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      <datestamp>2023-11-10T11:42:54Z</datestamp>
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        <dc:identifier>https://verfassungsblog.de/we-dont-need-no-education/</dc:identifier>
        <dc:title>We Don’t Need No Education? - Teaching Rules to Large Language Models through Hybrid Speech Governance</dc:title>
        <dc:creator>Schulz, Wolfgang</dc:creator>
        <dc:creator>Ollig, Christian</dc:creator>
        <dc:language>eng</dc:language>
        <dc:date>2023-11-09</dc:date>
        <dc:type>electronic resource</dc:type>
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        <dc:subject>ddc:342</dc:subject>
        <dc:subject>AIA</dc:subject>
        <dc:subject>DSA</dc:subject>
        <dc:subject>generative AI</dc:subject>
        <dc:subject>large generative ai models</dc:subject>
        <dc:subject>llm</dc:subject>
        <dc:subject>speech governance</dc:subject>
        <dc:publisher>Verfassungsblog</dc:publisher>
        <dc:relation>Verfassungsblog--2366-7044</dc:relation>
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        <dc:description>Artificial Intelligence doesn't know what's 'true'. Especially, generative AI models like chatbots veer from the truth, i.e. “hallucinate”, quite regularly. Chatbots simply invent information at least 3 percent of the time and sometimes as high as 27 percent. Given the (future) use of such systems in nearly all domains, we might want such systems to follow more stringent rules of accuracy. And those truth-related rules are not the only rules for AI systems that warrant societal scrutiny. How those systems are trained will be crucial. In this blog post, we argue that a new perspective is key to tackle this challenge: “Hybrid Speech Governance”.</dc:description>
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