Book · English edition · Alexanja Senke
Human-AI Research Without Pretending to Know
Mathematics, Physics, and the Architecture of Verifiable Co-Intelligence
AI can be brilliant, fast — and convincingly wrong. This book explores how human structural intuition and machine-assisted research can work together while keeping errors, failed routes and uncertainty visible before they become authority.
On request, the Interlink Presence voice reads original print passages from the A5 hardcover edition: Prologue — It Started With a Coffee (printed pages 7–9) or Chapter 6 — Fail Closed (printed pages 32–33). These are two separate selected excerpts, not a continuous chapter. Select a passage in Presence and use its audio controls. No book file or page-viewer is hosted.
Choose a passage to hear ↗“The AI may be wrong. It may not act from an unresolved wrong state.”
FAIL CLOSED is not a prompt book and does not treat a language model as an oracle. It describes reconstruction before agreement, adversarial testing, parallel-path verification, evidence maturity and clearly defined next admissible steps.
Unresolved hypotheses, contradictions and abandoned routes remain part of the record — not failures to be erased.
The book draws on research case studies in mathematics, physics and AI governance, including total-positive matrices, Gaussian shifts, exploratory Navier–Stokes and Riemann work, and execution-bound governance architectures.
The presence of a case study does not imply a solved Millennium problem, independent peer review, or a claim of universal correctness.