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.
The Difference Between Being Relevant and Being Retrieved
Explore the difference between an entity being relevant to an AI query and actually being retrieved in the answer. Understand how AI systems construct answers and why relevance isn't enough. Learn more from TS Blackwell-Hart.
When AI Knows Who You Are but Doesn't Recommend You
AI systems may recognize an entity when named but omit it from answers to relevant, non-branded questions. This experiment examines entity resolution, source relationships, category association, and recommendation across ChatGPT and Gemini.
Building BHM™: The Creation of a Methodology™
AI is changing how people discover individuals online. Learn how the BHM™ Individual Assessment measures identity recognition, category association, and the digital signals AI systems use to interpret professional identities.