tegwick
c0254aa2da
- checkpoints/run_checkpoint.py: window guard, web-fetcher fetch with provenance, record + raw JSONL, optional llm-connect assessment rejected if it contains numbers not in the fetched data - checkpoints/sources.json: BTOS (US), Eurostat isoc_eb_ai (EU, DE), FRED info-processing investment (US); manual entries for AR, usage indices, sentiment, legislation - activity definitions: label assembly-checkpoint (rein-aharness approach) - PLAYBOOK: automated path + manual/agent path Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Assistant: claude-code Assistant-Model: opus Assistant-Process: 1494246@bnt-lap001 Assistant-Session: caf6de6f-f9e4-47ce-a584-49baa271fa4b
37 lines
2.7 KiB
JSON
37 lines
2.7 KiB
JSON
{
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"note": "Machine-readable sources for checkpoint indicators (checkpoints/IndicatorCatalog.md). Fetched with web-fetcher. 'manual' = no machine-readable source yet; collected at reviews.",
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"specs": [
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{"id": "L1-US", "indicator": "L1", "kind": "light", "jurisdiction": "US",
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"label": "Firms using AI in any business function (last two weeks)",
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"adapter": "xlsx_wide", "url": "https://www.census.gov/hfp/btos/downloads/National.xlsx",
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"sheet": "Response Estimates", "filter": {"Question ID": "7", "Answer ID": "1"},
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"unit": "% of employer firms", "source": "U.S. Census Bureau, Business Trends and Outlook Survey (BTOS)"},
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{"id": "L1-US-next6m", "indicator": "L1", "kind": "light", "jurisdiction": "US",
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"label": "Firms expecting to use AI in the next six months",
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"adapter": "xlsx_wide", "url": "https://www.census.gov/hfp/btos/downloads/National.xlsx",
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"sheet": "Response Estimates", "filter": {"Question ID": "24", "Answer ID": "1"},
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"unit": "% of employer firms", "source": "U.S. Census Bureau, Business Trends and Outlook Survey (BTOS)"},
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{"id": "L2-EU-DE", "indicator": "L2", "kind": "light", "jurisdiction": "EU, DE",
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"label": "Enterprises (10+ employees) using at least one AI technology",
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"adapter": "eurostat", "dataset": "isoc_eb_ai",
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"filters": {"geo": ["EU27_2020", "DE"], "unit": "PC_ENT", "size_emp": "GE10", "indic_is": "E_AI_TANY"},
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"split_by": ["geo"], "last": 1},
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{"id": "L3-AR", "indicator": "L3", "kind": "light", "jurisdiction": "AR",
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"label": "AI use by firms or workers", "adapter": "manual",
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"source": "INDEC / national ICT surveys; OECD / IDB regional data"},
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{"id": "L4", "indicator": "L4", "kind": "light", "jurisdiction": "global",
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"label": "AI task usage by occupation; automation vs. augmentation", "adapter": "manual",
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"source": "Anthropic Economic Index (dataset releases)"},
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{"id": "L5-US", "indicator": "L5", "kind": "light", "jurisdiction": "US",
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"label": "Private fixed investment in information processing equipment (SAAR)",
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"adapter": "http_csv", "url": "https://fred.stlouisfed.org/graph/fredgraph.csv?id=Y033RC1Q027SBEA",
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"value_column": "Y033RC1Q027SBEA", "period_column": "observation_date",
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"unit": "billions of USD, SAAR", "source": "BEA via FRED (Y033RC1Q027SBEA)"},
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{"id": "L6", "indicator": "L6", "kind": "light", "jurisdiction": "US, EU, AR",
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"label": "Public sentiment toward AI", "adapter": "manual",
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"source": "Pew Research; Eurobarometer; Edelman Trust Barometer; Latinobarómetro"},
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{"id": "L7", "indicator": "L7", "kind": "light", "jurisdiction": "US, EU, AR",
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"label": "AI legislation milestones since last checkpoint", "adapter": "manual",
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"source": "official journals; legislative trackers"}
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]
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}
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