Methods of Bias-Reduction for Socially Resonsible AI Design
In this course, you will learn about proven methods for reducing bias in AI systems. These include both very specific practices that are effective at the product level and comprehensive approaches that help prevent bias across processes and organizations in the long term. These scientifically grounded methods are already being successfully applied in many fields to ensure that AI systems are not only technically advanced but also socially responsible and fair.
Using practical examples and small exercises, this course will equip you with a toolkit to actively and responsibly design and use AI systems – ensuring that they comply with the principles of fairness, transparency, and inclusivity.
Overview
In our course series on socially responsible AI design, this learning unit focuses specifically on methods and practices for reducing bias in the development and use of AI. You will learn about methodological tools that enable you to identify and avoid stereotypical distortions, as well as unfair or discriminatory content and practices.
Most people want to act fairly, responsibly, and ethically. However, they often lack concrete guidance on how to design and use AI systems in ways that reflect these values. So how can we recognize and reduce biases — that is, stereotypical distortions?
In this course, you will explore proven methods for mitigating bias. These include both targeted practices that are effective at the product level and comprehensive approaches that sustainably prevent bias at the process or organizational level. These scientifically grounded methods are already being successfully applied in many fields to ensure that AI systems are not only technically advanced but also socially responsible and fair.
Through practical examples and short exercises, this course will equip you with a toolkit to actively and responsibly design and use AI systems — ensuring that they uphold the principles of fairness, transparency, and inclusivity.
What can I expect to learn?
- Diversity Personas – Developing diverse and bias-free personas in the design of AI technologies
- De-Biasing through Prompting – Identifying and reducing biases in the use of generative AI
- Role Models – Strengthening the visibility of local role models to reduce biases in organizational structures and processes
- Designing AI together – Counteracting biases in organizations in a holistic, reflective, and sustainable manner
What will I achieve?
Upon completion of the course, you will be able to
- Generate examples of possible biases and develop targeted solutions.
- Identify the scientific background of the various methods of bias reduction that result in socially responsible AI design.
- Identify the appropriate areas within the company that can be optimized using bias reduction methods.
- Implement the various practices step by step in your everyday business life.
What requirements do I need to meet?
No specific requirements necessary. The courses "Designing Socially Responsible AI" and "Team Practices for Socially Responsible AI Design" are optional.
Who is offering the course?
Prof. Dr. Nicola Marsden and her team at the Lab for Social Informatics are working on national and international research projects to develop and implement participatory and user-centered methods for designing AI and ensuring equitable digitalization.
She is involved in various roles promoting diversity in STEM fields, e.g., as deputy chair of the Competence Center for Technology, Diversity, and Equal Opportunities (kompetenzz e.V.), and as an expert for the German UNESCO Commission on the topic of "AI as an opportunity for greater gender equality."
