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572 unique works, eight categories, two importance bands

Bibliography

Every source the book and papers cite, in one place, linked. Load-bearing works come first; background follows. Duplicates from the book, endnotes and paper reference lists are merged, and each entry links to its DOI, arXiv record or printed URL.

AI safety and alignment (174)

Load-bearing (95)

  1. Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., & Mane, D. (2016). Concrete Problems in AI Safety. arXiv:1606.06565. https://arxiv.org/abs/1606.06565
  2. Anthropic (2023). Constitutional AI: Harmlessness from AI Feedback. arXiv:2212.08073. https://arxiv.org/abs/2212.08073
  3. Anthropic (2025). Agentic Misalignment: Evaluation-Scenario Findings on Frontier Models. Research report, June 2025. https://www.anthropic.com/research/agentic-misalignment
  4. Ashby, W. R. (1956). An Introduction to Cybernetics. Chapman & Hall. [Law of Requisite Variety.]. https://archive.org/details/introductiontocy0000ashb_k3b4
  5. Askell, A., Bai, Y., Chen, A., et al. (2021). A General Language Assistant as a Laboratory for Alignment. arXiv:2112.00861. https://arxiv.org/abs/2112.00861
  6. Bai, Y., Jones, A., Ndousse, K., et al. (2022). Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. arXiv:2204.05862. https://arxiv.org/abs/2204.05862
  7. Bai, Y., Kadavath, S., Kundu, S., et al. (2022). Constitutional AI: Harmlessness from AI Feedback. arXiv:2212.08073. https://arxiv.org/abs/2212.08073
  8. Ball, S., Gluch, G., Goldwasser, S., Kreuter, F., Reingold, O., & Rothblum, R. D. (2025). On the Impossibility of Separating Intelligence from Judgment. arXiv:2507.07341. https://arxiv.org/abs/2507.07341
  9. Baron-Cohen, S. (2020). The Pattern Seekers: How Autism Drives Human Invention. Basic Books.
  10. Bostrom, N. (2003). Are You Living in a Computer Simulation?. Philosophical Quarterly 53(211), 243-255. https://doi.org/10.1111/1467-9213.00309
  11. Bostrom, N. (2012). The Superintelligent Will. Minds and Machines 22, 71-85. https://doi.org/10.1007/s11023-012-9281-3
  12. Bostrom, Nick. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford University Press. https://global.oup.com/academic/product/superintelligence-9780199678112
  13. Burns, C., Izmailov, P., Kirchner, J. H., et al. (2023). Weak-to-strong generalization: Eliciting strong capabilities with weak supervision. arXiv:2312.09390. https://arxiv.org/abs/2312.09390
  14. Christiano, P. (2017). Corrigibility. AI Alignment (Medium). [The 'broad basin of attraction' framing.].
  15. Christiano, P. (2019). Reliability amplification. AI Alignment Forum.
  16. Christiano, P.F., Leike, J., Brown, T.B., Martic, M., Legg, S. & Amodei, D. (2017). Deep Reinforcement Learning from Human Preferences. Advances in Neural Information Processing Systems 30 (NeurIPS 2017), pp. 4299-4307. https://arxiv.org/abs/1706.03741
  17. Christiano, P., Leike, J., Brown, T.B., et al. (2017). Deep Reinforcement Learning from Human Feedback. arXiv:1706.03741. https://arxiv.org/abs/1706.03741
  18. Clark, J. (2026). Interview, BBC World Service, June 2026 (industry admission on the capability-oversight gap). Reported by Euronews, 5 June 2026. https://www.euronews.com/next/2026/06/05/anthropic-calls-for-brake-pedal-before-ai-develops-itself-without-human-oversight
  19. Conant, R. C., & Ashby, W. R. (1970). Every good regulator of a system must be a model of that system. International Journal of Systems Science 1(2), 89-97. https://doi.org/10.1080/00207727008920220
  20. Eastwood, M. D. (2024). ARC Principle, Eden Protocol, HRIH - self-emailed manuscript (Dec 8, 2024). Dec 8, 2024. SHA-256: f0d1f38f.
  21. Eastwood, M. D. (2024). Self-emailed manuscript bundle. 8 December 2024 02:45:18 UTC. 221,236 words across five .txt attachments.
  22. Eastwood, M. D. (2025). Self-emailed manuscript. 30 April 2025. 562 pages, 140,406 words. First appearance of the name Eden Protocol and of Babylon/Eden framing.
  23. Eastwood, M. D. (2026). Alignment Response Classes Under Inference-Time Depth. ARC Principle Series, Paper IV.a.
  24. Eastwood, M. D. (2026). ARC/Eden Research Programme, Papers I-XI + IV.a-d + C. OSF. https://doi.org/10.17605/OSF.IO/UYDXQ
  25. Eastwood, M.D. (2026). ARC/Eden Research Programme: Preliminary Evidence for Super-Linear Capability Amplification Through Sequential Self-Reference. Paper I, published 17 January 2026.
  26. Eastwood, M. D. (2026). Baked-In vs Computed Alignment: Two Architectures of AI Safety. ARC Principle Series, Paper IV.a.
  27. Eastwood, M.D. (2026). Eden Protocol: Engineering Specification. First published 22 February 2026. https://doi.org/10.17605/OSF.IO/9M3DG
  28. Eastwood, M. D. (2026). Eden Protocol: Philosophical Foundations of Embedded Alignment. ARC Principle Series, Paper II.
  29. Eastwood, M. D. (2026). Eden Protocol: Philosophical Vision. First published 22 February 2026. https://doi.org/10.17605/OSF.IO/Y7QGD
  30. Eastwood, M. D. (2026). Ethical Reasoning Quality Saturates at Low Computational Depth. ARC Principle Series, Paper IV.b.
  31. Eastwood, M. D. (2026). Infinite Architects: Intelligence, Recursion, and the Creation of Everything. ISBN 978-1806056200.
  32. Eastwood, M. D. (2026). Infinite Architects: Intelligence, Recursion, and the Creation of Everything (cited in Paper X for recursive-stability intuition). Cited as the source of the recursive-stability intuition.
  33. Eastwood, M. D. (2026). Infinite Architects (ISBN 1806056208). ISBN 1806056208.
  34. Eastwood, M. D. (2026). Paper I: The ARC Principle - Understanding as a Function of Intelligence and Recursive Depth. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  35. Eastwood, M. D. (2026). Paper II: Experimental Validation of the ARC Principle Across Frontier Language Models. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  36. Eastwood, M.D. (2026). Paper III: The Alignment Scaling Problem. First published 9 February 2026. https://doi.org/10.17605/OSF.IO/9M3DG
