The podcast examines algorithmic price discrimination—the practice of charging loyal or frequent users more based on their data—and the rising wave of regulatory responses. China’s new Measures explicitly ban opaque, individualized pricing and require clear notifications of price changes, distinguishing lawful dynamic pricing from unfair personalization. Yet loopholes remain: platforms can still offer personalized coupons or recommendations based on inferred willingness to pay. Consumers are fighting back with incognito browsing and cookie clearing, while landmark cases like Trip.com signal growing legal accountability. In New York, disclosure laws now mandate transparency about data-driven pricing—with penalties for noncompliance—though enforcement challenges persist. Experts argue that effective oversight requires not just rules but regulatory algorithms capable of auditing platform behavior, alongside shared responsibility among platforms, consumers, and authorities to ensure fairness through transparency rather than secrecy.