Art · The Creative Process: Artists, Curators, Museum Directors Talk Art, Life & Creativity podkast

What can AI teach us about human cognition & creativity? - Highlights - RAPHAËL MILLIÈRE

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“Before I decided to become a philosopher, I wanted to become a filmmaker, and in my education in France, where I'm originally from, there was a lot of emphasis placed on the humanities and arts. I still have a deep passion for the arts, and when it comes to our future, I am of two minds about the role that AI will play in how we interact with creative fields. Going back to my first love of cinema, there are various young filmmakers who are experimenting with AI systems to generate shots and short videos. They’re using it creatively. I think there is a tremendous potential there to usher in a renaissance of surrealist cinema where we can generate images and shots that could never have been made with a traditional camera, certainly not without a huge budget. Lowering the barrier to entry to artistic creation is something I'm excited about. On the other hand, of course, there are the various issues we've raised about the potential for plagiarism, for exploiting human artists, and also concerns about people gradually losing artistic skills because we have these tools available, and about the homogenization of taste. How is AI going to influence the kind of art and content entertainment we like to consume? How does engagement with AI-generated artifacts change the way we relate to art? I don't have the answer to that question, and I think it could go either way. I think it could come with good and bad. It could homogenize preferences and the little quirks we have in the way we engage with music, video, and literature—but it could also, on the other hand, supercharge creativity. That's perhaps the one thing I'd like to say about the future: I hope these new technologies are used to empower human creativity and human flourishing instead of stifling it.”

Dr. Raphael Millière is Assistant Professor in Philosophy of AI at Macquarie University in Sydney, Australia. His research primarily explores the theoretical foundations and inner workings of AI systems based on deep learning, such as large language models. He investigates whether these systems can exhibit human-like cognitive capacities, drawing on theories and methods from cognitive science. He is also interested in how insights from studying AI might shed new light on human cognition. Ultimately, his work aims to advance our understanding of both artificial and natural intelligence.

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