Category: Weekly

📢 Exciting News! The first-ever Canada-Africa Academic Collaborations Conference (CAACC) 2025 is set to take place on February 27, 2025. This virtual event will bring together scholars, researchers, and professionals from Canada and Africa to foster meaningful academic partnerships.

With the theme “Academic Collaboration for Posterity,” this virtual conference will create a dynamic platform for discussing research, knowledge-sharing, and cooperative initiatives including education, policy, climate, and health that can drive sustainable development in both regions. The event is co-chaired by Pauline Omolo (University of Nairobi, Kenya) and Seyram Afealete (Western University, Canada) and promises an engaging program featuring keynote addresses, panel discussions, and thematic presentations.

📅 Date: February 27, 2025
⏰ Time: 8:45 AM – 3:25 PM (EST)
📍 Location: Online (Zoom Webinar)
🔗 More details & registration: The Africa Institute – CAACC 2025

Grounded Roots, Open Wings (GROW) is seeking two dedicated and passionate individuals to join its Board of Directors for a three-year term. GROW provides comprehensive pre- and postnatal care to individuals in the community who do not have a family doctor, as well as wrap-around support for those facing socioeconomic and psychosocial challenges.

Role & Responsibilities

Board members play a crucial role in providing governance, financial, and strategic oversight to help advance GROW’s mission. The Board meets once a month, with a combination of in-person and virtual meetings.

Who Should Apply?

Candidates with strong leadership and strategic skills who align with GROW’s mission and can effectively communicate its vision are encouraged to apply. This year, specific skills of interest include:
✅ Experience in fundraising and development
✅ Governance experience
✅ Coordination of volunteers

Commitment to Diversity

GROW is committed to broadening the diversity of its Board of Directors and encourages applications from individuals with a variety of lived experiences.

How to Apply

Expressions of interest, including resumes and any questions, can be sent to growboardofdirectors@prismahcc.ca for consideration by March 31, 2025.

This is an opportunity to contribute to equitable access to prenatal and postnatal care and support individuals in need. Those with relevant skills and experience are encouraged to apply.

Written by Mina Yu, CRHESI Student Collective, Community Engaged Learning placement, Bachelor of Health Sciences, Western University

Artificial Intelligence (AI) has undoubtedly transformed healthcare. Its applications—from improving diagnostic accuracy and resource allocation to streamlining workflows—promise to revolutionize patient care. AI’s potential to reduce human error, anticipate healthcare needs, and optimize management of chronic diseases paints an optimistic picture of timely, equitable healthcare. However, beneath its transformative capabilities lies a critical challenge: algorithmic bias.

AI, lauded for its potential to minimize human biases and inconsistencies, often inherits the same inequities embedded in healthcare systems. When trained on homogeneous datasets or data that over-represent privileged groups, AI systems perpetuate existing biases, undermining efforts to address systemic disparities. For instance, a review by Celi et al. (2022) revealed that most clinical AI models are built on datasets from middle- and high-income countries, especially the U.S. and China. When the relationships within data sources used to train AI models differ from those in the populations where these models are deployed, the resulting outputs are often inaccurate. This mismatch restricts the effectiveness of AI systems, particularly in underserved and underrepresented communities, including but not limited to those in lower-income countries. Consequently, AI-driven interventions are systematically misaligned with the needs of these individuals and groups, resulting in inappropriate or inaccessible care. Rather than reducing disparities, this failure to provide suitable care exacerbates existing inequities.

One striking example involves an AI algorithm used by insurance companies to predict healthcare needs. A 2021 study (NIHCM Foundation) found that while Black patients were significantly sicker than their white counterparts, both groups were assigned similar risk scores. This bias stemmed from the algorithm’s reliance on past healthcare expenditures—a metric influenced by systemic inequities in access and treatment. Because Black patients, for structural and systemic reasons, typically receive less care despite generally experiencing worse health outcomes, their needs are inaccurately assessed. This perpetuates a harmful cycle of unmet healthcare needs, declining individual health, and widening disparities in health outcomes between populations.

For Canada, algorithmic bias intersects with the digital divide, disproportionately affecting rural, remote, and Indigenous Peoples, who are more likely that non-Indigenous people to live in remote Northern communities. This highlights gaps in socioeconomic and demographic factors, limiting these groups’ ability to benefit from AI advancements. Researchers like Anawati et al. (2024) emphasize that AI and machine learning literature is only beginning to address the absence of diversity in training data, and the real-world impacts on the health and well-being of groups already facing marginalization.

AI offers incredible promise, but its true potential lies in fostering equity, not reinforcing disparity. To bridge these gaps, recalibrating the fundamental assumptions of AI systems is essential. Incorporating diverse datasets from underserved groups and regions can help mitigate bias and extend AI’s benefits to marginalized populations. Ultimately, for AI to truly revolutionize healthcare, its development must be inclusive, addressing not just technical challenges but also the societal inequities that shape healthcare outcomes.

