// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
AI Bill of Rights
A set of principles proposed by the U.S. government to protect people from potential harms caused by artificial intelligence systems.
TECHNICAL DEFINITION
The AI Bill of Rights, officially the "Blueprint for an AI Bill of Rights" from the U.S. Office of Science and Technology Policy, outlines five core principles (safe and effective systems, algorithmic discrimination protections, data privacy, notice and explanation, human alternatives/fallback/oversight) to guide the design, use, and deployment of automated systems to protect civil rights and promote democratic values.
SYNONYMS & ALIASES
- Blueprint for an AI Bill of Rights
- US AI Rights
- AI Rights Framework
USAGE NOTE
The AI Bill of Rights provides a policy vision for protecting individuals in an AI-driven society.
DEVELOPERS
Organizations developing technology related to AI Bill of Rights.
A U.S. government agency that develops standards and guidelines. NIST created the AI Risk Management Framework (AI RMF), a voluntary framework to help organizations design, develop, and use AI systems in a trustworthy manner, directly aligning with the principles of the AI Bill of Rights.
IBM develops open-source toolkits to help developers build more trustworthy AI. These include AI Fairness 360 (AIF360) for detecting and mitigating bias, AI Explainability 360 (AIX360) for understanding model decisions, and the Adversarial Robustness 360 Toolbox (ART) for securing AI systems.
A company providing an AI governance and oversight platform. Their software enables organizations to measure, monitor, and manage AI risks related to fairness, performance, and compliance, helping operationalize the principles outlined in the AI Bill of Rights.
Fiddler develops a Model Performance Management (MPM) platform that provides AI observability. It offers tools for explainable AI (XAI), fairness monitoring, and bias detection, addressing the principles of Notice and Explanation and Algorithmic Discrimination Protections.
Arthur provides an AI performance platform that monitors machine learning models for accuracy, explainability, and fairness. Their technology helps detect and mitigate algorithmic bias and ensures models are safe and effective, in line with the AI Bill of Rights.
Microsoft develops a suite of Responsible AI tools and frameworks. This includes the Fairlearn toolkit for assessing and improving the fairness of AI systems and InterpretML for training interpretable models and explaining black-box systems.
Google develops various tools to support responsible AI development. This includes TensorFlow Privacy for building privacy-preserving models, the What-If Tool for model understanding and fairness checks, and extensive research into AI safety and interpretability.
The UK's national institute for data science and artificial intelligence. It conducts foundational research and develops frameworks for AI ethics, safety, and fairness, contributing public-interest technology and guidance that supports principles like those in the AI Bill of Rights.