Seattle Method

The future of information processing spans a possible spectrum from symbolic spreadsheets, to AI‑augmented spreadsheets, to fully grounded pragmatic systems powered by neuro‑semantic and neuro‑pragmatic AI. As I see it, there is a spectrum of three broad possible alternatives for processing information going forward.  Those broad alternatives appear to be: Spreadsheet Centric (Status quo) : Continue using electronic spreadsheets as the primary mechanism for organizing, calculating, and reporting information. This approach remains symbolic and manual, with limited structure and no semantic or pragmatic grounding. Spreadsheet + AI (Augmented Symbolic) : Retain electronic spreadsheets as the core environment but use AI to assist/augment with formulas, modeling, cleaning, and analysis. This enhances productivity but still operates within a symbolic, ungrounded paradigm. Pragmatic Systems + AI (Grounded, Model Driven) : Transition to pragmatic systems that encode meaning, evidence,...

Information is constructed from concepts, is expressed as propositions, organized into structures, encoded in physical technical representations, transformed across time and scope, and verified for conformance, correctness, and coherence. This is the complete structural model of information separated into layers that accommodates different patterns of information including roll ups, roll forwards, restatements, reconciliations, and comparatives as structural primitives.  Each layer is clearly differentiated, each layer building on the layer below it, and each layer capturing the structural nature of information. Layer 1: Conceptual Layer (What exists) The layer of concepts, categories, and types that define the semantic universe in which the information lives. This layer answers: What kinds of things can information be about? Examples: Asset, Liability, Equity This is the “ontology” layer; the vocabulary of meaning. Layer 2: Propositional Layer (What is claimed) The layer of claims...

The Pragmatic Web is a thing. And accounting, reporting (in particular compliance reporting), audit, and analysis need the Pragmatic Web. The notion of the Pragmatic Web was first articulated in 2002 in a paper by Munindar P. Singh, The Pragmatic Web: Preliminary Thoughts , and in 2006 by Mareike Schoop, Aldo de Moor, and Jan L.G. Dietz in their paper, The Pragmatic Web: A Manifesto . In that manifesto, they state: " The vision of the Pragmatic Web is thus to augment human collaboration effectively by appropriate technologies, such as systems for ontology negotiations, for ontology-based business interactions, and for pragmatic ontology-building efforts in communities of practice. In this view, the Pragmatic Web complements the Semantic Web by improving the quality and legitimacy of collaborative, goal-oriented discourses in communities ." So, the Pragmatic Web complements the Semantic Web; it does not replace it.  The Semantic Web is simply not enough and it's purpose i...

As I explained in another blog post, accounting is the universal technology of accountability . There is no "open world assumption". The essence of accounting is that it is a deliberately and consciously created to be a deterministic system. Accounting has solid boundaries. Accounting is a closed world. People need to be aware of something.  Machines such as computers do not "understand" in the sense that humans understand.  Saying this another way, the notion of “understanding” in the human sense cannot be attributed to machines.  Computers are machines; they are not people. Meaning is mediated, situated, and carried by human collectives.  Meaning is agreed to by human collectives . Meaning is an agreement; meaning is intersubjective . Meaning is the mutual cognitive agreed upon understanding by the members of some specific group. Understanding is individual, dynamic, and a purely human characteristic. Machines simply have no capability to actually understand wh...

In her book, Ontology Pipeline: A framework for building knowledge infrastructures , author Jessica Talisman describes the notion of a "semantic knowledge management system" (SKMS). Paraphrasing, a semantic knowledge management system is an organized structure of concepts, definitions, and relationships that lets both people and machines interpret information consistently and act on that information with confidence . A semantic knowledge management system (SKMS) is essentially the institutional memory of an enterprise; formalized, organized, defragmented, structured, machine‑interpretable, and governed so both humans and AI can act on it with confidence. At a high level, it is the shift from “knowledge stored in people’s heads and scattered documents” to "knowledge engineered as a durable, computable asset". In the past, humans would "dip" into the well of knowledge.  Now, because of artificial intelligence, both humans and machines will be "dipping...

The purpose of the Triangle of Meaning is to understand how to make communication reliable, repeatable, and interoperable. Basically the triangle of meaning is about precision of communication. As explained by the Triangle of Meaning a conceptualization (a thought process), referents in the conceptualization (real world things being conceptualized in the form of a model ), and representations or implementations of the conceptualization of the real world thing needs to be in sync in order to communicate effectively . XBRL provides both a global open industry standard technical syntax ( implementation ) and a semantic model ( conceptualization ) of the real world notion of a "business report" ( real world thing ).  Both the technical syntax and the semantic model are described in the many  XBRL Specifications . The real world things that fit into that model are defined within my Essence of Accounting , reporting frameworks used , accounting and reporting standards written, con...