Topic

Algorithmic Accountability

Algorithmic Accountability refers to the principles, governance practices, and legal requirements used to ensure that AI and algorithmic systems are transparent, responsible, and subject to appropriate oversight. Explore U.S. and EU developments involving algorithmic impact and risk assessments, automated decision-making, bias and discrimination, explainability, human oversight, audits, privacy, consumer rights, enforcement, and accountability throughout the AI lifecycle.

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.

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