How to check AI answers before you rely on them
A practical workflow for checking AI-generated claims, citations and calculations, with a worked example and a reusable verification record.
A field guide to a changing world
The future is artificial.
The impact is human.
What happens to our work, our relationships, and our power when intelligence becomes a technology? Explore the evidence. Question the predictions.
The human perspective
More intelligence.
More questions.AI / HUMANITY
EST. 2026
More questions.AI / HUMANITY
EST. 2026
A little clarity goes a long way.Sources you can inspectEvidence separated from predictionPractical questions worth asking
Start with the big questions
All explainers →How to use AI for studying without skipping the learning
Build an AI study session around your own attempts, targeted hints and an independent check of what you can explain without assistance.
Will AI change your work? Start with a task audit
Map a normal working week, identify where AI might help, and compare total time and quality in a small, permitted trial.
Will AI replace your job? Start with tasks, not titles
A practical way to assess AI exposure at work, understand the evidence, and identify useful skills without relying on job-loss predictions.
Who benefits from AI productivity gains?
Faster work does not automatically mean higher pay. Understand how AI gains can reach workers, customers, business owners and technology suppliers.
What skills should you learn in the AI age?
A practical learning approach built around subject knowledge, evidence checking, problem framing and using AI without outsourcing understanding.
Build your understanding
You don’t need to be an engineer to join the conversation.
From language models to artificial general intelligence, our short glossary explains the terms behind the headlines. Start with a definition, then follow the questions that matter to you.
Open the AI glossary →