How to make elections fairer – a glimpse of math for democracy | Peter Gritzmann
TEDxTUM 2019 • Topics: Algorithm, Democracy, Math, Politics, Public Policy, Science

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How can it happen that, in an election, the voters’ will is turned upside down? Our voting systems are never entirely fair, but math can help at least make them fairer. One natural goal is to optimize the size, shape, and location of the electoral districts. In this talk, Peter Gritzmann sheds light on the complex mathematical algorithms that can achieve this and provides us with the knowledge to critically reflect on democracy and its underlying mechanisms. References: 1. A. Brieden, P. Gritzmann, F. Klemm, Constrained clustering via diagrams: A unified theory and its application to electoral district design, European Journal of Operational Research 263 (2017), pp. 18-34. DOI https://doi.org/10.1016/j.ejor.2017.04.018 2. S. Borgwardt, A. Brieden, and P. Gritzmann (2014), Geometric clustering for the consolidation of farmland and woodland. Mathematical Intelligencer (2014), pp. 37-44. DOI https://doi.org/10.1007/s00283-014-9448-2 Thanks: Special thanks go to Fabian Klemm for his support.  
About Peter Gritzmann
Peter Gritzmann is a man of many facets—academic teacher, entrepreneur, family man, citizen—but if you ask him to sum up his role in the world, he’d go with the term Mathematician. As someone who believes that there’s always something new to explore and understand, Peter is constantly on the hunt for a new problem to inspire him. An author of multiple books and numerous academic publications in addition to his work as a tenured professor of mathematics at TUM, Peter is an educator as well as a learner. He has worked with TUM for several years, not just in his current position but also formerly as Vice President for Academic and Student Affairs. Peter’s pointed international interest has also led him to Africa, where he worked with the African Institute for Mathematical Sciences. For Peter, life is about exploring the new and uncovering possibilities.
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