Justice dept. requires Realpage end sharing competitively sensitive information (www.justice.gov)

The Justice Department’s Antitrust Division filed a proposed settlement with RealPage Inc. to resolve claims that the company’s revenue‑management software and business practices enabled algorithmic coordination in U.S. rental markets. The complaint alleges RealPage used nonpublic, competitively sensitive data supplied by landlords to set rents, built product features that discouraged price decreases and aligned pricing across competitors, and hosted meetings where rival property managers exchanged sensitive information. If the consent judgment is approved, RealPage would be required to stop those information‑sharing and coordination practices; the settlement will be published under the Tunney Act with a 60‑day public comment period before a federal court may enter final judgment. For the AI/ML community this is a clear signal that algorithmic pricing tools are subject to rigorous antitrust scrutiny: models and product features that leverage nonpublic competitor data or that structurally facilitate tacit collusion can create legal risk. Technical implications include stricter data governance and provenance requirements, the need to avoid using competitor-sourced private inputs, redesigning optimization objectives to permit independent price movements, and adopting transparency, auditing and privacy‑preserving techniques (e.g., differential privacy, access controls, recordkeeping) to demonstrate independent decision‑making. The case sets an important precedent for how regulators will treat machine‑assisted market coordination and should prompt companies to build compliance into model design and deployment.