Bridging Gaps in the ELSI of Data Science Health Research in Nigeria (BridgELSI)

弥合尼日利亚数据科学健康研究ELSI的差距(BridgELSI) 项目摘要 数据科学将影响撒哈拉以南非洲的科学研究、创新、发现和医疗保健 (SSA)，因为手机和计算机等基础设施的快速增长，以及 像人工智能这样的技术。这些方法和资源为跨越提供了巨大的机会 目前在非洲的研究、公共卫生和临床护理，通过利用数据科学来解决 SSA的传染病和非传染性疾病。 然而，尽管有这些承诺，但人们对其伦理、法律和社会影响仍有很大担忧 (ELSI)在SSA的数据科学研究。这些关切源于对常规和非常规的使用 数据；数据科学中生成、操作、存储、共享和利用数据的方法；局限性 在这些情况下的当前知情同意模式以及法律监督的新战略的机会 在尼日利亚的数据科学研究的ELSI。 在尼日利亚生物伦理与研究中心(CBR)的这个合作项目中，乔治·华盛顿 大学、DC和马里兰大学医学院(UMSOM)，我们将评估现行法律 文书、准则和框架及其实施，并利用这些文书、准则和框架制定新的和创新的 支持尼日利亚数据科学卫生研究的治理框架。我们还将实施混合 前瞻性评估数据科学家的知识、态度和实践(KAP)的研究方法 伦理委员会对尼日利亚当前和新兴的数据科学研究的ELSI。鉴于数据的新颖性 在尼日利亚，我们将实施一般和具体的、短期和中期的数据伦理培训 为数据科学研究人员提供尼日利亚科学研究，并为以下组织成员介绍数据科学 伦理委员会审查数据科学研究项目。

Bridging Gaps in the ELSI of Data Science Health Research in Nigeria (BridgELSI) Project Summary Data science is poised to impact scientific research, innovation, discovery and healthcare in sub-Saharan Africa (SSA) because of the rapid growth of infrastructure such as cell phones and computers, and the availability of technologies like Artificial Intelligence. These methods and resources present huge opportunities to leapfrog current research, public health and clinical care in Africa by utilizing data science to address the huge burden of communicable and non-communicable diseases in SSA. Despite these promises however, there are substantial concerns about the ethical, legal and social implications (ELSI) of data science research in SSA. These concerns arise from the use of conventional and unconventional data; the methods for generating, manipulating, storing, sharing and utilizing data in data science; the limitations of current informed consent models in these scenarios and opportunities for novel strategies for legal oversight of the ELSI of data science research in Nigeria. In this collaborative project between the Center for Bioethics and Research (CBR), Nigeria, George Washington University, DC and University of Maryland School of Medicine (UMSOM), we will evaluate current legal instruments, guidelines and frameworks, and their implementation, and use these to develop new and innovative governance frameworks to support data science health research in Nigeria. We will also implement mixed research methods to prospectively evaluate the knowledge, attitude and practices (KAP) of data scientists and ethics committees to current and emerging ELSI of data science research in Nigeria. Given the novelty of data science in Nigeria, we will implement general and specific, short and medium-term training in ethics of data science research in Nigeria for data science researchers and an introduction to data science for members of ethics committees reviewing data science research projects.