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What makes AI generative?

Generative AI creates proposals, not guaranteed truths

How language models generate text

How image and multimodal generation work

Concept check: what a generated answer means

From a prompt to a dependable workflow

Choose tasks by consequence, not novelty

Prompting as specification

Grounding with retrieval, tools and structured data

The TRACE verification method

Workflow check: improve reliability

Risk, rights and human responsibility

Hallucinations, bias and brittle confidence

Privacy, intellectual property and synthetic content

Human-centred use in education and public-interest work

Applied synthesis: should AI do this task?

Understand how generative and multimodal models produce outputs, then turn prompting into a dependable workflow. Apply retrieval, structured evidence, the TRACE verification method, privacy safeguards and accountable human review.

Understand how generative models produce text and media, turn vague requests into inspectable workflows, and apply a rigorous verification method before using an output.

Copy of Generative AI in Practice

<div class="simple-box-wrapper"> <div class="simple-box"> <div class="column"> <h3>Description</h3> <div class="ck-horizontal-line"><hr></div> <p>I'm a paragraph. Click to start writing that will inform, inspire, or encourage your community. We know you have so many things to share with the world. Happy editing!</p> </div> </div> </div>