There are two distinct approaches to Bayesian modelling in cognitive science. Black-box approaches use Bayesian theory to model the relationship between the inputs and outputs of a cognitive system without reference to the mediating causal processes; while mechanistic approaches make claims about the neural mechanisms which generate the outputs from the inputs. This paper concerns the relationship between these two approaches. We argue that the dominant trend in the philosophical literature, which characterizes the relationship between black-box and mechanistic approaches to (...) Bayesian cognitive science in terms of the dichotomy between instrumentalism and realism, is misguided. We propose that the two distinctions are orthogonal: black-box and mechanistic approaches to Bayesian modelling can each be given either an instrumentalist or a realist interpretation. We argue that the current tendency to conflate black-box approaches with instrumentalism and mechanistic approaches with realism stems from unwarranted assumptions about the nature of scientific explanation, the ontological commitments of scientific theories, and the role of abstraction and idealization in scientific models. We challenge each of these assumptions to reframe the debates over Bayesian modelling in cognitive science. (shrink)

The term “medium independence” has different meanings. One sense maps onto “abstract-as-abstracta” descriptions while the other maps onto “abstract-as-omission” descriptions. Both senses have been deployed when it comes to understanding the nature of physical computation. However, because medium independence is a polysemic term, the sense being used should be clearly stated. If the sense is not clearly stated, then those who wish to engage in debates regarding medium independence and physical computation run the risk of conflating different but related issues (...) which can have consequences when it comes to thinking about physical computation across contexts. (shrink)

The authors argue that their target is orthogonal to the realism and instrumentalist debate. I argue that it is born directly from it. While the distinction is helpful in illuminating how some ontological commitments demand a theory of implementation, it's less clear whether different views cleanly map onto the epistemic and metaphysical uses defined in the paper.

The Physical Signature of Computation is the most “robust” mapping view that’s ever hit the market. It is impressive in its detail and the careful attention paid to its characterization of both the physical system and the formal computational description—a true service to the philosophical literature. The book promises a “unified account of artifact and biological computation,” but here’s where things take a turn: after handling artifacts, the Robust Mapping Account fades from view and the Mechanistic Account of Physical Computation (...) (in its neurocognitive form) emerges as the way to capture biological computation. To have a unified account, then, requires two distinct approaches to understanding the nature of physical computation. This raises questions about whether the Robust Mapping Account can be extended to neural computation, but most importantly, questions about the compatibly of these two views is questionable given the history of the Mechanistic Account and its underpinning framework. (shrink)