A call for an ethical framework when using social media data for artificial intelligence applications in public health research
A call for an ethical framework when using social media data for artificial intelligence applications in public health research
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Full item details
- creativework.keywords - en
- ethics
- ethical research
- social media
- artificial intelligence
- dc.contributor.author
- Gilbert, Jean-Philippe
- Ng, Victoria
- Niu, Jingcheng
- Rees, Erin E.
- dc.date.accessioned
- 2024-07-05T19:44:17Z
- dc.date.available
- 2024-07-05T19:44:17Z
- dc.date.issued
- 2020-06
- dc.description.abstract - en
- Advancements in artificial intelligence (AI), more precisely the subfield of machine learning, and their applications to open-source internet data, such as social media, are growing faster than the management of ethical issues for use in society. An ethical framework helps scientists and policy makers consider ethics in their fields of practice, legitimize their work and protect members of the data-generating public. A central question for advancing the ethical framework is whether or not Tweets, Facebook posts and other open-source social media data generated by the public represent a human or not. The objective of this paper is to highlight ethical issues that the public health sector will be or is already confronting when using social media data in practice. The issues include informed consent, privacy, anonymization and balancing these issues with the benefits of using social media data for the common good. Current ethical frameworks need to provide guidance for addressing issues arising from the use of social media data in the public health sector. Discussions in this area should occur while the application of open-source data is still relatively new, and they should also keep pace as other problems arise from ongoing technological change
- dc.identifier.citation
- Gilbert J-P, Ng V, Niu J, Rees EE. A call for an ethical framework when using social media data for artificial intelligence applications in public health research. Can Commun Dis Rep 2020;46(6):169–73. https://doi.org/10.14745/ccdr.v46i06a03
- dc.identifier.doi
- https://doi.org/10.14745/ccdr.v46i06a03
- dc.identifier.issn
- 1481-8531
- dc.identifier.uri
- https://open-science.canada.ca/handle/123456789/2664
- dc.language.iso
- en
- dc.publisher
- Public Health Agency of Canada
- dc.rights - en
- Creative Commons Attribution 4.0 International (CC BY 4.0)
- dc.rights - fr
- Creative Commons Attribution 4.0 International (CC BY 4.0)
- dc.rights.uri - en
- https://creativecommons.org/licenses/by/4.0/
- dc.rights.uri - fr
- https://creativecommons.org/licenses/by/4.0/deed.fr
- dc.subject - en
- Health
- dc.subject - fr
- Santé
- dc.subject.en - en
- Health
- dc.subject.fr - fr
- Santé
- dc.title - en
- A call for an ethical framework when using social media data for artificial intelligence applications in public health research
- dc.type - en
- Article
- dc.type - fr
- Article
- local.article.journalissue
- 6
- local.article.journaltitle
- The Canada Communicable Disease Report
- local.article.journalvolume
- 46
- local.pagination
- 169–73
- local.peerreview - en
- Yes
- local.peerreview - fr
- Oui
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