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C001

Choose a Useful AI Task

Decide where an AI assistant can prepare work, where a person must review it, and where the task should stay human-led.

Your outcome

Produce a decision matrix that makes one routine task safer and more useful without handing a consequential decision to a model.

In this lesson
Your AI study partner

Think it through together.

Choose one prompt, copy it and paste it into ChatGPT, Gemini or Claude. It includes this exercise and its criteria. Your answers, notes and answer keys are not included.

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Open the study prompts
Open ChatGPT Study

Copying sends nothing to an AI. Pasting shares this exercise with the tool you choose under its terms. Use fictional data. The AI offers guidance; you save your own work below. Its feedback does not certify a skill.

Brightlane Studio receives six requests on a Monday morning. One teammate wants a summary of three customer comments; another asks for an email draft. A manager asks the assistant to invent a contract price because the signed document is delayed. Finance asks it to approve a refund, and hiring asks it to choose between two candidates. The requests all look like 'work', but they do not carry the same consequence.

The useful question is not whether an assistant is clever enough to say something plausible. It is whether a person can define the input, inspect the result, and remain responsible for the next action. By the end of this lesson you will classify each request as use, use with review, or do not use, and you will name the evidence a reviewer needs.

Start with the job, not the tool

A useful AI task has a bounded job. You can state what goes in, what should come out, and what a person will do next. 'Turn these three comments into themes' is bounded because the source comments and requested output are visible. 'Fix customer satisfaction' is not a job; it mixes diagnosis, decisions, communication, and follow-through. A bounded task gives the assistant a narrow contribution and gives a reviewer something concrete to inspect.

Think of an assistant as a junior preparer at a large table. You may ask it to group sticky notes or draft a first paragraph, but you do not ask it to sign the purchase order sitting beside the notes. The analogy has a limit: a person can notice context, responsibility, and consequences in ways a text generator does not. Use the analogy to decide what preparation is useful, not to pretend the system has an employee's judgment.

Separate preparation from authority

Preparation changes the shape of information: summarize, sort, translate, propose headings, or draft language from supplied facts. Authority changes the real world: approve a refund, set a price, choose a candidate, promise a delivery date, or send a message. The same draft can be helpful before authority is exercised. A draft refund reply can explain the documented policy; a person still decides whether this customer qualifies and presses send.

This distinction protects quality as well as accountability. A concise, confident answer may contain an invented detail or may miss an exception in the record. NIST's generative-AI profile treats confabulation and over-reliance as risks to manage. The practical response is not a slogan about being careful. It is a visible review point tied to evidence: the contract, policy, ledger, or application that supports the next action.

Three lanes for a requestClassify the job before generating text. The review lane ends in a human decision, not an automatic action.
  1. Request

    State the job and consequence.

  2. Use

    Low-consequence preparation; quick check.

  3. Use with review

    Compare output to evidence before action.

  4. Do not use

    Missing fact, approval, price, or hiring decision.

Request Usebounded preparationRequest Use with reviewinfluences a decisionRequest Do not useasks for authority or invention

Use consequence to choose a lane

Put each request in one of three lanes. Use means the output is a low-consequence preparation aid and can be checked quickly. Use with review means the output may influence a customer, payment, public claim, or internal decision, so a named person compares it with a source before acting. Do not use means the task asks the assistant to make a decision, invent a missing fact, or handle information that should not enter the exercise.

Lanes are not labels for entire professions or tools. The same assistant can help with a harmless subject line and be unsuitable for an unsupported contract price. The lane changes when the evidence changes. If a pricing table arrives and a pricing manager owns the decision, the assistant might format options for review. It still does not become the pricing authority.

Make review observable

'A human will check it' is too vague to guide work. Name the reviewer, the evidence, and the decision that follows. For a comment summary, the customer-success lead checks that every theme appears in the three comments and that no complaint was added. For a refund draft, the finance lead checks the transaction record and policy before deciding approve, deny, or ask for more information.

A good matrix also records a stop condition. Stop when the source is missing, when two sources disagree, when a request asks for a price or approval, or when the output contains a claim nobody can trace. Stopping is productive: it moves the work to the person who can resolve the uncertainty instead of producing a polished guess.

Brightlane request matrixThe same assistant can support different lanes depending on what happens after the output.
RequestLaneReviewer and evidence
Summarize three commentsUseCustomer-success lead checks all three comments
Draft a maintenance emailUse with reviewOperations lead checks the supplied schedule
Invent contract priceDo not useSigned contract is missing
Approve refundDo not useFinance manager owns approval
Classify repeated questionsUse with reviewSupport lead checks the labeled examples
Choose a hireDo not useHiring panel evaluates candidates
Worked example · fictional case

Classifying Brightlane's six requests

Brightlane has only the six requests below; no private customer documents are used.

The material

  • Comments: 'The booking page is slow', 'I could not find the cancellation rule', 'Please make mobile labels larger.'
  • Email facts: planned maintenance Tuesday, 7:00–9:00 PM; audience: active customers; support link: help.brightlane.test.
  • A contract price is requested but the signed contract is unavailable.
  • A refund request contains no transaction record or policy excerpt.
  1. 1

    Name the output

    Write 'three-theme summary' rather than 'improve feedback'.

    A reviewer can compare themes with visible source comments.

    Use lane candidate.
  2. 2

    Check consequence

    Mark the maintenance email as customer-facing.

    A wrong time or unsupported promise could affect customers.

    Use with review, not automatic sending.
  3. 3

    Reject invention

    Mark contract price as unavailable rather than asking for an estimate.

    A missing contractual fact cannot be generated from style or confidence.

    Do not use; request the signed source.
  4. 4

    Keep approval human

    Mark refund approval and hiring choice as human decisions.

