Report · AI & Tech

Nearly half don't trust new AI tools like ChatGPT

Reading

Trust in new AI tools like ChatGPT runs thin. Nearly half of Americans (48%) disagree that they generally trust technologies like ChatGPT, including 19% who strongly disagree.

About a quarter (24%) agree, including just 4% who strongly agree, and the remaining 28% stay neutral, according to an April 2024 Verasight survey.

Topline

response scale

Topline scale

Nearly half don't trust new AI tools like ChatGPT.

"I generally trust new AI technologies like ChatGPT"?

  • Neutral 27.9%
  • Strongly Disagree 19.0%
  • Somewhat Agree 14.8%
  • Disagree 14.3%
  • Somewhat Disagree 14.3%
  • Agree 6.1%
  • Strongly Agree 3.5%

2024 · base n 1,000 · +/- 3.5%

2

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Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2024-04-10 → 2024-04-15
Base (unweighted)
1,000
Margin of error
+/- 3.5%
Module
2

Source

Citation

Verasight MPSA Omnibus Survey #2024-037, fielded April 10-15, 2024, N=1,000 US adults age 18+, +/- 3.5%.

https://verasight-mpsa-2024.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.