The Blackwell-Hart Technical Bulletins
The Blackwell-Hart Technical Bulletins serve as the research and commentary archive for the Blackwell-Hart Methodology™ (BHM™). The archive documents applied observations, case studies, and structured analysis related to AI-assisted discovery systems, authority infrastructure, and entity interpretation.
When Recognition Isn't Enough
AI systems can recognise an entity without correctly understanding its category, relationships, purpose or work. Discover how the Blackwell-Hart Methodology™ examines the difference between AI recognition and accurate entity interpretation across AI-assisted discovery environments.
Blackwell-Hart Methodology™ Technical Bulletin 26-28: Interpretation Drift — When the Entity Changes Without Anyone Changing the Information
Interpretation drift occurs when AI systems represent an entity differently over time. Blackwell-Hart Methodology™ (BHM™) examines baseline observations, environmental changes, controlled re-observation, and attribution analysis to distinguish measurable changes in representation from assumptions about their causes.
Building BHM™: The Creation of a Methodology™
Discover how BHM™ developed from observation and recurring patterns into a methodology through testing, documentation, refinement, and measurement.