signed a lease in October 2017 for's cheapest floor plan for the following year. But come Christmas, the West Campus tower's management told him that the floor plan was sold out. They gave Maksoud two options: Pay more for a different unit, or find a new apartment.After settling for $4,500, Maksoud learned from previous Ion renters that his experience was not caused by a"software malfunction," as the property management company insisted.
"The problem is that they have all this data," Maksoud said."They know exactly how much they can squeeze you [in rent], and they do." Now a University of Texas law student, Maksoud advocates at City Hall against the housing crisis.– of Americans say housing affordability is a major problem in their communities, according to a 2021survey.
"Whenever you program an algorithm to do something, you have to ask a very specific question. You have to feed it data to train on, and [this data] might be sourced from a bad source that has biases," said Andrew D. Selbst, a postdoctoral scholar at, a New York-based nonprofit. Predictive analytics draw on data from potential tenants' social media profiles, criminal history, credit scores, and other personal information.
What might solutions involve? Maksoud said his work focuses on electing government officials who will address the housing crisis and on spreading general awareness across Austin. Selbst said transparency into choices made in designing algorithms, along with specific legislation, could help."It's hard," Selbst said."You'd also need community input into what the algorithm should be allowed to do and what counts as discrimination. None of that has been done yet.
Humber suggests that renters should be able to defend themselves against poor credit scores and that people experiencing evictions have greater right to counsel; she also supports an education campaign about the disparate impacts of tenant-screening algorithms."A lot of people that are harmed by these technologies don't even know the prevalence of these tools," Humber said.
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