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240412 ||| eng |
| 020 |
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|a 9789264420359
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| 020 |
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|a 9789264824294
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| 020 |
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|a 9789264817326
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| 245 |
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|a AI and the Future of Skills, Volume 2
|h Elektronische Ressource
|b Methods for Evaluating AI Capabilities
|c Organisation for Economic Co-operation and Development
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| 260 |
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|a Paris
|b OECD Publishing
|c 2023
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| 300 |
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|a 180 p.
|c 21 x 28cm
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| 505 |
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|a Assessing AI capabilities on occupational tests -- Eliciting expert knowledge: Methods and challenges -- -- Foreword -- Executive summary -- AI direct tests: LNE and NIST evaluations -- -- Project goals, constraints and next steps -- A framework for characterising evaluation instruments of AI performance -- Assessing AI capabilities with education tests -- Overview -- -- Towards a synthesis of language capability in humans and AI -- Occupational tests --
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| 653 |
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|a Education
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| 710 |
2 |
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|a Organisation for Economic Co-operation and Development
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OECD
|a OECD Books and Papers
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| 490 |
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|a Educational Research and Innovation
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| 024 |
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|a /10.1787/a9fe53cb-en
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| 856 |
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|a oecd-ilibrary.org
|u https://doi.org/10.1787/a9fe53cb-en
|x Verlag
|3 Volltext
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|a 370
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| 520 |
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|a As artificial intelligence (AI) expands its scope of applications across society, understanding its impact becomes increasingly critical. The OECD's AI and the Future of Skills (AIFS) project is developing a comprehensive framework for regularly measuring AI capabilities and comparing them to human skills. The resulting AI indicators should help policymakers anticipate AI's impacts on education and work. This volume describes the second phase of the project: exploring three different approaches to assessing AI. First, the project explored the use of education tests for the assessment by asking computer experts to evaluate AI's performance on OECD's tests in reading, mathematics and science. Second, the project extended the rating of AI capabilities to tests used to certify workers for occupations. These tests present complex practical tasks and are potentially useful for understanding the application of AI in the workplace. Third, the project explored measures from direct AI evaluations. It commissioned experts to develop methods for selecting high-quality direct measures, categorising them according to AI capabilities and systematising them into single indicators. The report discusses the advantages and challenges in using these approaches and describes how they will be integrated into developing indicators of AI capabilities
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