Institute of Philosophy (IPhil)
Main task
In-depth analysis of the cognitive and moral dimensions
of basic notions and principles concerning bias and discrimination in big data and algorithmic processing
Focus Points
• Human biases and computer biases
• Alternative measures of statistical fairness
• Debiasing strategies and affirmative action
• Justification and discrimination
Additional Project (Supported by VolkswagenStiftung)
Digital Contact Tracing, Privacy, and Discrimination: On the Ethics of Fighting Corona
Institute for Legal Informatics (IRI)
Main task
Comprehensive analysis of legal standards and questions regarding the application of AI under the overarching heading of bias and discrimination
Focus Points
• Data protection law
• Consumer, competition and anti-discrimination law
Research Center L3S
Institute for Information Processing (TNT)
Main task
Derivation of strategies, methods and tools for identifying computer bias and discrimination, for ensuring statistical fairness in the operations of AI systems, and for debiasing AI systems
Focus Points
• Computer bias, esp. caused by imbalanced data or rare classes
• Statistical fairness, esp. for non-stationary data
• Debiasing strategies, esp. focusing on explainability