PhilSci Archive

Epistemology and Anomaly Detection in Astrobiology

Kinney, David and Kempes, Christopher (2022) Epistemology and Anomaly Detection in Astrobiology. [Preprint]

This is the latest version of this item.

[img]
Preview
Text
Epistemology_and_Anomaly_Detection_in_Astrobiology - PhilSci Archive.pdf

Download (1MB) | Preview

Abstract

We examine the epistemological foundations of a leading technique in the search for evidence of life on exosolar planets. Specifically, we consider the ``transit method'' for spectroscopic analysis of exoplanet atmospheres, and the practice of treating anomalous chemical compositions of the atmospheres of exosolar planets as indicators of the potential presence of life. We propose a methodology for ranking the anomalousness of atmospheres that uses the mathematical apparatus of support vector machines, and which aims to be agnostic with respect to the particular chemical biosignatures of life. We argue that our approach is justified by an appeal to the "hinge" model of epistemic justification first proposed by Wittgenstein (1969). We then compare our approach to previous work due to Walker et al. (2018) and Cleland (2019a, 2019b).


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Kinney, Daviddavid.kinney@princeton.edu
Kempes, Christopherckempes@santafe.edu
Keywords: astrobiology, anomaly detection, hinge epistemology, bayesianism
Subjects: Specific Sciences > Biology
Specific Sciences > Complex Systems
Specific Sciences > Probability/Statistics
General Issues > Theory Change
Depositing User: Dr David Kinney
Date Deposited: 24 Jun 2022 19:56
Last Modified: 24 Jun 2022 19:56
Item ID: 20795
Subjects: Specific Sciences > Biology
Specific Sciences > Complex Systems
Specific Sciences > Probability/Statistics
General Issues > Theory Change
Date: 12 May 2022
URI: http://philsci-archive.pitt.edu/id/eprint/20795

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item