Landlords' go-to tool to set rent prices to be gutted under RealPage settlement (arstechnica.com)

The Department of Justice reached a proposed settlement with RealPage, the market-leading landlord revenue‑management software vendor, after alleging the company enabled landlords to coordinate and artificially raise rents across U.S. markets. The DOJ’s complaint said RealPage collected daily, sensitive pricing and concession data from participating landlords, making it easy to see competitor behavior and to identify where landlords could swap modest rent increases for larger ones or cut back renter-friendly concessions. The settlement, which admits no wrongdoing and carries no financial penalty for RealPage, is framed by the DOJ as a step to “restore free market competition” amid continued rent growth (BLS: 3.5% year-over-year) and affordability pressure. For the AI/ML community this is a notable regulatory intervention into algorithmic pricing and data‑sharing practices. Technically, the case centers on the effects of pooled, near‑real‑time market data feeding automated pricing models: such inputs can create coordinated outcomes even without explicit collusion. The decision could prompt product changes — limits on cross‑customer data aggregation, stricter privacy/antitrust compliance, transparency about model recommendations, and shifts in how dynamic‑pricing systems are trained and validated. It also signals increased scrutiny of commercial ML systems whose recommendations materially influence competitive markets, raising questions for developers about dataset provenance, feature design, and monitoring for anti‑competitive externalities.