An automated podcast network publishes more episodes in 24 hours than many broadcasters do in a year, using AI to convert news articles to audio in minutes. A specific case, that of the channel ‘The Daily News Now!’, helps us to consider how far the scraping of content in the era of generative AI.
To loot. The case was put on the table indicator: On January 31, at 2:57 in the afternoon, the newspaper ‘The Chronicle’ (a completely marginal publication: despite being 120 years old, it is published by Duke University, in Durham, and is run and produced entirely by students) published an article about Gemma Tutton, a student and pole vaulter who had won a university competition. Seventeen minutes later, a podcast called ‘Durham News Today’ uploaded an episode titled ‘Gemma Tutton’s Triumphant Return to Pole Vault’ to Spotify.
The podcast, of course, had no connection with the newspaper. But it reproduced almost all the data from the original article in the same order, including practically identical phrases. And it is not an isolated case: ‘Durham News Today’ is one of at least 433 programs that make up ‘The Daily News Now!’ podcast network created by Corey Cambridge. As of January 23, ‘DNN’ has published more than 350,000 episodes (approximately 11,000 per day).
How they do it. Obviously, with AI: a system of scraping (software automation that extracts large volumes of content) monitors media websites, excises text from published articles, processes it using natural language synthesis tools, converts it into audio and distributes it on platforms such as Spotify. All in a matter of minutes. And they don’t bother to dissemble: according to Indicator, they reproduce the structure, data and writing of pieces published by outlets such as local Fox and NBC affiliates, ‘TechCrunch’, ‘Toronto Star’, ‘The Verge’ or the radio station ‘WRAL’.
The tools. To understand why an operation of this type is technically possible today, we must take a look at the ecosystem of tools that has been democratizing synthetic audio production for two years. In September 2024, Google activated the feature globally Audio Overview of NotebookLM. The tool converts any document uploaded by the user into an audio summary. The impact was immediate: NotebookLM went from 652,000 monthly visits in August of that year to 10.5 million in September, an increase of 371% in thirty days. In the three months following the global launch, users accumulated audio with a total duration greater than 350 years of continuous reproduction.
NotebookLM normalized the idea of the synthetic podcast, and it was all downhill from there. ElevenLabsspecialized in speech synthesis and valued at more than a billion dollars, launched its GenFM function in December 2024, which allows you to generate complete episodes from text. Wondercraftfunded in part by ElevenLabs, introduced support for editing podcasts generated with NotebookLM. Podcastle, aimed at podcast creators, incorporated speech generation with text to complete or replace fragments of speech.
The secret: the price. In an analysis from a similar network (Inception Point AIwhich generates around 3,000 episodes per week with more than fifty AI announcers) producing an episode costs approximately one dollar, and with just 20 listeners the episode is profitable thanks to programmatic advertising. The model does not seek loyal audiences, but search engine positioning: by publishing hyper-specific episodes on cities or niche topics minutes after local media launch their articles, these networks anticipate humans’ capacity for informative immediacy.
In other words: ‘The Daily News Now!’ appears in the top Spotify results for local news searches in dozens of American cities. It directly competes (and in many cases surpasses) the media from which it steals content.
Legal issues. Cambridge defends itself by saying that its network only accesses “publicly available information” and merely summarizes it. But Indicator found almost thirty episodes of ‘Durham News Today’ that reproduced the structure, order and specific sentences of articles from ‘The Duke Chronicle’: it is not a specific pattern. And Cambridge may still be legally protected, but the problem is more about information ethics than legal details. In any case, in May 2025, the United States Copyright Office came to the conclusion that “publicly accessible” material is not necessarily free to use.
There are legal precedents in that direction: in November 2025, a federal judge from New York did not reject the lawsuit by fourteen major publishers (including Forbes, The Atlantic and the Los Angeles Times) against the AI company Cohere, considering that their summaries could constitute direct infringement if they reproduced “structure, sequencing, tone and expressive choices” of the original articles. On the contrary, in April of the same year, the case NYT vs. Microsoft dismissed claims related to the Copilot-generated summaries on the grounds that they were not “substantially similar” to the source articles. Meanwhile, and still without trialthere is the case of the New York Times against OpenAI and Microsoft, accused of using journalistic content to train their models
Very clever. There is another detail: we are not talking about the ‘New York Times’, but rather ‘DNN’ concentrates its production on local niche news (university athletics, student councils, cats trapped in trees), first because these contents generate specific searches with little competition on Spotify. And second, because legally it is safer. They point to more fragile journalism models. Meanwhile, distributors like Spotify are developing tools to detect artificial music (removed more than 75 million tracks), but the next step is to make big brands aware that they do not benefit from the exploitation of newsrooms that cannot defend themselves.
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