STAYM

As hybrid neuro-photography and generative visual tools become deeply embedded in contemporary creative practices, a central question increasingly demands attention: can artificial intelligence be regarded as a co-author of visual work, or does authorship remain the exclusive domain of human creative agency? The difficulty lies in the fact that neural networks now perform not merely technical functions but aesthetic and structural ones, shaping the image in ways that transcend simple execution of commands. Traditional photography links authorship to human intention — to a photographer’s control over framing, lighting, narrative, and conceptual direction. In hybrid visualization, however, AI models introduce their own patterns, biases, and decision-making logic learned from vast image datasets. This raises the issue of whether the human artist remains the sole origin of the creative act when the final image is partly determined by algorithmic processes. The degree of human control plays a decisive role. When AI assists only with minor post-processing or enhancing dynamic range, authorship remains clearly human. But the situation becomes far less straightforward when the artist provides prompts or guidelines, and the neural network generates new visual structures and textures that the human did not explicitly foresee. In cases where the system autonomously synthesizes most of the visual content from high-level input, the notion of a single human author begins to feel insufficient. The creative process becomes distributed between human intention and algorithmic transformation. Legally, most jurisdictions continue to treat AI purely as a tool. Copyright protection is granted only when a human contribution can be demonstrated, while fully AI-generated works increasingly fall into the public domain due to the absence of a legally recognized author. Yet this legal framework is misaligned with the practical realities of hybrid visualization, where creative responsibility and decision-making are shared across human and non-human actors. The philosophical challenge is equally pressing. If authorship requires consciousness and subjective intention, AI cannot be considered a co-author. But if authorship is defined simply as the origin of unique cultural artifacts, neural networks undeniably play a formative role in shaping the final visual product. Some researchers propose moving beyond the binary human-versus-machine opposition altogether. Instead of naming a single author, we might acknowledge a network of contributors: the human creator, the datasets and photographers whose images trained the model, the engineers who built the architecture, and the algorithmic patterns that emerge independently from any one individual or entity. In this perspective, hybrid visualization becomes a multi-authored practice in which both human and machine agencies are interwoven. This debate is not limited to intellectual property; it touches on identity, creativity, and cultural evolution. Whether acceptance of AI as a co-author represents a threat to human artistry or, conversely, a new paradigm of collaborative creation remains unresolved. What is clear is that the boundaries of authorship are shifting, and hybrid neuro-photography is one of the key arenas where these shifts are becoming visible.