Machine Readability Index (MRI)
MRIStructured Representation Quality for AI-Mediated Understanding
MRI measures how effectively property records enable AI-mediated understanding through structured, machine-readable representation.
Definition
MRI evaluates the machine-readiness of property records by assessing completeness, structure quality, verifiability, and consistency. Higher MRI correlates with improved AI-mediated discoverability and selection.
MRI evaluates representation quality from an AI-system perspective, assessing how effectively structured data enables discovery, comparison, and selection.
Conceptual Formula
MRI(e) = w1·C(e) + w2·S(e) + w3·V(e) + w4·Q(e), where C=completeness, S=structure, V=verifiability, Q=quality.What This Index Measures
MRI correlates with AI-mediated selection frequency.
Observational: Higher-MRI properties appear more frequently in AI selections.
Implications
- Improving MRI improves AI-mediated outcomes
Methodology
Type
index construction
Data Sources
Confidence Level
medium
Description
MRI(e) = w1·C(e) + w2·S(e) + w3·V(e) + w4·Q(e), where C=completeness, S=structure, V=verifiability, Q=quality.
Limitations
- Requires representation analysis
- Quality criteria may vary by domain
Key Takeaways
Key Points
- MRI scales 0-100
- Completeness is foundational
- Structure matters more than volume
Target Audience
Relevance Tags
Source Paper
Citation
For the Machine Readability Index (MRI), see HomeSelf Research (2026), The Zero-Click Economy.