Leveraging AI in Canada’s Social Response to COVID
Data and AI helping anticipate social needs before they become crises.
Project Budget* - $0.7M
Partner Co-investment* - $0.1M
Supercluster Co-investment* - $0.6M
The COVID-19 pandemic inflicted isolation, declining incomes, reduced access to care, and stresses that present new challenges to Canadian’s social wellbeing. Issues like homelessness, mental health, addictions, domestic violence, and community safety have been amplified. To date, our social responses during COVID-19 have been primarily reactionary rather than planned and proactive.
Canada has a robust social safety net to help individuals and communities tackle the challenges – but there are hurdles for people to navigate the complex web of 250,000+ supports across the country. As a result, many fall through the cracks.
This project is harnessing the power of Artificial Intelligence and Machine Learning (AI/ML) to give decision makers insights that can focus their responses to COVID-19 and mitigate its long-term social impacts. AI is a broad term referring to the use of computers to replicate human intelligence. Artificial general intelligence hasn’t been invented yet; the field is focused on developing artificial narrow intelligence such as natural language processing and computer vision. ML is a subfield of narrow AI referring to the use of computers to learn through experience (usually from large datasets) without being explicitly programmed.
The project is led by HelpSeeker, a social innovation and technology B-Corp active in 200+ communities to support systems change to resolve complex social issues. HelpSeeker has brought together A Way Home Canada, AltaML, Corsac Technologies, Canada Mortgage and Housing Corporation, the Faculty of Social Work at the University of Calgary, and the Canadian Observatory on Homelessness at York University.
Data is a prerequisite for machine learning, and the higher the volume, dimensionality and breadth of data, the higher the quality and variety of signals that can be generated to make predictions and create value. The foundation of the project is an existing HelpSeeker dataset of more than 134,000 services across Canada, as well as hundreds of thousands of interactions from users with these services. A new data pipeline will bring together information from 40+ existing Open Data sources from various governments, public agencies, and community groups. This integration will end the siloed nature of the information and help target COVID-19 responses related to homelessness, domestic violence, and suicide.
Once the various datasets have been acquired, AltaML will process and mine the data for insights and will build predictive AI/ML solutions to help decision makers anticipate When the data is brought together, it will be analyzed, organized, and structured so AI can process this coordinated pan-Canadian dataset. This AI processing will give decision makers real-time data and insights to help anticipate needs before they become crises using evidence-based information, rather than guesswork. AltaML is the strategic and technical AI/ML expert and will collaborate closely with the partner subject matter experts to ensure alignment between the data, the problem definitions and the resulting AI/ML solutions.
The project team is aiming to learn from the work being done to prepare a second phase that would expand to other social service areas in mental health, housing need, and community safety.