By: Kathleen Sandusky
21 Jun, 2022
Like most industries, the field of AI is now reckoning with its lack of diversity, waking up to the effects of bias and siloed perspectives that can bring about disastrous results like racial disparities in voice recognition and underdiagnosis of disease in women and under-served patient populations. These missteps reduce effectiveness and damage public trust in AI, and limit the many opportunities for novel ideas and solutions that come from diversity. Additionally, talent shortages in Canada’s growing tech industry may be due in part to a lack of welcoming work and learning spaces for diverse people.
“It’s the first time I’ve been a part of a women-only tech group, and it feels innately safe and welcoming.”
–Paige Lewis, AI4Good Lab Toronto Cohort 2022
Now in its sixth year, the AI4Good Lab is working to address the need for gender diversity in AI with a yearly seven-week summer training program that has grown from its first site in Montreal in 2017, to the second site at Edmonton’s Amii in 2019, to this year’s launch of its third site at Toronto Metropolitan University (TMU; formerly Ryerson University).
Supported by founding partners OSMO and CIFAR through the Pan-Canadian Artificial Intelligence Strategy, the AI4Good Lab emphasizes mentorship and curiosity-driven learning to prepare women and gender-diverse participants for a career in AI. This year’s 90 participants attend virtual lectures and workshops with leading AI researchers, followed by on-site training at their host institutions. They collaborate in local teams, striving together to create a real-world machine learning project to present in a culminating competition in the final week. They also attend networking events with tech startups and companies that are eager to recruit from this talented cohort.
One participant is Paige Lewis, a TMU biophysics and computer science student. On top of her studies and machine learning co-op placement, she occupies her spare time by building curiosity-driven algorithms, including a tool to predict book ratings and a personalized language learning module that uses open-source datasets.
Despite her talent and innate affinity for machine learning, Paige hasn’t always felt welcomed in tech. “There’s this pressure of having to exist as a woman in what can be a very male space, feeling you have to look a certain way, talk a certain way, dress a certain way,” she reports. “When I found out about this program, I was really excited to learn in a group where being a woman wouldn’t be an issue, and it’s been so much fun. It’s the first time I’ve been a part of a women-only tech group, and it feels innately safe and welcoming.”
That safe and welcoming environment is just what host university TMU is aiming for. “The increased participation of women and people of diverse genders and backgrounds is very much needed in STEM,” comments Johannes Dyring, Assistant Vice-President, Business Development and Strategic Initiatives in the Office of the Vice-President Research and Innovation at TMU. “Diversity and inclusion are key to Canada’s competitiveness, and TMU is proud to cheer on the contributions of women and people of diverse genders who have so much talent and insight to add to this important and growing field of AI.”
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.