Explaining Explainability: An Interdisciplinary Approach to Communicate Machine Learning Outcomes

Explore an interdisciplinary approach to communicating machine learning outcomes in this 37-minute talk from the Data Science Festival. Delve into the concept of Explainable AI (XAI) and learn how to extend technical interpretations of AI decision-making through a socio-technical lens. Gain insights from an industry-academia collaboration between Allianz Personal data science team and the University of Bristol. Discover the benefits of multidisciplinary approaches in enhancing AI explainability. Suitable for those with introductory-level technical knowledge, this session from the Data Science Festival MayDay event 2024 offers valuable perspectives on bridging the gap between technical explanations and broader understanding of machine learning outcomes.

Explaining explainability: an interdisciplinary approach to communicate machine learning outcomes