Anthem Looks to Fuel AI Efforts With Petabytes of Synthetic Data

The ultimate goal, he said, is to validate and train AI algorithms on large amounts of data, while reducing privacy issues surrounding personal medical information. “More and more…synthetic data is going to overtake and be the way people do AI in the future,” Mr. Bhatt said.

Anthem, which has been using

Amazon.com Inc.’s

Amazon Web Services as a cloud provider since 2017, tapped Google Cloud last year for its data analytics and AI capabilities as part of an ongoing effort to become more customer-centric and focus on members’ entire healthcare journeys, Mr. Bhatt said. It’s a continuing effort that includes Anthem’s work with synthetic data.

This week, Anthem’s shareholders are voting on a proposed rebranding of the company to Elevance Health as part of that same effort.

Synthetic data applies both to real-world data that’s been stripped of personal information and fully anonymized and artificial data that’s been generated from deep generative models, said Ritu Jyoti, group vice president of Worldwide Artificial Intelligence and Automation Research at market research firm International Data Corp. Anthem said it is using the second type.

The idea of synthetic data in enterprises has been around for decades, but it’s recently started picking up steam as companies begin making more use of AI itself and have greater need for faster access to better data sets on which to train AI algorithms, Ms. Jyoti said.

Anthem said the synthetic data will be used to validate and train AI algorithms that identify things like fraudulent claims or abnormalities in a person’s health records, and those AI algorithms will then be able to run on real-world member data.

Anthem already uses AI algorithms to search for fraud and abuse in insurance claims, but the new synthetic data platform will allow it to scale. Personalizing care for members and running AI algorithms that identify when they may require medical intervention is a more long-term goal, said Mr. Bhatt.

In addition to alleviating privacy concerns, Ms. Jyoti said another advantage of synthetic data is that it can reduce biases that exist in real-world data sets. That said, she added, you can also end up with data sets that are worse than real-world ones.

“The variation of the data is going to be very, very important,” said Mr. Bhatt, adding that he believes the variation in the synthetic data will ultimately be better than the company’s real-world data sets.

“Synthetic data models, in our opinion, will ultimately fuel the promise of what big data can deliver,” said Chris Sakalosky, managing director, US Healthcare & Life Science at Google Cloud. “We think that’s actually what will set this industry forward.”

Write to Isabelle Bousquette at [email protected]