Before You Decide: The Decision Series — Ten Papers on Artificial Intelligence for People Who Have to Decide

This volume collects ten papers arguing that four foundational definitions — of intelligence, AI, the robot, and the Silicon Era — share a common structural limitation and that completing them produces a unified account of what this technological transition is. Papers 1–3 establish the foundation: a deficiency-substrate account of human cognition, empirical evidence for disciplinary convergence under AI methodology (CKA measurements, bibliometric analysis, 2024 Nobel confirmations), and a formalization of connective abduction as research methodology. Papers 4–6 develop the definition arc: a tool-inversion analysis of AI, the structural incompatibility of human-centered workflows with AI capability, and a proof that every human is structurally priceless to the AI pipeline. Papers 7–9 develop the robot arc: Distributed Agency Computation, the carbon-silicon substrate competition, and World Signal Sufficiency — the thesis that Earth's physically governed signal flows constitute a sufficient computational environment for AI. Paper 10 closes the arc with the Definitional Cascade and a redefinition of the Silicon Era as the age of planetary computation. The series introduces thirty-two original concepts in a published dependency architecture. Empirical components include cross-model representational analysis, bibliometric phase-transition data, and proposed experimental designs. Revision Note: - Paper 5 (TAP): Corrected McKinsey (2025) figures throughout — adoption rate updated from 78% to 88%; "over 80% report no measurable performance improvement" corrected to "only 39% report any enterprise-level EBIT impact." Seven instances corrected including subtitle, abstract, Section 1.1, Section 1.2, Controls, and Section 5.- Paper 8 (Thermodynamic Wall): Same McKinsey correction applied (1 instance).- Original figures were derived from secondary interpretations and did not match the McKinsey primary source (The State of AI, November 2025).