Electoral Impact Assessment Model

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  "title": "Electoral Impact Assessment Model",
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  "lastUpdated": "2026-03-13",
  "dateCreated": "2026-02-15",
  "llmSummary": "This model estimates AI disinformation's marginal electoral impact by decomposing the causal pathway from AI capability to vote shifts. Analysis finds 0.2-5% probability of flipping individual elections (1-3 elections globally per year), with 2-5% potential vote margin shifts in close races, though systemic trust erosion (2-5% annual decline) may matter more than specific election outcomes.",
  "description": "This model estimates AI disinformation's marginal impact on elections. It finds AI increases reach by 1.5-3x over traditional methods, with potential 2-5% vote margin shifts in close elections.",
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    {
      "text": "Harvard Kennedy School Misinformation Review",
      "url": "https://misinforeview.hks.harvard.edu/article/the-origin-of-public-concerns-over-ai-supercharging-misinformation-in-the-2024-u-s-presidential-election/",
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      "resourceTitle": "World Economic Forum's 2024 Global Risks Report"
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        "title": "Fraud Sophistication Curve Model",
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        "title": "AI-Era Epistemic Security",
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        "title": "Disinformation",
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No external links