Stanford's Michael Bernstein builds a "What-If Machine" for simulating decisions with AI
msbernst · x · 2026-09-03
Stanford's Michael Bernstein writes at Simile about the "What-If Machine" — an AI behavioral simulation system.
- Core idea: big platform decisions (new products, pricing, policies) are all what-if questions, yet industry practice is mostly "launch-and-hope" followed by reactive damage control.
- A What-If Machine lets teams simulate how people might react before shipping, exploring paths and understanding why outcomes occur.
- The hard part: these are out-of-distribution predictions and counterfactuals — memorizing history isn't enough; you need to model the mechanisms of human behavior, both what people do and why.
More from Research
- Kanishka Misra's semantic cognition x LMs opinion piece to appear in Current Opinion in Behavioral Sciences — najoungkim · 2026-09-03
- Distillation debate: RL, not distilling from sol, likely explains the model's gains — JoshPurtell · 2026-09-03
- Fixing Ideogram 4's Banner and Boosting Prompt Adherence by Fine-Tuning the Text Encoder — mrjackspade · 2026-09-03
- William Tunstall-Pedoe: The 'Trust Ceiling' — Trillions In Value Stuck Behind Unreliable AI — williamtp · 2026-09-03
- TDmol uses 2D molecules as a bridge: text guidance boosts 3D structure similarity by 41% — bravo_abad · 2026-09-03
- Researchers turn to DSRL to improve BC diffusion policies via latent-space RL — DominiqueCAPaul · 2026-09-03