AI Safety & Ethics

Alignment research tries to make sure AI systems actually do what we want, not just what we literally asked for. Here’s why that’s harder than it sounds.

AI chatbots sometimes state false information with total confidence. Here’s why that happens, and how to catch it.

Before an AI model is released, teams try deliberately to break it. Here’s what red-teaming involves and why it’s now standard practice.

Every message you send an AI chatbot goes somewhere. Here’s what typically happens to your data, and how to use these tools more safely.

AI models can reflect and sometimes amplify biases present in their training data. Here’s how that happens and what’s being done about it.

Responsible AI isn’t one technique — it’s a set of practices companies use throughout a model’s lifecycle. Here’s what that actually looks like.