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Patient safety: the need for an open and fair culture [PDF]
Intermittent failures of healthcare delivery culminating in patient safety incidents are an international problem. Collecting information on incidents and where necessary analysing causes allows problems to be identified which, when resolved, can prevent future errors and incidents.
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The Open-Radio Access Network (O-RAN) alliance is leading the evolution of telecommunications towards a greater intelligence, openness, virtualization, and interoperability within mobile networks.
Jing Ren Sue +2 more
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FAIR and Open Computer Science Research Software
22 ...
Wilhelm Hasselbring +4 more
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Recent advances in generative AI have raised public awareness, shaping expectations and concerns about their societal implications. Central to these debates is the question of AI alignment—how well AI systems meet public expectations regarding safety ...
Andreas Jungherr, Adrian Rauchfleisch
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This study analyzes 194,151 tweets from the 2021 German federal election using sentiment analysis and statistical techniques to examine social media’s role in shaping group emotions, voters’ emotional expression and derogatory speech toward candidates ...
Yixuan Zhang +3 more
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Digital transformation in human resource department (HRD) within performance appraisal process is initiated from employee management and supported by the commitment of leaders to create aspects of openness and fairness. In this context, PT.
Alexander Wirapraja +2 more
doaj
Am 14./15. Mai fand in Göttingen das 3. von open-access.network organisierte Open Access Barcamp statt. In einer Session wurde die Frage diskutiert, was Bibliotheken tun können, um Fair Open Access zu fördern. Der folgende Blogbeitrag knüpft an diesen Austausch in einer Gruppe von ca. 20 Personen an.
Sarah Dellmann, Michaela Voigt
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Exploring Fairness Interventions in Open Source Projects
The deployment of biased machine learning (ML) models has resulted in adverse effects in crucial sectors such as criminal justice and healthcare. To address these challenges, a diverse range of machine learning fairness interventions have been developed, aiming to mitigate bias and promote the creation of more equitable models.
Sadia Afrin Mim +3 more
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