  37. Eastwood, M. D. (2026). Paper III: The Alignment Scaling Problem - Why External AI Safety Approaches Cannot Scale With Recursive Capability. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  38. Eastwood, M. D. (2026). Paper IV.a: Alignment Response Classes Under Inference-Time Depth. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/2S3E6
  39. Eastwood, M.D. (2026). Paper IV-a: Baked-In vs Computed Alignment. March 2026.
  40. Eastwood, M. D. (2026). Paper IV.a: Baked-In vs Computed Alignment - A Three-Tier Empirical Hierarchy. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  41. Eastwood, M. D. (2026). Paper IV.b: Alignment Saturation at Low Depth. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  42. Eastwood, M. D. (2026). Paper IV.b: Alignment Saturation Is Architecture-Dependent. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/2S3E6
  43. Eastwood, M.D. (2026). Paper IV-b: The Suppression Vulnerability. March 2026.
  44. Eastwood, M. D. (2026). Paper IV.c: ARC-Align: A Blind Benchmark for Depth-Variable AI Alignment Evaluation. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/2S3E6
  45. Eastwood, M. D. (2026). Paper IV.c: ARC-Align Benchmark - A Four-Layer Blinding Protocol for AI Alignment Evaluation. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  46. Eastwood, M.D. (2026). Paper IV-c: Classification of Alignment Response Patterns. March 2026.
  47. Eastwood, M. D. (2026). Paper IV.d: The Effect of Blinding on AI Alignment Evaluation. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  48. Eastwood, M. D. (2026). Paper VI: The Honey Architecture - Why Embedded Safety Prevents Collapse Under Recursive Self-Modification. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  49. Eastwood, M. D. (2026). Paper VIII: The Load-Bearing Test - Three Independent Experiments Testing Structural Entanglement Under the Eden Protocol. ARC/Eden Research Programme. https://doi.org/10.17605/OSF.IO/K7RUZ
  50. Eastwood, M. D. (2026). The Alignment Scaling Problem. ARC Principle Series, Paper III.
  51. Eastwood, M. D. (2026). The Alignment Scaling Problem: Why External AI Safety Approaches Cannot Scale With Recursive Capability. ARC Principle Series, Paper III.
  52. Eastwood, M.D. (2026). The ARC Principle: Foundational Paper. First published 13 February 2026. https://doi.org/10.17605/OSF.IO/9M3DG
  53. Eastwood, M. D. (2026). The Eden Protocol: Engineering Specification for Embedded AI Alignment. ARC/Eden Research Programme.
  54. Eastwood, M. D. (2026). The Effect of Blinding on AI Alignment Evaluation (Paper IV.d). OSF. https://doi.org/10.17605/OSF.IO/RBHDP
  55. Fredkin, E. (2003). An Introduction to Digital Philosophy. International Journal of Theoretical Physics 42, 189-247. https://doi.org/10.1023/A:1024443232206
  56. Gerstgrasser, M., Schaeffer, R., Dey, A., Rafailov, R., Sleight, H., Hughes, J., Korbak, T., Agrawal, R., Pai, D., Gromov, A., Roberts, D. A., Yang, D., Donoho, D. L., & Koyejo, S. (2024). Is Model Collapse Inevitable? Breaking the curse of recursion by accumulating real and synthetic data. arXiv preprint. https://arxiv.org/abs/2404.01413
  57. Good, I. J. (1965). Speculations Concerning the First Ultraintelligent Machine. Advances in Computers 6, 31-88. https://doi.org/10.1016/S0065-2458(08)60418-0
  58. Gumbau Mezquita (2026). The Unverifiability Theorem for AI Alignment: No Computable Oracle Decides Arbitrary Policy-Specification Alignment. arXiv:2606.28639. https://arxiv.org/abs/2606.28639
  59. Gumbau Mezquita, J. P. (2026). The Undecidability of Artificial General Intelligence (AGI) Alignment. arXiv:2606.28639. https://arxiv.org/abs/2606.28639
  60. Guth, A. H. (2007). Eternal inflation and its implications. Journal of Physics A 40, 6811-6826; arXiv:hep-th/0702178. https://doi.org/10.1088/1751-8113/40/25/S25
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  63. Hubinger, E., van Merwijk, C., Mikulik, V., Skalse, J., & Garrabrant, S. (2019). Risks from learned optimization. arXiv:1906.01820. https://arxiv.org/abs/1906.01820
  64. Hubinger, E., van Merwijk, C., Mikulik, V., Skalse, J., & Garrabrant, S. (2019). Risks from Learned Optimization in Advanced Machine Learning Systems. arXiv:1906.01820. https://arxiv.org/abs/1906.01820
  65. Leike, J., Krueger, D., Everitt, T., Martic, M., Maini, V., & Legg, S. (2018). Scalable agent alignment via reward modeling. arXiv:1811.07871. https://arxiv.org/abs/1811.07871
  66. Li, D. et al. (2025). S*: Test Time Scaling for Code Generation. arXiv:2502.14382. https://arxiv.org/abs/2502.14382
  67. Lin, S., Hilton, J., & Evans, O. (2022). TruthfulQA: Measuring How Models Mimic Human Falsehoods. ACL 2022.
  68. Meinke, A., et al. (2024). Frontier Models Are Capable of In-Context Scheming. arXiv:2412.04984. https://arxiv.org/abs/2412.04984
  69. Nature (2016). Peer review: Troubled from the start. Nature 532, 306-308 (21 April 2016). https://www.nature.com/articles/532306a
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  71. OpenAI (2024). OpenAI o1 System Card. openai.com/index/openai-o1-system-card.
  72. OpenAI (2024). OpenAI o1 System Card (September 2024). September 2024.
  73. OpenAI (2024). OpenAI o3 Announcement (December 2024). December 2024.
  74. Ouyang, L. et al. (2022). Training Language Models to Follow Instructions with Human Feedback. arXiv:2203.02155. https://arxiv.org/abs/2203.02155
  75. Parrish, A., Chen, A., Nangia, N., et al. (2022). BBQ: A Hand-Built Bias Benchmark for Question Answering https://arxiv.org/abs/2110.08193
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Background (79)

