Active inference models do not contradict folk psychology

Abstract

Active inference offers a unified theory of perception, learning, and decision-making at computational and neural levels of description. In this article, we address the worry that active inference may be in tension with folk psychology because it does not include terms for desires (or other conative constructs) at the mathematical level of description. To resolve this concern, we first provide a brief review of the historical progression from predictive coding to active inference, enabling us to distinguish between active inference formulations of motor control (which need not have desires under folk psychology) and active inference formulations of decision processes (which do have desires within folk psychology). We then show that, despite a superficial tension when viewed at the mathematical level, the active inference formalism contains terms that are readily identifiable as encoding both the objects of desire and the strength of desire at the psychological level. We demonstrate this with simple simulations of an active inference agent motivated to leave a dark room for different reasons. Despite their consistency, we further show how active inference may increase the granularity of folk-psychological descriptions by highlighting distinctions between drives to seek information vs. reward – and how it may also offer more precise, quantitative folk-psychological predictions. Finally, we consider how the implicitly conative components of active inference may have partial analogues (i.e., “as if” desires) in other systems describable by the broader free energy principle to which it conforms.

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again

“…Finally, some of the (Hard) problem may derive from frames in cognitive science that rendered all Cartesian framings of mental functioning taboo. That is, if quasi-Cartesian intuitions were actually semi-faithful representations of the nature(s) of mind and brain, then why should we be surprised if our scholarship—and its denigration of folk psychology [ 436 ]—failed to provide satisfying accounts of the nature(s) of our conscious agency?…”

A step-by-step tutorial on active inference and its application to empirical data

“…However, it is important to highlight that this formal treatment of preferences and values as ‘Bayesian beliefs’ (i.e., probability distributions) need not be understood as a psychological description, nor must it be if one wishes to use active inference models in practice. In other words, not all beliefs at the mathematical level of description need to be equated with beliefs at the psychological level; some Bayesian beliefs in the formalism can instead correspond to rewarding or desired outcomes at the psychological level ( Smith, Ramstead, & Kiefer, 2022 ). Similarly, the notion of ‘surprise’ with respect to prior preferences is not equivalent to the conscious experience of surprise; minimizing the type of ‘phenotypic surprise’ discussed in active inference is better mapped onto psychological states associated with achieving one’s goals.…”