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Methodology

How I build the data

If you read something wrong, please let me know.

Where the bills come from

Every bill comes from an official source. US state bills come through LegiScan. Federal bills come from congress.gov. EU bills come from EUR-Lex, and other jurisdictions use their own government sources.

How bills get tagged

Each bill gets a set of impact tags. Examples include grid capacity, water consumption, carbon emissions, local control, AI safety, and deepfake regulation. Tags describe what a bill is about. They don’t say whether it’s good or bad.

Tagging is done with Claude Sonnet 4.6. The model reads each bill’s summary and picks the applicable tags from a fixed taxonomy. I spot-check the output but I don’t hand-review every bill.

How stance gets picked

A jurisdiction’s stancecan be restrictive, concerning, review, favorable, or none. Claude Sonnet 4.6 picks it from the direction and weight of each jurisdiction’s active bills. Enacted bills count more than voted, voted more than committee, committee more than filed.

When a jurisdiction has contradictory bills in flight, it gets labeled “review” instead of one side. When there’s no policy activity at all, it’s “none,” not favorable-by-default.

Some of these calls will be wrong, or will age badly as bills move. If you work in one of these jurisdictions and think the read is off, please reach out.

Data centers

The frontier data center layer comes from Epoch AI’s open dataset (CC-BY). I supplement it with hand-researched entries from public reporting for sites Epoch doesn’t cover yet. Cost and compute figures only appear when the operator or a filing has disclosed them. A missing number means unknown, not zero.

Sources

Every dataset is drawn from a public source. Primary links for individual bills and news items stay in the detail panels; this is the rollup.

Legislation

  • LegiScanUS state and federal bill text, sponsors, progress events
  • Congress.govfederal bill authoritative source
  • unitedstates/congress-legislatorscurrent member roster and identifiers
  • EUR-LexEU primary legislation text (AI Act, Energy Efficiency Directive)
  • European ParliamentMEP roster and votes
  • State legislature portalsper-bill source links (Arizona, Kentucky, Washington, Montana, West Virginia, Arkansas, California, and 40+ others)

Data centers

  • Epoch AI — Data on AIfrontier data center inventory (CC-BY 4.0)
  • Public reportingoperator announcements, planning filings, and local news for sites Epoch doesn't yet cover

Politicians

Energy & infrastructure

Maps & geocoding

News

  • RSS & public article feedsArs Technica, Reuters, The Hill, Politico, state-press outlets, policy-analysis blogs (BABL.ai, ALEC, state-specific mirrors)

Classification & summarization

  • Anthropic — Claudebill categorization, stance inference, multi-dimension classification, and blurb summarization across every regenerated dataset
Impact tags by dimension

The full tag taxonomy

Tags are grouped into two lenses: Data Centers and AI Regulation. Each lens has its own set of dimensions. The map’s “Color map by” toggle uses these groupings to recolor jurisdictions by tag density.

Impact tags

Tags grouped by lens and dimension. Use the toggle above to recolor the map by any of these.

Data Centers
Environmental
Water ConsumptionCarbon EmissionsProtected LandEnvironmental ReviewRenewable Energy
Energy & grid
Grid CapacityEnergy RatesWater Infrastructure
Community
Noise & VibrationLocal ZoningLocal ControlResidential ProximityProperty Values
Land use
Protected LandLocal ZoningResidential ProximityProperty Values
AI Regulation
Governance
Algorithmic TransparencyAI Safety
Consumer protection
Data PrivacyChild Safety
Workforce & employment
AI in Employment
Public services
AI in HealthcareAI in Education
Synthetic media
Deepfake Regulation