Augmented Intelligence

While the technologies surrounding artificial intelligence (AI) and robotics were often seen as an opportunity to completely replace tasks performed by humans, it has turned out that this is often not at all expedient. Humans and machines have different characteristics: while computers are good at evaluating large amounts of data within a short time, they lack the ability to reflect on decisions. We therefore speak of Augmented Intelligence, which complements humans and supports them in their daily work, and does not replace them. We address the questions of how humans and AI/robots can work together efficiently, and how their respective capabilities can complement each other. In addition, we address issues of fairness and inclusion. Methods are being developed to prevent parts of the digital society from being excluded or discriminated against based on automated decisions.

All articles on Augmented Intelligence

Machine Learning , Artificial Intelligence, Ai, Deep Learning Bl

Transfer Learning: Making use of what is already there

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As the number of AI models grows, it becomes clear that many new applications share similarities with existing ones. Transfer learning and domain…
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Learning-to-be-Green: Focus on sustainability and digital transformation

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Can green entrepreneurship be learnt more effectively with the help of chatbots? What do innovative, digital teaching and learning scenarios…
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Empowering workers: A human-centered approach to robotic automation

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Automation can do more than just take over routine tasks – it has the potential to empower production workers. In an SNF project, researchers…
Kann uns Künstliche Intelligenz beim Klimaschutz helfen?

Can artificial intelligence help us protect the climate?

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Artificial intelligence (AI) promises to transform the economy and society and thus contribute to climate protection. However, despite over ten…

Bias in Language Models and Data Augmentation for AI in Mental Health

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Are societal stereotypes encoded in German language models, and how can data augmentation techniques support classification task in the context…
Deepfake Keyvisual Ta Studie

Deepfakes and manipulated reality – a study by TA-Swiss

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Artificial intelligence (AI) can generate and modify images, videos and sound recordings. It is already impossible to imagine the digital world…
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How the Brändi-GPT enables barrier-free access to information

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We usually use artificial intelligence and chatbots as a matter of course, for example to obtain information. However, access to information…

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…
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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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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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“We seek a relationship in every interaction – even with AI”

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AI is already present in many areas, even if this is not always obvious. Awareness of this is particularly important in sensitive contexts such…