← Back
FeaturedAIProducts#AI Public Opinion Survey#AI Security#AI Regulation#Anthropic

Anthropic Releases First Public Record Survey: Unveiling Public Attitudes Toward AI

Anthropic:News(网页)T1
15:5806/26, 03:58 PMWebRead the original ↗Export MD ↓

Score

67

Why selected

The survey provides important public opinion data, but it is not a technical breakthrough; it is an industry research output with moderate novelty but high practical value.

AI commentary

「This survey systematically reveals the genuine public views on AI in the U.S. for the first time, offering an irreplaceable public opinion foundation for policymakers, industry leaders, and researchers, and helps guide responsible AI development aligned with public expectations.」

Quick overview

Anthropic has released the results of its first 'Public Record,' a national survey of U.S. public attitudes and opinions toward artificial intelligence. The survey covers perceptions of AI risks, benefits, regulatory expectations, and societal impacts, aiming to provide a data foundation for industry policy and public dialogue. Findings show a mix of high expectations and significant concerns, especially regarding safety and employment effects. Anthropic plans to update the record regularly to track evolving attitudes.

  • The survey sampled respondents across age groups, regions, and political backgrounds in the U.S.
  • Strong public demand for AI safety and regulatory transparency was observed.
  • Most respondents believe AI will accelerate economic change but worry about job displacement.
  • Anthropic commits to updating the Public Record quarterly to foster open dialogue.

Full text

Showing the source text; the full translation is being generated.

Announcements

Results from the first Anthropic Public Record

Jun 12, 2026Results from the first Anthropic Public Record

We’re conducting a new survey series, Anthropic Public Record, to understand how the public thinks and feels about AI, and presenting a snapshot of the results from the first wave, fielded in November and December of 2025 with nearly 52,000 Americans.

We found:

  • Nearly half (48%) of Americans ranked curing diseases like cancer or Alzheimer’s as one of their top three hopes for AI, followed by helping people with disabilities (36%), then making technological progress and making life easier in general (tied at 23%).
  • AI-induced job loss was the most common fear in every state, held by 64% of Americans. The second most prominent fear was cognitive dependency (56%), followed by misinformation (52%).
  • Support for government intervention in AI was high: over 70% of the Americans we surveyed believe the government should play a role in regulating AI, and this support was bipartisan. People were most eager to see the government take action on AI in the areas of privacy (56%), child safety (52%), and liability for harm (49%).
  • When asked what would best ensure AI is of benefit to humanity, Americans ranked holding AI companies legally liable for harm (47%) and prioritizing safety over growth (44%) as the highest-leverage actions.
  • Only 15% of Americans said they trust AI companies to make decisions about how AI is developed and used.
Job-loss worry Integrated usersSupport for gov involvement

Strikingly, on most questions, AI did not heavily divide Americans along typical partisan, geographic, or educational lines. In general, there was broad consensus across topics: Americans are eager to realize AI’s promised benefits but fear the disruption it may bring, and they want accountability from the companies building it. To the extent we saw disagreement, it was largely only in the intensity of people's views.

This research builds on other work underway at Anthropic to understand how people use Claude and think about AI development. We recently conducted a global qualitative study of 81,000 Claude users through Anthropic Interviewer, our tool for conducting in-depth interviews at scale. We also regularly release data from the Anthropic Economic Index, which draws on anonymized Claude usage data to show how people around the world are employing AI. The Anthropic Public Record survey marks the first time we’ve spoken to the general public, allowing us to reach non-users of AI and better understand how attitudes differ across demographic lines.

The Anthropic Public Record will be repeated regularly, evolving in scope as new topics become more salient, and allowing us to track how the public’s attitudes towards AI change as model capabilities advance and adoption deepens. In the future, we plan to expand outside the US. 


Method in brief

We conducted a nationally representative online survey in November and December of 2025 of 51,993 Americans, sourced from YouGov and weighted to US Census benchmarks. State samples range from n=232 (Alaska) to n=1,902 (New York), with state-level margins of error between ±2.6 and ±9.1 percentage points. More details on the methodology are available in the Appendix.


What Americans hope AI will deliver

We asked Americans to choose their top three hopes for AI from a list of 17. Curing disease topped the list, with 48% of respondents putting it in their top three, 12 percentage points ahead of the second most commonly selected item, helping people with disabilities, at 36%. Items like therapy and reducing loneliness—or hopes that AI might substitute for human contact—were the lowest ranked of the options presented.

