Margaret H. McKay

Program Leader, Digital Privacy and Security and AI for Logistics, National Research Council of Canada
 https://nrc.canada.ca/en/corporate/contact-us/nrc-directory-science-professionals/margaret-mckay

Margaret H. McKay, B. Sc., M. Sc., J.D., L.L.M.

Margaret McKay leads the Digital Privacy and Security and the AI for Logistics R&D programs at the National Research Council of Canada, including ethics components for both programs. Previously, she has held a variety of management and advisory roles in ethics, program and project management, performance measurement, policy and risk, and intellectual property law. She is a member of the NRC Research Ethics committee. Her publications include work on legal challenges to transparency for artificial intelligence systems. Margaret has been an in-demand speaker on topics at the intersection of law and technology for over twenty years.

Social Profiles

All Sessions by Margaret H. McKay

  • Tuesday, April 30


  • 14:10  - 14:55
    SESSION KEYWORDS: Artificial intelligence, Ethical AI, Transparency, Privacy

    SESSION ABSTRACT

    The rise of artificial intelligence (AI) as a research tool has significant implications for research ethics boards. Some institutions may transfer broad AI review responsibilities on to REBs, while other REBs may consider AI tools only within specific proposals for research involving human participants. Both scenarios will present challenging questions requiring REB members to apply core understandings of how AI works and how to apply principles of ethical AI in the field of the research project. Facilitated by some of Canada’s leading experts in AI ethics, this workshop will provide participants with a solid grounding in the nature of AI tools and advances in AI ethics as well as examples of AI ethics challenges to date. Participants will then leverage this information in smaller-group discussions on how AI principles can apply to REB assessments in specific research disciplines (e.g. medicine, social science, etc.). Topics of discussion will include: choosing amongst the various existing ethical AI frameworks (e.g. the Montreal Declaration in Canada, the Berkman-Klein Principled AI Framework in the USA, and the Digital Catapult Ethical Framework in the UK), reconciling inconsistencies between different frameworks, addressing the underlying tension between individual ethical principles (e.g. participant privacy versus data transparency), and how AI-specific guidance is situated within the broader landscape of research ethics and existing regulatory frameworks.
    Sessions

  • 15:05  - 15:50
    SESSION KEYWORDS: Artificial intelligence, Ethical AI, Transparency, Privacy

    SESSION ABSTRACT

    The rise of artificial intelligence (AI) as a research tool has significant implications for research ethics boards. Some institutions may transfer broad AI review responsibilities on to REBs, while other REBs may consider AI tools only within specific proposals for research involving human participants. Both scenarios will present challenging questions requiring REB members to apply core understandings of how AI works and how to apply principles of ethical AI in the field of the research project. Facilitated by some of Canada’s leading experts in AI ethics, this workshop will provide participants with a solid grounding in the nature of AI tools and advances in AI ethics as well as examples of AI ethics challenges to date. Participants will then leverage this information in smaller-group discussions on how AI principles can apply to REB assessments in specific research disciplines (e.g. medicine, social science, etc.). Topics of discussion will include: choosing amongst the various existing ethical AI frameworks (e.g. the Montreal Declaration in Canada, the Berkman-Klein Principled AI Framework in the USA, and the Digital Catapult Ethical Framework in the UK), reconciling inconsistencies between different frameworks, addressing the underlying tension between individual ethical principles (e.g. participant privacy versus data transparency), and how AI-specific guidance is situated within the broader landscape of research ethics and existing regulatory frameworks.
    Sessions




Share

Margaret H. McKay