You have audited AI answers that sounded confident when they were wrong, judged synthetic media and online claims, and trained and tested simple image and pose models. Today you weigh both sides of AI in young people's lives. There is no right answer the lesson is steering you toward. You will take a stand, hear the strongest case for each side, argue, and see whether anyone moves.

Today's motion:

Both sides get a fair hearing. On the promise side: creativity (starting points for writing, art and ideas), access (explanations, language support, help when you are stuck), speed (draft help and pattern-spotting that can free time for human judgement), and models that learn a pattern you chose when the training examples are balanced. On the pitfalls side: confident wrong answers (you practised spotting these), bias when training data or design skews, over-reliance that stops you thinking, synthetic media that makes trust harder, and how easy a thin or unbalanced model was to fool. Your job is to steelman whichever side you are given (argue the strongest fair version of that side, even if it is not your own view).

Use the interactive activity to place where you stand on the motion. Markers can move; changing your mind is allowed.

1. Place your marker on the statement without talking.
2. Listen while two or three voices from each end of the line give their strongest reason.
3. Read the "things to think about" prompts when your teacher reveals them, then you may move.

Read only your side's list. You will hear the other side's case when they speak.

Promise case (argue its strongest fair version)

• Creativity: starting points for writing, images and ideas, so more students can make something.
• Access: explanations on demand, and another way in when a topic will not stick.
• Speed: draft help and pattern-spotting that can free time for human judgement.
• Agency: used well, AI supports the checks and choices only a human can make.
• Good training data: when your image or pose examples were balanced, the model learnt the pattern you chose.

Pitfalls case (argue its strongest fair version)

• Confident errors: chat tools can sound sure while inventing facts - you practised verify or reject.
• Bias in, bias out: outputs skew when the data and design behind a system are unbalanced.
• Over-reliance: if a tool always drafts first, your own thinking gets less practice.
• Trust and media: synthetic images, voices and video make it harder to know what is real.
• Easy to fool: the image or pose model you tested could be tricked when examples were thin or unbalanced.

Do this now:

1. Pair up. Same side. Pick two points and one piece of class evidence. You have 2 minutes. Fill in:
   • Point 1: …
   • Point 2: …
   • Evidence from class: when the AI / media / model …
   Evidence can be an AI answer you audited, a synthetic-media tell you judged, or something from training, testing or fooling an image or pose model.
2. Speakers: each side nominates one opener (90 seconds) and a different replier (45 seconds). Every pair still preps so the nominees have points to use. Your teacher clocks and calls the four speakers only.
3. Promise speaks (90 seconds); pitfalls side only listens.
4. Pitfalls speaks (90 seconds); promise side only listens.
5. Reply (45 seconds each side): aim at the other side's strongest point, not a new speech.
6. Re-place (1 minute): silently place yourself again on the main motion (agree / disagree / not sure).

Pull the threads together. AI can open doors (creativity, access, speed, models that learn from balanced examples) and create real costs (errors that sound true, biased outputs, over-reliance, weaker trust in media, models that are easy to fool when data skews). Those are not slogans; several of them connect to answers you audited, media you have had to judge, and image or pose models you trained or tested.