Report · AI & Tech

AI-generated video detection inspires confidence in seven-in-ten Americans

Reading

In a Verasight survey of 1,000 U.S. adults conducted Nov. 14 to 20, 2025, 71% of Americans said they had at least some confidence in their ability to recognize AI-generated videos. Including 26% who said somewhat confident, 34% who said fairly confident, and 11% who said completely confident.

About three-in-ten said they had little or no confidence (29%), with 16% who said slightly confident and 13% who said not confident at all.

Topline

response scale

Topline scale

71% of Americans have at least some confidence in spotting AI-generated videos.

How confident are you in your ability to recognize AI-generated videos when you see them?

  • Fairly confident 33.7%
  • Somewhat confident 26.2%
  • Slightly confident 16.0%
  • Not confident at all 13.3%
  • Completely confident 10.8%

2025 · base n 1,000 · +/- 3.2%

Module 3

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
2025-11-14 → 2025-11-20
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
Module 3

Source

  • 01
    AI-generated video detection inspires confidence in seven-in-ten Americansreports.verasight.io/reports/verasight-apha-omnibus-survey-2025-148

Citation

Verasight APHA Omnibus Survey #2025-148, fielded November 14-20, 2025, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/reports/verasight-apha-omnibus-survey-2025-148#how-confident-are-you-in-your-ability-to-recognize-ai-generated-videos-when-you-see-them

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
AAPOR transparency standards.

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