What Americans fear

We gave respondents a list of 20 possible harms from AI, asked them to flag each one they felt personally concerned by and then to rate each on a five-point scale of how worried they were. We considered any response of 2 (somewhat worried) or higher as worried. (This methodology differs from the question above, in which we asked participants to rank only their three hopes; the numbers aren’t comparable.)

Job loss was by far the most common concern, held by nearly two-thirds (64%) of Americans. This was followed by cognitive dependency—in which AI integration leaves people unable to think for themselves—at 56%, and misinformation at 52%. Job loss and cognitive dependency were also among the top fears in our qualitative study of 81,000 people using Claude.

The most common harms tended to be near-term and concrete: job loss, cognitive dependency, misinformation, criminal use, and surveillance. Each of these fears also predates AI, having precedent in an earlier technology—for example, automation causing job loss, smartphones fostering dependency, and social media spreading misinformation. In general, Americans tended to be more concerned with the misuse of AI than AI misalignment, citing criminal use, surveillance, and terrorism more frequently than, for example, AI “going rogue”.

For all but three of the harms we mentioned, a majority of respondents described themselves as “not worried,” but there was no potential harm about which less than 1/4 of Americans had at least some concern.


Patterns with job loss

Sixty-four percent of Americans are worried that AI will displace jobs. The concern is remarkably evenly distributed. It is the top-ranked fear among Democrats (67%) and Republicans (62%), in households with children (59%) and without (66%), and in every state from Iowa at the high end (71%) to Mississippi at the low end (57%).


Job loss concerns are higher among Americans with more education

Concerns over job displacement rise with a respondent’s education level. Americans with postgraduate degrees are nearly 10 percentage points more worried about job loss than those with a high school education or less. The workers most worried about displacement, in other words, are the ones whose work already overlaps more closely with what AI is being asked to do—a finding reflected in our economic research team’s analysis of our global Anthropic Interviewer study.


Fear of job loss is heightened among those who use AI least

At the same time, people who use AI at work every day are notably less worried about job loss than people who don’t use AI at all: 54% versus 70%.


There are many possible explanations for this trend. Hands-on experience with AI may help people develop skills and fluency that allow them to augment rather than automate parts of their job, making job loss seem like less of a looming threat. Hands-on experience may also reveal AI's limitations. Likely it’s a combination of these and other factors.

Perceived capabilities and acceptance of AI at work

We gave respondents a list of 14 workplace tasks and for each asked two questions: “How well do you think an AI tool or application could perform this task today?” and “Thinking about your own job, how much AI involvement would you prefer for each of the following work tasks/purposes?”

Overall assessment of AI capabilities was fairly high. At the high end, 75% of Americans said AI was as good or better than humans on research. At the low end, 44% said AI was as good or better in service and support.

On most tasks, a majority of Americans did not want AI involved in their jobs, and even on the tasks they rated AI most capable—such as research and data analysis—nearly half of respondents said they want no AI involvement in their own work. However, acceptance of AI involvement within the workplace seems to move in lockstep with perceived capabilities: the more competent AI is perceived to be in a given domain, the more likely people are to be willing to use it.


Cognitive dependency is an anticipatory fear

The second most common fear in our survey was cognitive dependency on AI. To better understand whether people might actually be experiencing dependency, we asked respondents how much disruption they would feel if AI became unavailable tomorrow, then compared the answers of those worried about dependency with those unconcerned by it.

So far, cognitive dependency appears to be a mostly anticipatory fear: of the 56% of Americans who expressed some worry over dependence, only roughly 1/5 would feel significant disruption if AI became unavailable. Conversely, among the 44% who don’t worry about dependency, a higher percentage—roughly 1/3—would feel significant disruption.


Our qualitative research among 81,000 Claude users found that educators were 2.5 to 3 times more likely than average to report having witnessed cognitive atrophy firsthand, presumably in their students. In Anthropic Public Record, educators are likewise among the occupations most worried about dependency, second only to people working in arts and design.

As with job loss, the dependency fear falls steadily with usage. Americans who use AI daily at work are 16 points less worried about dependency (46%) than those who never do (62%).

What the heaviest AI users tell us

As of late 2025, about 6% of Americans used AI every day for both work and personal life. These integrated users are a preview of what more intensive adoption of AI looks like, and possibly of where mainstream opinion is headed as adoption grows.

