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CATEGORIES:Departmental Seminars in History and Philosophy of
  Science
SUMMARY:Physical computations are idealisations - Mark Spr
 evak (University of Edinburgh)
DTSTART;TZID=Europe/London:20211118T153000
DTEND;TZID=Europe/London:20211118T170000
UID:TALK163135AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/163135
DESCRIPTION:"Register to attend in person":https://www.eventbr
 ite.co.uk/e/hps-departmental-seminar-tickets-19647
 6595787\n\nWhat does it mean when we say that the 
 brain implements a computation? In this paper\, I 
 build on recent work on idealisation to suggest th
 at we should re-think this question about computat
 ional implementation. First\, it is a mistake to a
 pproach the problem in the abstract\, by reflectin
 g on physical computation in a topic-neutral way. 
 It is essential to have an idea of why theorists a
 pply the notion in certain domains\, why they feel
  motivated to provide a specific computational mod
 el of a physical system\, and what benefits they r
 egard flow from doing so. Second\, an underappreci
 ated feature of computational descriptions is that
  they involve a major degree of abstraction and id
 ealisation. Normally\, only a handful of physical 
 properties of a target physical system feature in 
 a computational model and these are themselves ide
 alised in ways that depart from reality. The dynam
 ics of a select\, idealised group of properties ar
 e the fare of a computational model. I suggest tha
 t one should expect this rationale to be reflected
  in conditions of computational implementation. I 
 argue that this explains the appeal of rival\, inc
 ompatible theories of implementation among philoso
 phers: in the real world – and in particular\, in 
 cognitive neuroscience – implementation is often c
 onstrained in different ways for different ends.
LOCATION:Mill Lane Lecture Room 9 and Zoom
CONTACT:Richard Staley
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