AI Literacy

An AI system that can take actions, such as searching, booking or editing files, rather than only answering.

A set of step-by-step instructions a computer follows to solve a problem or make a decision.

Using technology to perform tasks with little or no human input, from simple rules to AI-driven systems.

Systematic skew in a model’s outputs, often inherited from patterns in the data it learned from.

Further training of an existing model on a narrower set of examples to suit a particular task.

A confident but false or unsupported output. It is a known failure mode of language models.

A model trained on vast amounts of text to predict and generate language, like the systems behind AI chat tools.

Testing how well a system performs, on benchmarks and, more usefully, on the real task you need.

The instruction or question you give an AI system. Its clarity shapes the quality of the response.

The record of where information came from and how it was produced, increasingly vital when content can be generated.

A small chunk of text, often part of a word, that language models read and write in.

The examples a model learns from. Its scope and quality shape what the model can and cannot do.