video1.0<iframe src="https://www.loom.com/embed/2b60b4ae65234860abe23aaf2baa2734" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/2b60b4ae65234860abe23aaf2baa2734-b7fe166b52556d2b.gif10415.106This Loom explains how to use public data and critical thinking to build credible, values-aware models for Universal Basic Income while avoiding misleading KPIs. It discusses SSI and data access limits, points viewers to data.gov and specific micro-simulation approaches, and emphasizes self-critique about hidden bias from what data can or cannot be collected. The session also covers AI safety and alignment concerns via METR.org threat research, agent risks, and practical guidance for using projects, outlines, and character-driven dialogue for writing. It then runs writing exercises on clashing genres and visual styles and demonstrates using AI tools to generate story beats and refine scenes.