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    <title>Predicting Real-World Achievement from Open-Source Intelligence | Kris Yotam</title>
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    <meta name="description" content="Explores whether online public outputs (code, writing, competition rankings) can serve as better predictors of intelligence and talent than traditional IQ tests.">
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    <h1 class="acad-title">Predicting Real-World Achievement from Open-Source Intelligence</h1>
    <div class="acad-meta">2025-07-04 &middot; <a href="../../papers.html">psychology</a> &middot; <span class="status-rough">rough</span></div>
    <fieldset class="wrap abstract"><legend>abstract</legend>Explores whether online public outputs (code, writing, competition rankings) can serve as better predictors of intelligence and talent than traditional IQ tests.</fieldset>
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<h2>Idea</h2>
<p>This paper explores whether public online outputs (code quality, writing style, productivity, originality) can act as better predictors of intelligence or real-world ability than legacy measures like GPA or IQ scores. You’ll analyze open-source work, blog posts, portfolios, or contest results and correlate them with proxies of success or domain expertise. The paper challenges the conventional gatekeepers of intelligence assessment and raises questions about how we identify potential in the 21st century.</p>
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