High-stakes artificial intelligence describes AI systems whose outputs or actions can have serious consequences for people or organizations. Healthcare, employment, lending, legal decisions, critical infrastructure and public safety are common examples.
These systems require controls proportionate to their risks, including representative evaluation, expert oversight, traceability, secure data handling and clear human authority. Performance should be monitored in real use because standards, populations and model behavior can change after deployment.
