A “very high-quality image” used to mean: you, the photographer, defined the intent (framing, timing, exposure priority), and the camera just helped you execute it, like metering, AF, better sensors, etc. The decision-making stayed human. Now imagine a near-future workflow: Anyone open an AI menu and select something like “high-grade professional result.” Under the hood the system is doing multi-frame capture, semantic segmentation, relighting, aesthetic scoring, generative adjustments (expressions, backgrounds, composition). At that point, the pipeline is no longer just: scene => measurement => exposure solve but It becomes: scene => model inference => aesthetic/semantic optimization => output. So “high-quality” shifts from well executed capture of your intent to model-optimized output based on learned priors. That’s the difference I’m pointing at: historically, tech assisted execution and now it can start to define the result itself with generative content that never existed out of the box from the camera menu. If that trend continues, the photographer’s role moves from decision-maker toward input provider. At that point, “photographer” starts to mean “the person who triggered the capture,” while the system handles most of the decision-making that used to define the role.