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Artificial Continuing Bonds

A Proposed Framework for Responsible Integration of Generative AI in Clinical Thanatology

Bibliographic Data

ID13630509
AuthorsAlexander Manevich (0000-0003-4977-1116, Ruppin Academic Center, corresponding author), Shani Aluma (Kinneret College on the Sea of Galilee)
Year2025
Pages302228251372418-302228251372418
Publication date2025-08-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueOMEGA - Journal of Death and Dying (JOURNAL)
Journal identifiersISSN: 0030-2228 • E-ISSN: 1541-3764
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/00302228251372418
PMID40854560
OpenAlexW4413770298
LanguageEN
Citations received1
References cited30

This article explores the integration of generative artificial intelligence (GenAI) into the field of thanatology, with particular attention to its ethical, societal, and clinical implications. In recent years, GenAI technologies have increasingly been applied in mental-health settings, including the use of chatbots and so-called "deathbots" - digital simulations of deceased individuals that some mourners engage with to sustain a sense of connection and emotional comfort. While such technologies may offer therapeutic potential, they also raise significant ethical and practical challenges. Despite rising academic interest, empirical research in this domain remains scarce, and the field still lacks a cohesive body of knowledge. This article reviews current developments and key debates in the field and proposes a preliminary framework for the responsible integration of GenAI in grief-related practices. The framework outlines four critical pillars: ethical and regulatory oversight, development of theoretical foundations, promotion of empirical inquiry, and implementation of clinically informed practices

Cognitive science · Generative grammar · Social science · Sociology · Thanatology · Artificial Intelligence · Computer Science · Grief, Bereavement, and Mental Health · Palliative Care and End-of-Life Issues · Psychology

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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