Making Sense of AI Policy Using Computational Tools
In recent years, policymakers have rapidly increased their efforts to regulate artificial intelligence and automated decision systems through new legislation. These legislative approaches, however, are not advancing in isolation and often borrow and refine language from one another, creating interactions between proposals that otherwise appear to be moving in parallel.
To better understand this complex legislative landscape, the Center for Tech Responsibility at Brown University and the American Civil Liberties Union deployed carefully selected computational methods to analyze legislative trends across 1,804 state and federal bills related to AI and automated decision systems introduced between 2023 and April 2025.
The bills in this sample — which we selected based on the presence of various curated keywords related to AI — have varying degrees of substantive requirements and applicability; for example, roughly 30% relate to establishing task forces, and many bills focus only on uses of AI in particular sectors, such as health care.
Related Knowledge Center: Artificial intelligence
On top of a failing business model, newsrooms must navigate the powerful — and not fully reliable — new capabilities of artificial intelligence and the deployment of large language models.
State of the business model | Copyright and intellectual property
Related Knowledge Center: Media and the law
Toxic politics and vast shifts in the technology landscape have created a plethora of thorny issues — both legal and ethical — for newsrooms, courts, and regulators.
The Meta-FTC trial | Section 230