Journal article
Enabling demonstrated consent for biobanking with blockchain and generative AI
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.8MB, Terms of use)
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- Publisher copy:
- 10.1080/15265161.2024.2416117
Authors
+ Novo Nordisk Foundation
More from this funder
- Funder identifier:
- https://ror.org/04txyc737
- Grant:
- NNF17SA0027784
- Publisher:
- Taylor & Francis
- Journal:
- American Journal of Bioethics More from this journal
- Volume:
- 25
- Issue:
- 4
- Pages:
- 96-111
- Publication date:
- 2024-11-05
- Acceptance date:
- 2024-03-18
- DOI:
- EISSN:
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1536-0075
- ISSN:
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1526-5161
- Pmid:
-
39499856
- Language:
-
English
- Keywords:
- Pubs id:
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2055069
- Local pid:
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pubs:2055069
- Deposit date:
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2025-02-05
Terms of use
- Copyright holder:
- Barnes et al.
- Copyright date:
- 2024
- Rights statement:
- © 2024 The Author(s). Published with license by Taylor & francis Group, llc. This is an open Access article distributed under the terms of the creative commons Attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricteduse, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of theAccepted manuscript in a repository by the author(s) or with their consent.
- Licence:
- CC Attribution (CC BY)
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