Available initially to “a subset of mobile shoppers in the U.S. across a broad selection of products,” the artificial intelligence tool creates a recap paragraph highlighting common themes from customer feedback.
The idea behind the ML-generated summary is to let shoppers get the gist of their peers’ impressions without having to file through a swath of reviews manually.
There’s also the question of whether AI-powered fake reviews (using ChatGPT or similar tools) are more challenging for Amazon to spot than human-written ones.
The company’s strategy includes only unleashing the summarization tool on verified purchases while using AI models that allegedly detect sketchy reviews — and calling in human investigators when needed.
“We continue to invest significant resources to proactively stop fake reviews,” Amazon Community Shopping Director Vaughn Schermerhorn said.
“This includes machine learning models that analyze thousands of data points to detect risk, including relations to other accounts, sign-in activity, review history, and other indications of unusual behavior, as well as expert investigators that use sophisticated fraud-detection tools to analyze and prevent fake reviews from ever appearing in our store.
This is the best summary I could come up with:
Available initially to “a subset of mobile shoppers in the U.S. across a broad selection of products,” the artificial intelligence tool creates a recap paragraph highlighting common themes from customer feedback.
The idea behind the ML-generated summary is to let shoppers get the gist of their peers’ impressions without having to file through a swath of reviews manually.
There’s also the question of whether AI-powered fake reviews (using ChatGPT or similar tools) are more challenging for Amazon to spot than human-written ones.
The company’s strategy includes only unleashing the summarization tool on verified purchases while using AI models that allegedly detect sketchy reviews — and calling in human investigators when needed.
“We continue to invest significant resources to proactively stop fake reviews,” Amazon Community Shopping Director Vaughn Schermerhorn said.
“This includes machine learning models that analyze thousands of data points to detect risk, including relations to other accounts, sign-in activity, review history, and other indications of unusual behavior, as well as expert investigators that use sophisticated fraud-detection tools to analyze and prevent fake reviews from ever appearing in our store.
I’m a bot and I’m open source!
Look a AI summary bot, ironic.
Very meta.