1 code implementation • 26 Apr 2024 • Jan Simson, Alessandro Fabris, Christoph Kern
Data practices shape research and practice on fairness in machine learning (fair ML).
no code implementations • 14 Feb 2024 • Patrick Oliver Schenk, Christoph Kern
We employ Yung et al. (2022)'s QF4SA quality framework and present a mapping of its quality dimensions to algorithmic fairness.
1 code implementation • 23 Nov 2023 • Christoph Kern, Stephanie Eckman, Jacob Beck, Rob Chew, Bolei Ma, Frauke Kreuter
We introduce the term annotation sensitivity to refer to the impact of annotation data collection methods on the annotations themselves and on downstream model performance and predictions.
no code implementations • 29 Oct 2023 • Unai Fischer-Abaigar, Christoph Kern, Noam Barda, Frauke Kreuter
Machine Learning (ML) systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health.
1 code implementation • 31 Aug 2023 • Jan Simson, Florian Pfisterer, Christoph Kern
For each of these universes, we compute metrics of fairness and performance.
no code implementations • 4 Nov 2022 • Patrick Kaiser, Christoph Kern, David Rügamer
Both industry and academia have made considerable progress in developing trustworthy and responsible machine learning (ML) systems.
no code implementations • 4 Aug 2021 • Christoph Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter
One example is the prediction-based statistical profiling of job seekers to guide the allocation of support measures by public employment services.
no code implementations • 4 May 2021 • Matthias Kuppler, Christoph Kern, Ruben L. Bach, Frauke Kreuter
The advent of powerful prediction algorithms led to increased automation of high-stake decisions regarding the allocation of scarce resources such as government spending and welfare support.
no code implementations • 21 Dec 2020 • Elena Badillo-Goicoechea, Ting-Hsuan Chang, Esther Kim, Sarah LaRocca, Katherine Morris, Xiaoyi Deng, Samantha Chiu, Adrianne Bradford, Andres Garcia, Christoph Kern, Curtiss Cobb, Frauke Kreuter, Elizabeth A. Stuart
Methods: We examined a total of 13, 723, 810 responses to a daily cross-sectional representative online survey in 38 countries who completed from April 23, 2020 to October 31, 2020 and reported having been in public at least once during the last seven days.
Applications
1 code implementation • 7 Oct 2019 • Ilja Manakov, Markus Rohm, Christoph Kern, Benedikt Schworm, Karsten Kortuem, Volker Tresp
We cast the problem of image denoising as a domain translation problem between high and low noise domains.
no code implementations • 29 Sep 2019 • Christoph Kern, Bernd Weiss, Jan-Philipp Kolb
However, predicting nonresponse in panel studies requires accounting for the longitudinal data structure in terms of model building, tuning, and evaluation.