ICAI

Events

Spotlight: Civic AI Lab

March 28, 2024

16:00

18:00

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Events

Join us to learn more about how the Civic AI Lab is pioneering a future where AI serves everyone, equally and justly.

Find us today at Lab42 (room: L3.33) or join us online on Zoom.

This event aims to showcase the lab’s innovative approach to harnessing artificial intelligence for the public good, focusing on crucial areas such as education, welfare, environment, mobility, and health. The Civic AI Lab stands at the forefront of addressing the dual-edged nature of AI technology—its vast potential to improve urban life alongside the risks of exacerbating inequalities.

By delving into the challenges and opportunities AI presents, the lab commits to steering the development and application of AI towards enhancing equality and fairness within the cityscape. This initiative not only explores the technological and ethical boundaries of AI but also establishes a vital dialogue with residents and businesses, offering guidance and insights on navigating the evolving landscape of new technologies.

Event details

Spotlight: Civic AI Lab
28 March 2024 16:00-18:00
Lab42, Amsterdam Science Park (Room: L3.33)

Programme

16:00 – Welcome & introductions
16:05 – Presentation: “Hier moeten we wat mee” Closing the AI-policy gap by Paul Verhagen
16:25 – Q&A
16:30 – Presentation: Efficiency vs Strategy in One-sided Matching: The Case of Amsterdam Secondary School Choice by Mayesha Tasnim
16:50 – Q&A
16:55 – Closing
17:00 – Drinks
18:00 – End

About Paul Verhagen: Paul Verhagen is the political liaison at the Civic AI Lab, which means that he functions as the connector between sometimes abstract academic research and real-world policy problems. He has several years policy experience in the Hague but also has deep technical AI expertise, in particular on political polarization through algorithms.

About Mayesha Tasnim: Mayesha is a PhD student at the Civic AI Lab, University of Amsterdam with a focus on resource allocation problems in Education. Her research interests include the use of Multi-agent Reinforcement Learning and Automated Mechanism Design as decision support tools for policymakers.