Dr. Terrence Stewart, PhD

Senior Research Officer

Terrence Stewart

Dr. Stewart’s research involves analysing brains and human behaviour, identifying the underlying algorithms, building computer simulations of those algorithms, and evaluating those algorithms for industry-relevant energy-efficient AI solutions. He was a key team member behind the world’s largest functional brain model (“A large-scale model of the functioning brain,” Science, 2012). A core part of his overall research has been evaluating AI systems, comparing AI performance to human performance, and adapting experimental psychology methods to be applicable to evaluating AI systems.

All Sessions by Dr. Terrence Stewart, PhD

  • 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

Dr. Terrence Stewart, PhD