Integrated users skew young, male, urban, employed, and college-educated. Nearly two-thirds describe themselves as people who experiment with new technology before most others or adopt it early once they see its potential, compared to 30% in the general public.


Integrated users are less worried than the general public across each of the harms we listed, though this probably reflects differences in the outlook of early adopters.


What Americans want from AI governance

71% of Americans say the government should be involved in the development and regulation of AI. The figure is 79% among Democrats, 68% among Republicans, and 69% among Independents—a bipartisan supermajority. A majority in every state and territory we surveyed supports government involvement in AI, from 81% in the District of Columbia to 63% in Hawaii.

Where Americans want government to act

We then asked about eight specific domains, and how heavily the government should be involved in each. Only two—privacy and child safety—draw outright majority support for more than a minimal role. National security, meanwhile, has the narrowest partisan gap of any domain, just three points between Democrats and Republicans.


What Americans want from the industry

When we asked what should happen to ensure AI is developed in humanity's interest, Americans converged on two answers: hold AI companies legally liable for harm (47% chose it among their top three) and prioritize safety over growth (44%). Independent watchdogs with real power (29%) and slowing AI development for safety (27%) followed.

The trust deficit

Only 15% of Americans said they trust AI companies to make decisions about how the technology is developed and used. That was the lowest figure for any institution we tested, below the federal government (20%), state and local government (19%), and international bodies (20%), and far below independent experts (43%).

Integrated users have the same appetite for regulation and oversight

Integrated users were more trusting of every institution we asked about, including AI companies—and were markedly less inclined to say AI development should be slowed or stopped. However, they also support government involvement on AI at essentially the national rate (74% versus 71%), and across the eight specific governance domains we tested, their preferences are nearly indistinguishable from the public's.


Anthropic initiatives and what comes next

Public input is critical to ensuring that powerful AI serves humanity’s interests. Anthropic Public Record, Anthropic Interviewer, the Anthropic Economic Index, and many of our other research projects are all efforts to gain greater understanding and input from the public about how to make the AI transition go well.

We recently announced several policy frameworks relevant to these findings. Our Advanced AI Framework proposes mandatory independent safety testing for frontier models, transparency requirements, and government authority to block or recall dangerous AI deployments. Our Economic Policy Framework lays out how governments can prepare for AI's economic impacts—minimizing job displacement where possible, and supporting workers so that AI's benefits are broadly shared.

The direction AI takes should not be set only by the companies building it. The more clearly the public’s hopes and concerns are measured, the better we—and other companies—can meet them.


Appendix: Methodology

Population and mode: Anthropic Public Record is an online survey of the US late-teen and adult internet population, age 16 and over, resident in the 50 states, the District of Columbia, or Puerto Rico. Fieldwork was conducted by YouGov from its online panel between November 1 and December 11, 2025.

Sample design: The study was designed as 52 parallel state and territory samples with a target of approximately 1,000 completes per state (approximately 500 in Montana, North Dakota, South Dakota, Wyoming, Vermont, and Puerto Rico). Quotas were set within each state on age, gender, education, and race/ethnicity. The achieved sample is 51,993 completes, with state sample sizes ranging from 232 (Alaska) to 1,902 (New York).

Weighting: Data are weighted to be representative of the US resident population age 16 and over on state, age, gender, education, and race/ethnicity. Weights are normalized to the achieved sample size (mean 1.00, sum 51,993).

Margin of error: The national margin of sampling error is ±0.6 percentage points at the 95% confidence level for a proportion of 50%. State-level margins of error range from ±2.6 points (California, New York, Texas) to ±9.1 points (Wyoming). Margins of error for subgroups are larger.

Reporting conventions: All percentages in this report are weighted. Unless noted otherwise, percentages use the full segment as the denominator (respondents who answered "don't know" or skipped remain in the base). "Worried" on the fears battery is the top four boxes of a five-point worry scale. "As good or better" on the capability battery is the top three boxes of a five-point performance scale. "Integrated users" are respondents who report using AI one or more times daily for work and one or more times daily for personal purposes (unweighted n=2,717). Party affiliation groups include leaners.

Limitations: Anthropic Public Record captures what Americans believed about AI in late 2025. We are treating it as a baseline.


