Pew Research Center is a nonprofit survey research organization in Washington, D.C. It describes itself as "nonprofit, nonpartisan and nonadvocacy," funded from charitable dollars, doing no work for hire, maintaining "strict impartiality," and studying public views "without an agenda": "We don't make policy recommendations or offer solutions. We design our work to explain the public, rather than try to persuade." Its site metadata describes it as "a nonpartisan fact tank." It is led by president Michael Dimock and stewarded by a nine-member volunteer board. Funding comes from The Pew Charitable Trusts and other organizations; the Center states that its leadership and staff decide what to study, that research is published free of charge, and that no funder influences the work (Source: pewresearch.org).
The nonadvocacy posture is the reason the Center's output functions differently in AI policy debate from that of the think tanks and coalitions also tracked here: it supplies contested measurements rather than positions, and both sides of a policy argument tend to cite the same Pew numbers.
Methods
Most of the Center's AI work runs on the American Trends Panel, a probability-based panel of U.S. adults. Reports publish the questionnaire, the detailed topline responses and the methodology alongside the findings, and chart data is released in machine-readable form. The Center describes surveys as one tool among several, augmented with in-depth interviews and with digital, economic and demographic data (Source: pewresearch.org).
Outside the United States, the Center's Global Attitudes Survey uses national samples interviewed by telephone, face to face or online; the Spring 2026 wave was conducted under the direction of Gallup, Langer Research Associates and Social Research Centre. Cross-national reports combine it with American Trends Panel data for the United States, so a multi-country median can mix fieldwork periods. The Center's 2026 reports describe it as a subsidiary of The Pew Charitable Trusts, its primary funder, and state that it does not take policy positions (Globally, More People Expect AI to Cause Job Loss Than Growth (Pew Research Center, 2026)).
A single fielding often yields several separately published reports. The June 22–28, 2026 wave of 3,488 U.S. adults produced both the July 23, 2026 findings on perceived U.S.–China standing and the August 25, 2026 report on health chatbot use, which is a point of care when dating a Pew figure: the field window and the publication date can be two months apart.
AI survey work
The Center's Americans and AI 2026 report of June 17, 2026, drawn from 5,119 U.S. adults surveyed February 17–23, 2026, is the anchor for baseline adoption and sentiment figures used across Public Opinion on AI: about half of U.S. adults reported using chatbots, and 40% expected AI to harm society over the next 20 years against 16% expecting benefit (Americans and AI 2026: Chatbots, Smart Devices and Views on Impact).
Subsequent releases have tracked movement rather than levels. A short read of August 18, 2026 found 55% of U.S. adults under 30 more concerned than excited about increased AI use in daily life. The July 23, 2026 release found Americans saying by roughly three to one that China (36%) is more advanced, a figure carried at US-China AI Competition: Different Races, Different Metrics. Pew also recorded a partisan reversal on confidence in the government's ability to regulate AI, with Democrats' lack of confidence rising 20 points to 74% while Republicans' fell from 70%.
A report of August 25, 2026, From Diagnoses to Treatments, Why Americans Use AI Chatbots for Health, drawn from the same June 22–28 wave, found that 34% of U.S. adults use chatbots for at least one of eight health reasons and that 25% use them to diagnose symptoms, while pluralities of the public said chatbots do more to hurt than help people who use them for loneliness, depression or stress (From Diagnoses to Treatments, Why Americans Use AI Chatbots for Health).
The Center published a survey of views of AI in 25 countries in 2025. Its 2026 successor, Globally, More People Expect AI to Cause Job Loss Than Growth, published September 17, 2026 by Laura Silver, Richard Wike, Moira Fagan and Jordan Lippert, covered 42,151 adults in 36 countries surveyed February 8 to May 13, 2026, together with the February and June 2026 U.S. panel waves. In 34 of the 37 countries people tended to expect AI to lead to fewer rather than more jobs over the next 20 years (median 46% against 9%), a 37% median were more concerned than excited about AI's increased use in daily life and 41% equally concerned and excited, and in 12 mostly middle-income countries median trust to regulate AI effectively was 43% for China, 35% for the United States and 34% for the European Union (Globally, More People Expect AI to Cause Job Loss Than Growth (Pew Research Center, 2026)).
A short read by Brian Kennedy published September 22, 2026 (Americans' Views of Data Centers Have Turned More Negative (Pew Research Center, September 2026)) tracked views of data centers between January 2026 and a July 20 – August 9, 2026 wave of 10,548 U.S. adults: the share saying data centers are mostly bad for the environment rose from 39% to 54%, and 60% said they would be not too or not at all comfortable with a new data center in their area. The share who had heard at least a little about data centers reached 88%, and 81% of liberal Democrats said they would be uncomfortable with a new local data center. The figures are carried at Public Opinion on AI and Data Center Siting / AI Power Politics (Americans' Views of Data Centers Have Turned More Negative (Pew Research Center, September 2026)).
Measurement of AI-authored content
Separately from its survey work, the Center's Data Labs unit published an analysis on August 20, 2026 estimating the prevalence of AI authorship on the open web from a Common Crawl sample, together with linguistic-marker counts tracked against a 2023 baseline (How Much of the Internet Is Written With AI? (Pew Research Center, 2026)). That analysis is the independent general-web measurement cited at AI Content Saturation (\"AI Slop\"), AI Content Provenance and Model Collapse.
Relationships
- related: Public Opinion on AI — the concept its survey work principally anchors.
- supports: Americans and AI 2026: Chatbots, Smart Devices and Views on Impact — publisher.
- supports: How Much of the Internet Is Written With AI? (Pew Research Center, 2026) — publisher.
- supports: From Diagnoses to Treatments, Why Americans Use AI Chatbots for Health — publisher.
- supports: Americans' Views of Data Centers Have Turned More Negative (Pew Research Center, September 2026) — publisher of the September 2026 data-center short read.
- supports: Globally, More People Expect AI to Cause Job Loss Than Growth (Pew Research Center, 2026) — publisher of the 37-country Global Attitudes report.
- related: AI Labor Disruption — cross-national expectations of AI-related job loss.
- related: AI Content Saturation (\"AI Slop\") — the measurement question its Data Labs work addresses.
- related: AI Content Provenance — downstream use of the same analysis.
- related: US-China AI Competition: Different Races, Different Metrics — supplies the public-perception series.
- related: Healthcare — AI Deployment — consumer health chatbot use.