Generative AI is powerful but needs strong constraints to produce meaningful and trustworthy results. Without these controls, it can generate useless or harmful outputs, especially in areas requiring precision. Ensuring high-quality results requires continuous quantitative metrics and standardized benchmarks.

How can we impose and automate these controls? We can test this in quantitative finance, where trading signals are generated from various data sources (news, online chatter, custom datasets). Quantitative finance provides rigorous performance metrics, making it an ideal environment to test and refine AI control methods.