Attention is all they need: Cognitive science and the (techno)political economy of attention in humans and machines

Fuente: arXiv
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Autores principales: de la Torre, Pablo González, Pérez-Verdugo, Marta, Barandiaran, Xabier E.
Formato: Preprint
Publicado: 2024
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author de la Torre, Pablo González
Pérez-Verdugo, Marta
Barandiaran, Xabier E.
author_facet de la Torre, Pablo González
Pérez-Verdugo, Marta
Barandiaran, Xabier E.
contents This paper critically analyses the "attention economy" within the framework of cognitive science and techno-political economics, as applied to both human and machine interactions. We explore how current business models, particularly in digital platform capitalism, harness user engagement by strategically shaping attentional patterns. These platforms utilize advanced AI and massive data analytics to enhance user engagement, creating a cycle of attention capture and data extraction. We review contemporary (neuro)cognitive theories of attention and platform engagement design techniques and criticize classical cognitivist and behaviourist theories for their inadequacies in addressing the potential harms of such engagement on user autonomy and wellbeing. 4E approaches to cognitive science, instead, emphasizing the embodied, extended, enactive, and ecological aspects of cognition, offer us an intrinsic normative standpoint and a more integrated understanding of how attentional patterns are actively constituted by adaptive digital environments. By examining the precarious nature of habit formation in digital contexts, we reveal the techno-economic underpinnings that threaten personal autonomy by disaggregating habits away from the individual, into an AI managed collection of behavioural patterns. Our current predicament suggests the necessity of a paradigm shift towards an ecology of attention. This shift aims to foster environments that respect and preserve human cognitive and social capacities, countering the exploitative tendencies of cognitive capitalism.
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publishDate 2024
record_format arxiv
spellingShingle Attention is all they need: Cognitive science and the (techno)political economy of attention in humans and machines
de la Torre, Pablo González
Pérez-Verdugo, Marta
Barandiaran, Xabier E.
Computers and Society
Artificial Intelligence
Social and Information Networks
This paper critically analyses the "attention economy" within the framework of cognitive science and techno-political economics, as applied to both human and machine interactions. We explore how current business models, particularly in digital platform capitalism, harness user engagement by strategically shaping attentional patterns. These platforms utilize advanced AI and massive data analytics to enhance user engagement, creating a cycle of attention capture and data extraction. We review contemporary (neuro)cognitive theories of attention and platform engagement design techniques and criticize classical cognitivist and behaviourist theories for their inadequacies in addressing the potential harms of such engagement on user autonomy and wellbeing. 4E approaches to cognitive science, instead, emphasizing the embodied, extended, enactive, and ecological aspects of cognition, offer us an intrinsic normative standpoint and a more integrated understanding of how attentional patterns are actively constituted by adaptive digital environments. By examining the precarious nature of habit formation in digital contexts, we reveal the techno-economic underpinnings that threaten personal autonomy by disaggregating habits away from the individual, into an AI managed collection of behavioural patterns. Our current predicament suggests the necessity of a paradigm shift towards an ecology of attention. This shift aims to foster environments that respect and preserve human cognitive and social capacities, countering the exploitative tendencies of cognitive capitalism.
title Attention is all they need: Cognitive science and the (techno)political economy of attention in humans and machines
topic Computers and Society
Artificial Intelligence
Social and Information Networks
url https://arxiv.org/abs/2405.06478