Objective Computation Versus Subjective Computation

Abstract

The question 'What is computation?' might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object (can be said to) computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that informationprocessing considerations determine what type of computation takes place in physical systems. Abstract. The question 'What is computation?' might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object (can be said to) computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that information-processing considerations determine what type of computation takes place in physical systems.

The Nature of Physical Computation

“…Hamkins, for example, writes that infinite-time Turing machines "provide a natural model of infinitary computability" and are "computing machines" (2002: 521); Cohen and Gold (1978) titled their paper "ω-Computations on Turing Machines, " Löwe (2001) entitled his "Revision Sequences and Computers with an Infinite Amount of Time, " and Koepke (2005) called his "Turing Computations on Ordinals. " Moreover, the claim that ITTM computes is consistent with most accounts of computation-including the semantic account (Shagrir 2006b;Sprevak 2010), the mechanistic account (Miłkowski 2013;Fresco 2014;Piccinini 2015), the causal account (Chalmers 2011), and the BCC (broad conception of computation) account (Copeland 1997).…”

“…(2015: 11) In my view, concerns about objectivity are overrated. There is no reason to impose very strong objectivity constraints on an account of physical computation (see also Fresco 2015). What is meant here by objectivity, or "a matter of fact"?…”

The neural correlates of consciousness under the free energy principle: From computational correlates to computational explanation

“…In other words, if a computational explanation focuses on abstract computational properties (disregarding how they are implemented in the system), then it must be complemented by an account of physical implementation, showing that the same computational properties cannot be instantiated by systems we would not regard as computational. There is, however, no consensus on whether any account of physical computation can avoid trivial implementations (Sprevak, 2019), nor on whether computational properties are intrinsic properties of physical systems (Dewhurst, 2018;Fresco, 2015).…”

On Two Different Kinds of Computational Indeterminacy

“…2 Section 2 discusses the two kinds of indeterminacy in detail and examines aspects of the relations between them and computational implementation. Section 3 explores the interrelationships between the two indeterminacies, computational individuation and levels of organization 1 Some examples of such names include 'simultaneous implementation' (Shagrir 2001, 2020, Fresco 2015, Dewhurst 2018, 'the ambiguity of representation' (Maroney and Timpson, 2018), 'indeterminacy of computation' (Fresco et al, 2021), 'underdetermination of computation' (Duwell, 2018), 'multiple-computations theorem' (Hemmo and Shenker, 2019), 'multiplicity of computations', and various others. 2 In doing so, we may be seen as adopting the point of view of a scientist who employs computational characterizations for her studied systems and who may or may not have a particular theory of implementation in mind.…”