A Typology for Identifying Digitally-Induced Altered States of Consciousness Through Input Discrepancy

The development of digital technologies leads to new types of relationships between the digital world and human consciousness, increasingly inducing or influencing specific types of experiences, such as dreams, transcendental experiences, or derealisation. The varied devices used to induce these experiences, from brain-stimulating magnets to biofeedback-based VR headsets, constitute a new class of digital technologies. They are already starting to be utilised in various spheres of life from medicine to art. However, the full potential of technologies is only beginning to be revealed and implementations are somewhat limited; accordingly, researchers in the field must use alternative strategies when investigating the potential evolution of this phenomenon. Making use of speculative or fictional narratives is one productive approach. Finding relevant technologies within narratives has some challenges and requires a more specific criterion for defining this phenomenon. This work in progress suggests the conceptualization of altered states of consciousness (ASC) through the lens of the relationship between external input and processor as a practical strategy for identifying digitally-induced altered states of consciousness (DIAL). It provides "discrepancy of input" as a flexible navigational criterion that will help include unknown technologies into the discussion about altered states of consciousness. The implementation of the criterion is demonstrated in specific examples of identification technologies from sci-fi worlds.

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Publication Details

Published
2024-10-08
DOI
https://doi.org/10.1145/3681716.3689443
Citations
2
Primary Topic
Psychedelics and Drug Studies
Type
article
Field-Weighted Citation Impact
1.28
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article

A Typology for Identifying Digitally-Induced Altered States of Consciousness Through Input Discrepancy

Joseph Macey, Anatolii Belousov, Juho Hamari, Mila Bujić et al.
2 citations
Psychedelics and Drug Studies
1.28
article

A Typology for Identifying Digitally-Induced Altered States of Consciousness Through Input Discrepancy

Joseph Macey, Anatolii Belousov, Juho Hamari, Mila Bujić, Terho Ojell-Järventausta
article en
2 citations

Abstract

The development of digital technologies leads to new types of relationships between the digital world and human consciousness, increasingly inducing or influencing specific types of experiences, such as dreams, transcendental experiences, or derealisation. The varied devices used to induce these experiences, from brain-stimulating magnets to biofeedback-based VR headsets, constitute a new class of digital technologies. They are already starting to be utilised in various spheres of life from medicine to art. However, the full potential of technologies is only beginning to be revealed and implementations are somewhat limited; accordingly, researchers in the field must use alternative strategies when investigating the potential evolution of this phenomenon. Making use of speculative or fictional narratives is one productive approach. Finding relevant technologies within narratives has some challenges and requires a more specific criterion for defining this phenomenon. This work in progress suggests the conceptualization of altered states of consciousness (ASC) through the lens of the relationship between external input and processor as a practical strategy for identifying digitally-induced altered states of consciousness (DIAL). It provides "discrepancy of input" as a flexible navigational criterion that will help include unknown technologies into the discussion about altered states of consciousness. The implementation of the criterion is demonstrated in specific examples of identification technologies from sci-fi worlds.

University of Turku (FI), Tampere University (FI)
Reduced inequalities
Openalex Percentile: Top 19%
Psychedelics and Drug Studies
1.28
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A Typology for Identifying Digitally-Induced Altered States of Consciousness Through Input Discrepancy — Joseph Macey, Anatolii Belousov, et al. · (2024) | TGRS Research Map | TGRS