Quelltext der Seite Explainable Artificial Intelligence for Decision Support

{{Vortrag
|vortragender=Yannick Ettwein
|email=yannick.ettwein@student.kit.edu
|vortragstyp=Bachelorarbeit
|betreuer=Vadim Arzamasov
|termin=Institutsseminar/2023-03-24
|vortragsmodus=in Präsenz
|kurzfassung=Policy makers face the difficult task to make far-reaching decisions that impact the life of
the the entire population based on uncertain parameters that they have little to no control
over, such as environmental impacts. Scenarios provide a common and intuitive way to communicate
and characterize different uncertain outcomes in many decision support applications,
especially in broad public debates. However,
they often fall short of their potential, particularly when applied for groups with diverse
interests and worldviews, due to the difficulty of choosing a small number of scenarios to
summarize the entire range of uncertain future outcomes. Scenario discovery addresses these problems by using statistical or data-mining algorithms
to find easy-to-interpret, policy-relevant regions in the space of uncertain input parameters
of computer simulation models.
}}