4th & 5th of November, 2024 @University of Amsterdam
One of the central issues discussed in the context of the societal impact of language technology is that machine learning systems can contribute to discrimination, for instance by propagating human biases and stereotypes. Despite efforts to address these issues, we are far from solving them.
The goal of this workshop is to bring together researchers from different fields to discuss the state of the art on bias measurement and mitigation in language technology and to explore new avenues of approach. For more information, read our Call for Abstracts.
The Call for Abstracts is currently open (deadline: September 15th, 2024)!
This workshop is organized by Katrin Schulz, Leendert van Maanen, Jelle Zuidema, Oskar van der Wal and Dominik Bachmann as part of the project “The biased reality of online media - Using stereotypes to make media manipulation visible”, which is financed by the Dutch Research Council (NWO). In this project we integrate knowledge from AI, psychology and linguistics to develop measures for social biases in language models and humans, and then to use these to study the influence of our media consumption on our beliefs.
| • Deadline Call for Abstracts: | 15 September, 2024 |
| • Notification of acceptance: | 25 September, 2024 |
| • Workshop: | 4 & 5 November, 2024 |
We are excited to confirm the following invited speakers at the workshop.
Dr. Dong Nguyen is assistant professor Computer Science at Utrecht University. She works in the field of Natural Language Processing and is the head of the NLP and Society Lab. Her research focuses on computational text analysis for research questions from the social sciences. In recent years, she has also worked on bias measurement and transparent NLP. [Link to their website]
Dr. John Lalor is assistant professor of IT, Analytics, and Operations at the University of Notre Dame, Indiana. His research focuses on developing methods for evaluating machine learning (and especially Natural Language Processing) models and for quantifying uncertainty. [Link to their website]
Dr. Zeerak Talat is a research fellow at Mohamed Bin Zayed University of AI, and in November, he will be a Chancellor's Fellow in Responsible ML and AI at the Centre for Technomoral ML and AI at the Edinburg Futures Institute and Institute for Language, Cognition, and Computation. His research seeks to examine how machine learning systems interact with our societies and the downstream effects of introducing machine learning to our society. [Link to their website]
Dr. Abigail Jacobs is assistant professor of Information at the University of Michigan in the School of Information and assistant professor of Complex Systems in the College of Literature, Science, and the Arts. Her current research interests are around measurement; the hidden assumptions in machine learning, focusing on measurement and validity as a lens; structure, governance, and inequality in sociotechnical systems; and social networks. [Link to their website]
This workshop will be held in Amsterdam. More information on the workshop will follow later. For questions or comments, please contact Oskar via o.d.vanderwal@uva.nl.
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