There was once a time when creativity felt protected, when creators could make a living not just from their talent but also from laws that shielded their work. Copyright was a fortress. It allowed artists, writers, filmmakers, and musicians to decide how their creations were shared, used, and monetized. It was their shield in a world eager to reproduce and redistribute.
For decades, industries like film, music, and publishing thrived under the wings of copyright. Remember the fierce campaigns against data piracy in the era of torrent networks? Back then, the battle lines were clear: creators versus pirates. The message was simple—“Piracy hurts creators.”
But what do we hear now? The silence is deafening.
The conversation has shifted. Instead of torrents, we’re talking about artificial intelligence. AI tools have revolutionized how content is created, consumed, and mimicked. Yet their foundational training often leans heavily on existing works—texts, images, and videos scraped from the internet. The defense? “It’s for training purposes.” After all, how could machines learn to imitate human creativity without examples?
The irony is sharp: “All great artists steal,” we say, quoting Picasso. But when tech giants and corporations adopt this mantra to justify wholesale replication of creative works, who benefits? Spoiler alert: it’s not the individual creator.
The consequences of this shift are far-reaching. If original creators can no longer trust that their work will remain their own, where is the incentive to create? Why pour effort into a masterpiece if it’s destined to be copied, mimicked, and monetized by someone—or something—else?
This erosion of incentive is already reshaping the landscape. Fewer creators are thriving on their artistry alone. Many now pivot toward commercial partnerships, becoming influencers or brand ambassadors. These roles pay well but steer them toward a kind of creativity that serves commerce over art. The machine keeps rolling, powered not by fresh, original work, but by a feedback loop of recycled content and consumerism.
And here’s the real kicker: when AI begins to feed on its own regurgitated outputs—models training on AI-generated data—what happens to quality? The pool of inspiration becomes a stagnant pond. True innovation suffers because those who once created with passion and purpose have left the stage.
Is it time to wave goodbye to copyright? Perhaps the better question is, who benefits when we do? Because if it’s not the creator, then it’s probably the machine. And the machine doesn’t care about art—it only cares about output.