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New White House Policy Framework Calls for Blocking State AI Laws The Trump administration released a National Policy Framework for Artificial Intelligence that, among other things, urges Congress to...
VT Bill Addresses Privacy of AI in Healthcare The Vermont House passed a bill ( HB 814 ) to bolster privacy protections around the use of artificial intelligence in healthcare. The bill would establish...
Nearly two years after the Environmental Protection Agency set drinking water limits for so-called forever chemicals, the synthetic compounds remain a focus for state legislators. Formally known as per...
CA’s Wildfire-Driven Insurance Crisis Spreads to Lower-Risk Homes Insurers have stopped covering homes in some California neighborhoods at lower risk of wildfire damage, forcing thousands of homeowners...
WA Enacts Ban on Microchipping Workers Washington Gov. Bob Ferguson (D) signed a bill ( HB 2303 ) prohibiting companies from requiring their workers to get microchip implants. The new law allows workers...
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Just as state legislatures vary in their bill passage rates, some state agencies adopt far more of the rules they propose than others. The reasons for that disparity are even more difficult to discern than with the legislative process, but understanding how they shape adoption rate patterns is no less critical for organizations seeking to comply with the regulations or engage in the rulemaking process of any state. That knowledge is the foundation of the analytics tools developed by LexisNexis® State Net® to support legislative and now regulatory forecasting.
Pioneering research by State Net® beginning in the 1980s revealed that in spite of their diversity, legislative passage rates “remain highly consistent from session to session,” varying less than 2% over multiple bienniums. Rigorous tracking of regulatory actions from proposal to adoption over the past four decades has now made it possible for State Net® to document similar historical rule adoption patterns. “Just as we were surprised by the unyielding consistency in legislative passage rates, our analysis of regulatory adoption reveals an equally rigid pattern across agencies and states,” said Crain. “This stability, despite the processes’ diversity, provides a strong foundation for determining the timing and likelihood of rule adoption.
State Net has now built predictive models for every state agency that proposes regulations—8,992 forecasts in all—drawing on key indicator analytics derived from decades of regulatory activity and employing advanced machine learning. The graphic visualizations of these predictive models, along with other indicators, can provide important insights about pending rules, such as their likelihood of adoption or whether consideration is moving faster or slower than usual. By simply using these tools—and the State Net platform’s powerful searching and tracking capabilities across state, federal and local agencies—users gain access to extensive knowledge of regulatory processes, helping them make more informed data-supported decisions.
Download the latest State Net Capitol Journal thought leadership article to learn more.