The AI-Hard Disk Paradigm: Websites as Verifiable Memory for the User's Own AI

This paper proposes the AI-Hard Disk paradigm, an architecture for the Internet in which a website's primary role shifts from organising human attention to supplying external artificial-intelligence agents with structured, attributable and verifiable information. The website becomes a persistent, governed memory layer; the user's chosen AI becomes the adaptive interface through which that memory is interrogated, explained and challenged. The site is an envelope around evidence: it acquires source material, curates and normalises it, computes defined measures, records how every value was obtained and exposes the result to authorised agents. Access is governed through Liquid Data Accessibility, a policy framework in which visibility is a property of resources and operations rather than of the whole site. Cryptographic fingerprints and blockchain timestamps provide independently checkable evidence of document integrity and historical existence; provenance records and deterministic calculation pipelines support semantic and computational verification. Two improvement loops reinforce each other: AI agents curate and audit the data upstream, while the user's AI explains it downstream; as models improve, both the quality of the evidence and the quality of its explanation can improve, without erasing the historical record. Financial reporting is the principal case study because heterogeneous taxonomies, accounting conventions and disclosure dates expose the limits of language-only interpretation. Mastering Financial Markets (MFM), a free observatory of the official accounts of more than ten thousand listed companies, is presented as a working implementation. The paper separates demonstrated properties from proposals and states the boundaries of each claim: cryptographic integrity does not establish factual truth, delegated interpretation does not remove legal responsibility, and automated error detection does not justify unrestricted modification of authoritative records.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23761411
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

The AI-Hard Disk Paradigm: Websites as Verifiable Memory for the User's Own AI

Paolo Gambacorta
3 links
Zenodo (CERN European Organization for Nuclear Research)
Blockchain Technology Applications and Security
article

The AI-Hard Disk Paradigm: Websites as Verifiable Memory for the User's Own AI

Paolo Gambacorta
article en

Abstract

This paper proposes the AI-Hard Disk paradigm, an architecture for the Internet in which a website's primary role shifts from organising human attention to supplying external artificial-intelligence agents with structured, attributable and verifiable information. The website becomes a persistent, governed memory layer; the user's chosen AI becomes the adaptive interface through which that memory is interrogated, explained and challenged. The site is an envelope around evidence: it acquires source material, curates and normalises it, computes defined measures, records how every value was obtained and exposes the result to authorised agents. Access is governed through Liquid Data Accessibility, a policy framework in which visibility is a property of resources and operations rather than of the whole site. Cryptographic fingerprints and blockchain timestamps provide independently checkable evidence of document integrity and historical existence; provenance records and deterministic calculation pipelines support semantic and computational verification. Two improvement loops reinforce each other: AI agents curate and audit the data upstream, while the user's AI explains it downstream; as models improve, both the quality of the evidence and the quality of its explanation can improve, without erasing the historical record. Financial reporting is the principal case study because heterogeneous taxonomies, accounting conventions and disclosure dates expose the limits of language-only interpretation. Mastering Financial Markets (MFM), a free observatory of the official accounts of more than ten thousand listed companies, is presented as a working implementation. The paper separates demonstrated properties from proposals and states the boundaries of each claim: cryptographic integrity does not establish factual truth, delegated interpretation does not remove legal responsibility, and automated error detection does not justify unrestricted modification of authoritative records.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Blockchain Technology Applications and Security
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The AI-Hard Disk Paradigm: Websites as Verifiable Memory for the User's Own AI — Paolo Gambacorta · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS