Caspar Barnes, Mateo Riobo Aboy, Timo Minssen, Jemima Winifred Allen, Brian D Earp, Julian Savulescu, Sebastian Porsdam Mann
{"title":"Enabling Demonstrated Consent for Biobanking with Blockchain and Generative AI.","authors":"Caspar Barnes, Mateo Riobo Aboy, Timo Minssen, Jemima Winifred Allen, Brian D Earp, Julian Savulescu, Sebastian Porsdam Mann","doi":"10.1080/15265161.2024.2416117","DOIUrl":null,"url":null,"abstract":"<p><p>Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call \"demonstrated consent\" that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its metadata information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples.</p>","PeriodicalId":50962,"journal":{"name":"American Journal of Bioethics","volume":null,"pages":null},"PeriodicalIF":17.0000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Bioethics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/15265161.2024.2416117","RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ETHICS","Score":null,"Total":0}
引用次数: 0
Abstract
Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call "demonstrated consent" that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its metadata information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples.
期刊介绍:
The American Journal of Bioethics (AJOB) is a renowned global publication focused on bioethics. It tackles pressing ethical challenges in the realm of health sciences.
With a commitment to the original vision of bioethics, AJOB explores the social consequences of advancements in biomedicine. It sparks meaningful discussions that have proved invaluable to a wide range of professionals, including judges, senators, journalists, scholars, and educators.
AJOB covers various areas of interest, such as the ethical implications of clinical research, ensuring access to healthcare services, and the responsible handling of medical records and data.
The journal welcomes contributions in the form of target articles presenting original research, open peer commentaries facilitating a dialogue, book reviews, and responses to open peer commentaries.
By presenting insightful and authoritative content, AJOB continues to shape the field of bioethics and engage diverse stakeholders in crucial conversations about the intersection of medicine, ethics, and society.