Dimitris Agathopoulos is an independent New Media Artist.

His artistic research and work focus on creating Virtual and Augmented Reality experiences and narratives, algorithmic art, AI-aided art, 3D sculpting, 3D modeling, experimental animation, sound design, digital scenography, projection mapping, and painting. He teaches 3D Design in the MA in Digital Arts program at the Athens School of Fine Arts, and he also instructs courses in Plastic Arts with Digital Media and Digital Audiovisual Representations at the Department of Interior Architecture in the School of Applied Arts and Culture at the University of West Attica.

Art, AI, and the Transformation of Vision

Artificial intelligence (AI) is no longer a distant technological curiosity but an active medium within contemporary artistic practice. It represents both a tool and a critical subject, a means of generating imagery, translating data into sensory experience, and probing the limits of perception itself. Machine learning allows not only the emergence of new visual forms but also the reconfiguration of how we understand vision: not as a fixed human faculty, but as a fluid field of interpretation shared between humans and machines.

Consider a concert hall where sound unfolds as a living architecture of light, or an installation that exposes the fractured, algorithmic gaze of a self-driving car navigating an urban environment. These are not merely speculative scenarios; they exemplify how AI can be mobilized to expand aesthetic experience, to reveal unseen structures of data, and to confront us with alternative modes of seeing.

Yet this encounter is not without tension. Can a system devoid of memory, intention, and affect ever constitute an artist? If art has historically been the expression of human subjectivity, what does it mean to ascribe creativity to an algorithm trained on inherited datasets? Such questions destabilize long-held definitions of authorship, but they also open up a space for rethinking artistic agency in an era of pervasive computation.

The ethical dimensions are equally pressing. Every dataset carries traces of cultural bias, and every model risks reproducing the inequalities inscribed within it. In this sense, AI art is never “neutral.” It demands vigilance, a critical awareness of how technology reflects and amplifies the structures of power embedded in its code. Questions of authorship and ownership likewise remain unsettled, requiring frameworks that recognize both the human and machinic contributions to the creative process.

Rather than framing the debate as a competition between human and machine, I see it as a negotiation of collaboration. AI extends the artist’s practice, but it does not replace the artist’s role as the interpreter, the mediator of meaning, the bearer of emotional resonance. What emerges is not an abdication of human creativity but a frontier where technology becomes a co-agent in shaping new visual languages.

As AI continues to evolve, so too will the aesthetics of its use. The task for artists is not simply to adopt these tools, but to interrogate them, to critically reshape them, and to transform their outputs into experiences that speak to our shared condition. It is in this dynamic interplay, between human imagination and algorithmic processes, that the future of vision and artistic experience begins to take form.