Episode Summary
Executive Summary: The episode debates whether news can thrive in the AI era, with Ben Smith, Naima Raza, and Joe Marchese arguing that publisher-to-AI deals may provide short-term cash but likely won’t create durable businesses. They examine training data, citations, trust, brand value, legal risk, and how AI may favor incumbents while reshaping distribution, advertising, and political media dynamics.
Main Topics: AI licensing deals and the risk of repeating past platform mistakes (Priority: 5/5): The guests compare OpenAI deals with earlier Facebook/Twitter partnerships and warn that cash-for-content arrangements may function more as lawsuit insurance than real business-building. Who captures value in the AI news stack (Priority: 5/5): A major theme is whether value will accrue to AI distributors or to news brands, with arguments that trust, recency, and unique reporting could let publishers retain leverage. Brand, citations, and trust as differentiators (Priority: 4/5): The conversation suggests AI summaries may increase the importance of trusted brands and citations, because users may prefer known publishers over generic model outputs. AI’s impact on reporting incentives and journalism quality (Priority: 5/5): Speakers debate whether AI disintermediation could reduce incentives to report original news, while also acknowledging useful labor-saving and synthesis applications. Media fragmentation, partisanship, and the future of news consumption (Priority: 4/5): The group explores how AI may favor calmer, more authoritative brands while shrinking the reach of hyper-partisan outlets and changing how audiences discover news. Legal, regulatory, and creator-rights battles (Priority: 4/5): The discussion covers copyright, publicity rights, and the Scarlett Johansson controversy as signs that AI’s growth could trigger new legal and labor constraints. Business models for journalism beyond mass consumer news (Priority: 4/5): They point to niche, B2B, and high-trust vertical media as more durable models than broad consumer news, especially when paired with events, subscriptions, or specialized advertising.
Key Arguments: OpenAI-style licensing deals may be temporary revenue rather than a sustainable long-term model, especially if the real exchange is simply 'we pay you and you don't sue us.' Historic archives are already widely available, so the strategic value lies in fresh news and real-time reporting, not old content. News publishers may have more leverage than expected because AI outputs need trustworthy, recent, and exclusive information to stay useful. Citations could become a new form of discovery and soft advertising for publishers, especially if users learn to verify answers through trusted brands. AI may strengthen well-known news organizations like The New York Times while pressuring smaller or partisan outlets that depend on distribution platforms. Some AI use cases in journalism are genuinely useful, such as large-scale synthesis and data extraction, but not for high-stakes reporting or publication without verification. The biggest threat is disintermediation: if users get answers without visiting publishers, original reporting incentives may weaken, potentially lowering AI product quality too. Brand identity and individual journalist voices may matter more in an AI-mediated world, because consumers may seek trusted sources rather than generic summaries.
Data Points: OpenAI-News Corp deal value: $250 million - Mentioned as a major licensing agreement between News Corp and OpenAI. News Corp annual revenue: about $15 billion - Used to show the OpenAI deal is meaningful but not transformative for News Corp. News Corp deal annualized value: $50 million per year - Derived from the reported $250 million deal over multiple years. ChatGPT user growth: 100 million users in two months - Cited as evidence of rapid AI adoption after launch. Current date reference in discussion: May 2024 - Used while discussing the pace of AI product adoption. Bing search share: 3.6% of overall search share - Used to argue that consumer behavior has not fully shifted to AI search. Vox/OpenAI and Atlantic/OpenAI timing: deals announced on the same Wednesday - Referenced as examples of publishers striking AI licensing agreements together. Podcast/voice AI reference: Scarlett Johansson voice dispute - Used as an example of legal and PR risk around synthetic voice and publicity rights.
Pivotal Quotes: "whenever you're getting paid in credits, that should make you a little nervous" — Joe Marchese: On the structure of publisher-tech deals and why non-cash compensation may be a warning sign. "the value could accrue to the people who maintain trust at the consumer interface level" — Joe Marchese: On the possibility that trusted news brands could benefit in an AI-mediated ecosystem. "AI is sort of closing the door on some of these ideas about just like building massively, rapidly scaled news businesses" — Ben Smith: On how AI may favor incumbents and limit the old social/distribution-growth playbook.
Implications: News organizations may gain short-term revenue and some leverage, but long-term success likely depends on trust, originality, and control of distribution. AI could entrench incumbents, pressure partisan outlets, and force journalism toward niche, branded, and high-value reporting.
About Big Technology Podcast
The Big Technology Podcast takes you behind the scenes in the tech world featuring interviews with plugged-in insiders and outside agitators. Alex Kantrowitz, a Silicon Valley journalist who's interviewed the world's top tech CEOs — from Mark Zuckerberg to Larry Ellison — is the host.