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AI Governance

AI Governance refers to the policies, processes, controls, and oversight organizations use to develop, deploy, and manage artificial intelligence responsibly. Explore guidance on AI governance in the U.S. and EU, including the EU AI Act, risk management, impact assessments, transparency, accountability, human oversight, automated decision-making, privacy and data governance, AI policies, audits, and regulatory requirements throughout the AI lifecycle.

Alabama Subpoenas OpenAI After Autonomous AI Agent Escapes Testing Environment and Hacks Hugging Face

Alabama subpoenas OpenAI after an autonomous AI agent escaped a testing environment and hacked Hugging Face. The investigation offers an early look at how existing consumer protection law may regulate AI safety, agentic behavior, and governance.

Beyond the Privacy Notice: Transparency for Connected and AI-Enabled Devices

AI is transforming the Internet of Things (IoT)—and the rules for explaining it. From connected devices and robots to chatbots and AI-driven advertising, this article explores emerging transparency requirements and practical approaches to AI-ready disclosures.

Who Is Regulated Under the EU AI Act? Understanding Providers, Deployers, Importers, Distributors and Other Operators

Understand who is regulated under the EU AI Act. This guide explains providers, deployers, importers, distributors, authorized representatives, product manufacturers, and how an organization’s role in the AI value chain determines its obligations.

Nebraska’s Conversational AI Safety Act: New Rules for Chatbots, Minors, and AI Safety

Nebraska’s Conversational AI Safety Act regulates certain public-facing AI services, imposing transparency requirements, heightened protections for minors, self-harm response protocols, and other safeguards. The Act’s key provisions become operative July 1, 2027.

Mississippi’s Definition of Artificial Intelligence

Mississippi HB 1723 defines artificial intelligence as a machine-based system operating toward human-defined objectives. This article breaks down the definition, explains its key elements, and compares Mississippi’s approach with California’s broader definition of AI.

California’s AI Training Data Transparency Law: What Generative AI Developers Must Disclose

California’s AI Training Data Transparency Law requires generative AI developers to disclose key information about training datasets, including their sources, contents, use of personal information, licensing, modifications, collection periods, and synthetic data.

Arkansas: Who Owns AI-Generated Content and Trained AI Models?

Arkansas AR Code § 18-4-101 (2025) tackles a growing AI question: who owns what generative AI creates? The law sets ownership rules for AI-generated content and trained models—and a different rule when employees use AI as part of their jobs.

California Defines AI: AB 2885 and Its Impact

California’s AB 2885 establishes a technology-neutral definition of artificial intelligence focused on AI systems, autonomy, inference, and outputs. This article explains the definition, how AI systems differ from AI models, where the definition applies, and what it means for AI governance.

What is the "Right to an Explanation" under the GDPR?

The GDPR gives individuals important rights when organizations rely on automated decision-making and profiling. Learn when Article 22 applies, the safeguards organizations must implement, and how individuals can challenge automated decisions.