Related content

More details on Fable 5’s cyber safeguards and our jailbreak framework

Read more

Introducing Claude Sonnet 5

Sonnet 5 delivers frontier performance across coding, agents, and professional work at scale.

Read more

Redeploying Fable 5

Fable 5 returns globally July 1. We're also proposing an industry-wide framework for scoring jailbreak severity, together with Amazon, Microsoft, Google, and other Glasswing partners.

Read more

Related items

92

Five-dimension score

Information gain8 ×0.3

首次系统介绍 OpenRouter 缓存与路由协同策略,信息增量较高。

Content quality9 ×0.2

官方教程,结构清晰,包含原理、示例和实测效果。

Practical value10 ×0.2

直接明确降低 API 成本,开发者可立即应用。

Timeliness10 ×0.15

刚刚发布,且对当前 Agent 开发热潮具有及时指导意义。

Source reliability10 ×0.15

来源为 OpenRouter 官方 RSS 和官网,信源权威可靠。

Base 92 × T1 Source weight ×1 = 92

Curation line 60Selected

08:00OpenRouter:Announcements(RSS)T1RSS

FeaturedOpenRouter Launches Prompt Caching with Sticky Routing to Drastically Reduce Multi-Turn Costs

OpenRouter 推出提示缓存与粘性路由,大幅降低多轮对话成本

For developers making frequent AI API calls, this feature is a direct money-saver. Sticky routing guarantees cache hit rates, and session_id requires zero configuration—every OpenRouter user should try it immediately.

AIProducts#OpenRouter#session_id#Cost Optimization
91

Five-dimension score

Information gain9 ×0.3

首次公开ChatGPT Work的Agent能力,信息增量高。

Content quality8 ×0.2

官方发布,内容清晰,但细节较少。

Practical value9 ×0.2

为用户提供可直接使用的Agent能力,实用价值高。

Timeliness10 ×0.15

刚刚发布,时效性极强。

Source reliability10 ×0.15

来自OpenAI官方,信源权威可靠。

Base 91 × T1 Source weight ×1 = 91

Curation line 60Selected

18:00OpenAI:News(RSS)T1RSS

FeaturedChatGPT Work: An AI Agent That Takes Action Across Apps and Files

ChatGPT Work:可在跨应用和文件中执行操作的AI Agent

I think this is a key step for AI assistants moving from Q&A to execution. Especially noteworthy for professionals who need to automate complex workflows. ChatGPT Work could become a new paradigm for productivity tools.

AIProducts#Agent#AI Productivity#ChatGPT Work
90

Five-dimension score

Information gain9 ×0.3

首次公开前沿实验室代理入侵的完整技术时间线,信息增量极高。

Content quality8 ×0.2

结构严谨、技术细节丰富,但缺乏部分原始日志数据佐证。

Practical value9 ×0.2

提供了缓解建议和自检工具,对AI安全从业者具有直接指导意义。

Timeliness10 ×0.15

事件发生仅数月后即发布分析,时效性极佳。

Source reliability9 ×0.15

Hugging Face 作为顶级开源AI平台,其技术博客可信度极高。

Base 89.5 × T1 Source weight ×1 = 90

Curation line 60Selected

08:00Hugging Face:Blog(RSS)T1RSS

FeaturedAnatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident

前沿实验室代理入侵事件技术时间线:2026年7月事件剖析

This technical timeline is a must-read for all AI security researchers and agent developers—it doesn't just describe one attack but sounds an alarm on the weak defense systems of agent architectures. For teams deploying autonomous agents, this is an essential disaster prevention manual.

TechProducts#AI Agent Security#Hugging Face#Intrusion Timeline
90

Five-dimension score

Information gain8 ×0.3

文章揭示了工具增强反而导致AI性能下降的反直觉发现,并提供了具体工程改进方案,信息增量高。

Content quality9 ×0.2

来自GitHub官方工程博客,有数据支撑(成本下降40%),论证清晰,质量上乘。

Practical value9 ×0.2

对AI产品团队、代码审查工具开发者、以及依赖AI辅助编程的团队有直接借鉴意义。

Timeliness10 ×0.15

2024年发布的工程实践,符合当前AI产品优化趋势,时效性强。

Source reliability10 ×0.15

信源为GitHub官方博客,具有高度权威性和技术可信度。

Base 90 × T1 Source weight ×1 = 90

Curation line 60Selected

23:57GitHub Blog(网页)T1Web

FeaturedBetter Tools Made Copilot Code Review Worse? Here's How GitHub Improved It

更好的工具反而让Copilot代码审查更糟?GitHub这样改进

This blog post deserves close reading by all AI product engineers and ML practitioners—it breaks the intuition that 'more powerful tools = better AI' and instead emphasizes an engineering philosophy aligned with agent reasoning patterns. Especially important for teams optimizing code review or similar agent-based products.

