Am I Self-Conscious? (Or Does Self-Organization Entail Self-Consciousness?)

Abstract

Is self-consciousness necessary for consciousness? The answer is yes. So there you have it—the answer is yes. This was my response to a question I was asked to address in a recent AEON piece (https://aeon.co/essays/consciousness-is-not-a-thing-but-a-process-of-inference). What follows is based upon the notes for that essay, with a special focus on self-organization, self-evidencing and self-modeling. I will try to substantiate my (polemic) answer from the perspective of a physicist. In brief, the argument goes as follows: if we want to talk about creatures, like ourselves, then we have to identify the characteristic behaviors they must exhibit. This is fairly easy to do by noting that living systems return to a set of attracting states time and time again. Mathematically, this implies the existence of a Lyapunov function that turns out to be model evidence (i.e., self-evidence) in Bayesian statistics or surprise (i.e., self-information) in information theory. This means that all biological processes can be construed as performing some form of inference, from evolution through to conscious processing. If this is the case, at what point do we invoke consciousness? The proposal on offer here is that the mind comes into being when self-evidencing has a temporal thickness or counterfactual depth, which grounds inferences about the consequences of my action. On this view, consciousness is nothing more than inference about my future; namely, the self-evidencing consequences of what I could do.

A Theory of Predictive Dissonance: Predictive Processing Presents a New Take on Cognitive Dissonance

“…A rich affordance landscape, in turn, requires a highly generalizable and efficient predictive model. That, at least for our species, seems to have been phylogenetically satisficing (this is, in fact, self-evidenced by our very existence, see Friston, 2018). However, as discussed briefly below in Section “Underfitted Generative Models and Ecological Crises,” this strategy of overfitting-prevention is causing all kinds of trouble in a 21st century context, where our ecological niches and landscapes of affordances are changing more rapidly than our predictive capabilities.…”

Dissolving the self

“…To successfully navigate the world over longer timescales, and select policies that result in survival -and not dispersion or non-existence -organisms must possess models of the future; in other words, they require deep temporal models . The generative models that endow organisms with the capability of inferring the consequences of future actions must have the property of temporal thickness, which allows the organism to anticipate the downstream consequences of potential actions, conferring the ability to select policies or action scripts that are favourable to the organism's continued existence (Friston, 2018). The minimi-sation of surprise through active inference on the FEP involves acting so as to reduce uncertainty, and to do this the system must model itself across time and counterfactuals -that is, it must model what kind of agent it is at varying degrees of temporal depth.…”

“…The minimi-sation of surprise through active inference on the FEP involves acting so as to reduce uncertainty, and to do this the system must model itself across time and counterfactuals -that is, it must model what kind of agent it is at varying degrees of temporal depth. Self-modelling, then, emerges as a natural consequence of prospective action selection (Friston, 2018), where the principal function of a counterfactually rich self-model is to facilitate navigation of the affordance landscape and action selection across multiple interlocking timescales -for example expectations of what an agent can do on shorter timescales inform expectations of what the agent can do over longer timescales. The functional role of having a rich self-model, then, is that it enables the organism to predict outcomes across diverse policies, and endows the organism with "what if?"…”

“…The functional role of having a rich self-model, then, is that it enables the organism to predict outcomes across diverse policies, and endows the organism with "what if?" capabilities (Friston, 2018), which puts this picture into contact with mental time travel and offline simulation (Buckner & Carroll, 2007;Schacter, Addis, & Buckner, 2008).…”

“…In this paper I propose a novel account of ego-dissolution within an active inference framework. To this end, I initially furnish an account of self-modelling within active inference, where pre-reflective self-consciousness emerges in organisms as a consequence of "temporal thickness", the need to model the consequences of potential actions over time (Friston, 2018). I then give an account of the action of psychedelics within a predictive processing framework, unpacking the view that psychedelics "relax" high-level priors (Carhart-Harris, 2019;Carhart-Harris & Friston, 2019) in terms of a high Bayesian learning rate (Hohwy, 2017;Mathys et al, 2014).…”