Canada faces a housing crisis as rent and mortgage costs escalate. Substantial supply and demand gaps mean that existing unhoused and housing insecure populations could rise dramatically without intervention. Organizations and governments are increasingly using data and artificial intelligence (AI) in homelessness management, housing allocation and real estate markets to improve resource matching, predict trends and optimize housing support. While data and AI-driven practices aim to improve distributive efficiency, these technologies pose serious concerns around privacy, discrimination and bias. They reflect broader ideologies, such as technological solutionism, that disproportionately harm marginalized and vulnerable communities. Moreover, the real estate sector is employing data and AI in the form of “proptech” to financialize and commodify housing and renter-tenant relations. This approach reduces individuals to data points for profit maximization, reinforcing social injustices related to surveillance, sorting and classification. This working paper highlights the need for harmonized housing policies that materially recognize the deep and complex social, political and economic motivations behind the use of data and AI in the Canadian housing crisis, with the goal of ensuring equitable and meaningful change.
