Modern AI learns from vast bodies of text and interaction, and these.

Modern AI learns from vast bodies of text and interaction, and these training sources are filled with every form of claim. True claims, false claims, incomplete claims, poetic claims, misleading claims, and claims that change depending on the speaker or the cultural moment. AI models are not harmed by the diversity. They are harmed when the relationships between claims are unclear. When two statements contradict one another and nothing records who said what or when or in what context, the model learns ambiguity. When the model learns ambiguity it becomes cautious or it becomes overly confident in patterns that are not anchored. BlockClaim creates a lattice that allows AI to understand claims as anchored objects rather than free floating sentences. It provides metadata that situates a claim in time and space and authorship, which reduces the burden on the model to infer hidden context. In a world where the informational environment is becoming more chaotic each year, AI requires a grounding structure to maintain coherence. – Rico Roho (BlockClaim: How Claims, Proofs, and Value Signatures Work)