{"id":6649,"date":"2025-11-12T14:18:07","date_gmt":"2025-11-12T14:18:07","guid":{"rendered":"https:\/\/musictechohio.online\/site\/ai-turing-language-spam\/"},"modified":"2025-11-12T14:18:07","modified_gmt":"2025-11-12T14:18:07","slug":"ai-turing-language-spam","status":"publish","type":"post","link":"https:\/\/musictechohio.online\/site\/ai-turing-language-spam\/","title":{"rendered":"AI Is Failing at the Most Hilarious Task Imaginable"},"content":{"rendered":"
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With so many puff pieces out there about what AI can do, it\u2019s rare to see a story about what it can\u2019t <\/em>do. And as some researchers tell it, AI is falling terribly short at what many of us find to be one of the easiest tasks of all: getting into arguments on social media.<\/p>\n

First spotted by Ars Technica<\/em><\/a>, a team of researchers from Switzerland, the Netherlands, and the US recently released a paper<\/a> analyzing social media posts generated by large language models (LLMs).<\/p>\n

To conduct the yet-to-be-peer-reviewed study, the researches applied what they call a \u201ccomputational Turing test\u201d to posts LLMs on X-formerly-Twitter, Reddit, and Bluesky. They found that posts generated by AI bots \u2014 all open-weight models, ranging from DeepSeek to Qwen \u2014 were all \u201creadily distinguishable\u201d from ones by human users with a 70-80 percent accuracy rate, which is \u201cwell above [the threshold for] chance.\u201d<\/p>\n

In other words, it\u2019s laughably easy to catch an AI shitposter in the act by applying a one-size-fits-all screening to any text it spits out \u2014 let alone by using a little basic human judgement<\/a>.<\/p>\n

One of the major reasons for this, the scholars posit, is that AI can only mimic a human\u2019s emotional depth, what we might call the \u201cheat of the moment\u201d vitriol of a typical flame war. When we get into it, we really<\/em> get into it, with a level of both \u201ctoxicity\u201d and \u201csentiment\u201d that remain unmistakably human.<\/p>\n

\u201cEven after calibration, LLM outputs remain clearly distinguishable from human text, particularly in affective tone and emotional expression,\u201d the team wrote. <\/p>\n

Interestingly, they found that an LLM\u2019s size and complexity didn\u2019t necessarily correlate to more realistic vitriol. For example, \u201cthe large Llama-3.1-70B performs on par with, or even below, smaller models,\u201d the researchers wrote. \u201cThis suggests that scaling does not translate into more authentically human communication.\u201d<\/p>\n

The findings are particularly ironic given that one of AI\u2019s most prominent use-cases at the moment seems to be spamming social media<\/a>, particularly the well-trafficked platforms of X-formerly-Twitter<\/a>, Facebook<\/a>, and Instagram<\/a> (though other sites, like Reddit<\/a>, are also being overrun.)<\/p>\n

Even the wannabe tech CEOs are getting on board, with startups like Doublespeed offering clients access to an AI-powered bot army<\/a> tailored to their advertising needs.<\/p>\n

In a way, the paper\u2019s findings are good news for anyone worried about the rate at which AI was becoming indistinguishable \u2014 though something tells us it won\u2019t make much of a difference as AI bros continue to flood the internet<\/a> with algorithmic slop.<\/p>\n

More on AI: <\/strong>Scientists Created an Entire Social Network Where Every User Is a Bot, and Something Wild Happened
<\/a><\/em><\/p>\n

The post AI Is Failing at the Most Hilarious Task Imaginable<\/a> appeared first on Futurism<\/a>.<\/p>\n<\/div>\n

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With so many puff pieces out there about what AI can do, it\u2019s rare to see a story about what it can\u2019t do. And as some researchers tell it, AI…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[177,3841,3842,3885],"tags":[],"class_list":["post-6649","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-ethics","category-future-society","category-machine-learning"],"_links":{"self":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/6649","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=6649"}],"version-history":[{"count":0,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/6649\/revisions"}],"wp:attachment":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/media?parent=6649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/categories?post=6649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/tags?post=6649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}