Lately, I’ve been returning to a deceptively simple question: What does realism mean in AI-generated cinema?

This post is part of my ongoing reflections on what I call AI Cinematic Realism, a term I’m using to think through the aesthetics and meaning of AI-generated media.

It’s easy to marvel at how today’s AI tools simulate cinematic qualities—depth of field, natural light, human gestures, ambient soundscapes. The outputs can feel strikingly photographic. But cinematic realism has never been just about looking real. It’s about feeling real. And, more than that, it’s about how the image relates to the world.

A Quick Detour Through Film History

Realism in cinema has always been a contested idea. From André Bazin’s belief in the power of the image to Gilles Deleuze’s reflections on time and movement, film history is full of attempts to define what makes an image “real.” For some, it’s about fidelity to physical reality. For others, it’s about revealing emotional, psychological, or ethical truths.

Siegfried Kracauer, in particular, argued that film’s affinity with the material world—its ability to register the unexpected and the unnoticed—makes it uniquely suited to reflect life as it unfolds. For Kracauer, cinematic realism was as much about presence as it was about representation.

Realist cinema often avoids spectacle in favor of duration, ambiguity, and stillness. It grounds itself in everyday moments rather than scripted drama. It trusts the viewer to witness rather than consume. These qualities aren’t just stylistic—they’re philosophical. They reflect a belief that cinema, at its most honest, reveals rather than constructs, listens rather than declares.

Now, AI tools invite us to revisit those values in a radically new context. What happens when there is no camera—just a latent space and a prompt? When the realism is trained, not observed? When presence is simulated, not lived?

The Real in Synthetic Cinema

In my own work as an AI filmmaker, I’ve been drawn to scenes that emulate the quiet, layered, emotionally grounded qualities of realist cinema.

The tools are generative. The images are synthetic. But the creative impulse is deeply human: How do we represent what it means to be alive in time, in space, in relation to others?

And here lies the central tension I want to explore: Can AI-generated cinema move us—not just visually, but emotionally? Can it make us feel, reflect, or care? Or does its realism only go skin-deep?

This isn’t just a technical question. It’s a question about meaning, perception, and what we believe to be real.

When we see an AI-generated face register pain or joy, what exactly are we responding to? Is it performance? Projection? Pattern recognition? Does it matter?

These are questions about how we experience images—and how we make meaning from them when there’s no lived moment behind the lens. They challenge us to think about authenticity, spectatorship, and emotional truth in a cinematic space built entirely by algorithms.

Why This Series Exists

This series, AI Cinematic Realism, is an evolving reflection on the aesthetics and ethics of AI-generated film, the philosophical frameworks behind realism (old and new), the difference between photorealism and emotional truth, and the role of spectatorship in making meaning from synthetic images. Some posts will be meditative. Others will be grounded in case studies—my own and others’. All will orbit a shared concern: What kind of cinematic realism does AI make possible—and how should we engage with it?

Because realism is not just a matter of visual technique. It is a way of attending to the world—of witnessing presence, emotion, and ambiguity with care. Even when that world is entirely machine-made.