Dafna Burema obtained her BSc and MSc degrees in communication and media sciences at Erasmus University Rotterdam. She later pursued her PhD in sociology at the University of Bremen with a Marie Curie Fellowship, where she empirically constructed a definition and conceptual framework of social robots in elder care and analyzed the embedded biases towards older adults in the construction of such technologies. At SCIoI, she works with various academic and industry partners in the ETAMI network (Ethical and Trustworthy Artificial and Machine Intelligence) to create guidelines for ethical and trustworthy AI. In addition to AI and ethics, her research interests include; critical theory, STS, social robots, gerontechnology.
Artificial Intelligence: Examples of AI gone wrong and Ethical Questions
What to do when AI goes wrong and other important questions
In this lively debate, our researchers Dafna Burema, Jonas Frenkel from Science of Intelligence will talk about Artificial Intelligence and its ethical implications including examples of AI gone wrong. How do we imagine sustainable futures with robots? What are the open questions scientists face every day when dealing with Artificial Intelligence?
PUBLIC DISCUSSION AT THE CAMPUS. PLEASE REGISTER.
This event will take place as part of the Berlin Science Week CAMPUS‚. Admission is free. Please reserve your one or two-day ticket here.
Information about the physical accessibility of the Museum für Naturkunde can be found here. See ‚evolution in action‘ for exact location on the map.
Berlin, Berlin 10115 Germany
Jonas has a background in psychology and human factors. With a keen interest in the interplay between humans and machines, his research focuses on the field of human-robot interaction in general and social robotics in particular. Prior to joining SCIoI, he worked on developing robotic therapy scenarios for children with autism by using emotion-sensitive technology. At SCIoI, he is working on developing computational models of nonverbal social behaviors in order to improve our understanding of the underlying principles of social interactions and to eventually allow synthetic agents to perceive and appropriately react to social cues.