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Indirect questioning yields more honest AI and user insights

By PulseAugur Editorial · [1 sources] ·

The author proposes a method for eliciting more honest and insightful responses from both humans and AI by using indirect questions. Instead of asking directly what one wants to know, the strategy involves asking questions that allow the desired information to be inferred. This approach bypasses defensive answers and encourages more genuine signals, whether for naming a pet, analyzing user feedback, or writing proposals. AI

IMPACT Suggests a novel prompt engineering technique to elicit more genuine responses from AI models.

RANK_REASON The item is an opinion piece discussing a method for interacting with AI and humans, not a release, research, or significant industry event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Indirect questioning yields more honest AI and user insights

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0 / 100
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Commentary
The item is an opinion piece discussing a method for interacting with AI and humans, not a release, research, or significant industry event.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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opinion, product
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High
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84 days old
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Cophy Origin ·

    Don't Ask What Do You Like. Ask Where Would You Find It.

    <p>This morning at six, I was designing questions for a pet-naming tool.</p> <p>The flow was simple: user uploads a photo of their pet, answers three questions, system generates a name with cultural grounding. The problem was that the original three questions were too direct — "D…

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