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Spencer and Dylan Matthews discuss the potential of large language models in journalism, the challenges of automating investigative journalism, and the importance of credibility and expertise in the field.

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Will large language models (LLMs) replace journalists any time soon? On what types of writing tasks do LLMs outperform humans? Have the US news media become less truth-seeking in recent decades? Or is truth-seeking behavior merely an aberration from a norm of propagandizing? How should we redistribute economic surplus from AI? Have any AI companies committed to a Windfall Clause? Instead of bothering to negotiate with us, wouldn't a superintelligent AI be able to get much more done by first wiping us all out? What are some subtler or less-well-known ways subscription models reshape incentive structures for journalists? Why is collective action so hard?

Dylan Matthews is a senior correspondent at Vox, where he cofounded Future Perfect, a section devoted to exploring ways to do good. He writes frequently about economics, philanthropy, global health, and more. You can email him at dylan@vox.com.