Can Amazon AI voice replace customer reviews? It’s starting to try

Anyone who has ever gone in search of a product review on Amazon knows how valuable the experience of other shoppers can be, and how easy it is to fall down the rabbit hole of customer comments, from five-star raves to one-star takedowns — sometimes hundreds of words to get to the point. As Amazon continues to roll out AI features it says will make shopping easier, AI-generated audio descriptions of products are in the mix and scraping that customer commentary — maybe ultimately settling into a position to replace it as a go-to source of buying information. 

Called “Hear the Highlights,” the AI-voiced product descriptions rely on a large language model to script the summary based on a variety of sources, pulling from Amazon’s product catalog, customer reviews, and information from across the web, and then translating the content into short-form audio clips. The summaries began rolling out during the summer on select products to a subset of U.S. customers and have now reached all U.S. customers as a button in the mobile shopping app, scaling up to cover over one million products.

A unique appeal of Amazon, and other e-commerce options, has always been the ability to get information from actual users, not just product descriptions. Of course, bogus reviews have long been a problem for Amazon, even though it bans use of paid promotion and other inauthentic forms of review writing. You still have to sort through various efforts to game the system, and in recent years, signs that the newest review writers are chatbots like ChatGPT. But actual people sharing their actual, idiosyncratic experience with a product — customers as a source of information, and informed decision making — have been a key part of the learning process from clothing and shoe sizes to safety and more narrow questions: When purchasing a new toaster, does it do bagels, is the timer setting accurate, how easy is it to clean the crumb tray?

Can AI improve on that? Reviews are by nature unwieldy in the mass individuality, but human readers have proven pretty adept at distilling what they need from the human chaos. In some sense, the brain of the average Amazon review reader is a pretty good large language model, skimming and picking out key words and key information, so an AI will have to do it at least as well as a human would if it’s to add to the customer experience as promised. 

AI and cognitive overload

AI does have its advantages. For one, it won’t experience cognitive overload when facing an electric tea kettle on Amazon with over 32,000 reviews. It can comb through the data, but can it gives us only what we need or want to know? That can still be tricky for AI to get right, and it may be inherently problematic to mix product catalogs, customer reviews, and web information into a single distillation – with…