Health Analytics Community - Monthly Meeting - April 24 2-3 PM EST

Thank you to all who participated in the community meeting yesterday and to Frank Rudzicz for the fantastic presentation.
As promised, here are the resources Frank wanted to share with the group.

From Frank:

• I wanted to share a few links for the team. These are links I put up during my talk:

1. futureoflife.org/open-letter/ai-principles/
2. digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai
3. www.microsoft.com/en-ca/ai/responsible-ai
4. montrealdeclaration-responsibleai.com

• I also wanted to draw the team’s attention to a paper of ours I mentioned, MLHOps: Machine Learning Health Operations: ieeexplore.ieee.org/document/10811924. There are some actionable workflows there people can use to deploy AI in healthcare.

Hi Noah,

I am so sorry that I forgot to include the link to register for the zoom meeting in my post, and that I'm only seeing this now.

In case you would like to join us in the future, here is the link: infoway-inforoute.zoom.us/meeting/register/tZEpf-6uqj0vE9OH2tKgq8djO9u7-dlMTtF0

Thanks,

Lisa

Hi Lisa
Could you please send the calendar invite with video link for this? Thanks

Join the Infoway Health Analytics Community on April 24th at 2:00pm EST for a presentation by Frank Rudzicz, Associate Professor at Dalhousie University for a presentation on the importance of responsible AI in healthcare.

Frank Rudzicz is an Associate Professor at Dalhousie University, founding faculty member at the Vector Institute for Artificial Intelligence, status professor at the University of Toronto, Killam Memorial Chair, and Canada CIFAR Chair in Artificial Intelligence. His work is in machine learning in healthcare, especially in natural language processing, speech recognition, and safe AI. His students have founded several companies in AI and Health that have had successful exits, including Winterlight Labs and Mutuo Health Solutions. His research has appeared in popular media such as Scientific American, Wired, CBC, and the New York Times, and in scientific press such as ACL, NeurIPS, JAMA, and Nature.

His talk emphasizes the importance of responsible AI in healthcare, especially for small and medium enterprises (SMEs). It outlines four key principles: transparency, fairness, accountability, and privacy, arguing that ethical AI is not only a moral imperative but a practical one that reduces risk, builds trust, and creates a competitive edge. Through real-world healthcare examples—like diagnostic support, report generation, and resource optimization—we illustrate AI’s transformative potential while cautioning against biases, privacy issues, and the dangers of insufficient oversight.