Report · AI & Tech

Most Americans don't know what their state spends on facial recognition

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Facial recognition spending is a blind spot: most Americans (52%) say they are not familiar with the current level of government spending on facial recognition technology in their state, according to an April 2025 Verasight survey.

One-in-five Americans (20%) think the level is about right. Critics lean toward overspending: 18% say it is too much or far too much, including 9% who say far too much, while 11% call it too little or far too little, including 3% who say far too little.

Topline

single choice

Topline distribution

Most Americans don't know what their state spends on facial recognition.

How would you rate the current level of government spending on facial recognition technology in your state?

  • I'm not familiar with the current level of government spending on facial recognition technology in my state 51.6%
  • About right 19.6%
  • Too much 9.6%
  • Far too much 8.5%
  • Too little 7.9%
  • Far too little 2.7%

2025 · base n 1,000 · +/- 3.5%

policy

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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
2025-04-09 → 2025-04-15
Base (unweighted)
1,000
Margin of error
+/- 3.5%
Module
policy

Source

Citation

Verasight MPSA Omnibus Survey #2025-026, fielded April 9-15, 2025, N=1,000 US adults age 18+, +/- 3.5%.

https://verasight-mpsa-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.