New publications

[Anna Michalska]

Dear EENPS members,

The 32nd round of our newsletter is available under the link and also pasted below.

Best wishes,

Anna Martin

(Member of the Steering Committee)

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Kubiak, A.P., Warsaw University of Technology

“Perspectival Realism and Frequentist Statistics: The Case of Jerzy Neyman’s Methodology and Philosophy.” (2025), Synthese 205,13 

https://link.springer.com/article/10.1007/s11229-024-04842-2 

Abstract In this article I investigate the extent to which perspectival realism (PR) agrees with frequentist statistical methodology and philosophy, with an emphasis on J. Neyman’s frequentist statistical methods and philosophy. PR is clarified in the context of frequentist statistics. Based on the example of the stopping rule problem, PR is shown to be able to naturally be associated with frequentist statistics in general. I show that there are explicit and implicit aspects of Neyman’s methods and philosophy that are incompatible and both partially agree and disagree with PR. Additionally, I provide clarifications and interpretations to make Neyman’s methods and philosophy more coherent with the realist aspect of PR. Furthermore, I deliver an argument that, based on Neyman’s methods and philosophy, one is dealing with genuine and non-trivial perspectives. I argue that, despite Neyman being a normative anti-pluralist, there are some elements of perspectival pluralism present in his methods and philosophy. In conclusion, firstly, due to their ambivalence, Neyman’s conceptions align more closely with PR than with alternative, less moderate stances. Secondly, from the perspective of the statistical approach analysed, PR should be treated as a descriptive rather than a normative position, and as case (or aspect)-dependent, rather than a universal, absolute, or binding stance.

Greif, H., Kubiak, A.P., Stacewicz, P., Warsaw University of Technology

“Selection, growth and form. Turing’s two biological paths towards intelligent machinery.” (2024) Studies in History and Philosophy of Science 106, pp. 126-135.

https://doi.org/10.1016/j.shpsa.2024.05.017

Abstract We inquire into the role of Turing’s biological thought in the development of his concept of intelligent machinery. We trace the possible relations between his proto-connectionist notion of ‘organising’ machines in Turing (1948) on the one hand and his mathematical theory of morphogenesis in developmental biology (1952) on the other. These works were concerned with distinct fields of inquiry and followed distinct paradigms of biological theory, respectively postulating analogues of Darwinian selection in learning and mathematical laws of form in organic pattern formation. Still, these strands of Turing’s work are related, first, in terms of being amenable in principle to his (1936) computational method of modelling. Second, they are connected by Turing’s scattered speculations about the possible bearing of learning processes on the anatomy of the brain. We argue that these two theories form an unequal couple that, from different angles and in partial fashion, point towards cognition as a biological and embodied phenomenon while, for reasons inherent to Turing’s computational approach to modelling, not being capable of directly addressing it as such. We explore ways in which these two distinct-but-related theories could be more explicitly and systematically connected, using von Neumann’s contemporaneous and related work on Cellular Automata and more recent biomimetic approaches as a foil. We conclude that the nature of ‘initiative’ and the mode of material realisation are the key issues that decide on the possibility of intelligent machinery in Turing.