Catholijn M. Jonker

Catholijn Jonker (1967) is full professor of Interactive Intelligence at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology. Jonker studied computer science, and did her PhD studies at Utrecht University. After a post-doc position in Bern, Switzerland, she became assistant (later associate) professor at the Department of Artificial Intelligence of the Vrije Universiteit Amsterdam. From September 2004 until September 2006 she was a full professor of Artificial Intelligence / Cognitive Science at the Nijmegen Institute of Cognition and Information of the Radboud University Nijmegen. She chaired De Jonge Akademie (Young Academy) of the KNAW (The Royal Netherlands Society of Arts and Sciences) in 2005 and 2006, and she was a member of the same organization from 2005 to 2010. She is a member of the Koninklijke Hollandsche Maarschappij der Wetenschappen andof the Academia Europaea. She was the president of the National Network Female Professors (LNVH) in The Netherlands from September 2013 till January 2016. She served TU Delft for one year as interim head of department for the Design Engineering Department (2014/2015). Catholijn is EurAI Fellow since 2015, and EurAI board member since 2016, EurAI is the European Association for Artificial Intelligence.

Her publications address cognitive processes and concepts such as negotiation, teamwork and the dynamics of individual agents and organizations. In all her research lines Catholijn has adopted a value-sensitive approach. In particular, she works towards intelligent agents that can interact with their users in value-conflicting situations when also meta-values no longer solve the situation.  In Delft she works with an interdisciplinary team to create synergy between humans and technology by understanding, shaping and using fundamentals of intelligence and interaction. End 2007 her NWO-STW 1.5 M€ VICI project “Pocket Negotiator” has been awarded. In this project she develops intelligent decision support systems for negotiation. An experimental version of the Pocket Negotiator can be found at:http://ii.tudelft.nl/negotiation/index.php/Pocket_Negotiator.

30 January 2023

Grote vragen: aflevering 4: hoe kunnen we zelflerende kunstmatige intelligentie in toom houden?

Grote vragen: aflevering 4: hoe kunnen we zelflerende kunstmatige intelligentie in toom houden?

Hoe maken we optimaal gebruik van de mogelijkheden van zelflerende kunstmatige intelligentie zonder de controle te verliezen? Volgens hoogleraar kunstmatige intelligentie Catholijn Jonker kan dit alleen als mens en machine beter samenwerken.

14 December 2022

This is how AI explains it well

This is how AI explains it well

We are proud to see Dr. Jasper van der Waa publish this article for IT professionals. If you are interested in following up on this research, please reach out to either Jasper himself, Catholijn Jonker (TUD), Jurriaan van Diggelen (TNO), or Mark Neerincx (TUD / TNO).

05 December 2022

Self-Reflective Hybrid Intelligence: Combining Human with Artificial Intelligence and Logic

Self-Reflective Hybrid Intelligence: Combining Human with Artificial Intelligence and Logic

At the IC3K 2022 conference in Malta last October, Prof. dr. Catholijn Jonker gave a presentation about creating forms of human-AI intelligence.

04 October 2022

Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid

Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid

People seem to hold the human driver to be primarily responsible when their partially automated vehicle crashes. But is this reasonable? Researchers Niek Beckers, Luciano Cavalcante Siebert, Merijn Bruijnes, Catholijn Jonker & David Abbink from the AiTech initiative investigated the apparent mismatch between the public’s attribution of blame and finding from the human factors literature regarding human’s ability to remain vigilant in partially automated driving.

30 September 2022

Drivers of automated vehicles are blamed for crashes that they cannot reasonably avoid

Drivers of automated vehicles are blamed for crashes that they cannot reasonably avoid