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LIT Robopsychology Lab
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Our work at the LIT Robopsychology Lab is based on the following methodical approach and under the following guidelines:

Quantitative Psychology as a Foundation

As a rule, our research projects are based on methods and statistical analysis procedures of empirical psychology and quantitative social sciences. In general, we are interested in the cause-and-effect relationships and ultimately in causality testing research designs. We conduct empirical surveys both in laboratory settings (with the advantage of better controllability), and in the field (the advantage of better external validity).

Fostering an Interdisciplinary Approach

Future-oriented and human-centered technology research requires diverse approaches, skills, and perspectives. In the area of education, we are committed to building bridges between technical-scientific and human-social-scientific degree programs. In the area of research, we work together with experts stemming from a wide variety of backgrounds, ranging from robotics and philosophy to game design and art.

An Open Mind for Innovative Methods

We are open to exploring new approaches in education and research. In cooperation with experts in computer sciences, for example, we combine social science survey methods with analysis methods in machine learning and text mining. During early stages of research in particular, meaning as part of hypothesis development, we also rely on qualitative methods and participative approaches in User-Centered Design and Citizen Science.

The Importance for Society and Real-World Practices

When it comes to university research ("the Third Mission"), creating usable knowledge is an important task. Our research findings aim to strengthen social discourse and serve those who becoming increasingly confronted with robots and AI systems.Practice-oriented experts benefit from empirically based guidelines regarding the technology design, and with our work we would like to contribute to the development of these guidelines.

The LIT Robopsychology Lab investigates how the interaction of different influencing factors affects the individual experiencing of intelligent machines and the interaction with them. User-specific factors (e.g. age, personality factors, technical experience) as well as robot-specific factors (visual form, behavioral and communication design) and contextual factors (area of application, prior information, media reporting) are considered. ©LIT Robopsychology Lab