U.S. Rep. Castor takes aim at High Rents and Predatory Housing Practices
WASHINGTON, D.C. - U.S. Rep. Kathy Castor (FL-14) introduced the Housing Price Transparency Act to help make housing more affordable for renters by disincentivizing predatory AI algorithmic and surveillance pricing. Rents rise when landlords implicitly collude through computer software and algorithms to raise prices together. This new predatory price-fixing demands new solutions to keep rents affordable.
"The cost of living is already soul-crushing, and rental pricing algorithms make it worse as invisible systems quietly push rents up, putting profits before people who need affordable homes," said Rep. Castor. "Rental software can look at a lot of data-things like what other landlords charge-and suggests rent prices that maximize profit and push housing even further out of reach. Instead, the data should be kept out in the open, algorithms disclosed and collusion ended to protect renters from corporate greed and unreasonable rent increases."
The Housing Price Transparency Act is a commonsense approach that would require transparency in pricing practices and give renters more power to combat predatory models. Specifically, the bill would:
Require disclosure by companies that use an algorithm to help set monthly rental prices.
Empower the FTC to pursue unfair and deceptive practices in the rental housing market.
Authorize state attorneys general to bring civil enforcement actions.
Establish a private right of action, allowing individuals to sue within two years of an alleged violation, with statutory damages of $10,000 per violation.
The bill builds on Rep. Castor's record of standing up for consumers, including championing the largest piece of Housing legislation in decades, targeting hidden fees in the hotel and timeshare industries, and leading legislation for pricing transparency in government deals with Big Pharma.
BACKGROUND:
Algorithmic pricing, the use of formulas to automatically set prices to maximize profit, is increasingly common across industries, including residential rentals. When these formulas incorporate personally identifying information, the practice is known as surveillance pricing, which is distinct from ordinary dynamic pricing based on real-time supply and demand.
While new AI-driven tools can simplify the process of finding and comparing housing, they also carry risks: discrimination, lack of transparency in decision-making, and misuse of sensitive personal data.
Full text of the bill is available
HERE.