Make a verification request to the sighted AI to catch a possible fabrication. Return JSON {"prompt":"...","verification_step":"...","risky_assumptions":"..."}: prompt - task, verification_step - a technique that will separate honest reading from speculation, risky_assumptions - what exactly AI can invent in this frame and how to catch it.
Sighted AI does not “photograph” the truth - it assumes the most probable. In a clear photograph this is almost always true, but in a blurred, glare or cropped area, the model completes what is plausible: it confuses 3 and 8, reads text that is not there, and confidently names the wrong brand. And the tone is as confident as with the correct answer - this is the main trap. Test technique: separate reading and interpretation. Ask the AI to first rewrite verbatim what it sees (for example, each digit of the counter in order), and SEPARATELY - the interpretation. A discrepancy between “read” and “concluded” is a red flag. The second technique: he was directly instructed to mark the unreadable as “unknown”, rather than guess, and to indicate how confident he was in each fragment. Hidden lever: re-photograph the disputed area from a different angle or at a larger angle and compare the two answers - a stable match is more reliable than one confident one. A typical rookie mistake: taking a smooth, confident answer as a fact and letting the AI fill in the obscured numbers with fiction.
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