Fairness und Privacy in ML-Systemen

The public is beginning to recognize the effects of ML-based decision-making. This is not the only reason why it is important to consider non-functional characteristics such as fairness or data protection. How can we ensure that ML-based decisions are made “fairly” and without algorithmic bias? At the same time, the testing of ML-based software is an open field without established best practices. What can we do to meet these challenges? And what exactly makes ML testing in running systems so complicated?

Date
2020-12-09
Time
14:45 - 15:45
Online Event
INNOQ Technology Day 2020

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