The public debate on artificial intelligence is increasingly focused on issues such as the creation of artificial consciousness by genius scientists based on a deep understanding of the human brain or mind. However, AI should be seen as a symptom of a paradigm shift that has placed data at the center of research interest. According to this paradigm, emergence is observed above a certain threshold. Thus, instead of focusing on analytical deduction, logical axioms, and deriving formulae, scientists now focus on the quantity and quality of data from which algorithmic structures emerge. But this data is not a “natural given” and needs to be structured in certain ways to produce good outcomes. The panel will focus on this idea of “emerging data” and also try to dialectically address positive developments in the field. AI will therefore be seen as a tool for solving specific challenges rather than a universal truth.
Moderated by Alexander König