Artificial Intelligence Impact Atlas (AIIA)

Biocomplexity Institute · University of Virginia

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Overview, tutorial, and estimate descriptions for the AIIA dashboard.

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Overview

Artificial Intelligence Impact Atlas (AIIA) is an interactive dashboard for exploring county-level AI impact estimates across Virginia.

Use the Estimates selector to switch between baseline county stats, AI use estimates, and partial AI automation estimates. Hover the map for quick details and click any county to open a deeper panel with population, workers, and estimate-specific ranges.

The dashboard is designed for fast comparison across localities to support planning, workforce discussions, and policy analysis.

Tutorial

Watch this short walkthrough to learn how to navigate the dashboard, switch estimate sets, and interpret county-level results.

Tutorial walkthrough (1 min 45 sec): overview, estimate switching, map legend updates, county hover/click, and reset controls.

More Feature Videos

Estimate Comparison (47 seconds)

Shows how switching estimate sets updates county colors, legends, and 3-category context instantly.

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County Search and Drilldown (47 seconds)

Demonstrates county search by name or FIPS and automatic detail-panel drilldown.

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Estimates

When AIIA is loaded, County Stats shows baseline county information which includes county population and workers number. Switch to any estimate set to view projected impact levels across the map:

  1. AI Use (All Job Categories): Computes the proportion of workers in each county who use AI tools, summarizing mean exposure to AI across simulation runs.
  2. AI Use (3 Highest Categories): Restricts the analysis to SOC groups 15 (Computer & Mathematical), 25 (Education & Library), and 27 (Arts/Design/Entertainment/Media) and evaluates the share of workers using AI within these categories at the county level.
  3. Partial AI Automation (All Job Categories): Estimates the fraction of workers in each county whose jobs are classified as automatable, capturing overall automation risk.
  4. Partial AI Automation (3 Highest Categories): Computes automation exposure specifically within SOC groups 15, 25, and 27 to identify counties with concentrated task-automation risk.

For the 3 Highest Categories options, the map subtitle shows the included groups: Computer and Mathematical; Educational Instruction and Library; Arts, Design, Entertainment, Sports, and Media.

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