Meta-scientific research examines the research process itself and pursues the goal of initiating developments that enhance the quality of research. We observe and describe developments within the field of psychology. In empirical studies, we investigate, for example, how the availability of research data changes over time and which boundary conditions are responsible for this. We derive concrete recommendations for action from our meta-scientific research.

Contact:
Prof. Dr. Markus Huff

In this project, we investigate how humans perceive the risks of Artificial Intelligence (AI) and how their risk assessments are associated with psychological factors like prior knowledge and judgmental confidence. The behavioral consequences of risk perception are investigated, as well as intervention methods aimed at raising an awareness of AI risks.

In this project, we investigate how insight into ones’ own cognition relates to information selection and processing, as well as opinion and judgment formation.
The main goal of this project is to gain a better understanding about the influence of metacognition regarding information selection (e.g., media choice), information processing (e.g., polarization), and action (information propagation in social media). Leveraging methods from Signal Detection Theory, the role of metacognitive insight will be investigated with regard to belief propagation, formation and polarization, as well as the evaluation of new information like whether or not people deem information from different sources as trustworthy.

Contacts:
Dr. Nadia Said
Prof. Dr. Markus Huff

Collaboration partners:
Dr. Helen Fischer (Max Planck Institute for Human Development, Berlin)
Prof. Dr. Patrick Müller (Stuttgart Technology University of Applied Sciences, Economic Psychology)
Prof. Dr. Marc-André Reinhard (University of Kassel, Psychology)
Sarah Volz (University of Kassel, Psychology)

Further information:
IWM project page

As the world becomes technologcally increasingly advanced, the presence of artificial agents in day-to-day life also becomes more apparent. To expand our research possibilities on the topic, we are in the process of setting up a robot interaction lab together with the Leibniz-Institut für Wissensmedien (IWM). We will be using Pepper , a social robot, which can identify emotions based on facial and vocal cues. Our interest lies in descipehring and understanding the human – robot dynamics occuring in interaction. While the research field of human robot interaction is frequently focused on how artificial agents can improve our lives, we aim at fillping the focus on how humans can help robots. We seek to use our modern robot interaction lab to comprehend the conditions under which people show prosocial behaviour towards artificial agents, including robots.

Spatial configurations are an important part of the organization of visual working memory. Even when asking observers to encode multiple object locations independently, for example, they also automatically process and encode the spatial configuration of those objects. With this project, we contribute to the theoretical understanding of how spatial configurations are processed within visual working memory. Thereby, this project tries to expand our understanding of the structure of visual working memory. This project focuses on the following two research questions: a.) Can spatial configurations be updated during active memorization? b) Is there a common mechanism driving the configuration and context effects that were observed in multiple paradigms by previous research?

This project is funded by the Deutsche Forschungsgemeinschaft (DFG): gepris.dfg.de/gepris/projekt/357136437

How do human observers comprehend their dynamic environment, such as when watching sport broadcasts on television, movies, or natural actions? Instead of processing all information presented in this constant stream of information equally, observers segment the information stream into meaningful units, the so called events. In this project, we study how human observer construct event models of their dynamic environment and how they update these event models during the observation of dynamic scenes. Furthermore, we investigate the consequences of event model construction on human perception, such as the illusory perception of information that was actually missing in the dynamic environment.

Contact:
Prof. Dr. Markus Huff

Collaboration partners:
Dr. Frank Papenmeier
Julian Sittel, M.A.