Artificial intelligence and robots are in the fast lane, providing many opportunities for humanity that range from improving medical diagnoses, enabling seniors to be more independent, to house cleaning and better energy efficiency. In public discourse, however, smart technologies are often represented by stereotypical images of an android robot, meaning the artificial replication of a human being. Research on the uncanny valley phenomenon indicates that a depiction of this kind of machine makes many people feel particularly unsettled and is even considered threatening. Based on empirical findings, Mara argues that a human-centered approach towards AI and robotics should foster new visions of complementary human-machine relationships instead of fueling fears of being substituted. Furthermore, as many outside of the expert circles continue to lack information regarding technical functions and are uncomfortable with technology they do not understand, a human-centered approach would serve to demystify AI and robotics by explaining basic technological concepts to the public and designing machines that can explain themselves.   

Univ. Prof. Dr. Martina Mara LIT Robopsychology Lab

Manufacturing companies continue to face major challenges such as shortened product life-cycles, increased product variability and global markets that are becoming progressively more volatile. In order to remain competitive, production equipment and production facilities need to be more adaptable, allowing for quick and efficient adjustment to these changes. Over the past few years, attempts in these directions have been compiled under the term Industry 4.0. Control equipment is a key factor to successfully achieve these goals. New, distributed architectures are considered to be a potential approach to master the new requirements. However, these changes require new interaction and communication patterns as well as new ways to control devices and programming systems built from networked control devices. This presentation will introduce initial findings on how to attain this kind of flexibility while simultaneous keeping the complexity in these architectures under control.
 

Univ. Prof. Dr. Alois Zoitl, LIT – Cyber-Physical Systems Lab