Diffusion Timeline

Temporal analysis showing when states adopted specific provisions and identifying early adopters

Diffusion Overview
Overall timeline of AI bill adoption across 10 enacted bills
First Bill

Jan 2023

Illinois (HB 3773)

Diffusion Period

731 days

From first to most recent bill

Most Recent Bill

Jan 2025

Texas (HB 149)

Transparency Requirements

0 states • 0 days

No enacted bills with this provision yet

Impact Assessments

0 states • 0 days

No enacted bills with this provision yet

Accountability Mechanisms

0 states • 0 days

No enacted bills with this provision yet

Enforcement Provisions

0 states • 0 days

No enacted bills with this provision yet

Stakeholder Engagement

0 states • 0 days

No enacted bills with this provision yet

Interpreting Diffusion Patterns
Understanding temporal adoption patterns

Early Adopters: States that first introduce specific provisions often serve as "policy laboratories" and may influence later adopters. Early adopters typically face higher political costs and uncertainty.

Diffusion Speed: Faster diffusion (shorter time periods) suggests strong policy consensus or external pressure. Slower diffusion may indicate contested provisions or state-specific adaptation.

Temporal Gaps: Long gaps between adoptions may indicate policy learning periods, changes in political context, or the need for evidence from early adopters before others follow.

Research Applications:

  • Compare early adopter characteristics (ideology, tech employment) to identify predictors
  • Analyze whether lobbying intensity changed over time as provisions diffused
  • Test "policy learning" hypothesis: do later adopters modify provisions based on early adopter experiences?
  • Identify critical junctures or external events that accelerated diffusion