JADS – KPN Responsible AI-lab (ICAI)

Facilitating responsible AI

The upsurge in AI and machine learning technologies offers an enormous potential to develop predictive tools for industry. In contrast to traditional machine learning, novel representation-learning algorithms (e.g., deep learning) result in breakthrough performances in a wide variety of domains, including natural language processing, image processing, signal processing, and data processing.

The overall objective of the lab is to facilitate the use of modern AI technology by the industry in a responsible way. To achieve this goal, an interdisciplinary team of experts affiliated to JADS collaborates with KPN to develop solutions that exploit the power of AI to create value from data.

The Challenge

The goal of the Responsible AI Lab is to develop transparent, privacy aware, and personalized AI solutions for businesses.

What we did

For five years, six PhD students work in the lab on projects contributing to the technical and legal aspects of transparency, on data engineering approaches that ensure privacy-by-design, on personalized and responsible offerings through text analytics and responsible up-lift modelling.

The outcome

The result of the responsible AI Lab will be new valuable scientific insights in topics, for example, how to deal with privacy and transparency. How to better make use of streaming data in a data service hub and how to achieve accurate personalized offerings.

More information

JADS & KPN launch responsible AI Lab: Using AI in a Responsible Way (press release)

ICAI is joining forces with leading Dutch telecommunications and IT provider KPN and Jheronimus Academy of Data Science (JADS), for the launch of a new public-private research lab. The KPN Responsible AI Lab will focus on developing technologies that allow Artificial Intelligence (AI) to be used in a responsible way.


Find out more about funding PhD research at JADS

Various PhD research projects are active within JADS. A project with a PhD regularly has a duration of 4 years and is a long term commitment in valuable research. Because of our focus on 'impact in practice', we focus every year in a PhD process on the completion of a sub-question.

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