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AI policy is moving from conference-paper abstractions to binding regulation, and the people writing and implementing those rules need sources that take both the technical and institutional realities seriously. This page collects them.
We index 900+ articles from 150+ sources on AI policy and government. Coverage is split across news analysis from The Guardian and CIO, specialist AI commentary, and enough research from arXiv to let policy readers see the technical ground underneath the debates — what can and cannot actually be enforced.
Unlike our AI Ethics & Safety directory, which focuses on the technical work of alignment and interpretability, this page is written for the institutional side: legislation, procurement, international AI governance, and the public-sector agencies implementing the rules on the ground.
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The EU AI Act classifies AI systems by risk level: banned (social scoring, real-time biometric surveillance), high-risk (hiring, credit scoring, law enforcement), limited (chatbots requiring disclosure), and minimal (spam filters). High-risk AI requires conformity assessments, human oversight documentation, and transparency reports. Non-compliance fines reach 7% of global revenue. It affects any company serving EU customers regardless of where the company is based.
The US takes a sector-specific approach versus the EU's comprehensive framework. Key actions include the AI Executive Order establishing safety standards, state laws like Colorado's algorithmic discrimination protections, and agency-specific guidance from the FDA (medical AI), SEC (financial AI), and FTC (consumer protection). Companies operating globally often adopt EU standards as the highest common denominator.
Essential policies: acceptable AI use policy defining approved tools and data handling, AI disclosure requirements for customers, human oversight procedures for automated decisions, vendor AI risk assessment criteria, and incident response plans for AI failures. Regulated industries need additional policies for model governance, bias monitoring, and algorithmic impact assessments. Template frameworks from NIST and ISO provide strong starting points.
Government AI applications include fraud detection in tax and benefits systems, predictive analytics for public health resource allocation, citizen service chatbots handling routine inquiries, traffic management optimization, immigration document processing, and emergency response coordination. Results vary widely. Some deployments save millions while others face bias lawsuits. Transparency and accountability requirements for government AI use are expanding rapidly.
Growing roles include government AI advisor, corporate AI ethics officer, think tank researcher, regulatory compliance specialist, AI auditor, and technology policy journalist. Backgrounds in law, public policy, computer science, or philosophy all provide valid entry paths. Salaries range from $80K to $200K depending on sector and seniority. Demand is accelerating as AI regulations expand globally.
Key sources: EU AI Office official updates, NIST AI Risk Management Framework revisions, your industry-specific regulators (FDA, SEC, FTC), AI practice alerts from major law firms like Gibson Dunn and DLA Piper, and policy newsletters from Brookings and Center for AI Safety. Join your industry trade association, as they typically provide regulatory guidance documents and compliance templates tailored to your sector.