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27.05.2021 18:00 - 19:30 in Frankfurt am Main (Deutschland)

Von trügerischer Objektivität und historic bias bei algorithmenbasiertem Kreditscoring

Katja Langenbucher (Goethe University, Professor of Civil Law, Commercial Law and Banking Law)

Algorithms – and the actors behind them – are surveying and impacting ever more dimensions of our modern lives. They recommend which movies to watch; they calculate risk-appropriate credit scores; and they play a role in meting out “just” punishment; to only name a few areas. At the same time, they correct imperfect human decisions and add new informational dimensions to decisions prior impossible. To assess and evaluate the impeding transformations of normative orders in a predictive society, we approach algorithms in light of the juxtaposition of trust and control. Why and under which conditions do – or don’t – we trust algorithms? Indeed, can and should we trust them? Especially because their algorithmic normativity was (not) produced in justificatory fora where trust is brought about in and through social conflicts? But then, how much trust – if any – should algorithms put into us as citizens? For example, do they have to presume us non-dangerous and harmless? Vice versa, how much control do we need to retain over algorithms? And how much control should they exert over us? Can we use algorithms to control the effect of algorithms and thus create a meta-level of trust? Especially in order to negate, or as a matter of fact: to entertain, the freedom to deviate in the algorithmic society? These are but a few of the questions that internationally renowned speakers raise in “Algorithms between Trust and Control”, a lecture series convened by Indra Spiecker gen. Döhmann and Christoph Burchard, and co-organized by the research clusters ConTrust, Normative Orders and ZEVEDI in the line with the Frankfurt Talks on Information Law and under the auspices of Goethe University Frankfurt am Main.

The lectures will take place via Zoom. Please register to receive the login data.





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