Ethical Issues in Data Science
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 Published On Apr 28, 2017

McGill University Centre of Genomics & Policy Director Dr. Bartha Maria Knoppers present a webinar titled, "Ethical Issues in Data Science."

Abstract
Big Data discussions often center on related privacy and security issues, to the neglect of the importance of other ethical issues in data-intensive research. The privacy protections in the European Union’s new General Data Protection Regulation, for example, although essential, must be balanced with the right of everyone to share in scientific advancement and its benefits, which originates in the 1948 Universal Declaration of Human Rights and has become the foundation of the Global Alliance for Genomics and Health's Framework for Responsible Sharing of Genomic and Health-Related Data. In this context, it is worthwhile examining whether the hitherto antinomy between privacy and security concerns and the benefits of data sharing still remains, or are health data governance frameworks, such as the 2017 OECD Recommendation on Health Data Governance, and other policies beginning to address and assuage such concerns?

Presenter
Bartha Maria Knoppers, PhD (Comparative Medical Law), is full professor, Canada Research Chair in law and medicine and Director of the Centre of Genomics and Policy, Faculty of Medicine, Human Genetics, at McGill University. She is a member of the Scientific Steering Committee of the International Cancer Genome Consortium (2009-present ), and Co-Chair of the Regulatory and Ethics Working Group of the Global Alliance for Genomics and Health. She holds four doctorates Honoris Causa and she is a fellow of the American Association for the Advancement of Science (AAAS), the Hastings Center (bioethics), the Canadian Academy Health Sciences (CAHS), and of the Royal Society of Canada. She is also an Officer of the Order of Canada and of Quebec.

Download presentation slides:
https://drive.google.com/open?id=0B4I...

Visit our webpage to see the lecture schedule and learn how to join our next live lecture:
http://www.bigdatau.org/data-science-...

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