From Detection to Interpretation The Epistemic Function of AI in Scientific Imaging

This project investigates how the epistemic role of scientific images changes when they no longer arise from indexical detection of the visible, but from algorithmic generation through artificial intelligence. Traditional scientific imaging has been tied to observation and physical trace, granting it epistemic authority. In contrast, AI-based methods such as convolutional neural networks and diffusion models produce visualisations as probabilistic reconstructions or generative outputs. These images open epistemic possibility spaces rather than secure knowledge. The study combines philosophical analysis with case studies from astronomy and digital pathology to compare detection-based with AI-based imaging. The central thesis is that AI does not replace human judgement but shifts epistemic responsibility: what counts as knowledge depends less on image production than on validation and accountability within hybrid human–machine systems.