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

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          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.

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          Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

          Carsten F Dormann, Jane Elith, Sven Bacher … (2013)
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            Thematic analysis

            Victoria Clarke, Virginia Braun (2017)
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              Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

              Justin Grimmer, Brandon M. Stewart (2013)
              Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation.
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                Author and article information

                Contributors
                Giovanni Spitale: URI : http://loop.frontiersin.org/people/2559840/overviewRole: Role: Role: Role: Role: Role: Role: Role:
                Gerold Schneider: URI : http://loop.frontiersin.org/people/2249342/overviewRole: Role: Role: Role: Role: Role: Role: Role:
                Federico Germani: Role: Role: Role:
                Nikola Biller-Andorno: URI : http://loop.frontiersin.org/people/1432090/overviewRole: Role: Role: Role: Role: Role: Role:
                Journal
                Journal ID (nlm-ta): Front Artif Intell
                Journal ID (iso-abbrev): Front Artif Intell
                Journal ID (publisher-id): Front. Artif. Intell.
                Title: Frontiers in Artificial Intelligence
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2624-8212
                Publication date (Electronic): 14 December 2023
                Publication date Collection: 2023
                Volume: 6
                Electronic Location Identifier: 1328865
                Affiliations
                [1] 1Institute of Biomedical Ethics and History of Medicine, University of Zurich , Zürich, Switzerland
                [2] 2Department of Computational Linguistics, University of Zurich , Zürich, Switzerland
                Author notes

                Edited by: Kezhi Li, University College London, United Kingdom

                Reviewed by: Mayank Kejriwal, University of Southern California, United States; Sabine Salloch, Hannover Medical School, Germany

                *Correspondence: Nikola Biller-Andorno biller-andorno@ 123456ibme.uzh.ch

                †These authors share first authorship

                ‡ORCID: Giovanni Spitale orcid.org/0000-0002-6812-0979

                Gerold Schneider orcid.org/0000-0002-1905-6237

                Federico Germani orcid.org/0000-0002-5604-0437

                Nikola Biller-Andorno orcid.org/0000-0001-7661-1324

                Article
                DOI: 10.3389/frai.2023.1328865
                PMC ID: 10757918
                PubMed ID: 38164497
                SO-VID: 3816ba37-719f-4702-b5c6-5b9c4137fc12
                Copyright © Copyright © 2023 Spitale, Schneider, Germani and Biller-Andorno.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 09 November 2023
                Date accepted : 24 November 2023
                Page count
                Figures: 1, Tables: 3, Equations: 3, References: 64, Pages: 12, Words: 10332
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Subject: Artificial Intelligence
                Subject: Original Research
                Custom metadata
                section-at-acceptance Medicine and Public Health

                Keywords: ai,artificial intelligence,assisted suicide,euthanasia,ethics committee,synthetic data,case classification
                Data availability:
                Keywords: ai, artificial intelligence, assisted suicide, euthanasia, ethics committee, synthetic data, case classification

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