Amazon announced this morning it can begin to leverage generative AI to assist customers higher understand what customers are saying a couple of product, without necessarily having to read through dozens of individual reviews. The retailer says it can use the brand new technology to offer a brief paragraph of text right on the product detail page that may highlight the product features and customer sentiment mentioned across the client reviews.

This blub of text might be used to get an overall sense of the common themes across the reviews more easily, Amazon noted.

Along with the summary text, Amazon may even highlight key product attributes as clickable buttons. For instance, if a customer desired to know in regards to the product’s “ease of use” or “performance,” they might tap a button to see just those reviews that mention those terms.

Amazon had already offered an identical feature by surfacing frequently-used words present in the reviews, which were also available as clickable buttons.

The brand new AI-powered features will initially be rolled out to a subset of U.S. shoppers on mobile devices across a “broad selection” of products, Amazon said. During these tests, the corporate will work to learn and fine-tune its AI models to enhance their effectiveness. It’s also working to expand the highlights feature over time to incorporate additional categories, because the feature becomes more broadly available to customers.

In fact, the AI summaries will only be pretty much as good as the information they ingest. And Amazon has struggled for years with fake and misleading product reviews, including paid reviews.

In 2021, the corporate admitted it had blocked 200 million fake reviews the yr prior, for instance. It has also tried to crack down on the sources of pretend reviews for years via lawsuits and other actions, including suing sellers who bought fake reviews. Last yr, it also sued the admins from 10,000 Facebook groups who were engaged in fake review brokering.

More recently, the FTC got involved, forcing a complement maker to pay $600K in a case involving hijacked Amazon reviews — a situation where products are combined right into a single listing to spice up the reviews of 1 product with the great reviews of one other.

With the growing capabilities of AI, fake reviews may now be even tougher to identify because the technology advances to sound more human, which could lead on to a different explosion of pretend reviews. That will make Amazon’s AI-powered summaries of reviews less helpful, if the corporate doesn’t produce other technique of keeping AI-written reviews off its site.

Amazon addresses the priority around fake reviews today, saying it can only summarize those reviews from verified purchases. Plus, it continues to speculate “significant resources” to proactively stop fake reviews.

“This includes machine learning models that analyze hundreds of knowledge points to detect risk, including relations to other accounts, sign-in activity, review history, and other indications of surprising behavior, in addition to expert investigators that use sophisticated fraud-detection tools to research and stop fake reviews from ever appearing in our store,” notes the retailer.