BEGIN:VCALENDAR
VERSION:2.0
PRODID:https://github.com/derhansen/sf_event_mgt
METHOD:PUBLISH
BEGIN:VEVENT
UID:1964-1413@rg-rhein-neckar.gi.de
CLASS: PUBLIC
SUMMARY:Ethics and Accountability of Algorithmic Decision Making Systems
DESCRIPTION:Abstrakt:\n\nThe new 'sexiest job on earth' according to former
  Google-CEO Schmidt is the "Data Scientist". As data scientists we are enti
 tled to crawl through data, finding patterns that can predict the future. O
 ur tool set is huge and increases every day, foremost by methods from machi
 ne learning. In many cases, the question to be solved by our learning syste
 ms are clear cut and so is the quality measure by which we can evaluate whe
 ther the systems are good enough to be applied. However, neither is the cas
 e when we build systems to predict future human behavior or to classify cur
 rent human behavior. For this, 1) intricate social concepts have to be quan
 tified ("operationalization"), 2) it is often unclear how to define a "good
  decision", and 3) it is hard to observe whether the system embedded in a s
 ocial system will actually improve the latter or not. While these problems 
 are often discussed under the term "ethics of algorithms", I will argue tha
 t a large part of it is actually a question of accountability. As a communi
 ty of computer and data scientists, we will have to make sure that we only 
 decide on those parts of these systems for which we are trained - and inclu
 de the expertise of psychologists, sociologists, lawyers, and politicians w
 here this is not the case. I will show a framework that helps to sort these
  two aspects and to thus avoid mistakes in building learning algorithmic de
 cision making systems.\n\nReferent:   Prof. Dr. Katharina Zweig, TU Kaiserl
 autern\n\n\n\n
LOCATION:Universität Heidelberg
DTSTAMP:20190108T095350Z
DTSTART:20190116T171500Z
DTEND:20190116T184500Z
END:VEVENT
END:VCALENDAR