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Philipp Lerch, All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation, 14 (2023) JIPITEC 108 para 1.
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%0 Journal Article %T All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation %A Lerch, Philipp %J JIPITEC %D 2023 %V 14 %N 1 %@ 2190-3387 %F lerch2023 %X The term “Artificial Intelligence” comprises different approaches. They can be roughly divided into rule-based approaches and approximative machine learning. The author discusses the legal implications of this technological choice on the background of Product Liability law. It stands to reason that using rule-based approaches may be prone to stricter safety standards than approximative. %L 340 %K Artifical Intelligence %K Product Liability %K Product Security %U http://nbn-resolving.de/urn:nbn:de:0009-29-57114 %P 108-NoneDownload
Bibtex
@Article{lerch2023,
author = "Lerch, Philipp",
title = "All Agents Created Equal? The Law's Technical Neutrality on AI Knowledge Representation",
journal = "JIPITEC",
year = "2023",
volume = "14",
number = "1",
pages = "108--None",
keywords = "Artifical Intelligence; Product Liability; Product Security",
abstract = "The term ``Artificial Intelligence'' comprises different approaches. They can be roughly divided into rule-based approaches and approximative machine learning. The author discusses the legal implications of this technological choice on the background of Product Liability law. It stands to reason that using rule-based approaches may be prone to stricter safety standards than approximative.",
issn = "2190-3387",
url = "http://nbn-resolving.de/urn:nbn:de:0009-29-57114"
}
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TY - JOUR AU - Lerch, Philipp PY - 2023 DA - 2023// TI - All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation JO - JIPITEC SP - 108 EP - None VL - 14 IS - 1 KW - Artifical Intelligence KW - Product Liability KW - Product Security AB - The term “Artificial Intelligence” comprises different approaches. They can be roughly divided into rule-based approaches and approximative machine learning. The author discusses the legal implications of this technological choice on the background of Product Liability law. It stands to reason that using rule-based approaches may be prone to stricter safety standards than approximative. SN - 2190-3387 UR - http://nbn-resolving.de/urn:nbn:de:0009-29-57114 ID - lerch2023 ER -Download
Wordbib
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ISI
PT Journal AU Lerch, P TI All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation SO JIPITEC PY 2023 BP 108 EP None VL 14 IS 1 DE Artifical Intelligence; Product Liability; Product Security AB The term “Artificial Intelligence” comprises different approaches. They can be roughly divided into rule-based approaches and approximative machine learning. The author discusses the legal implications of this technological choice on the background of Product Liability law. It stands to reason that using rule-based approaches may be prone to stricter safety standards than approximative. ERDownload
Mods
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<titleInfo>
<title>All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation</title>
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<topic>Artifical Intelligence</topic>
<topic>Product Liability</topic>
<topic>Product Security</topic>
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Full Metadata
| Bibliographic Citation | Journal of intellectual property, information technology and electronic commerce law 14 (2023) 1 |
|---|---|
| Title |
All Agents Created Equal? The Law’s Technical Neutrality on AI Knowledge Representation (eng) |
| Author | Philipp Lerch |
| Language | eng |
| Abstract | The term “Artificial Intelligence” comprises different approaches. They can be roughly divided into rule-based approaches and approximative machine learning. The author discusses the legal implications of this technological choice on the background of Product Liability law. It stands to reason that using rule-based approaches may be prone to stricter safety standards than approximative. |
| Subject | Artifical Intelligence, Product Liability, Product Security |
| DDC | 340 |
| Rights | DPPL |
| URN: | urn:nbn:de:0009-29-57114 |
