Report · AI & Tech

Above all, Americans want government AI to be unbiased

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Bias is the thing Americans most want kept out of AI in government decision-making: 31% of U.S. adults say an unbiased system matters more than anything else, ahead of the 27% who prioritize accuracy, according to a September 2023 Verasight survey.

A smaller share (16%) says the key is that the AI's decisions be accountable to elected officials, and 12% want an AI that is understandable. At the bottom of the list, 7% point to something else entirely and 7% say the AI must be cost-effective.

Topline

single choice

Topline distribution

Above all, Americans want government AI to be unbiased.

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%

2023 APSA Omnibus Survey #2023-071

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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
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://verasight-apsa-2023.tiiny.co#importance-of-factors-in-using-artificial-intelligence-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. 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.