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Technology DECODED

Previous edition: 25 Mar 2024
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BBC in talks to sell archive to tech companies as AI training data

The BBC is is in talks with technology companies to sell access to its content archive to use as AI training data, according to a Financial Times report, citing people familiar with the matter.

The BBC seeks to diversify its revenue streams, and selling archives for AI training has proven lucrative. 

Sources told the FT that Amazon was one of the companies that had met with the broadcaster. 

French media organisation Le Monde recently partnered with OpenAI to use the newspaper's back catalogue to train ChatGPT. 

The UK national broadcaster is also reportedly looking to use its television and radio content archive to train its own GenAI model. The model will then power BBC production applications, like aiding journalists with writing and sourcing stories, the FT reported. 

In 2023, the BBC confirmed that it was looking to explore the application of GenAI in journalism but said it would not let OpenAI scrape its content. 

Rhodri Talfan Davies, director of nations at the BBC, said in a blog post that GenAI could provide a significant opportunity for the broadcaster to deepen and deliver its mission in exciting ways. 

"Innovation has always been at the heart of the BBC. From the very first radio broadcasts in 1922 to colour television in the 1960s and the rapid development of our online and mobile services over the last 25 years - innovation has driven the evolution of the BBC at every step," Davies said.

"At the same time, we are taking steps to safeguard the interests of Licence Fee payers as this new technology evolves," he added. "For example, we do not believe the current ‘scraping’ of BBC data without our permission in order to train GenAI models is in the public interest and we want to agree a more structured and sustainable approach with technology companies." 

However, despite efforts to keep companies out, some BBC executives are reportedly concerned that AI companies have already scraped content - due to most of it being in the public domain.

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