News Customization with AI

Felix Chopra, Ingar K. Haaland, Fabian Roeben, Christopher Roth and Vanessa Sticher

No 12121, CESifo Working Paper Series from CESifo

Abstract: News outlets compete for engagement rather than reader satisfaction, leading to persistent mismatches between consumer demand and the supply of news. We test whether offering people the opportunity to customize the news can address this mismatch by unbundling presentation from coverage. In our AI-powered news app, users can customize article characteristics, such as the complexity of the writing or the extent of opinion, while holding the underlying news event constant. Using rich news consumption data from large-scale field experiments, we uncover substantial heterogeneity in news preferences. While a significant fraction of users demand politically aligned news, the vast majority of users display a high and persistent demand for less opinionated and more fact-driven news. Customization also leads to a better match between the news consumed and stated preferences, increasing news satisfaction.

Keywords: news consumption; customization; artificial intelligence; matching (search for similar items in EconPapers)
JEL-codes: C93 D83 L82 P00 (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-dcm and nep-exp
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Working Paper: News Customization with AI (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_12121

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