Reference

Core Terms

  • Generative AI: AI systems that generate text, images, code, audio, or other outputs from prompts or input material.
  • LLM (Large Language Model): A model trained on large amounts of text that predicts and generates language-like output.
  • Prompt: The instruction or input given to an AI tool.
  • Source boundary: An explicit instruction about what source, document, or evidence the tool should rely on.
  • Hallucination: A false, unsupported, or invented output presented as if it were reliable.
  • Validation: The checking work needed to confirm whether an AI output is accurate, relevant, and usable.
  • Role prompting: Asking the model to answer in a particular style or perspective, such as researcher or policy adviser.
  • Prompt chain: A sequence of smaller prompts used to refine, check, and restructure output.
  • Workflow: A repeatable set of steps that turns a task into a more consistent process.
  • Agent: A more structured AI setup that performs a narrow repeated task with defined steps and outputs.
  • AI use note: A short record of what tool was used, for what task, with what inputs, and what checks were performed.
  • Disclosure: A decision about whether AI use should be reported formally in methods, acknowledgements, or internal records.

Quick Decision Guide

Should I use AI for this task?

Situation Usually sensible Usually risky
public or low-risk source material summarising, comparing, outlining, drafting structure trusting claims without checking
code or technical scaffolding explanations, toy examples, boilerplate, debugging support running uninspected code on real or sensitive data
sensitive, unpublished, or restricted material only within approved tools and governance rules pasting into a public AI chat tool
interpretation and judgement asking for questions, alternatives, or critique outsourcing conclusions you cannot defend

Prompt ingredients worth including

Use prompts that define:

  • the task
  • the audience or context
  • the source boundary
  • the output format
  • the uncertainty instruction
  • the validation step you will apply afterwards

A Useful Prompt Pattern

Help me with [task] for [context or audience]. Use [source or boundary]. Return the output as [format]. If something is uncertain, flag it explicitly. Do not invent evidence or citations.

Validation Checklist

Output type What to check
summary or explanation source accuracy, date, missing caveats
citation or quotation exact wording, existence, relevance
comparison whether the comparison reflects the actual source texts
code or workflow suggestion assumptions, edge cases, whether it runs or makes sense
agent output consistency, whether validation steps were actually followed

A Lightweight AI Use Note

You do not need a complex logging system. A short note can include:

  • date
  • tool
  • task
  • prompt or template
  • input material
  • checks performed
  • what was kept
  • disclosure decision

Example:

Date: 2026-03-23
Tool: Copilot
Task: Compared two public AI policy pages
Input: Public web text copied into prompt
Output kept: A short comparison table
Checks: Manual comparison against source pages
Disclosure: Internal project log only

What Not To Paste Into a Public AI Tool

Avoid sharing:

  • identifiable participant data
  • unpublished findings or draft papers that should remain confidential
  • contract-restricted or commercially sensitive material
  • peer review reports or confidential reviewer comments
  • anything your institution would not permit you to email to an external collaborator without agreement

If In Doubt

Ask:

  1. Is the material safe for this tool?
  2. What part of the output will I need to verify manually?
  3. Am I using AI for support, or trying to outsource judgement?
  4. What would I need to record so this use could be explained later?