Where Law meets Artificial Intelligence: Discrimination and Unfair Differentiation in Insurance

Artificial intelligence (AI) seems to change the way insurers assess risks and set prices: insurers can now analyse large amounts of new data types — ranging from Internet of Things (IoT) devices to social media. This may allow insurers to estimate risks in greater detail. In this dissertation, I address the central research question: To what extent do insurers introduce discrimination-related risks when they use AI systems for underwriting? I organise the PhD thesis around four topics: trends in how insurers apply AI and the possible risks of these practices, the legal obstacle to testing for bias under the General Data Protection Regulation (GDPR), the effectiveness of a de-biasing-exception in the EU AI Act, and how the public evaluates these practices.