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Exploring the role of AI in classifying, analyzing, and generating case reports on assisted suicide cases: feasibility and ethical implications

Spitale, Giovanni; Schneider, Gerold; Germani, Federico; Biller-Andorno, Nikola (2023). Exploring the role of AI in classifying, analyzing, and generating case reports on assisted suicide cases: feasibility and ethical implications. Frontiers in Artificial Intelligence, 6:1328865.

Abstract

This paper presents a study on the use of AI models for the classification of case reports on assisted suicide procedures. The database of the five Dutch regional bioethics committees was scraped to collect the 72 case reports available in English. We trained several AI models for classification according to the categories defined by the Dutch Termination of Life on Request and Assisted Suicide (Review Procedures) Act. We also conducted a related project to fine-tune an OpenAI GPT-3.5-turbo large language model for generating new fictional but plausible cases. As AI is increasingly being used for judgement, it is possible to imagine an application in decision-making regarding assisted suicide. Here we explore two arising questions: feasibility and ethics, with the aim of contributing to a critical assessment of the potential role of AI in decision-making in highly sensitive areas.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
04 Faculty of Medicine > Institute of Biomedical Ethics and History of Medicine
06 Faculty of Arts > Linguistic Research Infrastructure (LiRI)
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:December 2023
Deposited On:03 Jan 2024 10:18
Last Modified:30 Dec 2024 02:52
Publisher:Frontiers Research Foundation
ISSN:2624-8212
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3389/frai.2023.1328865
Related URLs:https://osf.io/7zgmj/ (Research Data)
PubMed ID:38164497
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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