0.7.16 Module 7 Quiz Study Guide

AI Systems Perform Different Kinds of Tasks

Artificial intelligence is a broad category.

AI systems can:

  • classify;
  • predict;
  • recommend;
  • generate content.

Different systems accept different inputs and produce different outputs.

Do not assume that every AI system has the same capabilities or access to the same information.

Generative AI Produces New Output

Generative AI can produce:

  • text;
  • images;
  • audio;
  • code;
  • other generated content.

A generated response is not a guaranteed factual record.

The system produces output from its model, prompt, context, and available tools.

Prompts Help Define the Task

A prompt can include:

  • the goal;
  • audience;
  • context;
  • format;
  • constraints.

A more specific prompt can reduce ambiguity.

A detailed prompt still does not guarantee a correct answer.

Input Can Include More Than Text

Depending on the AI tool, input can include:

  • text;
  • images;
  • documents;
  • audio;
  • prior conversation context.

Share only information needed for the task and permitted for the system.

AI Output Is Not Guaranteed

A response can sound:

  • confident;
  • polished;
  • detailed;

and still be wrong or incomplete.

Important factual claims should be evaluated rather than accepted based on style.

Accuracy, Credibility, and Relevance Are Different

Accuracy

A response can be strong in one area and weak in another.

Bias and Missing Context Can Affect a Response

Ask:

  • What assumptions are present?
  • Which perspectives are included?
  • Which are missing?
  • What context would change the answer?
  • Is a broad statement being treated as universal?

Missing context can make a generally reasonable response inappropriate for a specific situation.

Verification Connects Claims to Evidence

A verification process is:

Activity diagram showing identify claim, then choose appropriate evidence, then compare evidence with claim, then supported contradicted partly supported unresolved.
IdentifyClaim.
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Two AI responses agreeing with each other is not the same as independent verification.

Authority Depends on the Domain

Choose a source based on:

  • who controls the information;
  • whether the source addresses the exact claim;
  • whether it is current;
  • whether it is the authoritative original rather than an uncontrolled copy.

Examples include current:

  • course sources;
  • institutional policies;
  • official product documentation;
  • responsible government sources.
Data Minimization Protects Information

Share only what is needed.

Do not provide:

  • passwords;
  • authentication codes;
  • security secrets;
  • confidential information you are not authorized to share.

Use fictional or de-identified examples when they can accomplish the task.

Responsible AI Use Includes Transparency

Follow the AI-use requirements that apply to the current course or workplace.

When disclosure is required, accurately represent how AI contributed.

Do not present AI-assisted work in a way that falsely implies a different creation process.

Comparing Responses Can Reveal Problems

Compare AI outputs for:

  • different claims;
  • unsupported assumptions;
  • missing context;
  • differences in relevance;
  • areas needing verification.

Agreement is not proof.

Disagreement creates a useful verification question.

Accept, Revise, Verify, or Reject

Use the framework to choose your next action.

Accept

Use the output when it fits the task and needs no meaningful correction or unresolved verification.

Revise

Change useful output that needs improvement.

Verify

Check an important factual claim with appropriate evidence.

Reject

Do not use an output that is substantially wrong, inappropriate, unsafe for the task, or outside the rules.

Human Judgment Is the Final Step

AI can produce information.

A human is responsible for deciding whether and how that information should be used.

Strong judgment includes:

  • understanding the task;
  • recognizing limitations;
  • seeking evidence;
  • knowing when expertise is needed;
  • explaining the final decision.
AI and Human Roles Can Be Modeled With UML

An activity diagram can use partitions:

Activity diagram showing Understand AI capability, then Provide appropriate input, then Receive generated output, then Evaluate accuracy, credibility, relevance, bias, and limitations, then Verify important claims, then Protect information and follow usage rules.
UnderstandAICapability.
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