Using AI at Children's and Women's: Guidance for Ethical and Value-Aligned Practice

Using AI at Children's and Women's: Guidance for Ethical and Value-Aligned Practice

by Haley Foladare

Humanities, Social Sciences & Thought AI & Society UBDigital and Information technology: general topicsUBJDigital and information technologies: social and ethical aspects
🎙 Haley Foladare 👥 251 📅 April 2, 2026 ⏱ 48 min 👁 14 📄 expert opinion 🧭 2026-08-16
Available in: English (current) Français

Keywords

AI biasethical frameworkshealth equityinstitutional guidanceresponsible AI

Summary

This presentation by Haley Foladare, Digital Health Research Manager at WHRI, provides guidance for ethical and value-aligned use of AI at Children’s and Women’s Health Centre. It begins with a land acknowledgement and emphasizes that AI is not neutral, reflecting colonial and capitalist worldviews. The talk covers common sources of AI bias (empathy, environment, evidence) and how they disproportionately affect marginalized groups, using the example of heart attack misdiagnosis in women. It introduces the Pan-Canadian AI for Health Principles as a high-level ethical framework. The presentation then details institutional resources: PHSA’s AI research toolkit, guidance on using generative AI for research work, and the AI and research working group, as well as UBC’s principles and library resources. It highlights the importance of using approved tools like Copilot within organizational tenants. A specific initiative is described: a pilot for AI-assisted translation of research documents with human review to ensure cultural and gender inclusivity. The talk concludes by encouraging researchers to engage with these resources and to consider equity and bias throughout the AI lifecycle.

173 words

Critical Evaluation

Value of the Information & Strength of the Argument

The presentation provides valuable information on AI bias and ethical frameworks, offering practical guidance for researchers. The argumentation is coherent, building from general principles to specific institutional resources. The speaker effectively uses examples, such as the heart attack misdiagnosis, to illustrate bias. However, the talk is more descriptive than analytical, and some claims could be strengthened with more detailed evidence.

Scientific Rigor, Source Quality, Title Accuracy

The presentation references several institutional and ethical frameworks, including the Pan-Canadian AI for Health Principles, PHSA guidance documents, and UBC resources. These are credible sources, though not all are formally cited with URLs. The title accurately reflects the content, which focuses on ethical and value-aligned AI practice. The talk is well-structured and aligns with the stated learning objectives.

133 words

Title / Content Match

The title accurately reflects the content, which provides guidance on ethical and value-aligned AI use in a healthcare research setting.

Quality & Reliability

7/10

The presentation is grounded in recognized ethical frameworks and institutional guidance, and the speaker demonstrates expertise in digital health research. However, the content is largely based on expert opinion and institutional resources rather than original research, and some claims lack direct citations.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

  • Pan-Canadian AI for Health Principles — Ethical framework endorsed by PHSA for AI in healthcare
  • PHSA AI research toolkit — Comprehensive guide for researchers using AI
  • PHSA guidance on generative AI for research work — Guidance for using GenAI in research tasks
  • PHSA generative AI interim direction and guidance — Staff guidance for using Copilot at PHSA
  • UBC principles for GenAI use — Broad principles for AI use at UBC
  • UBC library resources on generative AI in research — Curated resources for researchers

Concurring Sources

  • Pan-Canadian AI for Health Principles — Endorsed by PHSA, aligns with the ethical framework discussed.
  • PHSA AI research toolkit — Developed at CW, provides actionable considerations for AI research.

Contribution & Novelties

The presentation offers a practical overview of AI ethics and bias in a healthcare research context, emphasizing institutional resources and value alignment. It highlights the importance of considering equity and Indigenous perspectives in AI use. The discussion of a pilot for AI-assisted translation with human review is a novel initiative.

Pour aller plus loin :

88 words

Radar Profile

The radar profile shows moderate to high scores across all dimensions, with the highest in quality of information and reliability, reflecting the presentation's solid grounding in institutional guidance. The lower score in technical level indicates that the content is accessible to a general research audience rather than highly technical.

Reliability 7/10