Provenance - Bryant McGill

# Provenance **Domain:** Evidence / Identity / Data Governance **Doc Type:** Canonical Infrastructure Node **Maturity:** Foundational ## Definition **Provenance** is the documented history of an object's, claim's or system's origin, custody, transformation and interpretation. ## Evolutionary Nexus Fossils, genome assemblies, expert-system rules and corporate lineages become historical evidence only when their relations remain traceable. [[articles/The Evolutionary Roots of Silicon Valley|The Evolutionary Roots of Silicon Valley]] makes provenance the connective tissue joining those domains. ## Continuity Context A reconstructed person requires more than recognizable output. Sources, acquisition conditions, transformations, missing intervals and authorized custodians must be inspectable. Provenance can establish descent and restoration integrity without, by itself, proving first-person continuity. ## Key Insight **Without provenance, resemblance becomes assertion and continuity becomes administratively convenient fiction.** ## Computational Language Context [[projects/Ten Years Building a Symbolic Language Engine|Ten Years Building a Symbolic Language Engine]] applies provenance at the level of linguistic output. Its proposed modern architecture would preserve whether a suggestion came from phonological matching, a semantic or taxonomic relation, corpus attestation, a formal constraint, or a probabilistic model. [[wiki/Provenance-Sensitive Multiplicity|Provenance-sensitive multiplicity]] keeps those valid but non-equivalent kinds of evidence visible at once. It therefore offers a general design principle for hybrid intelligence: integrate heterogeneous sources without pretending that they make the same claim or carry the same evidentiary weight. ## See Also [[wiki/Proof of Descent|Proof of Descent]], [[wiki/Continuity Evidence vs Continuity|Continuity Evidence vs Continuity]], [[wiki/Technical Archaeology|Technical Archaeology]], [[wiki/Restoration Integrity|Restoration Integrity]], [[wiki/Corpus Engineering|Corpus Engineering]], [[wiki/Provenance-Sensitive Multiplicity|Provenance-Sensitive Multiplicity]] ## Relationships - **Collection route:** [[collections/Neurotech|Neurotech]]. - **Source context:** [[articles/Technologies for Consciousness Mapping and Transfer|Technologies for Consciousness Mapping and Transfer]] and [[articles/Mind Uploading and AI — The Host is Reusable and the Person is the Delta|Mind Uploading and AI — The Host is Reusable and the Person is the Delta]]. - **Inference provenance:** [[research/Research Inferences|Research Inferences]]. ## Research Inferences  These entries translate the forward-looking register in [[research/Research Inferences|Research Inferences]] into ordinary wiki prose. The tier labels apply to the inference, not automatically to every factual anchor inside it. The interpretive frame comes from [[articles/Technologies for Consciousness Mapping and Transfer|Technologies for Consciousness Mapping and Transfer]] and [[articles/Mind Uploading and AI — The Host is Reusable and the Person is the Delta|Mind Uploading and AI — The Host is Reusable and the Person is the Delta]]. Collection route: [[collections/Neurotech|Neurotech]]. - **INF-0115 — Strongly indicated.** If reconstructions are revised, then results derived from them must cite a version to be reproducible. Provenance infrastructure for neural data is therefore not bureaucratic overhead but a precondition for any claim about a specific mapped brain.  ## Research Inference Attractors  These are secondary semantic placements for the inference attractor network. Each statement keeps its original ID and tier; its canonical cluster page links back to every destination. Source register: [[research/Research Inferences|Research Inferences]]. Interpretive context: [[articles/Technologies for Consciousness Mapping and Transfer|Technologies for Consciousness Mapping and Transfer]] and [[articles/Mind Uploading and AI — The Host is Reusable and the Person is the Delta|Mind Uploading and AI — The Host is Reusable and the Person is the Delta]]. Collection route: [[collections/Neurotech|Neurotech]]. - **INF-0256 — Analytic.** Recording acquisition device, subject state, preprocessing, and software version alongside the data is what allows a result to be re-derived later. In a continuity context that same metadata is the difference between a person's record and an unattributable file. - **Canonical cluster:** [[wiki/Continuity Governance|Continuity Governance]] - **INF-0263 — Strongly indicated.** Capability domains accelerate once a benchmark exists because improvement becomes visible and comparable. Establishing benchmarks for residual sufficiency and emulation fidelity would do for continuity what ImageNet did for vision. - **Canonical cluster:** [[wiki/Continuity Governance|Continuity Governance]] - **INF-0265 — Analytic.** A person's hosted state will accumulate versions through migration, restoration, and model change, requiring an explicit versioning scheme with defined compatibility semantics. Software has a mature vocabulary for exactly this, and importing it is the fastest available route to coherence. - **Canonical cluster:** [[wiki/Continuity Governance|Continuity Governance]]  ## Simple Reminders, Quotations, and Thoughts > "As long as something can be relayed that resolves uncertainty, that is the fundamental nature of information. While this sounds surprisingly obvious, it was an important point, given how many different languages people speak and how one utterance could be meaningful to one person, and unintelligible to another. Until Shannon's theory was formulated, it was not known how to compensate for these types of "psychological factors" appropriately. Shannon built on the work of fellow researchers Ralph Hartley and Harry Nyquist to reveal that coding and symbols were the key to resolving whether two sides of a communication had a common understanding of the uncertainty being resolved." > **— Andrew Lih**, *2012, Edge Annual Question, “What Is Your Favorite Deep, Elegant, or Beautiful Explanation?”* [[reminders/Information/Information Resolves Uncertainty Across Every Medium by Andrew Lih|Information Resolves Uncertainty Across Every Medium by Andrew Lih]] > "Building models is very different from proclaiming truths. It's a never-ending process of discovery and refinement, not a war to win or destination to reach. Uncertainty is intrinsic to the process of finding out what you don't know, not a weakness to avoid. Bugs are features — violations of expectations are opportunities to refine them. And decisions are made by evaluating what works better, not by invoking received wisdom." > **— Neil Gershenfeld**, *2011, Edge Annual Question, “What Scientific Concept Would Improve Everybody's Cognitive Toolkit?”* [[reminders/Information/Uncertainty Is a Feature of Discovery by Neil Gershenfeld|Uncertainty Is a Feature of Discovery by Neil Gershenfeld]]