As India proposes a blanket licensing system that would require AI companies to pay creators when their content is used for model training, the debate over AI training data compensation has reached a critical inflection point. TechRound assembled a panel of tech leaders to weigh in — including Krazimo CEO Akhil Verghese.
Verghese’s take is nuanced and thoughtful. He argues that while it may be feasible to compensate large content generators like the New York Times or Reddit, creating a fair system for every blog author whose work contributed to training a state-of-the-art model would be extraordinarily difficult. He identifies three key areas of debate: whether the transformative way AI reuses content constitutes fair use, whether the practical difficulty of compensating everyone fairly means the issue can’t be addressed, and whether AI dominance is so strategically important that legal concerns become secondary.
On the fair use question, Verghese is direct: based on how transformers actually work, he finds it difficult to classify AI training data usage as fair use in the traditional sense. He also pushes back on the idea that difficulty justifies inaction — arguing that the brilliant minds who built these models could develop workable compensation structures if they dedicated effort to the problem.
The article features perspectives from six industry experts, making it a comprehensive look at one of the most important policy questions in AI today.
Originally published on TechRound. Krazimo is an AI consulting firm that builds reliable enterprise AI solutions with a focus on engineering excellence.
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