{"resourceId":"states-united-ai-platforms-direct-voters-to-state-election-sites-under-half-20260804","versions":[{"version":"external-1fb4918017f9742ebcb38d30058f1de2fa294e4a2fbdcba5a4e7f01d5176b69f","resource":{"id":"states-united-ai-platforms-direct-voters-to-state-election-sites-under-half-20260804","title":"States United study: ChatGPT and Google AI cut factual errors on voter questions to 0% in testing, but pointed voters to state election websites in under half of answers and often gave incomplete candidate lists","organization":"States United Democracy Center","sector":"Election information integrity; evaluation of AI platform answers for state election officials","geography":"United States (Arizona, Michigan, Nevada, North Carolina, Pennsylvania, Wisconsin tested)","publishedAt":"2026-08-04","publicationDate":"2026-08-04","eventDate":null,"sourceName":"States United Democracy Center","sourceLabel":"States United Democracy Center (Aug 4, 2026): 'AI and Elections: How Well Do AI Platforms Answer Voter Questions?'","sourceUrl":"https://statesunited.org/resources/ai-and-elections/","evidenceClass":"independent-research","outcomeClass":"mixed","topics":["knowledge-work","governance-procurement","operating-model"],"finding":"States United tested ChatGPT and Google AI on common voter questions in two rounds: 497 responses across six states in Sept-Oct 2025 and 402 responses across Arizona, Michigan and Pennsylvania in Jan-Feb 2026. Verifiable factual error rates fell from 6.9% (Google AI) and 8.2% (ChatGPT) to 0% in the second round, but answers were often incomplete. ChatGPT mentioned a state election site in 39.4% of responses and Google AI in 55.6%. ChatGPT returned incomplete candidate lists for 88.9% of gubernatorial queries. Of 3,481 cited links, state and local government sources made up 41.5% and Wikipedia 12.3%. Google AI switched to links-only answers around Feb. 2, 2026. Recommendations for election officials include structuring official sites for AI discoverability and building voter education around candidate filing windows.","sledRelevance":"Why now: published in August but newly relevant because Ohio's secretary of state launched an AI error-reporting channel on Oct 27, a week before the Nov. 3 election. It is the independent evidence check on that approach: platforms have become more accurate on simple facts, and the bigger gap is that they often do not send voters to official state sources. Not in our archive.","evidence":"Full report page opened, including findings, recommendations and methodology: standardized questions coded by researchers across two rounds and three platform conditions. Limits: two platforms, a few states, testing before the general-election period; not peer reviewed.","architectureImplications":"Interpretation: for state election offices, the practical lever is content structure: structured data markup, plain language and stable URLs on official sites so AI platforms retrieve and cite them, as the report recommends.","governanceImplications":"The report frames AI as a complement to official information and puts most fixes on platform operators (always link the state election site, prefer official sources, integrate candidate filing data); states can only influence these through outreach.","securityPrivacyImplications":"Limited relevance; the account-level personalization test (election-skeptic browsing profile) concerns information integrity rather than data security.","caveats":"Advocacy research organization; small state sample; platform behavior changes quickly, as the Google format change shows. Results may not hold for Claude, Grok or other platforms named by Ohio.","streamIds":["state-government"],"roles":{"sales":"Sales framing: the evidence points state election offices toward making their own content easier for AI to find and cite, not toward policing every answer. A credible, bounded offer is an AI discoverability review of the official election site and a candidate-filing data feed plan. Do not claim AI platforms are now error-free; the 0% figure covers verifiable factual errors in one test round and sits alongside high incompleteness.","engineering":"Engineering framing: apply structured data markup, plain-language pages and consistent URLs to official election content, and publish candidate filings and key dates in machine-readable form. Then test: run the report's style of standardized voter questions against major platforms and measure how often answers cite the state site. Repeat the test after site changes and at key points such as filing deadlines and certification.","delivery":"Delivery framing: schedule content and voter-education work around the election calendar, especially candidate filing windows when the report found answers least complete. Assign ownership for periodic platform testing and for outreach to platforms. Track the share of answers that point to the official site as the main measure, since factual accuracy alone already looked high in testing. Coordinate with counties so local pages follow the same structure."},"roleDetails":{"sales":{"customerProblem":"Voters use AI platforms for election questions, but those platforms send voters to official state sites less than half the time and give incomplete candidate information.","stakeholders":["Secretary of state or state election director","Election office web and communications team","State CIO digital services team","County election officials"],"discoveryQuestions":["Does the official election site use structured data and stable URLs?","Are candidate filings published in machine-readable form?","Has the office tested how AI platforms answer its voters' questions?","Who would own outreach to platforms?"],"valueHypothesis":"Interpretation: better-structured official content could raise the share of AI answers citing the state site; the report offers this as a recommendation, not a tested result.","potentialEngagement":"Bounded AI discoverability assessment of one state's election website with a repeatable platform test using standardized voter questions.","unsupportedClaims":["AI platforms are not shown to be fully reliable","Site changes are not proven to raise citation rates","Results may not apply to platforms not tested"]},"engineering":{"fit":"State election websites and candidate filing systems that AI platforms draw on for voter answers.","architectureIntegration":"Structured data markup on key pages; machine-readable candidate filing and election date feeds; consistent URL conventions; scheduled automated query tests against major AI platforms with citation logging.","prerequisites":["Content inventory of voter information pages","Candidate filing data access","Standardized question set per state","Staff to review test results"],"constraints":["No control over platform behavior","Platform formats change without notice","Candidate fields change during filing windows"],"security":"Limited relevance; ensure official feeds are authenticated and tamper-resistant so platforms cite accurate data.","proofOfValue":["Measure the share of AI answers citing the state election site before and after content changes","Measure candidate list completeness during a filing window","Track error and incompleteness rates across repeated test rounds"]},"delivery":{"work":"Improve official election content structure, publish machine-readable data, run periodic AI platform tests and align voter education with the election calendar.","dependencies":["Web team capacity","Candidate filing system data access","Election calendar","Platform outreach contacts"],"ownership":"State election office communications and web team, with the state digital services or CIO team for site changes.","skillsAdoption":"Web staff need skills in structured data and AI search behavior; communications staff need a routine for testing platform answers.","governanceCheckpoints":["Baseline platform test before changes","Retest at filing deadlines and before certification","Post-cycle review"],"acceptanceCriteria":["Proposed: AI answer citation rate to the state site measured each cycle","Proposed: candidate filing data available in machine-readable form during filing windows","Proposed: standardized test repeated at least twice per cycle"],"risks":["Platforms change formats and undo gains","Effort focuses on accuracy while incompleteness persists","Staff capacity during election season"]}},"retrievedAt":"2026-10-27T22:23:14-05:00","enrichedAt":"2026-10-27T22:26:40-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Recommends plain-language official content; adds periodic testing work for election web and communications staff.","procurementImplications":"Not addressed.","operatingModelImplications":"Positions state election offices as publishers optimizing for AI retrieval and as testers of platform answers, alongside traditional voter education.","sourceVerification":{"openedUrl":"https://statesunited.org/resources/ai-and-elections/","referenceExcerpt":"ChatGPT mentioned a state election site in 39.4% of its responses, and Google AI did so in 55.6% of its responses.","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}