Astrid did her PhD in Human-Computer Interaction at the Institut Polytechnique de Paris where she studied human-centric explainability of AI systems. She explored the design, usefulness and compliance of explainable AI in financial applications such as life-insurance and anti-money laundering. Her PhD research also investigated human cognitive biases in explainable AI, interactive algorithmic explanations, and the risk-based regulation approach of financial services regulators. She has an interdisciplinary background in computer science, social sciences and behavioural economics.
At the JRC, Astrid is committed to analysing algorithmic trustworthiness as part of the enforcement of the Digital Services Act.
Link:
Selected publications:
Bertrand, A., Maxwell, W. & Eagan, J. 2023. Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-making. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (FAccT '23). https://doi.org/10.1145/3593013.3594053
Bertrand A, Viard T, Belloum R, Eagan J.R, and Maxwell W. 2023. On Selective, Mutable and Dialogic XAI: a Review of What Users Say about Different Types of Interactive Explanations. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 411, 1–21. https://doi.org/10.1145/3544548.3581314
Bertrand A, Belloum R, Eagan J.R, and Maxwell W. 2022. How Cognitive Biases Affect XAI-assisted Decision-making: A Systematic Review. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES '22). Association for Computing Machinery, New York, NY, USA, 78–91. https://doi.org/10.1145/3514094.3534164
Maxwell W, Bertrand A, Vamparys X, Do AI-based anti-money laundering (AML) systems violate European fundamental rights?, International Data Privacy Law, Volume 11, Issue 3, August 2021, Pages 276–293, https://doi.org/10.1093/idpl/ipab010