fields who study and employ Machine Learning (ML) techniques, in order to discuss the changing face of science in the light of ML's constantly growing use. One major focus of the workshop was on the impact of ML on the concept and value of scientific explanation. One may speculate whether ML’s increased use in science exemplifies a paradigmatic turn towards mere pattern recognition and prediction (...)
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  2.  58
    Representation and Similarity: Suárez on Necessary and Sufficient Conditions of Scientific Representation.Michael Poznic - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (2):331-347.
    The notion of scientific representation plays a central role in current debates on modeling in the sciences. One or maybe the major epistemic virtue of successful models is their capacity to adequately represent specific phenomena or target systems. According to similarity views of scientific representation, models should be similar to their corresponding targets in order to represent them. In this paper, Suárez’s arguments against similarity views of representation will be scrutinized. The upshot is that the intuition that scientific representation involves (...)
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  3.  51
    Thin versus thick accounts of scientific representation.Michael Poznic - 2018 - Synthese 195 (8):3433-3451.
    This paper proposes a novel distinction between accounts of scientific representation: it distinguishes thin accounts from thick accounts. Thin accounts focus on the descriptive aspect of representation whereas thick accounts acknowledge the evaluative aspect of representation. Thin accounts focus on the question of what a representation as such is. Thick accounts start from the question of what an adequate representation is. In this paper, I give two arguments in favor of a thick account, the Argument of the Epistemic Aims of (...)
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  4.  39
    Modeling Organs with Organs on Chips: Scientific Representation and Engineering Design as Modeling Relations.Michael Poznic - 2016 - Philosophy and Technology 29 (4):357-371.
    On the basis of a case study in bioengineering, this paper proposes a novel perspective on models in science and engineering. This is done with the help of two notions: representation and design. These two notions are interpreted as referring to modeling relations between vehicles and targets that differ in their respective directions of fit. The representation relation has a vehicle-to-target direction of fit and the design relation has a target-to-vehicle direction of fit. The case study of an organ on (...)
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  5.  50
    Make-Believe and Model-Based Representation in Science: The Epistemology of Frigg’s and Toon’s Fictionalist Views of Modeling.Michael Poznic - 2016 - Teorema: International Journal of Philosophy 35 (3):201-218.
    Roman Frigg and Adam Toon, both, defend a fictionalist view of scientific modeling. One fundamental thesis of their view is that scientists are participating in games of make-believe when they study models in order to learn about the models themselves and about target systems represented by the models. In this paper, the epistemology of these two fictionalist views is critically discussed. I will argue that both views can give an explanation of how scientists learn about models they are studying. However, (...)
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  6.  40
    Scenarios as Tools of the Scientific Imagination: The Case of Climate Projections.Michael Poznic & Rafaela Hillerbrand - 2021 - Perspectives on Science 29 (1):36-61.
    Climatologists have recently introduced a distinction between projections as scenario-based model results on the one hand and predictions on the other hand. The interpretation and usage of both terms is, however, not univocal. It is stated that the ambiguities of the interpretations may cause problems in the communication of climate science within the scientific community and to the public realm. This paper suggests an account of scenarios as props in games of make-belive. With this account, we explain the difference between (...)
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  7.  7
    Tugendethik.Rafaela Hillerbrand & Michael Poznic - 2013 - In Armin Grunwald (ed.), Handbuch Technikethik. Metzler. pp. 165-170.
    Bis in die Mitte des 20. Jahrhunderts war die philosophische Ethik neben Vertragstheorien geprägt von zwei ethischen Theoriefamilien: der deontologischen Ethik und dem Konsequentialismus, Letzter vor allem in Form des Utilitarismus. Diese beiden Ethiktheorien scheinen in vielerlei Hinsicht diametral entgegengesetzt zu sein, etwa wenn die moralische Korrektheit einer Handlung entweder an ihren Folgen oder in Übereinstimmung mit einem allgemeinen moralischen Gesetz bemessen wird. Dennoch sind es in beiden Theorien die Handlungen, die bewertet werden.
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  8. Designing as playing games of make-believe.Michael Poznic, Martin Stacey, Rafaela Hillerbrand & Claudia Eckert - 2020 - Design Science 6:e10.
    Designing complex products involves working with uncertainties as the product, the requirements and the environment in which it is used co-evolve, and designers and external stakeholders make decisions that affect the evolving design. Rather than being held back by uncertainty, designers work, cooperate and communicate with each other notwithstanding these uncertainties by making assumptions to carry out their own tasks. To explain this, the paper proposes an adaptation of Kendall Walton’s make-believe theory to conceptualise designing as playing games of make-believe (...)
     
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  9. Models in Engineering and Design: Modeling Relations and Directions of Fit.Michael Poznic - 2021 - In Diane Michelfelder & Neelke Doorn (eds.), Routledge Handbook of Philosophy of Engineering. Taylor & Francis Ltd. pp. 383-393.
    This chapter distinguishes two different modeling relations between vehicles and targets: design relation and representation relation. The relations are characterized by their different directions of fit. Three examples of modeling enterprises are discussed: a bioengineering model, called the “lung chip,” an architectural model, called the “weekend cottage,” and an engineering design model, called the “jet engine.” The two modeling relations with different directions of fit are analyzed in the three examples. The lung chip is standing in a representation relation to (...)
     
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  10.  50
    Models in Science and Engineering: Imagining, Designing and Evaluating Representations.Michael Poznic - 2017 - Dissertation, Delft University of Technology
    The central question of this thesis is how one can learn about particular targets by using models of those targets. A widespread assumption is that models have to be representative models in order to foster knowledge about targets. Thus the thesis begins by examining the concept of representation from an epistemic point of view and supports an account of representation that does not distinguish between representation simpliciter and adequate representation. Representation, understood in the sense of a representative model, is regarded (...)
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