An autonomy interrogative

Abstract

This chapter considers autonomy as an economic concern, meaning as a matter of determining the outcomes from different ways of allocating scarce resources in a social setting. Specifically, it concerns the outcomes from decision-making mechanisms subject to capital rationing - constraints on available resources - under conditions of fundamental uncertainty. This kind of uncertainty has long been a topic of economic study: epistemic uncertainty distinguishes stochastic risk from uncertainty, while ontological uncertainty equates to non-stationarity and non-regularity in a dynamical systems sense. I also argue that this deeper ontological uncertainty is a manifestation of mathematical incompleteness and unsolvability, which are inherent limitations in reasoning due to logical paradox. Given that non-linear dynamics classifies different degrees of uncertainty in different classes, I propose plasticity as the maximum class that an organism, system, organisation or thing may successfully handle, in the sense of surviving in an environment characterised by that class for better than logarithmic time. Machines that manifest plasticity beyond the most benign classes of uncertainty may then be referred to as autonomous, distinguishing them from automations that rely on strong prediction. Economics also studies mechanisms for handling uncertainty and their system-wide as well as individual outcomes. Paradoxically, uncertainty can easily result from the very measures that were intended to deal with uncertainty, so although a strategy might make completely rational sense from the point of view of a single agent, it can just as easily produce dangerously unstable and unpredictable system-wide outcomes. I focus on a certain class of financial strategies in particular, known as ‘barbell’ and ‘dumbbell’ strategies - which divide investment into hedges against intolerable failure and opportunity bets where failure is tolerable - for their apparent applicability across different classes of uncertainty. At the centre of this picture is a requirement for a theory of self by which an agent can determine failure sensitivity and affordable opportunity in high uncertainty environments under partially observable hard resource limits. The limits of self-knowledge together with the complexity of decision-making under hard capital rationing with the possibility of unexpected budget changes appears to imply that autonomous problem solving must be intrinsically social.