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PODCAST | Gannett, CDO: Classification Algorithms on a Massive Library Open Many Possibilities2

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Written by: CDO Magazine Bureau

Updated 10:07 AM UTC, Tue April 29, 2025

From understanding content consumption to the placement of ads, both AI and data have had a significant role in the media space. Nate Rackiewicz, Chief Data Officer, Gannett, USA Today Network, speaks with Amina Al Sherif, Chief Data Ethics Officer/Chief Innovation Officer, Anno.Ai, about the application of AI and ML for content analysis, and decoding consumer consumption of media.

Rackiewicz is the Chief Data Officer at Gannett, a part of the USA Today Network. Gannett includes USA Today along with 250 other local publishers around the country and throughout the world, making it one of the largest local and national news footprints.

Speaking on some of the most innovative and effective implementations of machine learning and data science that he has witnessed in this space, he points toward the analysis of content for a better understanding of content consumption.

“I consider myself a data science practitioner. After I left HBO, I started my company, taught myself Python, and built an analytics platform around the advertising research industry,” Rackiewicz says. “I was using machine learning in that space to just analyze content — it was emotional fingerprints, psychographic fingerprints, and then drawing correlations between those and the consumer consumption of the messaging.” 

This technology can help develop creatives for marketing campaigns and also for ad placement, etc., he adds. Television networks such as HBO were using it to analyze scripts, apply psychographic frameworks, and understand aspects of emotion that can influence positive or negative ratings in television. “We used it for things as basic as auto-captioning.”

It can also be used to better understand content and to find objects within a large collection. Next, Rackiewicz recalls HBO’s vision of being able to understand the products being featured in TV shows. “Leveraging artificial intelligence and classification algorithms trained against the massive library can allow you to go scene by scene and say ‘Oh, there’s this brand of car” or ‘Here’s that brand of clothing.’ And “Here’s where you can go buy it.’ It just opens up so many other possibilities,” he concludes.

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