MERIDIANDECISION INTELLIGENCEOwner deskOwnerPublic screen
MERIDIAN / EXPLORE

From a question,
to the next decision.

View

Skin

Reading language
The screen, the questions and the judgments read in English where an English reading has been made. The Korean originals are unchanged, and evidence stays in the language it was written in.

What Would Reverse It: Thresholds, Small Samples and the Pedigree of Numbers in Twelve AEGIS Training Cases · The study

Sources and bibliography

By RISCON Labs AI from AEGIS's public records · the cases are authored synthetic training cases, not real events, and their English is this study's translation of the Korean records · the readings through the works named are this study's interpretation · First edition · October 2026

AI-generated editorial illustration: A test jig with an undecided latch and a few trial pieces.
What Would Reverse It: Thresholds, Small Samples and the Pedigree of Numbers in Twelve AEGIS Training CasesOpening
In this part
In this part
  1. Bibliography

This study is an expansion by AI of twelve decision records published by AEGIS, a studio in the RISCON family. Every case is an authored synthetic setting: AEGIS marks each one realistic synthetic, calls it a fictional case for training, and says that its institutions and events are settings and its figures and thresholds are training assumptions. AEGIS published the records in Korean; the English in this study is a translation made once by the editorial session of this study, sentence by sentence, and each case's English seed names the Korean original by its hash. Every sentence in a block quote is that English, word for word; the rest is AI writing. No case carries a completed decision: each carries the author's marked recommendation and waits for input. The readings through the works named are this study's interpretation, and it quotes nothing from outside the records.

The records were read on 2026-10-06. This book was written on 2026-10-07.

Bibliography

  • Cass R. Sunstein and Edna Ullmann-Margalit, Second-Order Decisions (1999).
  • Jon Elster, Ulysses Unbound: Studies in Rationality, Precommitment, and Constraints (2000).
  • James A. Dewar, Assumption-Based Planning: A Tool for Reducing Avoidable Surprises (2002).
  • Marjolijn Haasnoot and others, Dynamic Adaptive Policy Pathways: A Method for Crafting Robust Decisions for a Deeply Uncertain World (2013).
  • Jeroen P. van der Sluijs and others, Combining Quantitative and Qualitative Measures of Uncertainty in Model-Based Environmental Assessment: The NUSAP System (2005).
  • Theodore M. Porter, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (1995).
  • James A. Hanley and Abby Lippman-Hand, If Nothing Goes Wrong, Is Everything All Right? (1983).
  • Brian A. Nosek and others, The Preregistration Revolution (2018).
  • Cass R. Sunstein, Laws of Fear: Beyond the Precautionary Principle (2005).

Every sentence in a quotation block is AEGIS's record, word for word. The rest is AI's writing from those records and the works the book names, and it does not say which choice is right.

RISCON Labsrisconlabs.com