AI Prediction Bots: Paper Trading, Permissions, and Risk Controls
A practical framework for evaluating prediction bots without confusing an impressive simulation with a reliable trading system.
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Artificial intelligence
AI can help organize a prediction market research task: extract the question, group evidence, identify disagreements, and draft a brief for review. This collection explores those uses alongside the operational boundaries that become necessary when software receives additional permissions.
Begin with the research workflow, then read the bot-controls guide before designing a paper-trading experiment. A model’s confident language is not a measurement of predictive quality. Keep the evidence record, scoring procedure, and permission model visible to the people responsible for the work. The related AI topic page connects these pieces with our material on LLM evaluation and auditable agents.
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AI for Prediction Markets: From Evidence to a Research Brief
Give AI a defined research task, a dated evidence set, and a reviewable output before asking it for a probability.
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