Ciara Staunton, Roberta Biasiotto, Katharina Tschigg, Deborah Mascalzoni
{"title":"人工智能需要数据:访问意大利数据库以训练人工智能所面临的挑战","authors":"Ciara Staunton, Roberta Biasiotto, Katharina Tschigg, Deborah Mascalzoni","doi":"10.1007/s41649-024-00282-9","DOIUrl":null,"url":null,"abstract":"<div><p>Population biobanks are an increasingly important infrastructure to support research and will be a much-needed resource in the delivery of personalised medicine. Artificial intelligence (AI) systems can process and cross-link very large amounts of data quickly and be used not only for improving research power but also for helping with complex diagnosis and prediction of diseases based on health profiles. AI, therefore, potentially has a critical role to play in personalised medicine, and biobanks can provide a lot of the necessary baseline data related to healthy populations that will enable the development of AI tools. To develop these tools, access to personal data, and in particular, sensitive data, is required. Such data could be accessed from biobanks. Biobanks are a valuable resource for research but accessing and using the data contained within such biobanks raise a host of legal, ethical, and social issues (ELSI). This includes the appropriate consent to manage the collection, storage, use, and sharing of samples and data, and appropriate governance models that provide oversight of secondary use of samples and data. Biobanks have developed new consent models and governance tools to enable access that address some of these ELSI-related issues. In this paper, we consider whether such governance frameworks can enable access to biobank data to develop AI. As Italy has one of the most restrictive regulatory frameworks on the use of genetic data in Europe, we examine the regulatory framework in Italy. We also look at the proposed changes under the European Health Data Space (EHDS). We conclude by arguing that currently, regulatory frameworks are misaligned and unless addressed, accessing data within Italian biobanks to train AI will be severely limited.</p></div>","PeriodicalId":44520,"journal":{"name":"Asian Bioethics Review","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41649-024-00282-9.pdf","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Needs Data: Challenges Accessing Italian Databases to Train AI\",\"authors\":\"Ciara Staunton, Roberta Biasiotto, Katharina Tschigg, Deborah Mascalzoni\",\"doi\":\"10.1007/s41649-024-00282-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Population biobanks are an increasingly important infrastructure to support research and will be a much-needed resource in the delivery of personalised medicine. Artificial intelligence (AI) systems can process and cross-link very large amounts of data quickly and be used not only for improving research power but also for helping with complex diagnosis and prediction of diseases based on health profiles. AI, therefore, potentially has a critical role to play in personalised medicine, and biobanks can provide a lot of the necessary baseline data related to healthy populations that will enable the development of AI tools. To develop these tools, access to personal data, and in particular, sensitive data, is required. Such data could be accessed from biobanks. Biobanks are a valuable resource for research but accessing and using the data contained within such biobanks raise a host of legal, ethical, and social issues (ELSI). This includes the appropriate consent to manage the collection, storage, use, and sharing of samples and data, and appropriate governance models that provide oversight of secondary use of samples and data. Biobanks have developed new consent models and governance tools to enable access that address some of these ELSI-related issues. In this paper, we consider whether such governance frameworks can enable access to biobank data to develop AI. As Italy has one of the most restrictive regulatory frameworks on the use of genetic data in Europe, we examine the regulatory framework in Italy. We also look at the proposed changes under the European Health Data Space (EHDS). We conclude by arguing that currently, regulatory frameworks are misaligned and unless addressed, accessing data within Italian biobanks to train AI will be severely limited.</p></div>\",\"PeriodicalId\":44520,\"journal\":{\"name\":\"Asian Bioethics Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s41649-024-00282-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Bioethics Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s41649-024-00282-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ETHICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Bioethics Review","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s41649-024-00282-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ETHICS","Score":null,"Total":0}
Artificial Intelligence Needs Data: Challenges Accessing Italian Databases to Train AI
Population biobanks are an increasingly important infrastructure to support research and will be a much-needed resource in the delivery of personalised medicine. Artificial intelligence (AI) systems can process and cross-link very large amounts of data quickly and be used not only for improving research power but also for helping with complex diagnosis and prediction of diseases based on health profiles. AI, therefore, potentially has a critical role to play in personalised medicine, and biobanks can provide a lot of the necessary baseline data related to healthy populations that will enable the development of AI tools. To develop these tools, access to personal data, and in particular, sensitive data, is required. Such data could be accessed from biobanks. Biobanks are a valuable resource for research but accessing and using the data contained within such biobanks raise a host of legal, ethical, and social issues (ELSI). This includes the appropriate consent to manage the collection, storage, use, and sharing of samples and data, and appropriate governance models that provide oversight of secondary use of samples and data. Biobanks have developed new consent models and governance tools to enable access that address some of these ELSI-related issues. In this paper, we consider whether such governance frameworks can enable access to biobank data to develop AI. As Italy has one of the most restrictive regulatory frameworks on the use of genetic data in Europe, we examine the regulatory framework in Italy. We also look at the proposed changes under the European Health Data Space (EHDS). We conclude by arguing that currently, regulatory frameworks are misaligned and unless addressed, accessing data within Italian biobanks to train AI will be severely limited.
期刊介绍:
Asian Bioethics Review (ABR) is an international academic journal, based in Asia, providing a forum to express and exchange original ideas on all aspects of bioethics, especially those relevant to the region. Published quarterly, the journal seeks to promote collaborative research among scholars in Asia or with an interest in Asia, as well as multi-cultural and multi-disciplinary bioethical studies more generally. It will appeal to all working on bioethical issues in biomedicine, healthcare, caregiving and patient support, genetics, law and governance, health systems and policy, science studies and research. ABR provides analyses, perspectives and insights into new approaches in bioethics, recent changes in biomedical law and policy, developments in capacity building and professional training, and voices or essays from a student’s perspective. The journal includes articles, research studies, target articles, case evaluations and commentaries. It also publishes book reviews and correspondence to the editor. ABR welcomes original papers from all countries, particularly those that relate to Asia. ABR is the flagship publication of the Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore. The Centre for Biomedical Ethics is a collaborating centre on bioethics of the World Health Organization.