Economics is a very broad field. From macro policy to econometric micro optimization. Here the focus is on conceptualizing the decision maker as it is relevant for deciding a relevant policy alternative from a potential set. Undoubtedly future work and potential authors will expand this section greatly.
The foundation of economics is to scale decision making to collective systems. Traditionally, decision makers are seen as utility maximizers (or regret minimizers). With the underlying assumption of full information and (bounded) rationality.
However, active inference nuances this view by positing that rational choice is a limit case of decision making. Only occurring during absolute certainty of observing one’s preferences (Friston et al., 2013). Instead a pragmatic turn entails information seeking as part of the decision process such that actions are both pragmatically and epistemically informed (Schwartenbeck et al., 2015).
Such a shift in perspective - all the way up to perspective swaps - may not be limited to traditional economics by expanding existing frameworks with new methodologies. Instead, this shift from viewing choice as static towards a dynamic process, means that multiple economic approaches to collective policy selection become feasible.
One such alternative economic approach is broad prosperity. It involves taking inventory of a set of value-neutral indicators, of which gross domestic product is just one. Unfortunately, it is very difficult to express the causal relationships between these indicators as these span a variety of domains like social, environmental and economic concerns. Additionally, what occurs locally has impacts globally and vice versa (TNO, 2024).
Active inference is poised to address these limitations. Given the nature of scale-free action perception loops; any self-organising system may be described as a sense-maker. In doing so solve the issue of not being able to sum free energy across agents. For example when planning a new public transport line. One could calculate the total utility obtained via preference elicitation (willingness to pay, stated and revealed choice experiments). Or one could instantiate a niche constructing digital twin. The entire urban region which is assumed to itself be a scale-free niche constructor will then have to share its niche with a synthetic artifact.
Evaluating the potential of a policy alternative, like building a tram or bus line, becomes a practice of understanding the generative model of the digital twin. Which is assumed to approximate a real niche constructor.