|Number of Places||20|
|Room||Labor Exzellenzcluster "Bild Wissen Gestaltung", Sophienstr. 22a, 10178 Berlin|
|Start||Oct 18, 2018|
|end||Feb 14, 2019|
Algorithms are increasingly becoming a part of our life. They recommend products (and friends) to us, offer suitable services to our current situation, and photograph our beloved ones in the right situation. It seems that more and more algorithmic systems are arranging our activities. They help us to filter our everyday work flow and overspill in information and therefore seem to let us experience new leisure spaces. But many of these processes in sorting and structuring data cannot be perceived. Due to the lack of transparency in decision-making processes in algorithmic systems, many people do not actively notice these interventions in their daily life.
Emerging debates on „Fairness, Accountability and Transparency“ discuss these challenges, relating to intelligibility, interpretability and the ability to explain algorithmic systems. To achieve these goals, new approaches in the visualisation of algorithmic processes in learning and decision-making are required. Furthermore, for the interaction with algorithmic systems, interfaces have to be rethought. The ways in which machines learn from humans is not one-sided, it is based on “exchange“ and participation. This poses the following questions: Who trains whom? To what extent does the behaviour of the machine adapt to the user and vice versa?
Students of the Institute for Computer Science (FU-Berlin) and Product Design Department (KH-Berlin Weißensee) will form interdisciplinary teams, and strategies for the day to day handling of algorithmic systems will be developed. The aim is to conceptualise new interaction patterns and interfaces on the basis of machine learning technologies, and implement these in products (physical and digital). The focus should be particularly on the exchange between user and the algorithmic system.
During the semester the teams will run through the following project stages: the conception stage, the stage of designing and the stage of prototypical implementation. Due to the subject of the course, it will be necessary to undertake practical experiences with machine learning right from the start. The basics will be given in the process of the course.
Sophienstrasse 22a, rear building, 2. floor, 10178 Berlin