Track 3: Data Craftsmanship

Integrating fairness into
machine learning applications

How do we make sure that our meticulously trained algorithm does not discriminate against certain groups of people or individuals? How do we force our ML product to comply with ethical standards and local policies? These questions are becoming ever more important, given the ubiquitous adoption of data-driven applications.

During this workshop, you will get the chance to experience hands-on how to deal with biased data leading to biased algorithms. You will learn what methods are being used in the industry to produce ethical ML applications and how you can use these tools in your own work.

Learning goal

The participants will have gained an understanding of the various sources of bias and how to address them to build fair algorithms that comply with ethical standards and policies.

Pre-requisites

Some experience in Python and ML.

  • Bernhard Vennemann

    Bernhard received his Doctor of Science in 2019 and holds a M.Sc. and B.Sc. in Mechanical Engineering from the Swiss Federal Institute of Technology (ETH Zurich). Before joining D ONE, Bernhard worked as a University lecturer for machine learning at ETH Zurich. Bernhard has been with the team since 2021.

  • Christianna Toliopoulou

    Christianna holds an MSc in Business Analytics and a BSc in International Economics from Athens University of Economics & Business. She specializes as a BI Engineer and Scrum Master with hands-on experience in product analytics and visualization as well as in delivering insights and presenting results to various levels and stakeholders. She has extended experience working in multinational environments and client facing roles in Sports gaming, Technology and FMCG sectors. Christianna has been with the team since 2023.

  • Alexandros Kalimeris

    Alexandros holds an M.Sc. in Data Science & Information Technologies and a B.Sc in Informatics & Telecommunications from the National and Kapodistrian University of Athens. Before joining D ONE he worked as a Data Scientist at Athena Research Center. He has significant experience in Data Science and implementation of data driven solutions to real business problems and has a strong understanding of Machine Learning and Data Science concepts, algorithms and related technologies. Alexandros has been with the team since 2022.