Bias and Fairness in AI Systems

An e-learning unit with a real-life case study

Many businesses and governments are already using data-driven, algorithmic decision-making systems. In the foreseeable future, there will be few industries or areas of daily life where artificial intelligence (AI) systems will not be ubiquitous. However, we are increasingly seeing negative headlines about AI systems being used inappropriately and making discriminatory decisions. For example, a software called COMPAS was used for years in the US justice system to calculate the risk of offenders reoffending based on various factors. But it turns out that COMPAS makes different mistakes depending on ethnicity. African-Americans, for example, are more likely to be overestimated in their risk of reoffending.

The problem is that many people, both in the general population and among those who develop and use AI systems, still make the blanket assumption that algorithmic decisions are objective and neutral. But this is not a given, nor is a decision based solely on objective characteristics necessarily fair and non-discriminatory. Given this situation, there is a great need to gain a deep understanding of the challenges in the use and implementation of AI systems and possible solutions. Against this background, the interactive e-learning unit "Bias and Fairness in AI systems" has been developed at the University of Ulm to provide students, professionals and the interested public with a comprehensive, application-oriented understanding of fairness and bias of AI systems. The core of the course is the teaching of the fundamentals, the application and deepening of the knowledge through interactive exercises and the processing of a real-world case study. The project has been funded by the Péter Horváth Foundation.


Funding provider: Péter Horváth Foundation

Project duration: January 2022 - August 2022

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The e-learning unit aims to contribute to the transfer of knowledge to ensure the use of ethically sound AI systems. The e-learning unit provides interested parties with entertaining basics and practical examples as well as impulses for critical thinking in the handling and implementation of ethically sound AI. First, participants will learn about the concepts of "bias" and "fairness" in AI systems, which can be deepened through practical, interactive exercises. The newly learned skills can then be applied to a real-world case study

The e-learning unit is embedded in the course offerings for students in the Bachelor's and Master's programmes at the University of Ulm, but is also available to the general public. It serves as a basis for knowledge transfer into practice and subsequently as a starting point for the acquisition of application-oriented research projects in cooperation with companies or public administrations. The learning unit is intended to contribute to a well-founded public discourse on the potential and limitations of AI.