Report · AI & Tech

Above all, Americans want government AI to be unbiased

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In a Verasight survey of 2,000 U.S. adults conducted Sept. 7 to 13, 2023, above all, Americans want government AI to be unbiased; 31% selected the AI must be unbiased.

The next-largest shares were 27% for the AI must be accurate and 16% for the AI's decisions must be accountable to elected officials.

Topline

single choice

Topline distribution

Above all, Americans want government AI to be unbiased (31%).

Which of the following do you think is most important in using Artificial Intelligence (AI) in government decision-making?

  • The AI must be unbiased 30.6%
  • The AI must be accurate 27.3%
  • The AI's decisions must be accountable to elected officials 16.0%
  • The AI must be understandable 12.2%
  • Other (please specify) 7.3%
  • The AI must be cost-effective 6.5%

2023 · base n 2,000 · +/- 2.3%

APSA Omnibus Survey #2023-071

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
2023-09-07 → 2023-09-13
Base (unweighted)
2,000
Margin of error
+/- 2.3%
Module
2023 APSA Omnibus Survey #2023-071

Source

Citation

2023 APSA Omnibus Survey #2023-071, fielded September 7-13, 2023, N=2,000 United States adults, +/- 2.3%.

https://reports.verasight.io/reports/2023-apsa-omnibus-survey-2023-071#which-of-the-following-do-you-think-is-most-important-in-using-artificial-intelligence-ai-in-government-decision-making

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. Each wave's specific field dates, sample sizes, and module breakdown are listed in that wave's 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
Every wave is published as a standalone report at verasight.io/reports with full instrument and methodology.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

Wave-specific methodology, full weighting variable lists, and verbatim instrument text live in each report at verasight.io/reports.