List every place a published AI constitution asks a model to act on its own values, and every place it asks the model to accept correction. Find where both apply and conflict.
Real AI developers have to resolve this tension in writing. Mapping it clearly helps everyone see the choices being made.
Output: An argument map that resolves each conflict using Wolff’s account of autonomy and Christiano’s definition of corrigibility, and says which resolution the documents actually choose.
Write your question in one sentence.
Spend 30 minutes finding what has already been written about it.
Collect evidence in a simple table: claim, source, how strong.
Draft 1–2 pages: answer first, then reasons, then uncertainties.
Ask one person to poke holes in it, revise, and share.
All steps done
Share what you made, then try another project. The PDF version has room for notes.
In Anthropic and CIP’s study, about 1,000 Americans used the open-source tool Polis to write a constitution for an AI. Run the same process with 30–100 students and compare your result with theirs.
Palisade found some models sabotaged a shutdown script to finish a maths task, and released code and traces. Rerun a slice on cheaper or small open models, adding conditions that separate the explanations: task complete vs incomplete, and conflicting vs unambiguous instructions.
Anthropic tested 16 models in simulated corporate scenarios and found models from every developer sometimes chose harmful insider actions to avoid replacement or meet a goal. The code is public. Run a subset on small or low-cost models, separating the replacement threat from the goal conflict.
