Before touching a camera, participants examine what makes a traditional photograph fundamentally different from an AI-generated image. The session establishes the theoretical ground for the rest of the day.

• Understanding indexicality — Photography as a physical footprint. A photograph requires the actual subject to reflect real photons onto light-sensitive silver halide crystals or a sensor. AI images are mathematical predictions, not recordings of events.

• Manual camera mechanics — Mastering the exposure triangle (aperture, shutter speed, ISO), understanding the latent image, and operating mechanical tools without digital safety nets.

Practical Activity — The Intentional Frame Challenge

Your team will receive a manual film camera and 24 exposures of black-and-white film. No screen to review. No undo button. Every shot must be calculated with deliberate intent, forcing total reliance on pre-visualisation and mechanical skill.

Participants convert their latent exposures into tangible physical objects. Hand-developing demystifies the chemical transformation of silver and reveals why an unmanipulated negative historically commanded deep visual trust.

• Chemical reduction — The distinct roles of developers, stop baths, and fixers in converting light-struck silver into visible metallic clusters and achieving permanence.

• The irreversible negative — Physical permanence versus infinitely mutable digital data. Altering a film negative requires destructive physical manipulation, not effortless editing.

Practical Activity — Tank Operation & Chemistry Run

Blind-load film in complete darkness using light-tight changing bags. Execute the full chemical sequence — managing temperature, agitation, timing, and final wash. Negatives hang to dry during lunch.

With physical negatives in hand, the course pivots to contemporary synthetic imaging. Participants debate how prompt-driven AI challenges public trust in media — then build a practical framework to restore transparency.

• The erosion of visual belief — When photorealism decouples from documentation, trust in visual evidence shifts. Ripple effects across journalism, education, and archives.

• Defining non-indexical imagery — The boundary between a heavily edited photograph (which retains an indexical trace) and a purely prompt-driven AI image (which contains zero captured reality).

• Reclaiming value — Why traditional indexical photography gains unique ethical and archival weight when synthetic production becomes infinite.

Practical Activity — Self-Reporting Protocol Workshop

Collaboratively build an actionable metadata and transparency tagging model using clear tiers: Captured Reality, Minor Processing, Generative Augmentation, Pure Algorithmic Synthesis — a standardised rubric ready for deployment in schools, newsrooms, and studios.