Abstract
Much recent work on natural information has focused on probabilistic theories, which construe natural information as a matter of probabilistic relations between events or states. This paper assesses three variants of probabilistic theories (due to Millikan, Shea, and Scarantino and Piccinini). I distinguish between probabilistic theories as (1) attempts to reveal why probabilistic relations are important for human and non-human animals and as (2) explications of the information concept(s) employed in the sciences. I argue that the strength of probabilistic theories lies in the first project. Probability-raising can enable organisms to draw specific inferences they otherwise could not entertain and I show how exactly they help to explain the behaviour of organisms. In addition, probability-raising warrants inferences by providing incremental inductive support.
Original language | English |
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Pages (from-to) | 869-893 |
Number of pages | 25 |
Journal | Erkenntnis |
Volume | 80 |
Issue number | 4 |
Early online date | 19 Sept 2014 |
DOIs | |
Publication status | Published - Aug 2015 |
Bibliographical note
AcknowledgementsAndrea Scarantino, Nicholas Shea, Mark Sprevak, and three anonymous referees provided incisive and constructive comments, for which I am very grateful. In 2012, earlier versions of this paper were delivered in Edinburgh, at the Joint Session in Stirling, and at a workshop on natural information in Aberdeen. I thank participants for their feedback.
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Ulrich Stegmann
- School of Divinity, History & Philosophy, Philosophy - Reader
- School of Divinity, History & Philosophy, Centre for Knowledge and Society (CEKAS)
- School of Divinity, History & Philosophy, George Washington Wilson Centre for Art and Visual Culture
- School of Divinity, History & Philosophy, Centre for the History and Philosophy of Science, Technology and Medicine (CHPSTM)
Person: Academic