A maximum of the top 10 entries will be published in the Canadian Journal of Bioethics AND given a free 1-year CBS student membership.
The authors of the highest ranked submissions will also be granted free registration at the 31st CBS Annual Conference, in Toronto in June 2020 (up to a maximum of two undergraduate and two graduate students).
To enter, write a 2000-3000 word argument-based research commentary on one of the following:
Describe and justify the role, if any, that bioethics/bioethicists should play in relation to artificial intelligence and emerging health technologies.
In 2018, the Nuffield Bioethics Committee reported that biases in AI algorithms may reflect the values, beliefs, and prejudices of AI developers. Justify the extent to which the corresponding impact on healthcare and health equity should or should not be mitigated and what oversight mechanisms would be ethically appropriate.
The power in machine learning resides in unfettered access to large and complete datasets. In the interest of AI-based medical progress, justify what role, if any, the principle of autonomy ought to have when it comes to individual patients’ medical data.
An argument-based research commentary, of the author’s choosing, that brings together the topics of ethics, health, and AI/emerging technologies.
Both English and French submissions will be accepted.
Essays should be formatted according to Author Guidelines set by the Canadian Journal of Bioethics.
In a separate document, include a cover page indicating your name and current degree program. To ensure anonymity, no identifying information should be included on the actual submission.
Please email all submissions to: email@example.com
We look forward to receiving your submissions!
Please note that the free registration for the CBS Annual Conference does not include travel or accommodation expenses. Also, submissions to the Writing Contest are not the same as submissions to present your work at the CBS Annual Conference. You can submit an abstract for a conference presentation on the associated webpage.