Meeting KI-Postdocs: ‘Algorithmic political bias'

"Cause for special concern"
(Dr. Uwe Peters)
Focusing on the epistemological issue of how we may detect algorithmic biases and recognize their harmfulness, I argue that algorithmic bias against people’s political orientation differs from algorithmic gender and race biases in important ways. The reason is that there are strong social norms against gender and race biases, but this is not the case for political biases. Political biases can thus more powerfully affect individuals’ cognition and behaviour. This increases the chances that they become embedded in algorithms. It also makes it harder to detect and eradicate algorithmic political biases than gender and race biases even though they all can have similarly harmful consequences. Algorithmic political bias thus raises hitherto unnoticed and distinctive epistemological and ethical challenges.