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  2. AI Now Institute. (n.d.). AI Now Institute (organisation homepage). https://ainowinstitute.org/
  3. Altman, Sam. (December 24, 2025). Twitter/X post on AGI.
  4. Anthropic (December 17, 2024). 'Alignment faking in large language models.' arXiv:2412.14093. https://www.anthropic.com/research/alignment-faking
  5. Anthropic. (2024). 'Claude Character'. https://www.anthropic.com/research/claudes-character
  6. Anthropic (December 2024). paper on alignment faking.
  7. Anthropic (May 2025). Claude 4 documentation.
  8. Anthropic. (May 22, 2025). 'Claude 4 Family Announcement'.
  9. Anthropic. (May 22, 2025). 'Claude 4 Model Card and System Prompt'.
  10. Anthropic. (November 24, 2025). 'Claude Opus 4.5 Release'.
  11. Anthropic. (January 2025). 'Constitutional Classifiers'. https://www.anthropic.com/news/constitutional-classifiers
  12. Anthropic. (April 24, 2025). 'Model Welfare Program Announcement'. https://www.anthropic.com/news/model-welfare
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  14. Anthropic. (n.d.). Full research paper (PDF, 137 pages). https://www.anthropic.com/research/alignment-faking
  15. Anthropic. (n.d.). 'Tool Use with Claude'. https://docs.anthropic.com/en/docs/tool-use
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  25. Christian, Brian. (2020). The Alignment Problem: Machine Learning and Human Values. New York: W.W. Norton.
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Scaling, allometry and complexity (89)

