Advances in artificial intelligence, as well as its increased presence in everyday life, have brought the emergence of many new phenomena, including an intriguing appearance of what seems to be a variant of body dysmorphic disorder, coined “Snapchat dysmorphia”. Body dysmorphic disorder is a DSM-5 psychiatric disorder defined as a preoccupation with one or more perceived defects or flaws in physical appearance that are not observable or appear slight to others. Snapchat dysmorphia is fueled by automated selfie filters that reflect unrealistic sociocultural standard. In this paper, we discuss how body dysmorphic disorder and related body image distortions could arise, using the conceptual resources provided by the active inference framework. We suggest that these disorders involve dysfunctional self-modelling which entails maladaptive internalization of sociocultural preferences during adolescent identity formation. Identity formation is hereby described as cycles of interpersonal active inference that arbitrate between identity exploration and commitment. We propose that impaired self-modelling is unable to reduce interpersonal uncertainty during identity exploration, which, over time, degenerates into uncontrollable epistemic habits that isolate the body image from corrective sensory evidence. In light of these insights, we subsequently explore some of the consequences of image-centered social media platforms on the identity formation process. We conclude that heightened interpersonal uncertainty in this novel context could precipitate the onset of body dysmorphic disorder and related body image distortions, particularly when selfie filters are involved.
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However, this would be compatible with the notion of pre-reflective bodily intentionality that accompanies the habitual body (Merleau-Ponty 2013; Reuter 1999). According to this view, habitual actions are not directed toward anything specific, but they are nonetheless directed toward something in general (the lived world).
The criteria used in various taxonomies vary greatly. They comprise things such as availability to consciousness, dynamics, functional role, format, perspective, etc. (de Vignemont 2018).
It should be noted that, in the active inference framework, representations are always in the service of action.
Phenomenal transparency is a property of phenomenal representations where only the content is introspectively accessible, but not the process underlying its constitution (i.e. its vehicle) (Blanke and Metzinger 2009). The more the process of constitution (i.e. earlier processing stages) is accessible to introspective attention, the more a representation is opaque. Phenomenal transparency and opacity can be placed along a gradient of phenomenal “epistemic reliability” or “realness” (Metzinger 2014): transparency is experienced as mind-independent (external) reality while opacity is experienced as mind-dependent (internal) abstraction.
This follows from Metzinger’s “principle of virtual identity formation,” which explains transtemporal personal identity as nothing more than an adaptive form of (narrative) self-deception, a virtual simulation that enables long-term planning and motivation (Metzinger 2013, p. 5). It should be noted that this refers to a rather broad conception of narratives as sequences of representations that include subpersonal processes (e.g. automatic narratives) and non-linguistic representations (e.g. mental imagery).
Note that prediction can be understood in two different ways in active inference: First, in the correlational sense that involves one value “predicting” another. This type of inference can be considered “belief-free.” Second, in the abductive sense that involves hypothesis testing. This type of inference can be considered “belief-based.”.
With Clark (2017), we see the predictive system as a series of nested Markov blankets, each with its own set of inputs and outputs. Although the Markov blanket that marks the separation between the biological organism and its physical environment is interesting for many reasons, its inputs and outputs should not be viewed as the inputs and outputs to the system.
In this paper, “representations” is used in a rather liberal fashion and refers to various constructs that depend on the type of generative model employed. Representations involve generative models that correlate with states (continuous or discrete) in the (internal or external) environment. A suggestion as to what distinguishes them is that continuous representations involved in “belief-free” inferences are not representational in a strong sense (i.e. without involving the internal manipulation of content) while discrete representations involved in “belief-based” inferences are representational in a stronger sense (i.e. involving the internal manipulation of content) (for a similar proposal, see Constant et al. 2019, 2020). Of course, in this framework, “belief-free” and “belief-based” are understood as poles of a hierarchical continuum.
Under active inference, there is no competition between distinct model-free and model-based controllers. Instead, it is the hierarchical depth of the planning process that arbitrates between belief-free (shallow) and belief-based (deep) planning (Miller et al. 2018).
Because prediction errors are almost instantly resolved in the lower levels through unconscious peripheral reflexes, they almost never reach the motor cortex. As a consequence, there are very few error units (superficial pyramidal cells) in the primary motor cortex.
It should be noted that bodily agency is a causally enabling factor, but not a constitutive condition for minimal selfhood (Blanke and Metzinger 2009).
According to Metzinger’s “self-deception model of goal selection and action initiation”, the self-model integrates counterfactual misrepresentations of goal-states with intrinsic normativity (Metzinger 2017). Intrinsically normative goal-states are always organism-relative hallucinations, they provide an adaptive form of self-deception that continuously drives the organism forward.
Legault et al. (2019) explain that in the kind of 4E models of cognition that we deem compatible with our account, cognitive deficits, such as mentalization deficits, may be understood as mismatches between environmental resources and the particular form of neurological functioning of individuals.
Planning the future is remembering the past to survive the present. This is because the future tends to resemble the past in a world characterized by causal regularities.
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We wish to thank Jeffrey White for his insightful comments, as well as Michael L. Anderson and Thomas Metzinger for the helpful discussions.
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Tremblay, S.C., Essafi Tremblay, S. & Poirier, P. From filters to fillers: an active inference approach to body image distortion in the selfie era. AI & Soc 36, 33–48 (2021). https://doi.org/10.1007/s00146-020-01015-w
- Body dysmorphic disorder
- Body image distortions
- Snapchat dysmorphia
- Active inference
- Self-model theory
- Identity formation