Bei vielen Durchbrüchen der Künstlichen Intelligenz (KI) in
den vergangenen Jahren konnten selbst die Entwickler der Algorithmen oft nicht
sagen, wie genau die Ergebnisse zustande kamen. Insbesondere die beim so
genannten Deep Learning genutzten vielschichtigen neuronalen Netzwerke sind oft
Black Boxes. Wojciech Samek vom Fraunhofer Heinrich-Hertz-Institut (HHI)
ist es jedoch gelungen, das zu ändern. Unter anderem mit Klaus-Robert Müller
von der TU Berlin hat er seit 2015 Methoden entwickelt, um die Entscheidungen
von KI-Systeme zu erklären.
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