# AI-Assisted Research — Quiz

## Question 1

What is the best way to think about AI's role in product research?

A) AI replaces the need for user interviews
B) AI amplifies your analysis but doesn't replace human judgment
C) AI is only useful for quantitative data, not qualitative
D) AI should be used only for final report writing

<!-- ANSWER: B -->
<!-- EXPLANATION: AI works best as a research assistant—speeding up synthesis, structuring output, generating hypotheses. Human researchers still need to conduct interviews, validate insights, and make judgment calls. AI amplifies, it doesn't replace. -->

## Question 2

When prompting AI for research synthesis, which technique helps reduce hallucination?

A) Asking for longer responses
B) Requesting structured output (tables, bullets) and citation of sources
C) Using more creative, open-ended prompts
D) Running the same prompt multiple times and averaging

<!-- ANSWER: B -->
<!-- EXPLANATION: Structured output (tables, bullets) and explicit requests to cite sources or label [From data] vs [Inferred] make it easier to verify outputs and catch unsupported claims. Creative open-ended prompts can increase hallucination. -->

## Question 3

Before using AI-synthesized insights in a PRD, you should:

A) Accept them as-is since AI is objective
B) Trace insights to source data and validate with real users
C) Use them only for internal drafts, not stakeholder-facing docs
D) Run them through another AI for a second opinion

<!-- ANSWER: B -->
<!-- EXPLANATION: AI can be confidently wrong. Validating means tracing insights to source data and testing them with real users. Internal vs stakeholder-facing doesn't change the need for validation. A second AI can repeat the same biases. -->

## Question 4

Which of these is an ethical concern when using AI for research?

A) AI responses are too slow
B) Pasting user PII (names, emails) into AI tools
C) AI sometimes gives short answers
D) AI requires an internet connection

<!-- ANSWER: B -->
<!-- EXPLANATION: Pasting PII into AI tools risks privacy violations and may violate data policies. Always anonymize before sharing. Speed, answer length, and connectivity are operational concerns, not ethical ones. -->

## Question 5

In the AI-augmented research workflow, where do real user interviews fit?

A) They're optional once AI has synthesized existing data
B) They validate and fill gaps in AI-generated themes
C) They should be replaced by AI analysis of support tickets
D) They happen only before any AI use

<!-- ANSWER: B -->
<!-- EXPLANATION: The workflow is iterative: AI can pre-synthesize existing data → human designs interview guide from themes → interviews happen → AI can help cluster interview notes → human validates. Interviews validate and deepen AI synthesis; they're central, not optional. -->

## Question 6

What is a key limitation of AI for research?

A) AI cannot write in bullet points
B) AI tends to over-generalize and smooth over edge cases
C) AI only works with English
D) AI cannot process more than 1000 words

<!-- ANSWER: B -->
<!-- EXPLANATION: AI often produces "average" or consensus views and can miss outliers, edge cases, and segment-specific nuances. Manual review of raw data remains important to catch what AI smooths over. Other options are not typical limitations. -->