AI Governance
Articles tagged with "AI Governance"
- Answers to Critics: Where the AI Governance Framework Holds and Changes A direct response to serious criticism of the framework, including what changed, what was clarified, and what still holds. February 8, 2026
- AI Governance Update for February 2026 Two years of AI progress tested the oracle-versus-assistant distinction. The framework still holds, but agentic AI created new governance gaps. February 8, 2026
- The Universal Interface Thesis: Why AI May Replace Traditional Software Interfaces AI-generated code may become the universal interface for knowledge work, software, machines, and complex control systems. January 2, 2026
- EKA in Practice: What Happened When We Deployed the Framework What we learned by deploying Executable Knowledge Architecture in practice, including where the framework held up and what changed. January 2, 2026
- The Return of the Assistant: Why AI Beats DIY Knowledge Work AI assistants let knowledge workers delegate execution while retaining the autonomy they gained from doing the work themselves. January 1, 2026
- Why Automating Expertise Gets Easier as AI Improves As AI lowers the barriers to implementation, more expertise becomes software. This changes where value holds and where it moves. June 30, 2025
- Ontology Generation: How AI Logs Turn Work Into Organizational Knowledge When AI becomes the universal interface, interaction logs can reveal both what an organization does and the concepts it uses. June 30, 2025
- Agentic AI as Universal Interface: Why Expertise Becomes Software Agentic AI removes two barriers that kept expertise from becoming software: coding skill and system access knowledge. June 30, 2025
- Executable Knowledge Architecture for AI in Professional Work A framework for integrating AI into professional work while preserving expertise, improving reproducibility, and closing the governance gap around AI-generated output. January 7, 2025
- What AI Benchmarks Miss About Real Professional Work Benchmarks like GDPval measure well-specified tasks with verifiable answers. They miss the ambiguous, judgment-intensive work where professional expertise still matters. December 31, 2024
- Capability Governance: How to Govern AI-Generated Artifacts A practical framework for governing AI-generated artifacts through defensibility, exposed methodology, empirical track record, and clear stakeholder obligations. December 27, 2024
- The Strong Oracle Trap: Why Better AI Dialogue Still Does Not Solve Verification Thorough AI dialogue can improve outputs, but it still does not solve the verification problem in professional work. November 26, 2024
- AI as Oracle vs Assistant: The Choice That Determines Whether You Can Govern It The most important AI deployment choice is whether you ask for answers or execution. One creates verification problems; the other makes governance possible. November 5, 2024
- Why LLMs Seem Random but Still Produce Reliable Results Results from 700 runs across seven models show why direct answers stay inconsistent while executable methods can still produce reliable outcomes. November 1, 2024
- AI-First Software: What Changes When Language Becomes the Interface Generative AI changes software design by making language a usable interface, shifting applications from fixed screens toward on-demand interaction. April 4, 2024
- AI Table Extraction Comparison: Claude vs Docling vs ScaleDP A practical comparison of Claude, Docling, and ScaleDP for AI table extraction, with accuracy gaps that matter for document processing at scale. February 20, 2024
- Why 'Stochastic Parrots' Are More Powerful Than Critics Admit Why the 'stochastic parrot' critique misses the practical significance of generative AI for knowledge work. January 15, 2023