On May 5th 2022, DRESDEN-concept, Deutsches Hygiene-Museum Dresden and ScaDS.AI Dresden/Leipzig welcomed researchers, students and interested citizens to a Science Café with the topic Artificial Intelligence.
Program and discussion groups
A total of 90 participants discussed the role of AI in various areas of our everyday lives, for example in traffic, education or medicine and nursing. After a short introduction by Dr. Uta Bilow, group leader for Science Communication at the Institute for Nuclear and Particle Physics (IKTP) at TU Dresden, the participants each entered one of the individual discussion groups:
- XAI (Explainable AI): Can we really understand AI?
(Prof. Dr. Dietrich Kammer | Moderation: Dr. Peter Steinbach)
- Autonomously on the road? AI in road traffic
(Prof. Dr. Ostap Okhrin, Pia Hanfeld | Moderation: Prof. Dr. Pascal Kerschke)
- When the apartment thinks for itself: Curse or blessing?
(Mathias Klingner| Moderation: Romy Conrad)
- Data everywhere? Living in intelligent environments
(Joshwa Pohlmann | Moderation: Steffi Huiqing Hu)
- AI and medicine 1: Disease prevention through the use of AI?
(Miriam Goldammer, Alexander Hammer| Moderation: Suraka Al Baradan)
- AI and medicine 2: AI and robotics: The new doctors?
(Dr. Sebastian Bodenstedt, Moderation: Lena Jurkschat)
- AI and robotics in nursing: Machines and algorithms as helpers?
(Frank Bahrmann | Moderation: Dr. René Jäkel)
- Better learning with AI? AI in education
(Prof. Dr. Anke Langner | Moderation: Dr. Iryna Okhrin)
The first round of discussions was followed by a short break. The participants were able to use this break to familiarize themselves with the demonstrators as well as for networking. Afterwards there was a second round of talks. Therefore each participant was able to join two discussion groups, which consisted of one to two researchers, one moderator and up to ten interested citizens. Each discussion lasted for about 30 minutes.
The data experiment
Another highlight of the evening was the implementation of a short data experiment. Dr. Peter Steinbach collected data in form of height, weight and shoe size from the participants of the Science Café. Using this data, he was able to make accurate predictions about the shoe size of people who only knew their height and weight. Afterwards, Dr. Steinbach manipulated the data set and removed all data on women. The prediction now was highly inaccurate. With his experiment Dr. Steinbach was able to show the importance of the quality of a data set for AI applications and what it means to speak of a bias in relation to data.
We want to thank all researchers, moderators and participants for the interesting discussions.