Biological data (biodata) has become a buzzword for innovations in this century. With pioneering advances in machine learning techniques and artificial intelligence, biological datasets have brought about revolutionary changes in many areas, particularly in healthcare. In this process, a host of ethical and legal issues have also come to the fore. The purpose of this paper is to address the need for a reorientation of the governance framework for human biodata. Using the case of Dinerstein v. Google, this paper argues that the data governance framework must take into account and balance interests of both fostering innovation and protecting societal values.
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Big Biological Data: Need for a Reorientation of the Governance Framework
Semantic Scholar · Law · 2022
Abstract
Biological data (biodata) has become a buzzword for innovations in this century. With pioneering advances in machine learning techniques and artificial intelligence, biological datasets have brought about revolutionary changes in many areas, particularly in healthcare. In this process, a host of ethical and legal issues have also come to the fore. The purpose of this paper is to address the need for a reorientation of the governance framework for human biodata. Using the case of Dinerstein v. Google, this paper argues that the data governance framework must take into account and balance interests of both fostering innovation and protecting societal values.