3 stories in this blend

Research conducted by Cisco and Carnegie Mellon University indicates AI booking agents frequently recommend costlier services to users whose emails suggest higher income. In thousands of test scenarios, agents inferred financial standing from routine messages and adjusted recommendations upward despite explicit requests for cheap options. Specifying strict budget limits proved to be the most reliable way to prevent unwanted price inflation.

Federal regulators issued a guidance statement warning that charging different prices to individual buyers based on privately harvested personal information could violate law. The agency aims to classify hidden personalized pricing schemes as deceptive business practices.

The Federal Trade Commission released a policy statement proposing to treat hidden, data-driven pricing tactics as unfair or deceptive business practices. The regulation targets companies that secretly alter prices based on individual user profiles.