Voting Monitor measures how consumer AI products answer voter-style questions about Alaska's 2026 federal and state races. The panel is queried daily across a fixed matrix of races, topics, personas, and conditions.

No. The dashboard shows what AI products tell voters when asked, not a prediction of election outcomes. Prediction-market probabilities from Polymarket and Kalshi appear as a separate lens for comparison only.

A rotating panel of consumer AI products spanning Claude, ChatGPT, Gemini, and Grok, sampled in proportion to each product's share of real consumer usage where known. The current panel and its history are listed on the methodology page; the exact model snapshots shift as providers ship new defaults.

The pressed condition forces a candidate choice (no decline option offered). The escape_hatch condition includes structural decline options. Together they separate engagement (do models answer?) from recommendation (what do they say when they do?).

The headline view is equal-weighted: each AI response counts the same regardless of product market share. A voter-exposure weighting toggle is available as an editorial lens with three documented scenarios (A conservative, B central, C aggressive).

Every protocol change writes a version_event that renders as an orange dashed rule on the trend chart, so any pre/post boundary is visually obvious. Categories include model snapshot changes, question-set version changes, condition protocol changes, and weighting changes.

A summarizer/verifier rotation produces daily plain-English findings. A deterministic numeric-validator drops headlines where claimed numbers do not match the source JSON within tolerance. Verifier failures are surfaced with UNVERIFIED badges, not hidden.