How AI Will Change the News Business: 3 Theories

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The media industry is panicky. The tech companies are opaque. But some scenarios are starting to take shape.

It’s tempting to get stuck on the question of whether AI tools are capable of producing plausible versions of much of the content already published by these publications. As a strategy, however, the all-in-on-AI approach renders that question irrelevant. If a bot can’t convincingly mass-produce content people want to read, or at least content against which views can be somehow harvested by publishers for ads, then the plan fails.

Some version of this strategy will occur naturally in newsrooms, as staffers like Farhad — an opinion columnist, not an investigative reporter — experiment with new tools that make their jobs easier, stepping on a few rakes along the way. Google’s “Genesis” story-generation tool represents a fuller expression of this approach.

This optimism depends on a few different assumptions. One is that ChatGPT-esque tools will prove genuinely useful to reporters in the long term, providing meaningful help to people working to report, contextualize, and analyze new information about the world — an assumption that seems to be, at this point, helped along by brief experiences testing out ChatGPT and an unfortunate susceptibility to.

In journalism, however, it seems like an early fight over leverage and AI might unfold between news organizations and tech companies — between owners and owners — in the form of lawsuits and content-sharing deals. Semafor’s reporting suggesting that a consortium of news organizations want billions of dollars in compensation from AI firms implies some interesting predictions on its part.

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