no code implementations • 7 Feb 2024 • Jan Wehner, Frans Oliehoek, Luciano Cavalcante Siebert
Finally, we measure how informative the generated explanations are to a proxy-human model by training it on CTEs.
no code implementations • 12 Jul 2023 • Catholijn M. Jonker, Luciano Cavalcante Siebert, Pradeep K. Murukannaiah
With the growing capabilities and pervasiveness of AI systems, societies must collectively choose between reduced human autonomy, endangered democracies and limited human rights, and AI that is aligned to human and social values, nurturing collaboration, resilience, knowledge and ethical behaviour.
no code implementations • 25 Nov 2021 • Luciano Cavalcante Siebert, Maria Luce Lupetti, Evgeni Aizenberg, Niek Beckers, Arkady Zgonnikov, Herman Veluwenkamp, David Abbink, Elisa Giaccardi, Geert-Jan Houben, Catholijn M. Jonker, Jeroen van den Hoven, Deborah Forster, Reginald L. Lagendijk
The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging.
no code implementations • 2 Apr 2020 • Luciano Cavalcante Siebert, Rijk Mercuur, Virginia Dignum, Jeroen van den Hoven, Catholijn Jonker
This paper analyses to what extent an AA is able to estimate the values and norms of a simulated human agent (SHA) based on its actions in the ultimatum game.