Skip to content

R0029/2026-03-27/Q002 — Query Definition
Research R0029 — Plural Voice Attribution
Run 2026-03-27
Query Q002

Query as Received

What does current research say about public and technology community sentiment toward AI-generated content? Specifically surveys, polls, and studies measuring how people perceive AI-generated versus human-generated work, including trust levels and negative attitudes.

Query as Clarified

  • Subject: Public and technology community attitudes toward AI-generated content
  • Scope: Quantitative survey data on trust, perception, and attitudes — not opinion pieces or anecdotal reports
  • Evidence basis: Surveys with disclosed methodology and sample sizes; polls from reputable organizations; peer-reviewed studies
  • Temporal sensitivity: High — attitudes are shifting rapidly; most relevant data from 2024-2025

Ambiguities Identified

  1. "Public" vs. "technology community" may have very different attitudes — the query asks about both but findings may diverge significantly.
  2. "AI-generated content" spans text, images, code, music, and video — attitudes may vary by content type.
  3. "Negative attitudes" implies a hypothesis that attitudes are negative, which should be tested rather than assumed.

Sub-Questions

  1. What do large-scale global surveys say about trust in AI systems generally?
  2. Do people perceive AI-generated content differently from human-generated content?
  3. Are there measurable differences in trust/attitudes between advanced and emerging economies?
  4. What specific concerns do people express about AI-generated content?
  5. How have attitudes changed over time (2022-2025)?

Hypotheses

ID Hypothesis Description
H1 Predominantly negative — public sentiment is mostly distrustful Surveys show majority distrust or negative attitudes toward AI-generated content
H2 Predominantly positive — public sentiment is mostly accepting Surveys show majority trust or positive attitudes toward AI-generated content
H3 Mixed and context-dependent — sentiment varies by population, content type, and region No single characterization fits; attitudes are fragmented along demographic, geographic, and contextual lines