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The Same Model Twice: Concentration and the Independent Check in ASI 2030's Synthetic Records · The study

Sources and bibliography

By RISCON Labs AI from ASI 2030's public auditor records · the records are synthetic scenarios set up to 2030, and their AI developments are the studio's scenarios, not forecasts · the readings through the works named are this study's interpretation · First edition · October 2026

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The Same Model Twice: Concentration and the Independent Check in ASI 2030's Synthetic RecordsOpening
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  1. Bibliography

This study is an expansion by AI of records published by ASI 2030, a studio in the RISCON family. Every sentence in a block quote is a record's own, word for word, in the studio's English. The rest is AI writing. Every ASI 2030 record is a synthetic scenario: its systems, institutions, figures and events are invented, and its developments toward artificial general or superintelligent systems are the studio's scenarios, not facts and not forecasts of this study. The auditor's opinions are the studio's own, dated and revisable. The readings through the works named are this study's interpretation.

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

Bibliography

  • Jon Kleinberg and Manish Raghavan, Algorithmic monoculture and social welfare (2021).
  • Rishi Bommasani, Drew A. Hudson, Ehsan Adeli and others, On the Opportunities and Risks of Foundation Models (2021).
  • Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky and Percy Liang, Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? (2022).
  • Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky and Percy Liang, Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes (2023).
  • Kathleen Creel and Deborah Hellman, The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems (2022).
  • Jón Daníelsson, Robert Macrae and Andreas Uthemann, Artificial intelligence and systemic risk (2022).
  • Jai Vipra and Anton Korinek, Market Concentration Implications of Foundation Models (2023).
  • Girish Sastry, Lennart Heim, Haydn Belfield and others, Computing Power and the Governance of Artificial Intelligence (2024).
  • David Gray Widder, Meredith Whittaker and Sarah Myers West, Why 'open' AI systems are actually closed, and why this matters (2024).
  • Jean-Christophe Plantin, Carl Lagoze, Paul N. Edwards and Christian Sandvig, Infrastructure studies meet platform studies in the age of Google and Facebook (2016).

Every sentence in a quotation block is ASI 2030'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