Direct input variables: rethinking the limits of the extended mind hypothesis within predictive processing

Abstract

Predictive Processing theories and the Free Energy Principle (FEP) face a dilemma when addressing the problem raised by the Extended Mind Hypothesis (EMH): on the one hand, few can deny that some objects, such as phones, computers, or other people, have a disproportionate role in the reduction of free energy; hence, it is natural to accept that the mind is extended. On the other hand, this seems to go against the carefully built framework in which Markov blankets (MBs) create an evidentiary boundary between the brain and the external environment, thus rejecting the claim that the mind can be extended to external objects. One approach would be to allow for permeable MBs, where boundaries can move, hence allowing external objects to become part of the mind. I find these solutions to be unsatisfactory because they go against the FEP framework, and I propose a different solution instead: human agents have the possibility of using Direct Input Variables (DIVs), which involves directly using the results of other models without performing the statistical inference themselves. Reducing free energy can be achieved either by statistical inference performed by the brain or by using DIVs. The use of DIVs removes the need to accept the EMH, preserves the integrity of the FEP framework, and opens new questions regarding how DIVs can be integrated within the FEP framework.