A consumer watchdog has issued a warning about Google’s AI agent shopping protocol – Google says it’s wrong

Shortly after Google Announce A new global trade protocol for AI-based shopping agents, the consumer economics watchdog has sounded the alarm.

in A viral post now on X Viewed nearly 400,000 times, Lindsay Owens wrote on Sunday: “Big/bad news for consumers. Google came out today with an announcement about how they plan to integrate shopping into their AI offerings including Search and Gemini. The plan includes ‘personal upselling.’ That is, analyzing your chat data and using it to overcharge you.”

Owens is executive director of the Center for Consumer Economics Research Cooperative basis. Her concern stems from looking at Google’s roadmap And also delve into some From the detailed specification documents. The roadmap includes a feature that will support “deal uplift,” which can help merchants promote more expensive items to AI-powered shopping agents.

It also pointed to Google’s plans to adjust prices for programs such as new member discounts or loyalty-based pricing, which represents a major challenge. Google CEO Sundar Pichai described When he announced the new protocol at the National Retail Federation conference.

After TechCrunch inquired about Owens’ claims, Google responded publicly to X and spoke with TechCrunch directly to deny the veracity of her concerns.

In a post on X, Google He answered that“These claims about pricing are inaccurate. We strictly prohibit merchants from displaying prices on Google that are higher than what appears on their site. 1/ “Deal Upgrade” is not about overcharging. It is a standard way for retailers to offer additional options of premium products that people might be interested in. It is always the user’s choice as to what they want to buy. 2/ “Live Deals” are an experiential experience that enables merchants to offer a deal *at a lower price* or add additional services like free shipping – it cannot be used to bump up prices.”

In a separate conversation with TechCrunch, a Google spokesperson said that Google’s agent does not have functionality that allows it to change a retailer’s prices based on individual data.

Owens also pointed out that Google’s technical documentation When dealing with the identity of the shopper Say the following: “Domain complexity should be hidden in the consent screen displayed to the user.”

A Google spokesperson told TechCrunch that this isn’t about hiding what the user agrees to, but rather about consolidating actions (Get, Create, Update, Delete, Cancel, and Complete) rather than having the user agree to each one individually.

Even if Owens’ concerns about this specific protocol are as nonsensical as Google asserts, its general premise is still worth some thought.

She warns that shopping agents created by big tech companies may one day allow merchants to customize prices based on what they think you’re willing to pay after analyzing AI conversations and your shopping patterns. This is instead of charging everyone the same price. She calls it “monitoring pricing.”

Although Google says its agents can’t do such a thing now, it’s also true that Google is, at its core, an advertising company that serves brands and merchants. Last year a federal court ordered Google to change a number of search business practices After the ruling, the company engaged in anti-competitive behavior.

While many of us are excited to welcome a world where we’ll have a team of AI agents to handle annoying-for-us tasks (rescheduling doctor’s appointments, searching for replacement mini-blinds), it doesn’t take a fortune teller to see what kinds of abuse might be possible.

The problem is that the big tech companies that are best positioned to build agentic shopping tools also have mixed incentives. Their businesses depend on servicing vendors and collecting data about consumers.

This means that AI-powered shopping could be a huge opportunity for startups to build autonomous technology. We are seeing the first few sprinkles of AI potential. Start-up companies such as dupewhich uses natural language queries to help people find affordable furniture, and Pennywhich uses images and text for thrifty fashion, is one of the first entrants in this space.

Until then, the old adage may still ring true: Buyer beware.