References

Anawati, A., Fleming, H., Mertz, M., Bertrand, J., Dumond, J., Myles, S., et al. (2024). Artificial intelligence and social accountability in the Canadian health care landscape: A rapid literature review. PLOS Digit Health, 3(9): e0000597. https://doi.org/10.1371/journal.pdig.0000597 

Celi, L.A., Cellini, J., Charpignon, M.L., Dee, E.C., Dernoncourt, F., Eber, R., et al. (2022). Sources of bias in artificial intelligence that perpetuate healthcare disparities—A global review. PLOS Digital Health, 1(3): e0000022.  https://doi.org/10.1371/journal.pdig.0000022 

Igoe, K.J. (n.d.). Algorithmic Bias in Health Care Exacerbates Social Inequities — How to Prevent It. Artificial Intelligence and Technology. Retrieved from https://www.hsph.harvard.edu/ecpe/how-to-prevent-algorithmic-bias-in-health-care/     

Johns Hopkins. (2023, May 02). How Health Care Algorithms and AI Can Help and Harm. Retrieved from https://publichealth.jhu.edu/2023/how-health-care-algorithms-and-ai-can-help-and-harm 

Morales, K. (2022, January 5). Can Artificial Intelligence Help Increase Diversity in STEM? CSUF News. https://news.fullerton.edu/2022/01/can-artificial-intelligence-help-increase-diversity-in-stem/    

NIHCM Foundation. (2021, Sept 30). Racial Bias in Health Care Artificial Intelligence. Artificial Intelligence. Retrieved from https://nihcm.org/publications/artificial-intelligences-racial-bias-in-health-care

Panch, T., Mattie, H., Atun, R. (2019). Artificial intelligence and algorithmic bias: implications for health systems. J Glob Health, 9(2):020318. https://doi.org/10.7189/jogh.09.020318 

Written by Mina Yu, CRHESI Student Collective, Community Engaged Learning placement, Bachelor of Health Sciences, Western University

In 2024, the City of London launched the Stop Tolerhating campaign in collaboration with the Centre for Research on Health Equity and Social Inclusion (CRHESI) and over 60 local organizations. This initiative aims to confront hate, racism, and other forms of discrimination and stigma through City-wide education, collaboration and empowerment activities, fostering a more inclusive and equitable community.

During an interview with Zahra, Project Coordinator for the Anti-Hate Project, Stop Tolerhating, from the Anti-Racism and Anti-Oppression Division, City of London, involved in the campaign’s development and pilot launch, their passion for this project was obvious. Zahra shared that their personal experiences navigating discrimination inspired them to be a part of this initiative. “There’s so much power in starting something in your own community,” Zahra explained, emphasizing their commitment to making resources and support accessible to those facing hate and its impacts.

The campaign employs a multi-pronged approach, blending transformative media strategies, public education, and direct engagement with equity-denied communities. Guided by principles of intersectionality, the campaign is based on the knowledge that individuals often experience discrimination through overlapping identities such as race, gender, sexual orientation, and ability.

The campaign’s collaborative nature is one of its greatest strengths. It draws insights from equity-denied groups—including Black, Indigenous, Muslim, and LGBTQIA+ communities—through one-on-one conversations, surveys, and guided data-sharing sessions. Zahra described how these conversations revealed unique challenges, such as the lack of resources for Indigenous health in rural areas and the rise of online hate targeting Muslim communities. These insights directly shaped the development of educational content and resources for the campaign, ensuring relevance and impact.

The campaign also addresses broader audiences through its accessible website and social media presence. The website is designed to provide quick, easy access to crisis hotlines, anti-racism education, and tools for fostering anti-racist practices for individuals and organizations in the health, social services, business and educational sectors. Social media platforms amplify these resources and provide posts that inspire reflection by presenting educational content in an approachable way.

This Stop Tolerhating team recognizes the challenges of combating hate, ranging from resistance by individuals who deny the existence or severity of discrimination to those who refuse to change—particularly when they are not directly impacted or perceive advantages in maintaining the status quo. However, Zahra emphasized the importance of grounding the campaign in facts and meaningful engagement. “We’ve received a mix of feedback, but seeing how it resonates with the community makes it worth it.”

As Stop Tolerhating evolves, the campaign will continue adapting to emerging challenges and societal needs, such as the rise of anti-Asian racism post-COVID-19. With this flexibility, the campaign remains dynamic, responsive, and rooted in its mission to build a more inclusive London. The ultimate reward is fostering a city where diversity is celebrated, and hate is no longer tolerated. The passion and leadership of those involved in this project are the driving forces behind this transformative initiative.

Together, CRHESI, the City of London, and their collaborators are proving that tackling hate requires bold strategies, sustained commitment, and the collective voices of a diverse community.