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Americans want policymakers to focus on AI

Source reportMethodology

Overview

Given seven policy ideas on AI, just 8.7% of adults would ask state or federal policymakers to do nothing. The most-selected ask is taxing AI companies and data centers to fund a dividend paid to all Americans, at 39.9%.

The issue also sits in view. About two-thirds of adults (67.8%) saw AI-related news at least weekly in the past month, and 53.9% are worried about the health effects of AI data centers.

Topline

39.9% would ask policymakers to tax AI companies and data centers to fund a dividend paid to all Americans; just 8.7% would ask them to do nothing.

Among the following policy or regulatory ideas below, check all of the following that you would ask your state or federal policymakers to adopt to address AI

  • Tax AI companies and data centers, redistribute those tax revenues using an AI dividend payment to all Americans. 39.9%
  • Provide free retraining programs for all workers to ensure optimal and safe AI use. 37.3%
  • Make it easier to access unemployment benefits in the case of job loss or if young workers cannot find a job (e.g., by removing earnings and work experience requirements to qualify). 36.3%
  • Remove tax breaks or other incentives for data centers. 35.9%
  • Change student loan repayment to make payment conditional on employment and income. 24.5%
  • Ban the use of AI. Strictly enforce these regulations. 17.7%

2026 · base n 1,000 · +/- 3.1%

Verasight PAA Omnibus Survey #2026-051

View source data

Few would ask policymakers to do nothing

Asked to check any of seven policy or regulatory ideas they would ask state or federal policymakers to adopt on AI, just 8.7% of adults chose doing nothing.

The most-selected idea is taxing AI companies and data centers and redistributing the revenue as a dividend to all Americans, at 39.9%. Free retraining programs for workers (37.3%), easier access to unemployment benefits (36.3%) and removing tax breaks for data centers (35.9%) follow closely.

Topline

53.9% are worried about the health effects of AI data centers, while 12.8% are not worried.

How concerned are you about the health effects of AI data centers?

  • Very worried 27.0%
  • Worried 26.9%
  • Neutral 22.6%
  • I'm not aware of the health effects of AI data centers 10.6%
  • Not worried 8.6%
  • Not worried at all 4.2%

2026 · base n 1,000 · +/- 3.1%

Verasight PAA Omnibus Survey #2026-051

View source data

Data-center health worries run through the demand

More than half of adults (53.9%) are worried or very worried about the health effects of AI data centers.

Just 12.8% are not worried, and another 10.6% say they are not aware of the health effects of AI data centers.

AI news is hard to avoid

About two-thirds of adults (67.8%) saw news related to artificial intelligence at least weekly in the past month, including 22.9% who saw it multiple times a day.

Just 12.0% saw no AI-related news at all in the past month.

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Population
US adults age 18+
Field dates
2026-06-03 → 2026-06-08
Base (unweighted)
1,000
Margin of error
+/- 3.1%
Module
A
Sponsor
Verasight
Weight variable
weight
Weighting targets
age, race/ethnicity, sex, income, education, region, metropolitan status

Sources

[3]

Citation

Verasight PAA Omnibus Survey #2026-051, fielded June 3-8, 2026, N=1,000 US adults age 18+, +/- 3.1%.

https://reports.verasight.io/r/paa-2026#q-12

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.