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States Continue to Target AI-Driven Rental Pricing Nineteen states are considering bills that would limit the use of third-party software relying on competitor data to set rental housing prices, according...
Trump, Congress Weigh Measures to Preempt State AI Laws The Trump administration circulated—and then put on hold—a draft executive order aimed at preempting state laws regulating artificial...
Last year, after Colorado and California became the first states in the nation to expand privacy protections to include neural data, we said more states could follow suit . This year two more have done...
MI Lawmakers Advance Medical Debt Protections The Michigan Senate’s Health Policy Committee has advanced a trio of bipartisan bills aimed at reducing the burden of medical costs on residents of...
EU Reversing Course on Tech Regulation After aggressively regulating the technology industry for over a decade, the European Union is moving to loosen its landmark digital privacy and artificial intelligence...
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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.