A bill to prohibit certain uses of automated decision systems to inform individualized prices, and for other purposes.

Legislative bill overview

S 3387 prohibits the use of automated decision systems (algorithms) to set individualized prices for goods and services based on personal characteristics or behavioral data. The bill restricts "algorithmic price discrimination" practices where companies use AI or machine learning to charge different prices to different consumers for the same product or service.

Why is this important

Price discrimination through algorithms is already widespread in e-commerce, airlines, and ride-sharing platforms, with consumers often unaware they're paying different prices than others. This bill addresses concerns about fairness, consumer protection, and whether such systems perpetuate discrimination based on protected characteristics like race, income level, or geography. The outcome could significantly reshape how pricing algorithms work in the digital economy.

Potential points of contention

• Business opposition: Companies argue dynamic pricing based on demand and consumer data improves efficiency and enables personalized discounts; restrictions could reduce their competitiveness and innovation
• Definitional complexity: "Automated decision systems" and "individualized prices" require precise legal definitions to avoid unintended consequences (e.g., does this affect legitimate bulk discounts or loyalty programs?)
• Enforcement challenges: Detecting and proving algorithmic price discrimination is technically difficult; determining which factors are impermissible (personal data, behavior) versus permissible (inventory levels, demand) creates implementation complexities