{"id":10153,"date":"2026-04-11T13:00:00","date_gmt":"2026-04-11T13:00:00","guid":{"rendered":"https:\/\/musictechohio.online\/site\/ai-polls-silicon-sampling\/"},"modified":"2026-04-11T13:00:00","modified_gmt":"2026-04-11T13:00:00","slug":"ai-polls-silicon-sampling","status":"publish","type":"post","link":"https:\/\/musictechohio.online\/site\/ai-polls-silicon-sampling\/","title":{"rendered":"Foolish Pollsters Are Now Just Asking AI What Voters Would Say in Response to Questions and Publishing It at Face Value"},"content":{"rendered":"
\n

Last month, Axios<\/em> was forced to issue a bizarre correction for a blog post<\/a> about a growing maternal health crisis in the United States.<\/p>\n

The story quoted new poll findings by a company called Aaru, representing them as research based on the feedback of American adults. But according to an editor\u2019s note, the piece had to be \u201cupdated to note that Aaru is an AI simulation research firm.\u201d<\/p>\n

In other words, Axios<\/em> had failed to disclose that it was citing alleged \u201cpolling data\u201d that wasn\u2019t drawn from human respondents at all. Instead, it was dreamed up by a large language model \u2014yet the latest sign of every imaginable industry trying to leverage AI, even when doing so makes absolutely no sense.<\/p>\n

As Digital Theory Lab director Leif Weatherby and University of California, Berkeley, computer sciences professor Benjamin Recht explain in a guest essay for the New York Times<\/em><\/a>, the practice that tricked Axios <\/em>is called \u201csilicon sampling,\u201d and it\u2019s a recipe for disaster.<\/p>\n

\u201cThe idea behind silicon sampling is simple and tantalizing,\u201d they write. \u201cBecause large language models can generate responses that emulate human answers, polling companies see an opportunity to use AI agents to simulate survey responses at a small fraction of the cost and time required for traditional polling.\u201d<\/p>\n

If that sounds like vast overreach that could undermine the value of opinion polling itself, you may be correct. The data only has value \u201cinsofar as it summarizes the beliefs and opinions of actual humans,\u201d as Weatherby and Recht argue. \u201cUsing simulations of human opinions in place of the real thing will only worsen our broken information ecosystem, and sow distrust.\u201d<\/p>\n

Pollsters have long relied on statistical models to make up for a relatively small pool of responses while addressing possible variables that could skew the data. After all, convincing people to answer questions on the phone or online isn\u2019t exactly easy.<\/p>\n

But making up responses wholesale using AI is obviously a terrible alternative, and can easily introduce biases and \u201cinfluence public opinion itself, rather than merely to report what the public thinks,\u201d as Weatherby and Recht warn.<\/p>\n

Silicon sampling supercharges the trend by introducing biases of the AI models themselves. In a 2025 paper<\/a>, researchers from Northeastern University found that silicon sampling are \u201cgenerally not reliable substitutes for human respondents, especially in policy settings.\u201d<\/p>\n

\u201cThe models struggle to capture nuanced opinions and often stereotype groups due to training data bias and internal safety filters,\u201d the paper reads. \u201cTherefore, the most prudent approach is a hybrid pipeline that uses AI to improve research design while maintaining human samples as the gold standard for data.\u201d<\/p>\n

A separate paper<\/a> by University of Bern psychology postdoc Jamie Cummins, which has yet to be peer reviewed, found that generating \u201csilicon samples\u201d involves making \u201cmany analytic choices\u201d that could have a significant \u201cimpact on sample quality.\u201d<\/p>\n

Even a \u201csmall number of decisions can dramatically change the correspondence between silicon samples and human data,\u201d Cummins found.<\/p>\n

Despite these widespread concerns, Aaru,and other companies like it are raising hundreds of millions of dollars in funding, according to Weatherby and Recht, including partnerships with Stanford University<\/a> and public opinion poll heavyweight Gallup<\/a>.<\/p>\n

It\u2019s an alarming new trend, highlighting how AI tools continue to erode public trust by presenting often hallucinated fiction as fact. It\u2019s especially concerning given its potential to sway public opinion with polls based on AI slop, further entrenching the values of AI models that have long been found to suffer from inherent biases<\/a>.<\/p>\n

\u201cPure fictions are on the brink of being treated as scientific and political knowledge,\u201d Weatherby and Recht concluded in their essay. \u201cIf we do not pull back, our understanding of society might become artificial, too.\u201d<\/p>\n

More on AI slop:<\/strong> Wall Street Journal Editor-in-Chief Instructs Staff to Welcome AI Sloplords<\/em><\/a><\/p>\n

The post Foolish Pollsters Are Now Just Asking AI What Voters Would Say in Response to Questions and Publishing It at Face Value<\/a> appeared first on Futurism<\/a>.<\/p>\n<\/div>\n

<\/div>","protected":false},"excerpt":{"rendered":"

Last month, Axios was forced to issue a bizarre correction for a blog post about a growing maternal health crisis in the United States. The story quoted new poll findings…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[177,3841],"tags":[],"class_list":["post-10153","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-ethics"],"_links":{"self":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10153","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/comments?post=10153"}],"version-history":[{"count":0,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10153\/revisions"}],"wp:attachment":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/media?parent=10153"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/categories?post=10153"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/tags?post=10153"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}