Myrthe Tielman

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AI*MAN Lab: Transparent & Traceable AI in Human-AI Teamwork (2020- )

In this interdisciplinary research line, in which the faculties of AE (Control and Simulation Section) and EEMCS (Intelligent Systems Department) cooperate, we will focus on human-AI teamwork. The main challenges of human-AI teamwork include obtaining mutual understanding among the teammates while making optimal decisions to realize the team's global objectives. We will integrate various methods from control theory with knowledge-based methods from AI. This way we will combine the strengths of control theory in making adaptive and optimal decisions with the strengths of knowledge-based AI in context modeling and transparency.


Modelling Trust (2020-)

AI systems are increasingly involved in decision making, either supporting people or autonomously. This also means that how much we trust these systems becomes increasingly important. Our trust in AI should be appropriate, not to much, and not too little. For any system to calibrate trust to be appropriate, it first needs to understand what trust is. In this project, we look at how we can formally capture trust and reason with it from an AI perspective, but also at how well these formalisms capture actual trust in human-AI interactions.


Hybrid Intelligence (2020-)

Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values. Our goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the centre, changing the course of the ongoing AI revolution.


VESP (2013-2017)

The Virtual E-coaching and Storytelling technology for Post-traumatic stress disorder (VESP) project looked at a home-therapy for PTSD patients where they can follow therapy at home. As this is challenging, we studied how a virtual agent could assist and motivate PTSD patients during therapy. The main focus lay on how the possibilities of the software can be used to provide personalized support and motivation.


Aliz-e (2012-2013)

The Aliz-e project concerned a robot as companion and teacher for children with diabetes. In this project, I studied how emotional engagement could be modeled in the robot to support the interaction between robot and child.