What we (should) talk about when we talk about fruitfulness

Putting inference to the best explanation into context

It is often assumed that Inference to the Best Explanation, or 'IBE', belongs to the context of justification. But several recent developments might lead one to ask whether it is more appropriate to situate it in the context of pursuit. Peircean abduction, which has been designated as an immediate precursor to IBE, is, according to recent scholarship, best located in the context of discovery and pursuit, rather than justification. Furthermore, alleged difficulties in reconciling IBE with Bayesianism have led to a proposal for giving IBE a non-justificatory role, which is close to that of pursuit. I argue, however, that these considerations do not make a strong case for locating IBE in the context of pursuit. Although abduction plays an important role in the context of pursuit, IBE is not simply a renaming of abduction. It has been reconceptualised in a way which makes it unsuitable to operate in the context of pursuit. Considerations concerning the compatibility between IBE and Bayesianism also do not give strong grounds to locate IBE outside the context of justification. This is because we should not expect that the context of justification can be characterised in purely probabilistic terms. Thus IBE should continue to be regarded as a candidate for characterising epistemic appraisal in the context of justification.

Schema-Centred Unity and Process-Centred Pluralism of the Predictive Mind

Proponents of the predictive processing (PP) framework often claim that one of the framework’s significant virtues is its unificatory power. What is supposedly unified are predictive processes in the mind, and these are explained in virtue of a common prediction error-minimisation (PEM) schema. In this paper, I argue against the claim that PP currently converges towards a unified explanation of cognitive processes. Although the notion of PEM systematically relates a set of posits such as ‘efficiency’ and ‘hierarchical coding’ into a unified conceptual schema, neither the frameworks’ algorithmic specifications nor its hypotheses about their implementations in the brain are clearly unified. I propose a novel way to understand the fruitfulness of the research program in light of a set of research heuristics that are partly shared with those common to Bayesian reverse engineering. An interesting consequence of this proposal is that pluralism is at least as important as unification to promote the positive development of the predictive mind.