{"id":13148,"date":"2023-04-03T07:32:21","date_gmt":"2023-04-03T05:32:21","guid":{"rendered":"https:\/\/humanfactors.uni-mainz.de\/?page_id=13148"},"modified":"2026-05-12T11:49:13","modified_gmt":"2026-05-12T09:49:13","slug":"home-department-of-human-factors-engineering-psychology","status":"publish","type":"page","link":"https:\/\/humanfactors.uni-mainz.de\/en\/","title":{"rendered":"Home Department of Human Factors & Engineering Psychology"},"content":{"rendered":"\n<\/jgu-base-pageheader>\n\n\n
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Welcome to the homepage of the Department of Human Factors and Engineering Psychology at Johannes Gutenberg University Mainz.<\/strong><\/p>\n\n\n\n

The Human Factors and Engineering Psychology department<\/strong> at Johannes Gutenberg University Mainz<\/strong> is headed by Prof. Dr. Johannes Kraus. We research the interaction between humans and modern technology<\/strong> – such as artificial intelligence, robotics, and automated vehicles – from a psychological perspective with an interdisciplinary approach.<\/p>\n\n\n\n

With our research, we want to contribute to a better understanding of the use of technology in various social contexts and to shaping it in a responsible manner. The focus is on the question of how technical systems can be developed in such a way that they take the abilities, needs, and limitations of humans into account as best as possible.<\/strong><\/p>\n\n\n\n

On our homepage, you will find information about our team, our research and teaching, as well as current projects and news.<\/p>\n\n\n\n

Please note that due to upcoming system updates, the display of the JGU websites on mobile devices may currently be limited. We therefore recommend using a laptop or tablet for a complete and correct display<\/strong>.<\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n<\/jgu-base-section>\n\n\n

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Human factors and engineering psychology are disciplines of applied psychology<\/strong>. The aim is to generate knowledge about how people interact with modern, intelligent technologies, process and understand information, learn about systems, and make decisions in collaboration. In addition to classic topics such as perception and cognition, the department investigates current issues relating to trust in AI, explainability of technical systems (explainable AI), accessibility, and the ethical and social implications of technological innovations.<\/p>\n\n\n\n

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