Machine Philosophy - A Foundation of Philosophical Methodology

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URI: http://hdl.handle.net/10900/118477
http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1184779
http://dx.doi.org/10.15496/publikation-59851
Dokumentart: Dissertation
Date: 2021-09-02
Language: English
Faculty: 5 Philosophische Fakultät
Department: Philosophie
Advisor: Sattig, Thomas (Prof. Dr.)
Day of Oral Examination: 2021-07-19
DDC Classifikation: 100 - Philosophy
Keywords: Philosophie , Metaphilosophie , Methodologie , Wissenschaft , Maschine
Other Keywords:
methodology
philosophy
metaphilosophy
science
machine learning
Carnap
Strawson
License: Publishing license including print on demand
Order a printed copy: Print-on-Demand
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Abstract:

This essay designs an evolved architecture for doing philosophy, which I call ‘machine philosophy’. I identify the core issues of current philosophical practice as an unhealthy mix of boolean argumentation, obsession with ordinary language, and a lack of methodological clarity. Machine philosophy entails that philosophical methodology should be continuous with that of the sciences. Specifically, philosophical theories are descriptive and objective, and the activity of philosophical theorising should be governed by the norms of statistical learning. In this regard, machine philosophy makes two core claims. One: intuitions are fallible evidence in philosophy, which reflect objective facts about our socio-linguistic realities. Two: philosophical theories are descriptive of our socio-linguistic realities in virtue of being statistically adequate models of our intuitions. This new architecture does not demand, but enables philosophical theorising to utilise formal, computational, machine learning mechanisms. However, unlike pluralistic proposals, this enabling of distinct mechanisms places a hierarchy on the epistemic quality of each method, measured by their ability to produce true descriptions.

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