SCIENCE MAGAZINE SOCIETYBYTE

We are a science magazine of Bern University of Applied Sciences and focus on digital transformation with the human being at the centre. We publish scientific articles and interviews about research projects, results and studies by our scientists, our partners and researchers from related organisations. We connect science and practice, whereby administration and politics are just as much a part of practice for us as the economy.

On the blind spots of AI – from discrimination to technological responsibility

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The relationship between AI and societal diversity is intricate. BFH-researcher Mascha Kurpicz-Briki probes this in her interview with AI luminary…

How to balance privacy and informativeness 

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Privacy is a fundamental ethical requirement in data usage. Protecting privacy means safeguarding the rights and freedoms of data subjects. But…
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How neuromonitoring can prevent post-operative brain damage

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Analysing signal data in intraoperative neuromonitoring using machine learning - Simon Koller won over the jury at the DMEA in Berlin with this…
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Shadow IT and Accidental Servitization

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In the labyrinth of modern business shadow IT and accidental servitization lurk like shape-shifting monsters, transforming helpful tools into…

How digitalisation is affecting local taxi companies

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The taxi industry has been particularly affected by digitalisation in recent years. Whereas previously you had to look for free taxis on the…

Data ethics: balance between innovations and responsibility

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POSMO, as an ethical data market, prioritizes the protection of rights and freedoms of its data producers. Accordingly, the ethical principles…

How BFH promotes digital skills among students

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BFH has been offering the "Digital Skills Coaching" (DSC) initiative for a year now. BFH students act as coaches and pass on their knowledge…
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Federated Learning: The Future of AI Without Compromising Privacy

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Federated Learning (FL) has become a paradigm-shifting technology in AI, allowing data scientists to work with private data. In comparison to…
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Fairness and Bias in AI Applications for the Labor Market

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For the 2024 Applied Machine Learning Days (AMLD) conference held at EPFL, the BFH Applied Machine Intelligence group and NLP expert Dr. Elena…
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