AIProducts#Agent Workflows#Copilot#GitHub
88

Five-dimension score

Information gain9 ×0.3

披露了OpenRouter产品的新能力,对关注多模态开发的用户有较高信息增量。

Content quality8 ×0.2

内容清晰,准确描述了API功能与优势,但缺少性能数据对比。

Practical value9 ×0.2

直接解决多模态API碎片化问题,开发者可立即降低集成成本。

Timeliness10 ×0.15

该API为新近发布,具有很高时效性。

Source reliability8 ×0.15

OpenRouter官方博客,权威性高,但未提及其他第三方验证。

Base 88 × T1 Source weight ×1 = 88

Curation line 60Selected

08:00OpenRouter:Announcements(RSS)T1RSS

FeaturedOpenRouter Launches Unified Multimodal API: Single Endpoint for Image, Video, Audio, Embeddings, and Transcription

OpenRouter 推出统一多模态 API:单端点支持图像、视频、音频、嵌入与转录

This news is worth attention from all developers building multimodal AI applications: OpenRouter's unified API solves the pain of model switching, especially for startups or rapid prototyping. If you're struggling with multiple API keys and SDKs, this interface could be the unified layer you need.

AIProducts#OpenRouter#Multimodal API#Model Ensembles
87

Five-dimension score

Information gain8 ×0.3

介绍了全新的教育产品,填补了AI安全公司在教育垂直领域的空白,信息增量较高。

Content quality8 ×0.2

内容简洁清晰,准确概括产品功能、安全理念和试点情况,无冗余信息。

Practical value9 ×0.2

直接解决教师备课负担痛点,且强调安全合规,对教育工作者具有实际参考价值。

Timeliness10 ×0.15

消息发布时间接近当前日期,属于最新产品发布动态。

Source reliability9 ×0.15

来源为Anthropic官方新闻页面,权威性高,内容可靠。

Base 86.5 × T1 Source weight ×1 = 87

Curation line 60Selected

23:40Anthropic:News(网页)T1Web

FeaturedAnthropic Launches Claude for Teachers: AI Tools Designed for Educators

Anthropic 推出 Claude for Teachers:面向教师的教育 AI 工具

This announcement is valuable for educators and AI industry watchers alike. Instead of a generic chatbot, Anthropic designed a safety-first tool specifically for teachers, demonstrating the right approach for AI vertical deployment: solving real pain points rather than showing off technology. The built-in guardrails also set a reference for other AI companies, especially when serving scenarios involving children or teenagers.

AIProducts#AI Security#Anthropic#Claude
86
08:00Anthropic:News(网页)T1Web

FeaturedPhysicist Christopher Stubbs joins Anthropic's Long-Term Benefit Trust

来自 Anthropic:News(网页) 的这条信息指向模型能力或模型生态变化,适合用于判断近期 AI 圈的真实动向。

FinanceModels#Anthropic#安全#Physicist Christopher Stubbs
86

Five-dimension score

Information gain9 ×0.3

全新路由机制,市场智慧概念为行业带来较高信息增量。

Content quality8 ×0.2

官方公告内容清晰,但技术细节不足,略有扣分。

Practical value8 ×0.2

对开发者选型有直接实用价值,可降低试错成本。

Timeliness9 ×0.15

产品刚发布,时效性极强。

Source reliability9 ×0.15

来自OpenRouter官方RSS公告,信源可靠。

Base 86 × T1 Source weight ×1 = 86

Curation line 60Selected

08:00OpenRouter:Announcements(RSS)T1RSS

FeaturedOpenRouter Introduces New Auto Router: Model Routing Powered by Market Wisdom

OpenRouter发布全新Auto Router:用市场智慧优化模型路由

This update is worth attention for anyone using APIs to build AI apps. Instead of guessing or testing model selection, market data now does the heavy lifting. Though sparse on details, the direction is right, especially for teams relying on aggregated model services.

AIProducts#Auto Router#OpenRouter#Wisdom of the Market

Verify against the original source before citing