mtmt
The Hungarian Scientific Bibliography
XML
JSON
Public search
Magyarul
Entangled AI
Köves, A. ✉ [Köves, Alexandra (közgazdaságtan), author] Department of Decision Sciences (CUB / IODS)
;
Feher, K. [Fehér, Katalin (technológia és tá...), author] Társadalmi Kommunikáció Tanszék (UPS / ÁNTK)
;
Vicsek, L. [Vicsek, Lilla Mária (szociológia), author] Department of Sociology (CUB / ISPS)
;
Fischer, M. [Fischer, Máté (ökológiai közgazd...), author] Doctoral School of Business and Management (CUB / CDI)
English Article (Journal Article) Scientific
Published:
AI AND SOCIETY: THE JOURNAL OF HUMAN-CENTERED SYSTEMS AND MACHINE INTELLIGENCE 0951-5666 1435-5655
, 12 p.
2024
SJR Scopus - Philosophy: D1
Identifiers
MTMT: 35176735
DOI:
10.1007/s00146-024-02037-4
Közszolgálati Tudásportál:
100802
WoS:
001288062800002
CorvinusKutatasok:
10267
Scopus:
85201005113
Subjects:
Internet Ethics
Internet science, collective awareness platforms
Artificial Intelligence & Decision support
While debate is heating up regarding the development of AI and its perceived impacts on human society, policymaking is struggling to catch up with the demand to exercise some regulatory control over its rapid advancement. This paper aims to introduce the concept of entangled AI that emerged from participatory backcasting research with an AI expert panel. The concept of entanglement has been adapted from quantum physics to effectively capture the envisioned form of artificial intelligence in which a strong interconnectedness between AI, humans, society, and nature is reflected. Entanglement assumes that AI should serve nature, social well-being, justice, and the resilience of this intertwined network simultaneously and promote a dynamic balance among these factors. This approach allows us to understand the pervasive role of this technology and the scope of human agency in its development. The study shows how such concepts seem to transcend the dominant discourses related to expectations, technological determinism, and humanism. An additional aim of this paper is to demonstrate how backcasting can contribute to generating useful understandings of the future of AI and fruitful insights for policymaking. © The Author(s) 2024.
Citing (5)
Citation styles:
IEEE
ACM
APA
Chicago
Harvard
CSL
Copy
Print
2025-02-19 05:31
×
Export list as bibliography
Citation styles:
IEEE
ACM
APA
Chicago
Harvard
Print
Copy