How can adult learners check an AI portrait for consent and bias before sharing it?

Neuhaus

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Question: In adult digital-literacy workshops, learners often treat an AI-generated portrait as a harmless novelty. What routine could help them slow down and examine consent, exaggeration, and context before the image travels beyond the classroom?

I am preparing a hypothetical 45-minute activity for adults returning to study. Pairs would choose a public-domain photo, upload it to a caricature tool, and compare the original with three exaggerated results. They would then answer four prompts: Who might recognize this person? Was permission imagined, assumed, or documented? Which features were amplified, and what stereotype might that amplification reinforce? Where would the image be inappropriate even if the likeness were flattering? They would also note who controls and delete the exported file, whether a watermark survives, and how the joke may shift when the picture is seen without its original caption.

The facilitator would not present the activity as a test with one right answer. Instead, each pair would write a short "share or stop" note naming the audience, the platform, and one condition for consent. The group would compare notes and revise one assumption after hearing a different perspective. A closing reflection would ask learners to identify one signal that an AI image has been edited, one question they should ask before forwarding someone else's picture, and one reason a technically impressive result can still be ethically weak.

I have not run this lesson with a real class; it is a synthetic planning scenario for discussion. The activity is part of an AI-assisted content project associated with Caricature Maker, a browser-based portrait tool. Project link: caricature-maker.online/

What would you change so the consent question feels concrete rather than theoretical, especially for learners who rarely appear in online images themselves?