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Responsible AI & Dokumentation

Authors: Schulz, Konstantin;

Responsible AI & Dokumentation

Abstract

Diese Präsentation widmet sich der verantwortungsvollen Entwicklung und Dokumentation von KI-Systemen. Sie bietet einen Überblick über zentrale ethische Herausforderungen und deren Bedeutung in der Praxis. Unter Berücksichtigung aktueller Forschungsarbeiten werden Schlüsselthemen wie Werteorientierung bei Datensätzen, Bias-Erkennung sowie die Integration ethischer Normen im Entwicklungsprozess beleuchtet. Ergänzt wird dies durch Ansätze wie das "Red Teaming" von Sprachmodellen, um potenzielle Schwachstellen offenzulegen. Ein weiterer Fokus liegt auf den Anforderungen an die Dokumentation von KI-Systemen gemäß EU AI Act, einschließlich Aspekten wie Transparenz, menschlicher Aufsicht, Cybersicherheit und Risikoanalyse. Die Präsentation veranschaulicht auch die Initiativen der Humboldt-Universität zu Berlin, darunter Leitlinien zur Nutzung generativer KI in Forschung und Lehre sowie deren Einbettung in eine breite Governance-Strategie. Abschließend werden praktische Instrumente wie Model Cards und Data Statements vorgestellt, die die strukturierte Dokumentation von KI-Systemen fördern. Diese Ansätze bieten eine Grundlage für ethisch und technisch fundierte KI-Lösungen und unterstützen die Schaffung eines öffentlichen Transparenzstandards, wie er in Städten wie Helsinki und Amsterdam umgesetzt wird.

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Keywords

Artificial intelligence, Artificial Intelligence, Natural language processing, Natural Language Processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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