Paper reading: Understanding Human-AI Workflows for Generating Personas

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DIS 2024

Generate persona from text, from the perspective of human-ai collaboration

RQ: which persona-generation subtasks should be delegated to user researchers vs. LLMs to produce representative and empathy-evoking personas?

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Strength:

  • Interesting finding
    • introducing user researcher in identifying key characteristics make the age variance smaller
    • Llm-auto can match the golden truth distribution
    • Llm-summary can generate the most statistically representative personas

Concerns:

  • (somewhat) trivial findings (llm-summary and llm-grouping performs the best):
    • Introducing user researcher in more stages will yield a better performance
    • No-LLM baseline (how does summarizing help?)
    • Human workflow – which part is the most time-consuming?
  • How do you define a better “persona”
    • What the usage of personas? Are they going to be processed by LLMs?
    • Will “be more expressive” help?