Research by Prof. Tom Lenaerts :
From pro-self to pro-social AI

image d'une intelligence artificielle

Over het evenement

11:30 - 12:30 (GMT+1)
thursday 18th March

The advent of high-quality autonomous AI systems raises a number of questions on how these systems should decide and act when released into the wild. To avoid disasters, solutions are being proposed that aim to ensure that the use of AI in business and society is able to align both individual and societal preferences and norms, avoiding thus negative disruptions.

This ambition is captured by a booming new field of AI research that has the intention to develop cooperative or prosocial AI systems, a task which is especially difficult when the participants, being human or AI, may have conflicting interests.

Starting with an introduction on game theory and the question of cooperation, this presentation will zoom in on a recent study we made wherein people delegated their strategic choices to simple agents in a game capturing the problem of climate negotiation.  Will humans or agents produce better group outcomes? If you like to know more, join this seminar during the Belgian AI week.


11:35 : KEYNOTE
12:10 : Q&A

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Prof. Tom Lenaerts

Tom Lenaerts, is professor at the Université Libre de Bruxelles (ULB) where he is co-heading the Machine Learning Group (MLG) and acting as Director for the Interuniversity Institute of Bioinformatics in Brussels (a.k.a. (IB)2). He currently holds a partial affiliation as research professor with the Artificial intelligence lab of the Vrije Universiteit Brussel and is visiting scholar in the Center of Human-Compatibel AI (CHAI) at the University of Berkeley. He is also vice-chair of the Benelux Association for Artificial Intelligence (BNVKI) and board member of the grass-roots organisation AI4Belgium.

He has worked in a variety of interdisciplinary domains and has co-authored many AI-related papers in areas like evolutionary optimisation, collective intelligence, evolutionary game theory, computational biology and bioinformatics. His current main interests are machine learning in rare diseases, on the one hand, and AI delegation analysis using evolutionary game theory on the other hand.


Nathanaël Ackerman

Nathanaël Ackerman is the current lead of the AI4Belgium coalition.He is “AI & Innovation expert” at the Federal Public Service Policy and Support (BoSa).He is also the National Contact point for AI4EU, and ONE AI expert @OECD.

Nathanaël has had a mixed public-private career: from research & teaching AI @ Université Libre de Bruxelles, to entrepreneurship.He was involved in the technology transfer @ULB for several years.

In 2012, he was appointed as Director for Innovation and International Relations @Brussels Enterprise Agency (now recently, Nathanael has been appointed as Advisor for Innovation and AI (to Secretary of State Axelle Lemaire) for the French Government.

He leaded the #France IA  strategic plan. And then co-founded and managed the Hub France Artificielle for 2 years, before coming back to Belgium, his native country, to do quite the same job : contribute to the national AI strategy, and implement it with the ecosystem.

Nathanael is both graduated from Polytechnic School of Brussels, and Ecole Centrale Paris.

Elias F. Domingos

Elias F. Domingos received the M.Sc. degree in Telecommunication Engineering in 2015 at the University of Vigo. In 2017, he was awarded a F.W.O. (Fonds Wetenshappelijk Onderzoek) Strategic Basic Research (SB) Ph.D. fellowship which allowed him to pursue his Ph.D. studies in the Vrije Universiteit Brussels jointly with the University of Vigo. In 2020 he obtained his Ph.D. degree, where he investigated collective dynamics in strategic situations affected by collective risk, such as the COVID19 pandemics. Currently, he is working as a Postdoctoral Researcher at the Artificial Intelligence Laboratory in Brussels, studying strategic interactions in a smart grid energy market. His topics of interest are (evolutionary) game theory, multi-agent systems, human-machine interactions, behavioral experiments and intelligent systems.


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