Abstract
Computational explanations in the cognitive sciences span multiple levels of analysis. The indeterminacy of computation complicates the endeavour of answering the question ‘What does a particular neural—or physical—system do?’ in computational terms. A single physical process may often be described equally well as computing several different mathematical functions—none of which is explanatorily privileged. But at which level of analysis is the computational identity of a physical system P fixed? Some argue that the computational identity of P is wholly exhausted by P’s functional or narrow physical structure. Others argue that contextual factors also play a role in determining P’s computational identity, but they diverge on what that role is precisely. Yet others argue that contextual factors essentially determine the identity of P. This chapter surveys some of these views and ultimately claims that the environment can and often does play an important role in fixing the computational identity of P, thereby proposing a new, long-arm functional strategy for individuating computation.
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Notes
- 1.
Note, however, that the computational mechanist need not bite the bullet and pay this price (Fresco & Miłkowski, 2019).
- 2.
Some computational mechanists indeed deny that multiple realisability is an essential feature of physical computation. Miłkowski, for one, claims that “there are no facts of the matter that could easily establish that a given computational capacity is actually multiply realized” (2016, pp. 29–30). The computational mechanist faces a dilemma. Either computational explanations are functional, and, thus, cannot fully explain the structural aspects of mechanisms, or they provide full structural detail, but give up multiple realisability as an essential feature of computation (Haimovici, 2013, p. 178). Miłkowski, like Dewhurst, opts for the second horn of the dilemma.
- 3.
Suppose that ‘∼’ is a binary equivalence relation on A. Reflexivity means that for all a ∈A, a ∼ a. Symmetry means that for all a, b ∈A, if a ∼ b, then b ∼ a. And transitivity means that for all a, b, c ∈A, if a ∼ b and b ∼ c, then a ∼ c.
- 4.
A possible answer is that this individuative strategy somehow specifies the system’s algorithmic level. The “different functional profiles [of two computing systems] would [result a difference] in their capacity to carry out logical and mathematical functions” (Coelho Mollo, 2017, n. 20) (3495, fn 20). Evaluating this answer, though, exceeds the scope of this chapter.
- 5.
Piccinini also adds that the task individuation argument would not go through, if we rejected the assumption that explanatia and their explananda must be individuated by the same properties (2015, p. 40).
- 6.
It should be stressed here that Shagrir’s example of the tri-stable system exhibits a different kind of indeterminacy (resulting from how different microstates are grouped together) from the one discussed in relation to gates G, G*, and H above (resulting from how state types are labelled). An analysis of the relation and difference between these two kinds of indeterminacy exceeds the scope of this chapter and is undertaken elsewhere (Papayannopoulos et al., 2022).
- 7.
Piccinini (2020, pp. 153–154) asserts that such cases of indeterminacy are addressed differently in natural and artificial computing systems. In the case of natural systems, we should identify (a) the capacity of interest, (b) the structures that fulfill that capacity, and (c) the specific organisation that enables those structures to fulfill the capacity. However, the tri-stable system described by Table 6.4 is an artificial one, and, thus, we “define the correct equivalence classes between [its] microstates as we please” (ibid). The specific mathematical function that is computed by that system depends, then, on a choice made by the engineer who designed and built the system.
- 8.
Coelho Mollo would similarly argue that the functional decomposition of the computing system depends on a capacity of interest, and this capacity may often be determined in part by the context in which it is embedded.
- 9.
An exclusive disjunction (XOR) interpretation under these circumstances is implausible. For it entails that when the organism is hungry and sees food, it does not reach out to grab it.
- 10.
Despite possible minute differences between S in the golden hamster and in the hopping mouse, what matters here are the input-output relations and the connectivity between S and the relevant upstream/downstream subsystems. Thus, even if to qualify as a “positive” input to S, the orexin threshold is slightly higher, say, in the mouse (as compared to the hamster), this difference is not functionally important. Such differences may manifest even between different mice of the same species. For similar reasons, we do not doubt that the hypothalamus as a neuroendocrine organ exists in both the hamster and the mouse despite any physical differences between them.
- 11.
It is probably for that reason, that vets often recommend to make home-grown hamsters work hard for their meals and hide food pellets or seeds inside paper bags or cardboard tubes.
- 12.
A seed-like object with similar surface properties of a seed may be further discriminated by the rodent’s main olfactory system, which influences its foraging behaviour and food preferences.
- 13.
Dewhurst indeed raises this objection against Piccinini’s short-arm mechanistic strategy. He claims that it is not clear how Piccinini’s strategy avoids the risk of being equated with a semantic theory of computation. For “once we have teleological functions we are not far from having a full-blown teleosemantic theory of representation” (Dewhurst, 2016, p. 796). Coelho Mollo’s individuative strategy—discussed in Sect. 6.2.2—similarly appeals to teleological function, but denies even narrow content, such as logical properties.
- 14.
For Millikan, a representation simply requires that the organism (or a consumer subsystem) can fulfil its task normally when the producer (such as S in the case of our rodents) goes into a state that correlates with a given environmental condition (e.g., the existence of seeds in the proximal environment).
- 15.
This interesting objection was suggested by Marcin Miłkowski.
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Fresco, N. (2022). How Context Can Determine the Identity of Physical Computation. In: Ioannidis, S., Vishne, G., Hemmo, M., Shenker, O. (eds) Levels of Reality in Science and Philosophy. Jerusalem Studies in Philosophy and History of Science. Springer, Cham. https://doi.org/10.1007/978-3-030-99425-9_6
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