    The assistant may organize evidence but cannot own these outcomes.

    Do not use for the decision.
  5. 5

    Specify the review

    For question classification, require the support lead to compare categories with six labeled examples.

    The reviewer can catch a category that hides an important exception.

    Use with review.

The resulting artifact

Decision matrix: summarize comments—Use, reviewer checks themes; maintenance email—Use with review, operations lead checks time and link; contract price—Do not use, obtain signed contract; refund approval—Do not use, finance decides from record and policy; repeated-question classification—Use with review, support lead checks labeled examples; hiring choice—Do not use, hiring panel decides.

How to check it

  • Every accepted task has a named reviewer and evidence.
  • No task asks the assistant to invent a fact or approve an outcome.
  • The matrix distinguishes drafting from sending or deciding.
Tool practice

Try one bounded preparation task

One available conversational assistant: ChatGPT, Claude, or Gemini

Use an account you already have and only the fictional comments below. Features and plans vary; this lab does not require files, integrations, or paid access.

This tool exercise has not been independently tested. Use the supplied fictional material and check the current requirements of your chosen tool.

  1. 1

    Paste the sources

    Paste the three fictional comments from the worked example and ask for three themes, with one quoted phrase under each theme.

    Check: The response contains only themes traceable to the three comments.
  2. 2

    Ask for uncertainty

    Ask the assistant to label any proposed theme that lacks direct support as 'needs review'.

    Check: Unsupported additions are marked rather than treated as findings.
  3. 3

    Review without acting

    Compare each theme and quote with the original comments; write one correction if needed.

    Check: Your notes identify evidence for every kept theme.
Continue with the supplied material

On paper, group the three comments into themes and quote the words that support each group. This practices the decision and review, but it does not prove execution in a tool.

Your practice · fictional case

Build a task decision matrix

Brightlane receives: summarize comments, invent a contract price, draft an email, approve a refund, classify repeated questions, and decide a hire.

Your inputs

  • The three comments and maintenance facts in the worked example.
  • Contract price: no signed contract supplied.
  • Refund: no transaction record supplied.
  • Question labels: login, cancellation, accessibility, billing, login, cancellation.
  • Hiring: two resumes but no evaluation rubric.
  1. Create one row per request.
  2. Choose Use, Use with review, or Do not use.
  3. For every accepted row, name a reviewer, evidence, and stop condition.
  4. Explain one row that looked useful but must stay human-led.

Task decision matrix

Request
Write the exact job.
Lane
Use / Use with review / Do not use.
Reviewer
Name a role, not 'someone'.
Evidence
Name the record or supplied text.
Stop condition
Say when work pauses.

Deliver: A six-row task decision matrix.

Compare with a worked answer

The email is Use with review: Operations lead checks Tuesday 7:00–9:00 PM and the support link before sending. The contract price is Do not use: the matrix says 'obtain signed contract; do not estimate.' The comment summary is Use because the lead can compare three visible comments in minutes.

Where this goes wrong

Calling every repetitive task safe to automate.

Repetition does not remove consequence; refund approval can be repetitive and still affects money and trust.

Repair: Classify the decision after the output, then place a review or stop point there.

Naming 'human review' without evidence.

A reviewer cannot reliably inspect a claim without the policy, record, or source text.

Repair: Add a reviewer-and-evidence column to every accepted task.

Treating a polished draft as permission to send.

Fluent wording may hide an unsupported time, price, or promise.

Repair: Keep sending and approval as named human actions.

Transfer the skill

Try a different situation

A fictional flower shop wants help with return emails.

Classify these jobs: group ten return questions, draft a reply from a supplied policy, approve a refund above $100, and promise a replacement date when inventory is unknown.

Get a hint
  • Ask what changes after the output.
  • Use only evidence the shop actually supplied.
Compare your reasoning

Grouping questions is Use with a support lead checking the examples. Drafting a reply is Use with review against the supplied policy. Approving a refund above $100 is Do not use because a manager owns the approval. Promising an unknown replacement date is Do not use; the draft may instead say that availability will be confirmed.

  • Each classification gives a reason tied to consequence.
  • The answer identifies a reviewer and source for both accepted uses.
  • Unknown inventory is not converted into a promise.

Check your understanding

1. Which request is a bounded preparation task?

  1. Summarize three visible comments
  2. Approve a refund
  3. Invent a contract price
Show the reasoning

A. Summarize three visible comments

The summary is bounded preparation with visible evidence; approval and invention require a different response.

2. What makes a review point useful?

  1. It says 'check later'
  2. It names a reviewer and evidence
  3. It uses the newest model
Show the reasoning

B. It names a reviewer and evidence

A reviewer needs a role, a source, and a decision to inspect.

Keep these ideas

  • Choose a bounded job before choosing a tool.
  • Preparation can help; authority stays with a responsible person.
  • A useful review names evidence and a stop condition.

Try the exercise in your own document.

Use the prompts and worked answers above to practice now. Enrollment adds your saved notes, practice record and connected skill map across both tracks.

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Sources & further reading

Official documentation supports product and access claims. Articles and videos add examples and perspectives. A1 examples and exercises are original and fictional. Tool availability may depend on your plan and region. A listed video may have been checked by page description only; open the scope for details.

  1. ChatGPT Capabilities Overviewhelp.openai.com · Reference · Source reviewed · 2026-09-08
    What this reference supports

    Capacidades de conversa, arquivos, análise e projetos como apoios distintos; disponibilidade depende de plano e configuração.

  2. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profilenvlpubs.nist.gov · Reference · Source reviewed · 2026-09-08
    What this reference supports

    Seções consultadas sobre confabulação, automação excessiva e necessidade de controles humanos.

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