Centering AI Within the Political Economy of Housing

My commentary seeks to re-embed automated mortgage futures and the prospects of AI envisioned by Richard Burrows and his colleagues within the 21st century political economy of housing. First, I suggest treating property markets as historical and ongoing sites of multisided datafication and acute social classification, in order to situate how granular data and algorithms reshape market structures and housing politics, and how algorithmic systems transforms the construction of mortgages and risk, along with the creation and destruction of housing wealth. Second, I argue that fairness and privacy, while important for regulation, become an analytical trap in pursuing fairer housing futures once data externalities and organizational dynamics are taken into account. Finally, I discuss why, in the era of big geodata, shifting insurance interests, and heightened climate risks, foregrounding a spatial approach is necessary to enrich our understanding of mortgage futures and the inequalities they renew and lock in.