We live in a moment where anyone can open a website, type a few words, and within seconds generate an image worthy of a magazine cover, a song that could top the charts, or even a text that looks a lot like this one. Artificial intelligence is no longer science fiction: it has become an extension of our creative everyday life.

But when that happens, what, or who, is really behind the work?

The notion of authorship has never been static. There were times when masterpieces were produced in workshops of painters and sculptors where no one signed anything, authorship was collective, almost invisible. Later, during the Romantic period, we elevated the artist to the status of solitary genius, a near-divine source of originality. With the cultural industry, the author became a trademark, a packaged product for consumption.

And now, in the 21st century, we face another shift: perhaps the first time authorship is no longer exclusively human.

Or does it merely reorganize?

An AI model doesn’t invent out of nothing. It trains on billions of examples, texts, images, music, voices. It learns statistical patterns and from there generates something that looks new. But if everything is derivative, can we really speak of creation?

And if we can, who is the creator?

• The programmer who built the model?

• The community that supplied the data?

• The user who typed the prompt?

• Or the machine itself, even without consciousness?

Roland Barthes once provoked, in the 20th century, that “the author is dead”, arguing that the meaning of a work lies not in the creator’s intention, but in the reader’s interpretation.

Does AI radicalize this idea?
If an AI-generated painting moves us, does it matter who made it?
If a text touches us deeply, does it matter if it was written by a human or a machine?

Or is this indifference dangerous, because it also dissolves responsibility? Who is accountable if a model generates plagiarism, or hate speech?

In a world flooded by AI outputs, traditional concepts of copyright and intellectual property feel increasingly fragile. If an AI-generated song sounds identical to a famous hit but copies nothing literally, is it plagiarism or inspiration?

If a journalist uses AI to draft part of a report, is the author the journalist, the machine, or the thousands of writers whose texts trained the model?

And more: when we already let algorithms decide what shows up in our feeds, hadn’t we given up authorship long before generative AI?

Many argue that the human role will be that of a curator: choosing prompts, editing outputs, giving direction and context. But how far is that enough?

If anyone can ask the same model for the same image or text, where does uniqueness lie?
And if AI starts suggesting not only the answers but also the questions, can we still talk about curation?

Perhaps the future of human creativity lies in another layer: in intention, in emotion, in purpose.

Today, AIs already write poems about pain, love, and longing. But we know there is no beating heart behind those words. The emotion is only imitation.

But if the simulation is convincing enough, does it matter?
When we cry at a movie, aren’t we reacting to fiction?
If art has always involved performance, does distinguishing real emotion from simulated emotion still make sense?

If everything can be generated, what still has value?

We are facing radical abundance: infinite texts, infinite images, infinite songs. But when everything is abundant, nothing is rare. And symbolic value has always been tied to uniqueness.

Are we heading toward a world with no more classics, only endless streams of disposable content?
Or will this abundance push us to seek even more meaning, intentionality, and depth in what we choose to create and consume?

Some see AI as a democratic revolution: anyone can create without years of training or access to expensive tools.

Others fear saturation: a world where everything is possible and therefore nothing stands out.

Is this a new era, where thousands of voices gain space?
Or a new deafening noise, where signals are lost in the excess?

Maybe the question is no longer “who is the author?” but “what does authorship mean in 2025?”

Will authorship be more about process than result?
Will value lie in showing how something was created, rather than the final product?
Or will authorship dissolve altogether, replaced by collective and anonymous flows of creation?

In the end, there are no easy answers. Only more questions:

• If authorship is no longer individual, what happens to the idea of genius?

• If machines produce as much as we do, what are the limits of human creativity?

• In the future, will being an “author” no longer be a title, but a shared practice?

• What happens to cultural memory when most works have no face, no name, no clear intention behind them?

Perhaps what AI has created most so far are not images or texts, but questions we still don’t know how to answer.