TY - JOUR

T1 - Adversarial inference

T2 - Predictive minds in the attention economy

AU - Bruineberg, Jelle

N1 - Funding Information: I would like to thank Alistair Isaac, Colin Klein, Odysseus Stone, the members of the Monash Centre for Consciousness & Contem-plative Studies (in particular, Andrew Corcoran, Mengting Zhang, and Jakob Hohwy), as well as two anonymous reviewers for provid-ing critical comments on earlier drafts of this paper. This research was generously supported by a Macquarie University Research Fellowship. Publisher Copyright: © 2023 The Author(s).

PY - 2023

Y1 - 2023

N2 - What is it about our current digital technologies that seemingly makes it difficult for users to attend to what matters to them? According to the dominant narrative in the literature on the "attention economy,"a user's lack of attention is due to the large amounts of information available in their everyday environments. I will argue that information-abundance fails to account for some of the central manifestations of distraction, such as sudden urges to check a particular information-source in the absence of perceptual information. I will use active inference, and in particular models of action selection based on the minimization of expected free energy, to develop an alternative answer to the question about what makes it difficult to attend. Besides obvious adversarial forms of inference, in which algorithms build up models of users in order to keep them scrolling, I will show that active inference provides the tools to identify a number of problematic structural features of current digital technologies: they contain limitless sources of novelty, they can be navigated by very simple and effortless motor movements, and they offer their action possibilities everywhere and anytime independent of place or context. Moreover, recent models of motivated control show an intricate interplay between motivation and control that can explain sudden transitions in motivational state and the consequent alteration of the salience of actions. I conclude, therefore, that the challenges users encounter when engaging with digital technologies are less about information overload or inviting content, but more about the continuous availability of easily available possibilities for action.

AB - What is it about our current digital technologies that seemingly makes it difficult for users to attend to what matters to them? According to the dominant narrative in the literature on the "attention economy,"a user's lack of attention is due to the large amounts of information available in their everyday environments. I will argue that information-abundance fails to account for some of the central manifestations of distraction, such as sudden urges to check a particular information-source in the absence of perceptual information. I will use active inference, and in particular models of action selection based on the minimization of expected free energy, to develop an alternative answer to the question about what makes it difficult to attend. Besides obvious adversarial forms of inference, in which algorithms build up models of users in order to keep them scrolling, I will show that active inference provides the tools to identify a number of problematic structural features of current digital technologies: they contain limitless sources of novelty, they can be navigated by very simple and effortless motor movements, and they offer their action possibilities everywhere and anytime independent of place or context. Moreover, recent models of motivated control show an intricate interplay between motivation and control that can explain sudden transitions in motivational state and the consequent alteration of the salience of actions. I conclude, therefore, that the challenges users encounter when engaging with digital technologies are less about information overload or inviting content, but more about the continuous availability of easily available possibilities for action.

KW - active inference

KW - attention

KW - attention economy

KW - digital technology

KW - distraction

UR - http://www.scopus.com/inward/record.url?scp=85171149331&partnerID=8YFLogxK

U2 - 10.1093/nc/niad019

DO - 10.1093/nc/niad019

M3 - Journal article

C2 - 37635900

AN - SCOPUS:85171149331

VL - 2023

JO - Neuroscience of Consciousness

JF - Neuroscience of Consciousness

SN - 2057-2107

IS - 1

ER -