# Workflow 01 — From topic to question, and why it matters

**When:** weeks 1–3. **Feeds:** the proposal (Oct 11).

## Goal

Turn a topic you care about ("AI and misinformation," "data centers") into **one specific, answerable question**, and a short, honest case for why it matters.

## You produce

- **Your question**: 1–2 sentences, ending in a question mark.
- **Its type**: *descriptive* (what does X look like?), *causal* (does X change Y?), *evaluative* (did X work?), or *normative* (should we do X?).
- **Key terms**: 2–4 terms a reader would need defined.
- **Motivation**: one paragraph on why the question matters and to whom.

## Steps

1. **You.** Name the challenge in one sentence, e.g. "City councils are deciding on data-center permits without good information about water use." Then say what you want to know about AI's effect on it.
2. **You.** Write a first draft of your question. It doesn't have to be good yet.
3. **With AI.** Sharpen it. Paste in your challenge and your draft question:

   ```
   You are a research-design coach for an undergraduate political science course on AI and politics.
   Here is the challenge I care about and my draft question.
   1. Tell me whether my question is a topic in disguise, and why.
   2. Ask me who, where, when, and what outcome, one at a time, until the question is specific.
   3. Point out any assumption built into the question.
   4. Suggest 3 sharper versions that go in different directions. For each, say what type of question
      it is (descriptive, causal, evaluative, normative) and what kind of evidence it would need.
   ```

4. **You decide.** Pick, combine, or reject the versions, and write the final question in your own words. Check two things. First, could an answer you dislike come out of it? ("Why does AI destroy trust in elections?" assumes the answer.) Second, are you asking what *is* happening or what *should* happen? Both are fine. Just know which one you're doing.
5. **You.** Write the motivation paragraph. It needs at least one strong reason, grounded in something concrete:
   - **Magnitude**: many people or a lot of money or power are affected. Give a number or an example.
   - **Gap**: existing work misses or gets this wrong. Name the work.
   - **Audience**: someone specific (a regulator, a campaign, an NGO) would act on the answer.
6. **With AI.** Stress-test the motivation:

   ```
   Play a skeptical classmate. Here is my question and my motivation paragraph.
   Ask me "so what?" until I can't answer, one round at a time.
   Then tell me which of my reasons is weakest, and what kind of number, study, or audience
   would make it stronger. If you name a specific source, tell me I need to verify that it exists.
   ```

If the AI suggested a framing you adopted, note it in your AI-use note.

## Check before moving on

- [ ] A stranger could read the question and know exactly what you're investigating.
- [ ] You can name the question type, and the kind of evidence that would answer it.
- [ ] The question is small enough for ten weeks, not a dissertation.
- [ ] The motivation rests on something concrete (a number, a named study, a named audience), not just "this is important."
- [ ] The final wording is yours.

## Common traps

- **Topic, not question.** If it has no question mark, it isn't a question.
- **"Nobody has studied this."** That isn't enough on its own. Say why the gap matters.
- **Overclaiming.** "This will transform how we regulate AI." A modest contribution, stated honestly, is more convincing.
- **Picking causal because it sounds rigorous.** Every type of question has its own kind of rigor. Pick the type that matches what you actually want to know.
- **Taking the AI's version as is.** Its suggestions are options. The question you pick has to be one you understand and care about.

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*Course framing adapted from the POLISCI 158 syllabus, Project-Based Assessments.*