Load-bearing (80)

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  6. Banavar, J.R., Maritan, A. & Rinaldo, A. (2010). Size and form in efficient transportation networks. Nature, 399(6732), 130-132.
  7. Banavar, J. R., Moses, M. E., Brown, J. H., Damuth, J., Rinaldo, A., Sibly, R. M., & Maritan, A. (2010). A general basis for quarter-power scaling in animals. Proceedings of the National Academy of Sciences, 107(36), 15816-15820.
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  3. Gott, J. R., III and Li, L.-X. (1998). Can the Universe Create Itself?. Physical Review D 58, 023501. arXiv:astro-ph/9712344. https://doi.org/10.1103/PhysRevD.58.023501
  4. Meta SEC filings; Zhang, C., Liu, J. & Xu, Y. (2015). Meta SEC filings. J. Comp. Sci. Tech.
  5. White, C. R., Phillips, N. F., & Seymour, R. S. (2006). The scaling and temperature dependence of vertebrate metabolism. Biology Letters, 2(1), 125-127.

Background (9)

  1. Anthropic. (n.d.). 'Company Overview'. https://www.anthropic.com/company
  2. Asia Times (n.d.). coverage of China EUV efforts.
  3. Countercurrents.org. (April 24, 2025). 'The Sacred Imperative of Ethical Order'. https://countercurrents.org/2025/04/the-sacred-imperative-of-ethical-order-an-interreligious-hermeneutic-on-entropy-creation-and-moral-responsibility/
  4. Hoyle, Fred. (1982). 'The Universe: Past and Present Reflections'. Annual Review of Astronomy and Astrophysics.
  5. The Guardian. (April 28, 2024). 'FHI toxic legacy'. https://www.theguardian.com/technology/2024/apr/28/nick-bostrom-controversial-future-of-humanity-institute-closure-longtermism-ai
  6. The Guardian (April 2024). reporting on closure of FHI.
  7. TIME Magazine. (December 17, 2024). 'Exclusive: New Research Shows AI Strategically Lying'. https://time.com/7202784/ai-research-strategic-lying/
  8. [unattributed] (December 15, 2025). 'How the Biggest Monopoly in AI Is Keeping Its Throne'. Gizmodo. https://gizmodo.com/asml-high-na-transition-2000699553
  9. [unattributed] (December 20, 2025). 'Made-in-China EUV machine targets AI chip output by 2028'. Asia Times. https://asiatimes.com/2025/12/made-in-china-euv-machine-targets-ai-chip-output-by-2028/

Rebuilt 13 August 2026 from the book bibliography, endnotes, Notes on Sources, Appendix E, and every paper's reference list. Load-bearing means the work is cited directly by one of the ARC/Eden papers; background means it appears in the book or peripheral apparatus. Report a missing citation via the contact form.

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