Report · AI & Tech

Americans are split on whether generative AI is neutral

Reading

A plurality of Americans (39%) reject the idea that generative AI is a "neutral" tool, saying it comes loaded with assumptions no matter how it is used, according to a June 2025 Verasight survey.

A nearly equal share (35%) call it neutral and say everything depends on how it is used, while the remaining 26% are unsure.

Topline

single choice

Topline distribution

Americans are split on whether generative AI is neutral.

Would you describe generative AI (such as ChatGPT, Gemini, Claude.ai, etc.) as a "neutral" tool?

  • No, it is not neutral. Independent of how it is used, it comes with a set of assumptions that do not make it neutral. 38.7%
  • Yes, it is a neutral tool. It all depends on how it is used. 35.4%
  • I am unsure. 25.9%

2025 · base n 1,000 · +/- 3.8%

ICA Conference Omnibus Survey #2025-058

View source

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-06-25 → 2025-06-30
Base (unweighted)
1,000
Margin of error
+/- 3.8%
Module
ICA Conference Omnibus Survey #2025-058

Source

Citation

ICA Conference Omnibus Survey #2025-058, fielded June 25-30, 2025, N=1,000 US adults age 18+, +/- 3.8%.

https://verasight-ica-2025.tiiny.co

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. When a wave report is published, its field dates, sample sizes, and module breakdown are listed in that report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
The canonical report hub is reports.verasight.io. Verified legacy reports remain on their original hosts, and unpublished reports are marked pending.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

The canonical report hub is reports.verasight.io; older reports may remain on verified legacy hosts.