Music legend Elton John, in an interview with the BBC, spotlighted the UK government’s approach to the use of data. John was at loggerheads with the government over a proposal that would ease copyright laws in the country, giving AI developers and firms access to data for training AI models. “The danger is for young artists, they haven’t got the resources to keep checking or fight big tech,” John stated.
If the government were to move ahead with the proposal, it would allow AI firms to use artists’ content without permission or compensation. John calls this “committing theft, thievery on a high scale,…and I feel incredibly betrayed.”
In an open letter to Prime Minister Keir Starmer, the musician requested that the government withdraw the proposal. The letter was endorsed by popular artists in the UK like Paul McCartney, Eric Clapton, Kazuo Ishiguro, Ed Sheeran, and Dua Lipa, along with 400+ signatories from groups including the National Union of Journalists, Getty Images, and Sony Music Publishing.
The artists stated, “We will lose an immense growth opportunity if we give our work away at the behest of a handful of powerful overseas tech companies and with it our future income, the UK’s position as a creative powerhouse, and any hope that the technology of daily life will embody the values and laws of the United Kingdom.”
In an era where data transparency in AI training is no longer optional, companies are expected to disclose not just about what data they collect but also about how they train their models.
Aman Priyanshu, an AI researcher, stated that most companies follow an accepted data collection practice for their operations, but AI training represents a new vertical that needs explicit disclosure.
According to the GDPR and CCPA [California Consumer Privacy Act], businesses must clearly specify how they plan to use customer data. This could mean updating privacy policies, sending clear communications to users about the new AI uses of their data, and implementing systems to track both user consent and data usage throughout its lifecycle.”
However, many companies struggle to articulate whether data is used for improving algorithms, shared with third parties, or retained for future training purposes. This incapability not only leaves users in the dark but also complicates internal efforts to enforce consistent data-handling policies, increasing the risk of non-compliance or misuse.
