[hist-analytic] Supervenience and Neutral Monism
Jlsperanza at aol.com
Jlsperanza at aol.com
Tue Oct 11 10:23:43 EDT 2011
In a message dated 10/11/2011 10:15:23 A.M. Eastern Daylight Time,
Baynesr at comcast.net writes:
I have been thinking about something no body appears to have been thinking
about so far: supervenience in a neutral monist ontology. If anyone knows
of anything on this, please let me know (on or off list). If no one has
discussed this, I will. I have some thoughts here related to "cross
classification." (kim in Mind in a Physical World, MIT, 1998, p.68-69
--- I was recently led to this link which may be of interest. Below.
----*I'm NOT claiming this below is the latest thing on things, but it _is_
recent, and as such often linked.
Joshua T. Vogelstein,R. Jacob Vogelstein & Carey E. Priebe write:
"Questions and assumptions about mind-brain supervenience go back at least
as far as Plato's dialogues circa 400 BCE1. While there are many different
notions of supervenience, we find Davidson's canonical description
[mind-brain] supervenience might be taken to mean that there cannot be two
events alike in all physical respects but differing in some mental respect,
or that an object cannot alter in some mental respect without altering in
some physical respect.
Colloquially, supervenience means “there cannot be a mind-difference
without a physical-difference.” This philosophical conjecture has potentially
widespread implications. For example, neural network theory and artificial
intelligence often implicitly assume a local version mind-brain
supervenience3, 4. Cognitive neuroscience similarly seems to operate under such
assumptions5. Philosophers continue to debate and refine notions of supervenience6.
Yet, to date, relatively scant attention has been paid to what might be
empirically learned about supervenience.
In this work we attempt to bridge the gap between philosophical conjecture
and empirical investigations by casting supervenience in a probabilistic
framework amenable to hypothesis testing. We then use the probabilistic
theory of pattern recognition to determine the limits of what one can and cannot
learn about supervenience through data analysis. The implications of this
work are varied. It provides a probabilistic framework for converting
philosophical conjectures into statistical hypotheses that are amenable to
experimental investigation, which allows the philosopher to gain empirical
support for her rational arguments. This leads to the construction of the first
explicit proof (to our knowledge) of a universally consistent classifier on
graphs, and the first demonstration of the tractability of answering
supervenience questions. Supervenience therefore seems to perhaps be a useful
but under-utilized concept for neuroscientific investigations. This work
should provide further motivation for cross-disciplinary efforts across three
fields—philosophy, statistics, and neuroscience—with shared goals but
mostly disjoint jargon and methods of analysis."
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