Open Science Data Catalog
Download reproducible empirical datasets, inspect schemas, and verify benchmark scores
Open Data Access & Replicability
In adherence to scientific transparency and open-science standards, the Human Superintelligence Readiness Index (HSRI) distributes all normalized indicator matrices, composite country evaluations, and empirical evidence audit tables as standalone CSV datasets. All data is licensed under CC BY 4.0 for academic, policy, and independent auditing.
📖 Complete technical documentation with indicator definitions, weighting equations, and psychometric notes is published indata-dictionary.md.
Canonical Benchmark Datasets
hsri-country-scores.csv
Last updated: 2026-10-11Composite readiness scores and pillar coverage metrics across 39 benchmark economies.
Schema Reference
| Column | Type | Description |
|---|---|---|
country_iso3 | String (ISO-3) | Three-letter ISO nation identifier (e.g. USA, SGP, DEU) |
overall_score | Float [0-1] | Composite geometric readiness score normalized to [0, 1] |
core_pillars_available | Integer | Count of core pillars with observed empirical data (4) |
overall_coverage | Float [0-1] | Total observed indicator coverage fraction |
status | String | Qualification status (Rated) |
AI_Literacy_score | Float [0-1] | Pillar 1 cognitive & technical skills score |
Critical_Discernment_score | Float [0-1] | Pillar 2 epistemic verification score |
Institutional_Governance_score | Float [0-1] | Pillar 3 state regulatory agility score |
Digital_Infrastructure_score | Float [0-1] | Pillar 4 sovereign compute & grid resilience score |
hsri-normalized-indicators.csv
Last updated: 2026-10-11Direction-adjusted, min-max normalized indicator matrix preserving empirical structural missingness.
Schema Reference
| Column | Type | Description |
|---|---|---|
country_iso3 | String (ISO-3) | Three-letter ISO nation code |
AI_LIT_001..005 | Float / NaN | PIAAC, PISA digital reading, tertiary STEM & ITU skills |
META_COG_001..003 | Float / NaN | PISA discernment, EMLI (European-scope only), and cognitive calibration |
DEC_AGY_001..005 | Float | WGI regulatory quality/rule of law, V-Dem, and AI readiness |
ENAB_001..005 | Float | Sovereign compute density, high-speed fiber, and clean grid power |
hsri-evidence-table.csv
Last updated: 2026-10-11Claim-to-citation empirical audit matrix underpinning HSRI construct validity and literature synchronization.
Schema Reference
| Column | Type | Description |
|---|---|---|
claim | String | Audited scientific claim text regarding automation bias, metacognition, or governance |
page_reference | String | Methodology documentation reference |
evidence_tier | Categorical | Epistemic confidence tier (Strong, Moderate, Preliminary, Speculative) |
source_citation | String | Primary academic reference in APA format |
source_url_or_doi | URL / DOI | Permanent digital object identifier or publication URL |
reconciliation_flag | Categorical | Lane 1 literature audit synchronization status (CURRENT, REVIEW_REQUIRED, UPGRADE_CANDIDATE) |
hsri-unrated-nations.csv
Last updated: 2026-10-11Diagnostic register of 86 evaluated economies lacking sufficient multi-pillar microdata to receive benchmark ratings.
Schema Reference
| Column | Type | Description |
|---|---|---|
country_iso3 | String (ISO-3) | Three-letter ISO nation identifier |
country_name | String | Standard international English nation name |
region | Categorical | UN geoscheme continental region (Africa, Americas, Asia, Europe, Oceania) |
un_subregion | String | Detailed UN continental subregion |
available_pillars | Integer [0-4] | Count of pillars with observed empirical indicator tracking |
missing_pillars | String | Pillars lacking observed empirical survey microdata |
primary_data_gap | String | Root taxonomy reason for missingness (e.g. missing_cognitive_pillars) |
model-divergence-log.csv
Last updated: 2026-10-11Multi-model epistemic debate and divergence audit ledger tracking evaluation consensus and disagreement across frontier AI families.
Schema Reference
| Column | Type | Description |
|---|---|---|
timestamp | ISO-8601 Timestamp | UTC timestamp of the ensemble evaluation round |
topic_id | String | Unique debate topic identifier (e.g. TOPIC-002, TOPIC-003) |
topic_description | String | Methodological query under adversarial evaluation |
model_family | String | Model provider family (e.g. google, anthropic, openai) |
model_version | String | Specific model checkpoint tested (e.g. gemini-3.8-flash) |
verdict | Categorical | Evaluated verdict (NO CHANGE, PROPOSED DIFF, ESCALATE, SKIPPED) |
dominant_concern_lane | Categorical | Dominant analytical lane: Psychometrics, HAI-Interaction, etc. |
Multi-Model Epistemic Divergence Log
HSRI methodology questions are evaluated across multiple frontier LLM families to detect systematic geographic or institutional bias in AI-assisted policy evaluation. Results are logged as a citable dataset (CC BY 4.0).
⚠️ Current data is from a single live model family (Google Gemini). Cross-model comparison requires Anthropic and OpenAI keys. See divergence log CSVand dataset documentation.
Interactive Multi-Pillar Data Explorer
Country Readiness Scores
Phase 7 EmpiricalComprehensive country-level HSRI readiness scores across all 4 pillars for 39 benchmark nations
Direct Downloads
Pillar-Level Scores & Z-Scores
Phase 7 EmpiricalStandardized z-scores and normalized aggregate pillar ratings across all 4 dimensions
Direct Downloads
Readiness-Exposure Gap & Horizons
Phase 7 EmpiricalMacro exposure trajectories and predicted milestone crossing horizons under 3 AI pace scenarios
Direct Downloads
Labor Dislocation & Transition Risk
Phase 7 EmpiricalOccupational risk factors, displacement exposure, and labor crossing horizon projections
Direct Downloads
Harmonized Indicator Database
Harmonized 2026Complete catalog of 20 empirical indicators, measurement units, directionality, and source attributions
Direct Downloads
Timeline & Forecast Synthesis
Forecast 2026Beta distribution milestone forecasts, expert distributions, and readiness/exposure trajectories
Direct Downloads
Data Usage & Provenance Guidelines
Terms of Use & Attribution
HSRI data is provided under Creative Commons Attribution 4.0 International (CC BY 4.0). Users are free to share and adapt the material with appropriate credit:
- Cite the Human Superintelligence Readiness Index (v0.2 Release) in all research and policy publications
- Preserve missingness notes: structural NaNs (such as non-European EMLI) must never be imputed
- Acknowledge that proxy indicators capture enabling environments rather than demonstrated psychological readiness
Recommended Citation
HSRI Research Consortium (2026). Human Superintelligence Readiness Index: Country Scores and Indicator Matrix. Empirical Benchmark Release v0.2. Available at: https://humanreadinessindex.org/data/