The case for banning cookie banners

What It Covers

The Vergecast covers two technology topics: Saint John's professor Kate Klonick argues cookie consent banners should be eliminated entirely rather than reformed, and Verge senior reviewer Allison Johnson tests Google Maps' Ask Maps feature, which uses Gemini AI to plan real-world itineraries based on user-specified criteria like transit routes, weather, and time constraints.

Key Questions Answered

• •Cookie Banner Origins: The EU's e-Privacy Directive never mandated pop-up banners — the regulation only required users receive the right to refuse data processing. Industry lawyers and lobbyists collectively interpreted compliance as banner pop-ups to avoid fines, creating a de facto standard that calcified over 15-25 years without regulatory challenge or meaningful user protection.
• •Manufactured Consent Problem: Cookie banners create a false sense of regulatory accountability on both sides. Regulators point to banners as proof privacy is addressed; companies point to user clicks as proof of consent. Neither outcome protects users, since the underlying ad-tracking technology has long since evolved beyond cookies into methods banners never address or restrict.
• •The Case for Zero Banners: Klonick argues users are better off with no cookie banners than the current system. Eliminating banners removes the regulatory detente that blocks innovation, forcing genuine legislative conversation about modern tracking harms. The compliance infrastructure companies built around banners costs them little now, giving them zero incentive to pursue better privacy solutions.
• •Brussels Effect and Regulatory Capture: When one large market regulates technology design, transnational companies adopt that standard globally because maintaining separate systems is too costly — the same dynamic as California's car emissions standards reshaping all US vehicles. This means EU cookie law effectively governs American users, while US tech companies unilaterally dictate product design for European users.
• •Ask Maps Practical Use Case: Google Maps' Ask Maps feature processes natural language requests combining multiple criteria simultaneously — transit availability, weather conditions, time constraints, and location type — returning a sequenced itinerary with departure times. Standard Maps search requires manual filter stacking; Ask Maps collapses that into a single conversational query, reducing planning time for multi-stop outings.
• •AI Personalization Ceiling: Ask Maps currently underperforms on personalization by recommending places users have already visited, failing to cross-reference location history Google Maps already stores. The feature handles fuzzy conceptual searches well — finding laptop-friendly cafes open past 4PM — but requires explicit prompting to exclude known locations, revealing a gap between available user data and active recommendation logic.