Data Science Day 2023: Afternoon programme

Registrations now open!

What does interdisciplinary data science collaboration look like at the UvA? How do we balance ethical, legal and social aspects of artificial intelligence? These topics will be addressed and discussed at the upcoming Data Science Day on 13 October.

Date: 13 October 2023
Time: 13:30 -18:30
Location: KNAW, Het Trippenhuis

Listen to a Keynote presentation by Prof. dr. Gabriele Jacobs on responsible AI in the field of public safety, be witness to the launch of the very first DSC research laboratory on human-aligned video-AI (DSC HAVA-Lab) and get updated on the latest developments in data science in leading research programmes across the UvA. Meet former colleagues and potential new ones at the concluding networking drinks.

Data Science Day is organised by the UvA Data Science Centre to highlight the importance of interdisciplinary data science in current research and society. Renowned experts and DSC-researchers share their knowledge and insights on the latest developments in the field of data science and AI.

Can't make it to Amsterdam in-person? The programme will be streamed via Zoom. We kindly ask you to register for the online livestream in advance.

Programme

UvA researchers can participate in interactive workshops during a morning programme, from 09:00 to 13:30 (including lunch). Read more about the morning programme.

13:30	Walk-ins and networking
14:00	Welcome to Data Science Day
14:05	Updates from UvA theme-based collaboration programmes Responsible Digital Transformation theme by Christine Erb Sustainable Prosperity theme by Dylan Suijker Healthy Future theme by Agneta Fischer Fair and Resilient Societies theme by Roel Beetsma
14:35	Interdisciplinary data science collaboration at the UvA: What does it look like? Responsible Digital Transformation theme project: Understanding the Human in the Loop - Behavioural insights to develop responsible AI tools by Shaul Shalvi (Faculty of Economics and Business), Chris Starke (Faculty of Social and Behavioural Sciences) Data Science Centre Away Day: Debunking AI-Ethics Myths by DSC members Paula Helm (Faculty of Humanities), Owen Kapelle (Faculty of Humanities and Faculty of Science) Launch of the DSC HAVA-Lab (winning recipient of the DSC Interdisciplinary PhD Lighthouse Call) by Cees Snoek (Faculty of Science)
15:15	Networking break
15:55	Keynote 'Studying AI in Public Safety: Learnings from a multi-stakeholder perspective' by Gabriele Jacobs, Professor of Organisational Behaviour and Culture at Erasmus University, Principal Investigator AI-MAPS
16:40	Closing remarks
16:45	Networking drinks
18:30	End of event

Keynote by Prof. Gabriele Jacobs

Studying AI in Public Safety: Learnings from a multi-stakeholder perspective
What can responsible artificial intelligence in the field of public safety look like? Together with interdisciplinary colleagues and experts from diverse private and public organizations we aim to explore the ethical, legal and social aspects of this question within our project AI-MAPS. In this presentation I will share insights on learnings from our field studies into manifestations and living-labs. These learnings refer to conceptual and methodological developments on how to study complex “AI-cologies”, but also open questions around how to position ourselves as researchers and how to live “critical friendships” within multi-stakeholder settings.

Gabriele Jacobs
Gabriele Jacobs is Professor of Organisational Behaviour and Culture at the Erasmus University Rotterdam. Her research interests include culture, justice and identity and multi-stakeholder management. She focusses in her research mainly on the context of public safety, where she coordinated and conducted several national and EU-projects. Since September 2022, Gabriele Jacobs leads the NWA project AI-MAPS (Artifical Intelligence in Multi-Agency Public Safety), a multi-disciplinary research project with more than 20 partners from academia, the private and public sector and civil society.

Data Science Day 2023: Afternoon programme

Programme

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