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How Angry AI Will Train Telemarketers to Handle Angry Real People

The robot apocalypse will come with the howling fury of an angry customer service call.

(Ryan Etter/Ikon Images/Corbis)
smithsonian.com

There’s a special kind of zen required of those who work in customer service. Now, a company in New Zealand wants to design a computer program that can mimic the hatred of angry callers in order to help those same customer representatives deal with riled up customers.

The project is named Radiant, after a supercomputer in Isaac Asimov’s Foundation series that could predict the future. While the real-life Radiant won’t be quite so omniscient, its designers at the technology firm Touchpoint hope it will be able to accurately simulate millions of angry customers to help companies figure out what makes people fly off the handle, writes Michael Bingemann for The Australian. They’ll spend the next six months feeding Radiant reams of data collected on people at their worst.

Radiant works by examining data from the worst of the worst customer service calls and determining what factors and experiences could set someone off in any given scenario. Touchpoint is working with one of Australia’s biggest banks and several insurance companies and telecommunications firms that are supplying the customer service data that is embittering Radiant towards everyday life. By the time the program is up and running, Radiant will be able to react angrily and irrationally to telemarketers and customer service representatives-in-training who will have to try and calm the computer down. They hope to complete the program by the end of the year.

The wrathful robot comes at a high price though: so far about $400,000 has already been invested in Radiant’s development. But if it works, it might make your next angry phone call to a company go just a little bit smoother.

h/t Popular Science

About Danny Lewis

Danny Lewis is a multimedia journalist working in print, radio, and illustration. He focuses on stories with a health/science bent and has reported some of his favorite pieces from the prow of a canoe. Danny is based in Brooklyn, NY.

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