The aim of this paper is to offer a formal criterion for physical computation that allows us to objectively distinguish between competing computational interpretations of a physical system. The criterion construes a computational interpretation as an ordered pair of functions mapping (1) states of a physical system to states of an abstract machine, and (2) inputs to this machine to interventions in this physical system. This interpretation must ensure that counterfactuals true of the abstract machine have appropriate counterparts which are (...) true of the physical system. The criterion proposes that rival interpretations be assessed on the basis of simplicity. Simplicity is construed as the Kolmogorov complexity of the interpretation. This approach is closely related to the notion of algorithmic information distance and draws on earlier work on real patterns. (shrink)

Daniel Dennett distinguishes real patterns from bogus patterns by appeal to compressibility. As information theorists have shown, data are compressible if and only if those data exhibit a pattern....

Dennett [1991] proposes a novel ontological account of the propositional attitudes—real patterns. Despite its name, the degree to which this account is committed to realism remains unclear. In this paper, I propose an alternative criterion of pattern instantiation, one that assesses the difficultly of faithfully interpreting a physical system as instantiating a particular pattern. Drawing on formal measures of simplicity and similarity, I argue that, for well-instantiated patterns, our interpretation will be computable by using a short program. This approach preserves (...) the flexibility of Dennett’s original, while offering substantially stronger realist commitments. (shrink)

Machery & Mallon [The moral psychology handbook (pp. 3–47). New York, NY: Oxford University Press, 2010] argue that existing evidence does not support the claim that moral cognition, understood as a specific form of normative cognition, is a product of evolution. Instead, they suggest that the evidence only supports the more modest claim that a general capacity for normative cognition evolved. They argue that if this is the case then the prospects for evolutionary debunking arguments are bleak. A debunking argument (...) which relied on the fact that normative cognition in general evolved might threaten all areas of normative belief, including the epistemic norms upon which the argument relies. For the sake of argument, we accept their claim that specifically moral cognition did not evolve. However, we reject their contention that this critically undermines evolutionary debunking arguments of morality. A number of strategies are available to solve what we call the “containment problem,” or how to effectively debunk morality without thereby debunking normative cognition tout court. Furthermore, debunking arguments need not rely on the claim that normative cognition in general evolved. So long as at least some aspects of moral cognition have evolved, this may be sufficient to support an evolutionary debunking argument against many of our moral beliefs. Thus, even if Machery & Mallon are right that specifically moral cognition did not evolve, research in evolutionary psychology may have radical implications for moral philosophy. (shrink)

What does it take to implement a computer? Answers to this question have often focused on what it takes for a physical system to implement an abstract machine. As Joslin observes, this approach neglects cases of software implementation—cases where one machine implements another by running a program. These cases, Joslin argues, highlight serious problems for mapping accounts of computer implementation—accounts that require a mapping between elements of a physical system and elements of an abstract machine. The source of these problems (...) is the complexity introduced by common design features of ordinary computers, features that would be relevant to any real-world software implementation. While Joslin is focused on contemporary views, his discussion also suggests a counterexample to recent mapping accounts which hold that genuine implementation requires simple mappings. In this paper, I begin by clarifying the nature of software implementation and disentangling it from closely related phenomena like emulation and simulation. Next, I argue that Joslin overstates the degree of complexity involved in his target cases and that these cases may actually give us reasons to favor simplicity-based criteria over relevant alternatives. Finally, I propose a novel problem for simplicity-based criteria and suggest a tentative solution. (shrink)