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Found 8 papers, 1 papers with code
Delete My Account: Impact of Data Deletion on Machine Learning Classifiers
Due to the lack of credible data on actual user behaviour, we make reasonable assumptions for various deletion modes and biases and provide insight into the effects of different plausible scenarios for right to erasure usage on data quality of machine learning.
Participatory Research as a Path to Community-Informed, Gender-Fair Machine Translation
Recent years have seen a strongly increased visibility of non-binary people in public discourse.
"Schöne neue Lieferkettenwelt": Workers' Voice und Arbeitsstandards in Zeiten algorithmischer Vorhersage
Wir beschreiben die technischen und kulturellen Bedingungen f\"ur algorithmische Vorhersage und erkl\"aren, wie diese -- aus Perspektive von Leitunternehmen -- bei der Bearbeitung beider Herausforderungen hilft.
"Es geht um Respekt, nicht um Technologie": Erkenntnisse aus einem Interessensgruppen-übergreifenden Workshop zu genderfairer Sprache und Sprachtechnologie
With the increasing attention non-binary people receive in Western societies, strategies of gender-fair language have started to move away from binary (only female/male) concepts of gender.
Wer ist schuld, wenn Algorithmen irren? Entscheidungsautomatisierung, Organisationen und Verantwortung
Im Folgenden m\"ochten wir einen \"Uberblick \"uber die wichtigsten Fragestellungen rund um ADS, Verantwortung und Entscheidungsfindung in organisationalen Kontexten geben und einige offene Fragen und Forschungsl\"ucken aufzeigen.
Towards Resilient Artificial Intelligence: Survey and Research Issues
Artificial intelligence (AI) systems are becoming critical components of today's IT landscapes.
$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers
For use with anonymisation techniques, the $k$-anonymity criterion is one of the most popular, with numerous scientific publications on different algorithms and metrics.
Anomaly Detection Support Using Process Classification
Anomaly detection systems need to consider a lot of information when scanning for anomalies.
