Skip to content
Center for Digital Dignity
Projects

ARTIFICIAL INTELLIGENCE AND EXTREME SPEECH

AI4Dignity is a proof of concept project funded by the European Research Council (2020-2022) that aims to address challenges facing AI-assisted extreme speech moderation.

ARTIFICIAL INTELLIGENCE AND EXTREME SPEECH

AI4Dignity is a proof of concept project funded by the European Research Council (2020-2022) that aims to address challenges facing AI-assisted extreme speech moderation. Such challenges include ensuring the quality, scope and inclusivity of training data sets and developing AI that accounts for context and cultural nuances. These points are compounded by the overarching challenge in defining what constitutes extreme speech and hate speech. To address these, AI4Dignity seeks to develop a tool for content moderation that moves beyond keyword-based detection systems. To do this, AI4Dignity will pioneer a collaborative and community-based classification approach. In this way, AI4Dignity seeks to take a significant step towards setting procedural benchmarks to operationalize “the human in the loop” principle and bring inclusive training datasets for AI systems tackling urgent issues of digital extreme speech.

For more updates and information, visit the project website.

Principal Investigator: Sahana Udupa

Research Associates: Laura Csuka, Antonis Maranikolakis, Leah Nann, Axel Wisiorek

Computational Linguistics LMU Partner: Hinrich Schütze LMU Digital Humanities Partner: Stephan Leucke

Policy Consultant: Elonnai Hickok Technology Consultant: Abhineet Basan

Project Website:  ai4dignity.gwi.uni-muenchen.de

Related projects

Abstract art
Projects

SMALLPLATFORMS

The research project SMALLPLATFORMS examines how contentious speech emerges and spreads on small social media platforms using ethnographic and computational methods in four countries.

Mural against the abuse of women
Projects

ONLINE MISOGYNY

“Understanding, Detecting, and Mitigating Online Misogyny Against Politically Active Women” is a new multiyear interdisciplinary project funded by BIDT.