Systematic identification, scoring, and curation of hyper-entities from the Foresight Institute research community.
A hyper-entity is a coherent, future-instantiated system that does not yet exist, but is treated as if it will; whose realization would create a new stable action space for humanity; and which already reorganizes coordination, investment, and narrative around its anticipated existence. Term coined by Michael Nielsen.
| Entity Explorer Dashboard (v3) | All 189 entities with scoring, search, and cluster visualization |
| Spotlight Report (PDF) | v3 report: 19 Tier 1 spotlight entities, watch list, methodology |
| Entity Explorer Dashboard (v2) | Legacy v2 dashboard with 345 entities |
| v2 Report (Markdown) | v2 report: methodology, 39 consensus entities with deep write-ups |
| Part II Proposal (PDF) | One-pager for turning research into action |
Extraction — 189 hyper-entities extracted from 109 Foresight Institute sources (podcasts, world-gallery submissions, essays) using a multi-stage pipeline.
Scoring — Each entity scored on three dimensions:
- d/acc Values Alignment: 4 dimensions (Democratic, Decentralized, Defensive, Differential), max 20. Based on Vitalik Buterin's d/acc framework.
- Transformative Potential: 1–5 scale.
- Composite Score: Combines d/acc, transformative potential, foresight relevance, and TRL.
Research — Each entity enriched via web search with organizations, funding, TRL (1–9), publications, state of the art, and barriers.
Curation — 19 Tier 1 spotlight entities and 170 Tier 2 watch list entities, based on composite score thresholds.
Report — Full write-ups for all 19 Tier 1 entities, involvement matrix, and action recommendations.
├── results/
│ ├── v3/
│ │ ├── dashboard.html # v3 entity explorer (189 entities)
│ │ ├── report_v3.typ # v3 spotlight report (Typst source)
│ │ ├── report_v3.pdf # v3 spotlight report (compiled PDF)
│ │ ├── scatter_plot_v3.svg/png # d/acc vs Transformative scatter plot
│ │ └── *.json # Pipeline intermediate data
│ ├── dashboard.html # v2 entity explorer (345 entities)
│ ├── report_v2_data/
│ │ ├── report_v2.md # v2 report (Markdown)
│ │ ├── report_v2.docx # v2 report (Word/GDoc import)
│ │ └── scatter_plot.svg/png # v2 scatter plot
│ ├── proposal_part2.pdf # Part II proposal
│ ├── stage1_extraction/ # v2 Stage 1 extraction results
│ ├── stage2_assessment/ # v2 Stage 2 technology scoring
│ └── stage3_concrete/ # v2 Stage 3 d/acc scoring
├── v3_extract.py # v3 extraction
├── v3_dedup.py # v3 deduplication
├── v3_research.py # v3 web research enrichment
├── v3_score.py # v3 scoring
├── v3_curate.py # v3 tier curation
├── v3_report.py # v3 report generation
├── v3_dashboard.py # v3 dashboard generation
├── create_dashboard.py # v2 dashboard generator
├── METHODOLOGY.md # Full scoring framework
└── CLAUDE.md # Project instructions
# v3 pipeline
python v3_extract.py # Extract entities from sources
python v3_dedup.py # Deduplicate candidates
python v3_research.py # Enrich with web research
python v3_score.py # Score on d/acc + transformative dimensions
python v3_curate.py # Curate into tiers
python v3_report.py # Generate report
python v3_dashboard.py # Generate interactive dashboard
# v2 (legacy)
python create_dashboard.py # Regenerate v2 dashboardLinda Petrini & Beatrice Erkers, Foresight Institute. Extraction and analysis conducted with Claude.
Last updated: 2026-03-09