AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Free AI library
30 plain-English guides, structured learning paths, and an open library — built by an independent 501(c)(3) nonprofit so anyone can understand modern AI.
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Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
Topic tracks
Jump into the area you care about. Every track has multiple plain-English guides.
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AI bias can arise from data, measurement, modeling choices, human judgments, and the wider system in which a model is used.
SocietyAI privacy concerns how a system’s collection, inference, storage, and disclosure of information can affect people.
SocietyAI and copyright involves several separate questions: rights in input material, permission to use a service or model, possible infringement in outputs…
SocietyAI safety is the field focused on preventing AI systems from causing severe harm — from everyday failures and misuse up through catastrophic and existential…
SocietyArtificial General Intelligence (AGI) refers to AI systems with broad, human-level (or greater) competence across most cognitive tasks — not just one narrow…
SocietyOpen-weights models make learned parameter files available for download under specified terms.
SocietyAI alignment is the technical and institutional project of making advanced AI systems reliably do what humans intend — including in novel, high-stakes…
SocietySynthetic data is generated to represent some properties of real or imagined data.
SocietyModel collapse describes degradation that can occur when successive models learn recursively from generated data and lose information about the original…
SocietyAI governance is the set of rules, roles, and technical controls that decide who may build, train, evaluate, and deploy AI systems — and what happens…
SocietyTrust calibration means relying on an AI system in proportion to evidence about what it can do.
SocietyAI in digital education includes lesson planning, tutoring, feedback, translation, accessibility, and administrative support.
Check what you learned with topic quizzes, then explore our structured courses and current certification requirements. Core guides remain free to read.