The KPN Responsible AI Lab centers its research on one core theme: privacy-aware and personalized AI for improved services; data science, decision-making, privacy, and compliance.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
With a commitment to responsible AI systems.
The KPN Responsible AI Lab is dedicated to developing technologies that allow Artificial Intelligence to be used in a responsible way.
The lab’s mission and vision are to to develop transparent, privacy-aware, and personalized AI solutions for businesses that address topics of the KIA ICT roadmap.
The impact of the lab lies in projects contributing to the technical and legal aspects of transparency on AI, data engineering approaches that ensure privacy by design, personalized, and responsible offerings through text analytics, and responsible up-lift modeling.
Transparency of machine learning: technical aspects – Focuses on developing algorithms that convert complex machine learning models into transparent, user-friendly representations to improve human understanding and trust.
Transparency of machine learning: legal aspects – Investigates the legal and functional obligations, such as those arising from the GDPR, for providing honest and understandable explanations of complex AI-driven decisions.
AI and data engineering for privacy – Establish privacy-by-design in telecommunications by creating AI-based anonymization techniques that strip privacy-sensitive information from valuable data sources.
Uplift modeling: Optimizing personalized offering – Aims to use Bayesian AI methods on observational data to responsibly predict which customers will respond best to targeted marketing treatments.
Personalized AI for Dutch text analytics – Seeks to improve Dutch Natural Language Processing (NLP) performance by augmenting deep learning models with individual behavioral and demographic data to account for user differences.
Streaming data in business – Explores the optimal configurations of technology, business models, and organizational strategies required for a business to successfully transition to a dynamic infrastructure utilizing streaming data.
KPN is a leading telecommunication and IT provider and market leader in the Netherlands, serving both consumer and business customers with its fixed and mobile networks for telephony, broadband, and television.
Jheronimus Academy of Data Science (JADS) is a unique concept in the Netherlands. At three different locations, the study, research and application of data science is combined in bachelor, master and EngD programs, Data Science research centers and existing ecosystems.
HU University of Applied Sciences Utrecht sees opportunities where different disciplines and viewpoints intersect. In our ever-changing world, we are faced with challenges in health, technology, safety, climate and sustainability.
