FASS1000 Chap.6 Responsible AI and Academic Integrity

Responsible AI and Academic Integrity

Define generative AI

The course material gives this chapter a concrete anchor: The current LMS states permissions separately for open and secure assessments.

That generative AI anchor controls how verification is explained and how AI use declaration is tested in changed practice.

Responsible AI and Academic Integrity asks how generative AI, verification and AI use declaration change the interpretation of a text, case, institution or public problem.

The chapter's practical task is to distinguish learning support from authorship, evidence and prohibited secure-task use; that requires an argument, not a list of themes.

Define generative AI at the scale of the chosen case. Identify who uses the category, what it makes visible and what it may conceal.

This prevents the generative AI definition from floating above the evidence as an interchangeable opening paragraph.

Use verification to explain the relationship between the case and the claim.

Quote, describe or compare only the evidence that advances verification, and make the inferential step visible instead of assuming the example speaks for itself.

Trace verification

Bring AI use declaration in as a second lens or consequence. The AI use declaration reading may deepen the first account, expose a conflict or show why another audience would interpret the same material differently.

The comparison should change the conclusion, not simply add another term.

To distinguish learning support from authorship, evidence and prohibited secure-task use, build each paragraph around one contested move: claim, specific evidence, explanation and qualification.

A AI use declaration counter-reading is strongest when it identifies exactly which premise or piece of evidence it changes.

Make an evidence table for generative AI with four columns: passage, image, event or institutional fact; the concept it activates; the inference drawn; and a plausible competing reading. Place generative AI and verification in separate rows before combining them.

This keeps verification interpretation anchored in specific material and shows where disagreement enters the argument.

Test the scale of every claim. A detail involving generative AI may support an argument about one text, group or moment without supporting a claim about an entire culture or institution.

Use AI use declaration to decide whether the evidence should be widened, narrowed or compared with a counter-case before the paragraph reaches its conclusion.

Test with AI use declaration

For timed revision in fass1000, write a one-sentence thesis for the application — distinguish learning support from authorship, evidence and prohibited secure-task use — then list the minimum evidence needed to defend it.

Add one AI use declaration objection that would matter if true and revise the thesis so it survives.

The exercise trains AI use declaration argument selection and qualification rather than a memorised inventory of course terms.

A complete response should make the task visible before the detail: identify what must be decided, define the relevant terms, connect the evidence to verification, and use AI use declaration to test the result.

The final sentence about AI use declaration should answer the question actually asked rather than merely repeat the topic.

The controlling limit is specific: Fluent output can fabricate sources and cannot carry student accountability.

Keep that AI use declaration limit beside the worked example, because it separates a careful fass1000 answer from one that sounds confident but claims more than the task or evidence supports.

For revision, retrieve generative AI, verification and AI use declaration without notes, explain their relationship aloud, then complete a changed version of the application: distinguish learning support from authorship, evidence and prohibited secure-task use.

Record the first failed verification reasoning move and repair it before attempting another case.

What this chapter covers

• 01

  generative AI

• 02

  verification

• 03

  AI use declaration

• 04

  Applying generative AI

• 05

  Limits of verification and AI use declaration

Use AI for an open task

Key terms

generative AI

System producing new content from learned statistical patterns and prompts. This chapter uses the concept when students distinguish learning support from authorship, evidence and prohibited secure-task use. Use this definition when the task is to distinguish learning support from authorship, evidence and prohibited secure-task use.

verification

Independent checking of a claim against suitable evidence. It helps explain the reasoning required to distinguish learning support from authorship, evidence and prohibited secure-task use. Use this definition when the task is to distinguish learning support from authorship, evidence and prohibited secure-task use.

AI use declaration

Transparent record of permitted AI assistance in assessed work. Its limit matters because fluent output can fabricate sources and cannot carry student accountability. Use this definition when the task is to distinguish learning support from authorship, evidence and prohibited secure-task use.

Responsible AI and Academic Integrity FAQ

Assessment move

Reconstruct the relationship among generative AI, verification and AI use declaration; complete the chapter application without notes; then test the result against this limit: Fluent output can fabricate sources and cannot carry student accountability.

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